Preface

In recent decades there has been growing concern over the impact of greenhouse gas (GHG) emissions on global warming and climate changes. Fossil fuel use, deforestation, intensive livestock farming, use of synthetic fertilizers and industrial processes have been pointed out as the main human sources of GHG emissions. As population growth around the world is contributing to this global warming, several efforts have been made to mitigate GHGs by agricultural practices and industrial processes.

The Intergovernmental Panel on Climate Change (IPCC) has reported different strategies to promote atmospheric CO2 sequestration. However, as the methodologies and new strategies are constantly updated, the dissemination of this information becomes important within the current scenario of climate change.

As such, this book provides the reader with a comprehensive overview of the current state of the art of the strategies that contribute to reducing GHG emissions and promoting CO2 sequestration. Chapters broadly discuss alternatives such as soil carbon sequestration through conservationist management systems in agriculture, improvement of industrial processes and reuse of residues, adsorption processes that can be performed using activated carbon and effective methods of carbon capture and storage such as geological sequestration of CO2. The book is divided into eight chapters written by thirty-five researchers in different fields and organized by subjects related to CO2 sequestration in several regions of the world. The results presented here are directly from the authors' research as well as from studies in important publications.

This book contains relevant information about atmospheric CO2 sequestration and contributes to discussions on reducing the impacts of global warming and climate change. We recommend this reference to the general public, undergraduate and graduate students, and researchers who aim to deepen their knowledge on the topics discussed within.

**II**

**Chapter 7 111**

**Chapter 8 131**

Experimental Study of Adsorption on Activated Carbon for CO2 Capture

Carbon Capture and Storage (CCS): Geological Sequestration of CO2

*by Nediljka Gaurina-Međimurec and Karolina Novak Mavar*

*by Hesham G. Ibrahim and Mohamed A. Al-Meshragi*

**Leidivan Almeida Frazão and Junio Cota Silva** Universidade Federal Minas Gerais, Brazil

> **Adriana Marcela Silva-Olaya** Universidad de la Amazonia, Colombia

**1**

change [2–6].

**Chapter 1**

**1. Introduction**

policy options.

systems.

Sequestration

*Leidivan A. Frazão, Junio C. Silva* 

reducing CO2 concentration in the atmosphere.

financial offsets in terms of CO2 sequestration cost.

**2. Opportunities and challenges for CO2 sequestration**

*and Adriana M. Silva-Olaya*

Introductory Chapter: CO2

The Special Report from the Intergovernmental Panel on Climate Change (IPCC) [1] revealed that recent trends in greenhouse gas (GHG) emissions and the level of international ambition indicated by nationally determined contributions, within the Paris Agreement, deviate from a track consistent with limiting warming to well below 2°C. This will require a drastic reduction in greenhouse gas emissions by 2030 and thereafter removal of carbon from the atmosphere in large quantities. The IPPC reports found that many climate models can only meet the two-degree Celsius goal when carbon removal strategies are included among the potential

There are several strategies to promote carbon dioxide (CO2) sequestration by agriculture and industry. So, it is necessary to evaluate the methodologies that have been used and to understand the gaps to achieve more sustainable production

In agriculture, the management of agricultural systems that promote soil carbon sink depends on depth, clay content and mineralogy, plant available water holding capacity, nutrient reserves, landscape position, and the antecedent SOC stock [2]. As the soil carbon fluxes vary according to environmental and anthropogenic driving factors [3], soil carbon sequestration can be a short-term solution of

In addition to agronomic practices, several effective methods of carbon capture and storage (CCS) have been proposed to reduce the amount of emitted CO2 in the atmosphere. Adsorption processes can be performed using activated carbon [4] where the adsorptive process can use adsorbents derived from low-cost agro-wastes. Another way to reduce CO2 emission into the atmosphere is by capturing CO2 from the flue gases and storing that in deep geological formations [5]. The CCS provides

Therefore, this book provides a comprehensive overview of the current state of the art about the strategies that contribute to reducing GHG emissions and promote CO2 sequestration by agricultural techniques and carbon capture and storage.

Several studies have indicated the storage in biomass, soils, adsorption processes, and geological formations as viable techniques for CO2 sequestration. All these technologies have the potential to mitigate global warming and climate

#### **Chapter 1**

## Introductory Chapter: CO2 Sequestration

*Leidivan A. Frazão, Junio C. Silva and Adriana M. Silva-Olaya*

#### **1. Introduction**

The Special Report from the Intergovernmental Panel on Climate Change (IPCC) [1] revealed that recent trends in greenhouse gas (GHG) emissions and the level of international ambition indicated by nationally determined contributions, within the Paris Agreement, deviate from a track consistent with limiting warming to well below 2°C. This will require a drastic reduction in greenhouse gas emissions by 2030 and thereafter removal of carbon from the atmosphere in large quantities. The IPPC reports found that many climate models can only meet the two-degree Celsius goal when carbon removal strategies are included among the potential policy options.

There are several strategies to promote carbon dioxide (CO2) sequestration by agriculture and industry. So, it is necessary to evaluate the methodologies that have been used and to understand the gaps to achieve more sustainable production systems.

In agriculture, the management of agricultural systems that promote soil carbon sink depends on depth, clay content and mineralogy, plant available water holding capacity, nutrient reserves, landscape position, and the antecedent SOC stock [2]. As the soil carbon fluxes vary according to environmental and anthropogenic driving factors [3], soil carbon sequestration can be a short-term solution of reducing CO2 concentration in the atmosphere.

In addition to agronomic practices, several effective methods of carbon capture and storage (CCS) have been proposed to reduce the amount of emitted CO2 in the atmosphere. Adsorption processes can be performed using activated carbon [4] where the adsorptive process can use adsorbents derived from low-cost agro-wastes. Another way to reduce CO2 emission into the atmosphere is by capturing CO2 from the flue gases and storing that in deep geological formations [5]. The CCS provides financial offsets in terms of CO2 sequestration cost.

Therefore, this book provides a comprehensive overview of the current state of the art about the strategies that contribute to reducing GHG emissions and promote CO2 sequestration by agricultural techniques and carbon capture and storage.

#### **2. Opportunities and challenges for CO2 sequestration**

Several studies have indicated the storage in biomass, soils, adsorption processes, and geological formations as viable techniques for CO2 sequestration. All these technologies have the potential to mitigate global warming and climate change [2–6].

#### *CO2 Sequestration*

Improving agricultural land management techniques is an efficient way to increase carbon uptake and storage. Strategies to ensure soil carbon sequestration can be obtained through the adoption of different agronomic management practices [2]. Land use with grassland species can also maintain and increase soil organic carbon storage over time [7]. Other studies have reported that land use with perennial crops can also be adopted to promote CO2 sequestration in biomass, and soil is the main component storing the highest amount of carbon in these agroecosystems [8, 9].

Carbon removal can also be achieved through the technology of adsorption on activated carbon from low-cost raw material. Agricultural and forestry residues or biomass residue wastes could be used as suitable raw materials for the production of activated carbon [10]. Furthermore, CCS by geological sequestration is another technological form for carbon removal and can be applied to different industries [5].

#### **3. Perspectives**

As the population is growing around the world and indirectly contributes to global warming, several efforts have been made to mitigate GHG emissions. So, the adoption of CO2 sequestration technologies in the agricultural and industrial sectors has become essential to reduce the impacts of global warming and climate change.

#### **Author details**

Leidivan A. Frazão1 \*, Junio C. Silva1 and Adriana M. Silva-Olaya2

1 Universidade Federal de Minas Gerais, Montes Claros, MG, Brazil

2 Universidad de la Amazonia, Florencia, Colombia

\*Address all correspondence to: lafrazao@ufmg.br

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**3**

pp. 487-500

[6] Vaughan NE, Gough N,

Mander S, Littleton EW, Welfle A, Gernaat DEHJ, et al. Evaluating the use of biomass energy with carbon

*Introductory Chapter: CO2 Sequestration DOI: http://dx.doi.org/10.5772/intechopen.91747*

[1] International Panel on Climate Change (IPCC). In: Masson-Delmotte V,

Skea J, Shukla PR, et al., editors. Global Warming of 1.5°C. An IPCC Special Report on the Impacts of Global Warming of 1.5°C above Pre-Industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty. 2018. Available from: https://www.ipcc.ch/site/assets/ uploads/sites/2/2019/06/SR15\_Full\_

capture and storage in low emission scenarios. Environmental Research Letters. 2018;**13**:044014. DOI: 10.1088/1748-9326/aaaa02

[7] Hungate BA, Barbier EB, Ando AW, Marks SP, Reich PB, van Gestel N, et al. The economic value of grassland species for carbon storage. Science Advances. 2017;**3**:e1601880. DOI: 10.1126/

[8] Leblanc HA, Russo RO. Carbon sequestration in an oil palm crop system (Elaeis guineensis) in the Caribbean lowlands of Costa Rica. Proceedings of the Florida State Horticultural Society.

[9] Mohammed AM, Robinson JS, Midmore D, Verhoef A. Carbon storage in Ghanaian cocoa ecosystems. Carbon Balance and Management. 2016;**11**(6). DOI: 10.1186/s13021-016-0045-x

[10] Kaghazchi T, Soleimani M. Effect of raw materials on properties of activated carbons. Chemical Engineering and Technology. 2006;**29**:1247-1251. DOI:

10.1002/ceat.200500298

sciadv.1601880

2008;**121**:52-54

Zhai P, Pörtner HO, Roberts D,

Report\_High\_Res.pdf

2018;**24**:3285-3301

[3] Stockmann U, Adams M, Crawford JW, Field DJ,

[4] Mohammad SS, Wan Mohd

Ashri WD, Amirhossein H, Ahmad S. A review on surface modification of activated carbon for carbon dioxide adsorption. Journal of Analytical and Applied Pyrolysis. 2010;**89**:143-151

[5] Mosleh MH, Sedighi M, Babaei M, Turner M. Geological sequestration of carbon dioxide. In: Letcher TM, editor. Managing Global Warming: An Interface of Technology and Human Issues. London, United Kingdon: Academic Press (Elsevier); 2019.

[2] Lal R. Digging deeper: A holistic perspective of factors affecting soil organic carbon sequestration in

Henakaarchchia N, Jenkins M, et al. The knowns, known unknowns and unknowns of sequestration of soil organic carbon. Agriculture, Ecosystems and Environment. 2013;**164**:80-90

agroecosystems. Global Change Biology.

**References**

*Introductory Chapter: CO2 Sequestration DOI: http://dx.doi.org/10.5772/intechopen.91747*

#### **References**

*CO2 Sequestration*

systems [8, 9].

tries [5].

**3. Perspectives**

**Author details**

Leidivan A. Frazão1

\*, Junio C. Silva1

2 Universidad de la Amazonia, Florencia, Colombia

\*Address all correspondence to: lafrazao@ufmg.br

provided the original work is properly cited.

1 Universidade Federal de Minas Gerais, Montes Claros, MG, Brazil

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

Improving agricultural land management techniques is an efficient way to increase carbon uptake and storage. Strategies to ensure soil carbon sequestration can be obtained through the adoption of different agronomic management practices [2]. Land use with grassland species can also maintain and increase soil organic carbon storage over time [7]. Other studies have reported that land use with perennial crops can also be adopted to promote CO2 sequestration in biomass, and soil is the main component storing the highest amount of carbon in these agroeco-

Carbon removal can also be achieved through the technology of adsorption on activated carbon from low-cost raw material. Agricultural and forestry residues or biomass residue wastes could be used as suitable raw materials for the production of activated carbon [10]. Furthermore, CCS by geological sequestration is another technological form for carbon removal and can be applied to different indus-

As the population is growing around the world and indirectly contributes to global warming, several efforts have been made to mitigate GHG emissions. So, the adoption of CO2 sequestration technologies in the agricultural and industrial sectors has become essential to reduce the impacts of global warming and climate change.

and Adriana M. Silva-Olaya<sup>2</sup>

**2**

[1] International Panel on Climate Change (IPCC). In: Masson-Delmotte V, Zhai P, Pörtner HO, Roberts D, Skea J, Shukla PR, et al., editors. Global Warming of 1.5°C. An IPCC Special Report on the Impacts of Global Warming of 1.5°C above Pre-Industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty. 2018. Available from: https://www.ipcc.ch/site/assets/ uploads/sites/2/2019/06/SR15\_Full\_ Report\_High\_Res.pdf

[2] Lal R. Digging deeper: A holistic perspective of factors affecting soil organic carbon sequestration in agroecosystems. Global Change Biology. 2018;**24**:3285-3301

[3] Stockmann U, Adams M, Crawford JW, Field DJ, Henakaarchchia N, Jenkins M, et al. The knowns, known unknowns and unknowns of sequestration of soil organic carbon. Agriculture, Ecosystems and Environment. 2013;**164**:80-90

[4] Mohammad SS, Wan Mohd Ashri WD, Amirhossein H, Ahmad S. A review on surface modification of activated carbon for carbon dioxide adsorption. Journal of Analytical and Applied Pyrolysis. 2010;**89**:143-151

[5] Mosleh MH, Sedighi M, Babaei M, Turner M. Geological sequestration of carbon dioxide. In: Letcher TM, editor. Managing Global Warming: An Interface of Technology and Human Issues. London, United Kingdon: Academic Press (Elsevier); 2019. pp. 487-500

[6] Vaughan NE, Gough N, Mander S, Littleton EW, Welfle A, Gernaat DEHJ, et al. Evaluating the use of biomass energy with carbon

capture and storage in low emission scenarios. Environmental Research Letters. 2018;**13**:044014. DOI: 10.1088/1748-9326/aaaa02

[7] Hungate BA, Barbier EB, Ando AW, Marks SP, Reich PB, van Gestel N, et al. The economic value of grassland species for carbon storage. Science Advances. 2017;**3**:e1601880. DOI: 10.1126/ sciadv.1601880

[8] Leblanc HA, Russo RO. Carbon sequestration in an oil palm crop system (Elaeis guineensis) in the Caribbean lowlands of Costa Rica. Proceedings of the Florida State Horticultural Society. 2008;**121**:52-54

[9] Mohammed AM, Robinson JS, Midmore D, Verhoef A. Carbon storage in Ghanaian cocoa ecosystems. Carbon Balance and Management. 2016;**11**(6). DOI: 10.1186/s13021-016-0045-x

[10] Kaghazchi T, Soleimani M. Effect of raw materials on properties of activated carbons. Chemical Engineering and Technology. 2006;**29**:1247-1251. DOI: 10.1002/ceat.200500298

**5**

**Chapter 2**

**Abstract**

organic fertilizers

**1. Introduction**

Soil Carbon Sequestration through

Agronomic Management Practices

*Sikander Khan Tanveer, Xingli Lu, Shamim-Ul-Sibtain Shah,* 

Improper soil and crop management practices have resulted in loss of soil carbon. Worldwide, about 1417 Pg of soil carbon is stored in first meter soil depth, while 456-Pg soil carbon is stored in above–below ground vegetation and dead organic matter. Healthy soils can be helpful in combating the climate change because soils having high organic matter can have higher CO2 sequestration potential. Main agronomic practices responsible for soil carbon loss include improper tillage operations, crop rotations, residue management, fertilization, and similarly no or less use of organic fertilizers that have resulted in the loss of soil organic matter in the form of CO2. The share of agriculture sector in the entire emissions of global GHGs in the form of CO2, N2O, and CH4 is about 25–30%. Studies have shown that by adapting proper tillage operations, the use of such kind of crop rotations that can improve soil organic matter and similarly the application of organic fertilizers, i.e., FYM, compost, and other organic amendments such as humic acid, vermicompost,

**Keywords:** soil carbon, agronomic practices, tillage, crop rotation, crop residues,

Soil carbon (C) sequestration implies the removal of atmospheric CO2, by plants and storage of the fixed C through incorporation into soil organic matter [1]. Carbon exists in a variety of forms, mainly as plant biomass, soil organic matter, and gas carbon dioxide (CO2) in atmosphere and dissolved in sea water. Soil organic carbon (SOC), which is a main component of SOM, can be separated into stable and labile fraction [2], and soil organic matter and its contribution play a very vital role during its humification formation of stable humus fraction and in the management of fertilization [3]. Worldwide, about 1417 Pg of soil carbon is stored in first meter soil depth, while 456-Pg soil carbon is stored in above–below ground vegetation and dead organic matter. The Earth's soils include approximately 1500 Pg of C, which is about 2–3 times larger than the amount of C stored in Earth's vegetation [4, 5]. The atmospheric carbon pool contains ~800 Pg of CO2-C and is escalating at the rate of 4.2 Pg C per year, 0.54 percent per year. Over the past 150 years, the amount of carbon in the atmosphere has enlarged by 30%. An increase in the atmospheric concentration of CO2 from 280 ppm from the pre-industrial era to 390 ppm in 2010 (an enrichment of 39%) and other greenhouse gases (GHGs) has changed the

*Imtiaz Hussain and Muhammad Sohail*

etc., can be useful in soil carbon sequestration.

#### **Chapter 2**

## Soil Carbon Sequestration through Agronomic Management Practices

*Sikander Khan Tanveer, Xingli Lu, Shamim-Ul-Sibtain Shah, Imtiaz Hussain and Muhammad Sohail*

#### **Abstract**

Improper soil and crop management practices have resulted in loss of soil carbon. Worldwide, about 1417 Pg of soil carbon is stored in first meter soil depth, while 456-Pg soil carbon is stored in above–below ground vegetation and dead organic matter. Healthy soils can be helpful in combating the climate change because soils having high organic matter can have higher CO2 sequestration potential. Main agronomic practices responsible for soil carbon loss include improper tillage operations, crop rotations, residue management, fertilization, and similarly no or less use of organic fertilizers that have resulted in the loss of soil organic matter in the form of CO2. The share of agriculture sector in the entire emissions of global GHGs in the form of CO2, N2O, and CH4 is about 25–30%. Studies have shown that by adapting proper tillage operations, the use of such kind of crop rotations that can improve soil organic matter and similarly the application of organic fertilizers, i.e., FYM, compost, and other organic amendments such as humic acid, vermicompost, etc., can be useful in soil carbon sequestration.

**Keywords:** soil carbon, agronomic practices, tillage, crop rotation, crop residues, organic fertilizers

#### **1. Introduction**

Soil carbon (C) sequestration implies the removal of atmospheric CO2, by plants and storage of the fixed C through incorporation into soil organic matter [1]. Carbon exists in a variety of forms, mainly as plant biomass, soil organic matter, and gas carbon dioxide (CO2) in atmosphere and dissolved in sea water. Soil organic carbon (SOC), which is a main component of SOM, can be separated into stable and labile fraction [2], and soil organic matter and its contribution play a very vital role during its humification formation of stable humus fraction and in the management of fertilization [3]. Worldwide, about 1417 Pg of soil carbon is stored in first meter soil depth, while 456-Pg soil carbon is stored in above–below ground vegetation and dead organic matter. The Earth's soils include approximately 1500 Pg of C, which is about 2–3 times larger than the amount of C stored in Earth's vegetation [4, 5]. The atmospheric carbon pool contains ~800 Pg of CO2-C and is escalating at the rate of 4.2 Pg C per year, 0.54 percent per year. Over the past 150 years, the amount of carbon in the atmosphere has enlarged by 30%. An increase in the atmospheric concentration of CO2 from 280 ppm from the pre-industrial era to 390 ppm in 2010 (an enrichment of 39%) and other greenhouse gases (GHGs) has changed the

Earth's mean temperature and precipitation [6]. There is much interaction among the terrestrial and atmospheric C pools through the processes of photosynthesis and respiration. Due to land use, conversion factors, and deforestation, biotic pool also contributes in the rise of atmospheric CO2 concentration at the rate of ~1.6 Pg C per year. Different anthropogenic sources include the combustion of fossil fuel, deforestation, land use conversion, soil tillage, animal husbandry, cement manufacturing, etc. According to an estimate, 8.3 Pg C year<sup>−</sup><sup>1</sup> is emitted by combustion of fossil fuel [6, 7], and 1.6 Pg C per year is emitted by deforestation, land-use change, and soil cultivation. It is anticipated that terrestrial ecosystems have contributed as much as half of increases in CO2 emissions from human activity in the past two centuries [4, 8], and about 50 Pg CO2 additions to the atmosphere has been contributed by cultivated soils [9], through the process of mineralization of soil organic carbon (SOC). Terrestrial C pool is estimated approximately 3120 Pg, which is the combination of both pedologic and biotic C pools.

Historically, agricultural soils have lost more than 50 Gt (1 Gt = 1 billion tons) of carbon and agriculture is responsible for soil carbon reductions up to 60–75% [9]. Total anthropogenic emission of CO2 is 9.9 Pg C per year, of which 4.2 Pg C per year is absorbed by atmosphere and 2.3 Pg C per year by the ocean while remaining may be absorbed by unidentified terrestrial sinks.

In 1-m soil depth, estimated carbon pool is 2500 Pg, in two diverse forms including soil organic C (SOC) pool which is likely about 1550 Pg and soil inorganic C (SIC) pool at 950 Pg [10]. Soil inorganic C pool mostly consists of elemental C and carbonate minerals, i.e., calcite, dolomite, and likewise primary and secondary carbonates, whereas soil organic C (SOC) pool contains highly active humus and relatively inert charcoal C. According to United Nations Framework Convention on Climate Change (UNFCCC), carbon sequestration is the process of removing C from atmosphere and depositing it in a reservoir. It entails the transfer of atmospheric CO2 and its secure storage in long-lived pools [11].

The estimation of global carbon sequestration potential of agricultural soils is typically made for sequestration on annual basis, and its range is from 0.4 to 1.2 gigatons per year [1]. Land use, land use change, and forestry (LULUCF) activities can be a relatively cost-effective ways to offset emissions through increasing removals of greenhouse gases from the atmosphere (e.g., by planting trees or managing forests) or through dropping emissions (e.g., by deforestation) [12]. Likewise, emissions of CO2 from soil can be reduced by the adoption of such practices that can increase C input in soils and similarly can lessen the decomposition potential of soil organic matter. These kinds of practices have a vital role in storage and in release of C within terrestrial C cycle [13]. Nowadays, intensive agriculture usually results in a considerable soil degradation and soil carbon depletion [14], because in present agriculture and human's food chain, intensive soil utilization is very essential but it is very imperative so it should be followed and coupled with appropriate conservation practices [15]. Agriculture sector is responsible for the emissions of about 30% global greenhouse gases emissions, and primarily, inappropriate soil and crop management practices have resulted in the loss of soil carbon. In agricultural soils, C sequestration means the increase of soil C storage.

Main agronomic and related practices that can be helpful in SOC sequestration include:

**7**

*Soil Carbon Sequestration through Agronomic Management Practices*

• use of mulch either in the form of crop residues or synthetic materials;

• adoption of integrated nutrient management practices for the increase of soil

Agriculture sector can be supportive in the lessening of emissions of GHGs, and if suitable agronomic practices are to be adopted, then agricultural soils have the potential to act as a sink for CO2 sequestration. Healthy soils can be supportive in combating the climate change because soils having high organic matter can have

Different agronomic and related practices that can be supportive in CO2 seques-

The main aim of tillage is the physical disturbance of upper soil layers for the preparation of soil bed, incorporation of fertilizers, crop residues, and similarly to control weeds. Tillage methods in world vary depending upon the soil, climate, crop management, and availability of technology. The relationship between tillage, soil structure, and soil organic matter dynamics is essential to C sequestration ability of agricultural soils. Tillage effects on soil carbon dynamics are complex and often variable [16]. Global reductions in natural SOC due to cultivation by humans are obvious, and it is estimated to cause a loss of 60 (temperate regions) to 75%

• minimization of soil and water losses by surface runoff and erosion;

Benefits of soil carbon sequestration include the following:

• It can be helpful in the reduction of atmospheric temperatures.

• It can be helpful in the reduction of CO2 emissions.

• It can reduce the emissions of different GHGs.

• It helps in maintaining suitable biotic habitat.

• It can improve soil health and productivity.

• It can increase water conservation.

• It can promote and sustain root growth.

*DOI: http://dx.doi.org/10.5772/intechopen.87107*

• use of organic amendments; and

• promotion of farm forestry.

• It decreases nutrients losses.

• It can reduce soil erosion.

higher CO2 sequestration potential.

**2. Agronomic practices**

tration are given below.

**2.1 Tillage**

fertility;


*Soil Carbon Sequestration through Agronomic Management Practices DOI: http://dx.doi.org/10.5772/intechopen.87107*


*CO2 Sequestration*

Earth's mean temperature and precipitation [6]. There is much interaction among the terrestrial and atmospheric C pools through the processes of photosynthesis and respiration. Due to land use, conversion factors, and deforestation, biotic pool also contributes in the rise of atmospheric CO2 concentration at the rate of ~1.6 Pg C per year. Different anthropogenic sources include the combustion of fossil fuel, deforestation, land use conversion, soil tillage, animal husbandry, cement manufac-

fossil fuel [6, 7], and 1.6 Pg C per year is emitted by deforestation, land-use change, and soil cultivation. It is anticipated that terrestrial ecosystems have contributed as much as half of increases in CO2 emissions from human activity in the past two centuries [4, 8], and about 50 Pg CO2 additions to the atmosphere has been contributed by cultivated soils [9], through the process of mineralization of soil organic carbon (SOC). Terrestrial C pool is estimated approximately 3120 Pg, which is the

Historically, agricultural soils have lost more than 50 Gt (1 Gt = 1 billion tons) of carbon and agriculture is responsible for soil carbon reductions up to 60–75% [9]. Total anthropogenic emission of CO2 is 9.9 Pg C per year, of which 4.2 Pg C per year is absorbed by atmosphere and 2.3 Pg C per year by the ocean while remaining may

In 1-m soil depth, estimated carbon pool is 2500 Pg, in two diverse forms including soil organic C (SOC) pool which is likely about 1550 Pg and soil inorganic C (SIC) pool at 950 Pg [10]. Soil inorganic C pool mostly consists of elemental C and carbonate minerals, i.e., calcite, dolomite, and likewise primary and secondary carbonates, whereas soil organic C (SOC) pool contains highly active humus and relatively inert charcoal C. According to United Nations Framework Convention on Climate Change (UNFCCC), carbon sequestration is the process of removing C from atmosphere and depositing it in a reservoir. It entails the transfer of atmo-

The estimation of global carbon sequestration potential of agricultural soils is typically made for sequestration on annual basis, and its range is from 0.4 to 1.2 gigatons per year [1]. Land use, land use change, and forestry (LULUCF) activities can be a relatively cost-effective ways to offset emissions through increasing removals of greenhouse gases from the atmosphere (e.g., by planting trees or managing forests) or through dropping emissions (e.g., by deforestation) [12]. Likewise, emissions of CO2 from soil can be reduced by the adoption of such practices that can increase C input in soils and similarly can lessen the decomposition potential of soil organic matter. These kinds of practices have a vital role in storage and in release of C within terrestrial C cycle [13]. Nowadays, intensive agriculture usually results in a considerable soil degradation and soil carbon depletion [14], because in present agriculture and human's food chain, intensive soil utilization is very essential but it is very imperative so it should be followed and coupled with appropriate conservation practices [15]. Agriculture sector is responsible for the emissions of about 30% global greenhouse gases emissions, and primarily, inappropriate soil and crop management practices have resulted in the loss of soil carbon. In agricultural soils,

Main agronomic and related practices that can be helpful in SOC sequestration

• adoption of environmental and soil health friendly farming systems;

is emitted by combustion of

turing, etc. According to an estimate, 8.3 Pg C year<sup>−</sup><sup>1</sup>

combination of both pedologic and biotic C pools.

be absorbed by unidentified terrestrial sinks.

spheric CO2 and its secure storage in long-lived pools [11].

C sequestration means the increase of soil C storage.

• adoption of no-tillage (NT) or minimum tillage;

• incorporation of cover crops;

**6**

include:

Benefits of soil carbon sequestration include the following:


Agriculture sector can be supportive in the lessening of emissions of GHGs, and if suitable agronomic practices are to be adopted, then agricultural soils have the potential to act as a sink for CO2 sequestration. Healthy soils can be supportive in combating the climate change because soils having high organic matter can have higher CO2 sequestration potential.

#### **2. Agronomic practices**

Different agronomic and related practices that can be supportive in CO2 sequestration are given below.

#### **2.1 Tillage**

The main aim of tillage is the physical disturbance of upper soil layers for the preparation of soil bed, incorporation of fertilizers, crop residues, and similarly to control weeds. Tillage methods in world vary depending upon the soil, climate, crop management, and availability of technology. The relationship between tillage, soil structure, and soil organic matter dynamics is essential to C sequestration ability of agricultural soils. Tillage effects on soil carbon dynamics are complex and often variable [16]. Global reductions in natural SOC due to cultivation by humans are obvious, and it is estimated to cause a loss of 60 (temperate regions) to 75%

(temporal regions) of the original SOC [17]. Conventional tillage practices led to decline in soil carbon from 30 to 50% globally [18] to low as 20% [19]. Plowing is the basic cause of SOC oxidation and emissions of CO2 to the atmosphere [20], and when NT, CP, and MP are under a nonsteady state, all these types of tillage systems may fail in the sequestration of significant amount of soil organic carbon [21]. The large losses of C typically follow initial cultivation [22, 23]. Moldboard plow, followed by secondary tillage operations, is commonly used in world, which is basically intensive tillage practice, but over the several years, intensive tillage has replaced by less intensive tillage in which soil is minimum disturbed. No tillage often increases the stability and numbers of soil aggregates, but conventional tillage is detrimental to soil structure, which increases the decomposition of soil organic matter. Conservation tillage systems keep more crop residues on the soil surface and have a higher SOC concentration in surface layer than conventional tillage [24, 25].

Tillage and cropping systems can influence microbial activity, which ultimately affects SOC dynamics and stability [26, 27], and soil mineralization can be decreased by reducing or eliminating soil tillage and increasing cropping intensity and plant production efficiency. In case of no-tillage as litter accumulates at the soil surface, which reduces evaporation from the soil because surface residues [28] and similarly standing stubbles [29] decrease wind speed at the soil surface, which ultimately results in less turbulent exchange of water and heat. Reduction in soil temperature through the use of surface mulches and no-till practices is important for maintaining stocks of soil organic matter especially in tropical soils [30].

SOC is a prime determinant of biological activity and soil macro fauna, which controls most of the different soil functions, i.e., organic matter dynamics, nutrient release, soil structure, and its different associated physical properties [31, 32]. In no-tilled soils, there are generally higher densities of biota and especially microorganisms. A large number of studies have shown that no-tillage can increase soil carbon rapidly, particularly at the soil surface [33], and this increase is linked to increases in aggregation [34, 35]. Compared to the PT and RT systems, strong SOC gradients have been observed under NT systems in the surface to subsurface layers in paddy soil. Moreover, it has been observed that the impacts of tillage on SOC concentration are dependent on crop species and soil depth in paddy soil [36]. However, according to Grandy and Robertson [37], tilling a previously untilled soil quickly losses the previously reserved carbon gains by exposing carbon molecules to microbial attack due to the disruption of aggregates. This accelerated turnover also reduces the formation and stabilization of more recalcitrant organic matter fractions within micro aggregates that have a longer residence time in soil [38]. The results of a study, which was conducted to find out the influence of conservation tillage, land configuration, and residue management practices on soil health in a Pigeon pea+ Soybean intercropping system. The study consisted of six tillage systems, i.e., CT1: conservation tillage with BBF and crop residue retained on the surface, CT2: conservation tillage with BBF and the incorporation of crop residue, CT3: conservation tillage with flatbed with crop residue retained on the surface, CT4: conservation tillage with the incorporation of crop residue, CT5: conventional tillage with the incorporation of crop residue, and CT6: conventional tillage without crop residue. The conservation treatments significantly improved soil health. The pooled data of the study showed that all the conservation tillage systems, i.e., CT1, CT2, CT3, and CT4, had significantly higher soil organic carbon at 0–15 cm depth (0.62, 0.64, 0.60, and 0.62%, respectively) and at 15–30 cm depth (0.56, 0.56, 0.54, and 0.55%, respectively) in higher soil carbon sequestrations (15.07, 15.39, 14.58, and 14.72 t ha<sup>−</sup><sup>1</sup> , respectively), over conventional systems. The study also revealed that however biological soil quality, such as soil microbial biomass carbon

**9**

*Soil Carbon Sequestration through Agronomic Management Practices*

and nitrogen, was significantly higher in all the tillage systems except conventional tillage without crop residue [39]. It is estimated that the adoption of conservation tillage globally can sequester 25 Gt C over the next 50 years, which can be helpful in

All this indicates that the adoption of conservation tillage practices can be helpful in the reductions of emissions of CO2 into the atmosphere and similarly can be

Chemical fertilizers are a source of emission of GHGs, especially N2O. In addition to it, fertilizer production and its transportation are also associated with the emissions of GHGs. Judicious use of fertilizers increases crop yields and profitability, and about 50 Pg CO2 additions to the atmosphere has been contributed by the cultivated soils [9], through the process of mineralization of soil organic carbon (SOC). The use of fertilizers has dramatically increased agricultural productivity, but studies reveal that the chronic use of nitrogen fertilization decreases soil microbial activity [41–44]. Continuous use of balanced fertilizers is necessary for sustainable soil fertility and productivity of crops [45]. Crop residues and nutrients, especially N, help in carbon sequestration up to 21.3–32.5% [46]. However, ultimate effects of continuous nitrogen fertilization on soils are complicated and remain unclear. For example, in the long-term experiments in Canada, SOC sequestration

[47]. Research in the Great Plains shows that SOC sequestration is improved by the application of N fertilization [48–52], but opposite to it, long-term experiments in the Northern Great Plains (ND) have also shown that N fertilizer increased crop residue returns but generally did not increase SOC sequestration [53]. Liu Enke et al. [54] reported the results of a long-term study which was initiated in Northwest China in 1979, to find out the effects of fertilization on SOC and SOC fractions for the whole soil profile such as (0–100 cm) soil depth. The experiment included six treatments, i.e., unfertilized (control), N fertilizer (N), nitrogen and phosphorous fertilizer (NP), straw plus N and P fertilizers (NP + S), Farmyard manure (FYM), and Farmyard manure (FYM) plus N and P fertilizers (NP+ FYM). Results showed that SOC storage in 0–60 cm in NP + FYM, NP + S, FYM, and NP treatments increased by 41.5, 32.9, 28.1, and 17.9%, respectively, as compared to control treatment. Application of organic manure plus inorganic fertilizer also enlarged labile pool in 0–60 cm soil depth. These results show that long-term applications of organic manure have the most beneficial effects in building carbon

The results of Morrow plots, which is the world's oldest experimental site under continuous corn (*Zea mays* L.), revealed that after 40–50 years of synthetic fertilization that exceeded grain N removal by 60–190%, a net decline occurred in soil C despite increasingly massive residue C incorporation, the decline being more extensive for a corn-soybean (*Glycine max* L.) or corn-oats (*Avena sativa* L.) rotations than for the continuous corn rotation and of greater intensity for the profile (0–46 cm) than the surface soil [55]. Nayak et al. (2012) [56] reported that the application of combined inorganic fertilizers with or without manure can sequester carbon in the 0–60 cm soil layer at the Indean Sub-Himalayas. Majumder et al. [57] reported the results of a study that was conducted in hot humid subtropical Eastern India. According to them after 19 years in a puddle rice-wheat (*Triticum aestivum* L.) system, NPK + FYM treated plots had 14% larger labile C pools compared with

per year in well-fertilized soils with optimum cropping systems

*DOI: http://dx.doi.org/10.5772/intechopen.87107*

the stabilization of atmospheric carbon [40].

**2.2 Nutrient management**

were 50–75 g cm<sup>−</sup><sup>2</sup>

supportive in the sequestration of carbon in the soil.

pools among the investigated types of fertilization.

the control plots in the 0–60 cm soil depth.

and nitrogen, was significantly higher in all the tillage systems except conventional tillage without crop residue [39]. It is estimated that the adoption of conservation tillage globally can sequester 25 Gt C over the next 50 years, which can be helpful in the stabilization of atmospheric carbon [40].

All this indicates that the adoption of conservation tillage practices can be helpful in the reductions of emissions of CO2 into the atmosphere and similarly can be supportive in the sequestration of carbon in the soil.

#### **2.2 Nutrient management**

*CO2 Sequestration*

(temporal regions) of the original SOC [17]. Conventional tillage practices led to decline in soil carbon from 30 to 50% globally [18] to low as 20% [19]. Plowing is the basic cause of SOC oxidation and emissions of CO2 to the atmosphere [20], and when NT, CP, and MP are under a nonsteady state, all these types of tillage systems may fail in the sequestration of significant amount of soil organic carbon [21]. The large losses of C typically follow initial cultivation [22, 23]. Moldboard plow, followed by secondary tillage operations, is commonly used in world, which is basically intensive tillage practice, but over the several years, intensive tillage has replaced by less intensive tillage in which soil is minimum disturbed. No tillage often increases the stability and numbers of soil aggregates, but conventional tillage is detrimental to soil structure, which increases the decomposition of soil organic matter. Conservation tillage systems keep more crop residues on the soil surface and have a higher SOC concentration in surface layer than conventional tillage [24, 25]. Tillage and cropping systems can influence microbial activity, which ultimately affects SOC dynamics and stability [26, 27], and soil mineralization can be decreased by reducing or eliminating soil tillage and increasing cropping intensity and plant production efficiency. In case of no-tillage as litter accumulates at the soil surface, which reduces evaporation from the soil because surface residues [28] and similarly standing stubbles [29] decrease wind speed at the soil surface, which ultimately results in less turbulent exchange of water and heat. Reduction in soil temperature through the use of surface mulches and no-till practices is important for maintaining stocks of soil organic matter especially in tropical soils [30].

SOC is a prime determinant of biological activity and soil macro fauna, which controls most of the different soil functions, i.e., organic matter dynamics, nutrient

[31, 32]. In no-tilled soils, there are generally higher densities of biota and especially microorganisms. A large number of studies have shown that no-tillage can increase soil carbon rapidly, particularly at the soil surface [33], and this increase is linked to increases in aggregation [34, 35]. Compared to the PT and RT systems, strong SOC gradients have been observed under NT systems in the surface to subsurface layers in paddy soil. Moreover, it has been observed that the impacts of tillage on SOC concentration are dependent on crop species and soil depth in paddy soil [36]. However, according to Grandy and Robertson [37], tilling a previously untilled soil quickly losses the previously reserved carbon gains by exposing carbon molecules to microbial attack due to the disruption of aggregates. This accelerated turnover also reduces the formation and stabilization of more recalcitrant organic matter fractions within micro aggregates that have a longer residence time in soil [38]. The results of a study, which was conducted to find out the influence of conservation tillage, land configuration, and residue management practices on soil health in a Pigeon pea+ Soybean intercropping system. The study consisted of six tillage systems, i.e., CT1: conservation tillage with BBF and crop residue retained on the surface, CT2: conservation tillage with BBF and the incorporation of crop residue, CT3: conservation tillage with flatbed with crop residue retained on the surface, CT4: conservation tillage with the incorporation of crop residue, CT5: conventional tillage with the incorporation of crop residue, and CT6: conventional tillage without crop residue. The conservation treatments significantly improved soil health. The pooled data of the study showed that all the conservation tillage systems, i.e., CT1, CT2, CT3, and CT4, had significantly higher soil organic carbon at 0–15 cm depth (0.62, 0.64, 0.60, and 0.62%, respectively) and at 15–30 cm depth (0.56, 0.56, 0.54, and 0.55%, respectively) in higher soil carbon sequestrations (15.07, 15.39,

, respectively), over conventional systems. The study also

revealed that however biological soil quality, such as soil microbial biomass carbon

release, soil structure, and its different associated physical properties

**8**

14.58, and 14.72 t ha<sup>−</sup><sup>1</sup>

Chemical fertilizers are a source of emission of GHGs, especially N2O. In addition to it, fertilizer production and its transportation are also associated with the emissions of GHGs. Judicious use of fertilizers increases crop yields and profitability, and about 50 Pg CO2 additions to the atmosphere has been contributed by the cultivated soils [9], through the process of mineralization of soil organic carbon (SOC). The use of fertilizers has dramatically increased agricultural productivity, but studies reveal that the chronic use of nitrogen fertilization decreases soil microbial activity [41–44]. Continuous use of balanced fertilizers is necessary for sustainable soil fertility and productivity of crops [45]. Crop residues and nutrients, especially N, help in carbon sequestration up to 21.3–32.5% [46]. However, ultimate effects of continuous nitrogen fertilization on soils are complicated and remain unclear. For example, in the long-term experiments in Canada, SOC sequestration were 50–75 g cm<sup>−</sup><sup>2</sup> per year in well-fertilized soils with optimum cropping systems [47]. Research in the Great Plains shows that SOC sequestration is improved by the application of N fertilization [48–52], but opposite to it, long-term experiments in the Northern Great Plains (ND) have also shown that N fertilizer increased crop residue returns but generally did not increase SOC sequestration [53]. Liu Enke et al. [54] reported the results of a long-term study which was initiated in Northwest China in 1979, to find out the effects of fertilization on SOC and SOC fractions for the whole soil profile such as (0–100 cm) soil depth. The experiment included six treatments, i.e., unfertilized (control), N fertilizer (N), nitrogen and phosphorous fertilizer (NP), straw plus N and P fertilizers (NP + S), Farmyard manure (FYM), and Farmyard manure (FYM) plus N and P fertilizers (NP+ FYM). Results showed that SOC storage in 0–60 cm in NP + FYM, NP + S, FYM, and NP treatments increased by 41.5, 32.9, 28.1, and 17.9%, respectively, as compared to control treatment. Application of organic manure plus inorganic fertilizer also enlarged labile pool in 0–60 cm soil depth. These results show that long-term applications of organic manure have the most beneficial effects in building carbon pools among the investigated types of fertilization.

The results of Morrow plots, which is the world's oldest experimental site under continuous corn (*Zea mays* L.), revealed that after 40–50 years of synthetic fertilization that exceeded grain N removal by 60–190%, a net decline occurred in soil C despite increasingly massive residue C incorporation, the decline being more extensive for a corn-soybean (*Glycine max* L.) or corn-oats (*Avena sativa* L.) rotations than for the continuous corn rotation and of greater intensity for the profile (0–46 cm) than the surface soil [55]. Nayak et al. (2012) [56] reported that the application of combined inorganic fertilizers with or without manure can sequester carbon in the 0–60 cm soil layer at the Indean Sub-Himalayas. Majumder et al. [57] reported the results of a study that was conducted in hot humid subtropical Eastern India. According to them after 19 years in a puddle rice-wheat (*Triticum aestivum* L.) system, NPK + FYM treated plots had 14% larger labile C pools compared with the control plots in the 0–60 cm soil depth.

It can be concluded that the appropriate use of fertilizers according to the soil condition can be helpful in the maximum sequestration of carbon along with maximum crops production and in the reductions of emissions of different GHGs.

#### **2.3 Animal manure and compost application**

Animal manure is animal's excreta which is collected from livestock farms and barnyards and is used to enrich the soil, while compost is the material which largely consists of decayed organic matter and is used for fertilizing and conditioning of agricultural soil. Application of manures is important for the maintenance of soil health [58, 59] and is the source of C, and its application to different crops fields has effects on C contents [60]. As compared with the application of only NPK, application of FYM along with NPK increased C sequestration in the rice-wheat cropping system [61], while green manuring, as compared with the application of FYM along with green manure, sequestered more C in a Maize-Wheat cropping system [62]. Composting not only increases the net primary production but also enhances the C contents of the soil [63]. It has been reported that decreasing of manures and organic fertilizers application influences not only stable organic compounds but also soil microorganisms and nutrient regimes [64, 65]. Liu et al. [53] supported the positive effect of incorporation of mineral fertilizers with organic manures. Similarly, application of different organic wastes, i.e., municipal solid waste (MSW), farm yard manure (FYM), sugar industry waste (filter cake), and maize cropping residues, at 3 t C ha<sup>−</sup><sup>1</sup> alone and with a full or half dose of NPK mineral fertilizer showed that the addition of organic wastes (filter cake or MSW) has the best potential for improving SOC retention, WUE, and wheat yield in an irrigated maize-wheat cropping system [66].

This all indicates that the use of animal manure, compost, etc. along with other inorganic fertilizers is beneficial for both soil health and environment.

#### **2.4 Crop rotations**

Crop rotations mean the sequence of crops grown in regularly recurring successions on the same area of land. The succeeding crops may be for 2 or more years. Differences in crop rotations, climates, soils, and different crop-related management practices also affect carbon sequestration. Intensive cropping systems result in the depletion of SOM, but the use of balanced fertilization with NPK, application of organic amendments, and similarly application of crop residues can increase carbon sequestration levels to 5–10 Mg ha<sup>−</sup><sup>1</sup> per year because these amendments contain 10.7–18% C, which can also be helpful in the sequestration of carbon [67]. Different legume crops, such as peas, lentils, alfalfa, chickpea, sesbania, etc., can serve as substitute sources for nitrogen. Applications of crop rotations especially by using legume cover crops, which contain carbon compounds that are likely more resistant to microbial metabolism, can make soil carbon more stable [68]. Syswerda et al. [69] reported the results of a long-term study (over a 12-year period) of an organic management system that involved various crop rotations. According to them despite of extensive tillage for weed control, increase in soil carbon sequestration was recorded. The results of a long-term study, which was conducted in Dingxi, Northwest China, during 2013–2015, were shown in-spring wheat-field pea rotation in a rain-fed semi-arid environment. The treatments were: conventional tillage with stubble removed (T); no tillage with stubble removed (NT); no-till with stubble retained (NTS), and conventional tillage with stubble incorporation (TS). The SOC, microbial biomass carbon, and root biomass in NTS increased over T and NT, and similarly, average grain yield across the 3 years in NTS was better than T and

**11**

*Soil Carbon Sequestration through Agronomic Management Practices*

NT [70]. Recently, much attention has been given to alternate tillage and cropping systems as a means to mitigate the agricultural emissions of CO2 [27, 71]. Different types of cropping systems, i.e., cover cropping, ratoon cropping, and companion cropping, can be helpful in carbon sequestration. Intercropping which includes row inter cropping, strip inter cropping, mixed cropping, and relay intercropping can increase the income and can also raise soil fertility [72]. Some of the examples of inter cropping are wheat and mustard, cotton and peanut, peanut and sunflower, wheat and chickpea, etc. [73]. Organic farming can also improve soil organic carbon as compared with the conventional farming [68, 74]. Research regarding the restoration of grassland also shows that through their biotic and biotic effects, legume species have more positive effects on the restoration of grasslands as compared with

This above shows that keeping in view the economic considerations, selection of appropriate crop rotations according to the soil and environmental conditions can be helpful in the sequestration of carbon, which not only improve soil fertility but also reduce the emissions of CO2 into the atmosphere and increase farmer's income.

Crop residues are detached vegetative parts of crop plants that are intentionally left to decay in agricultural fields after crop harvesting. Worldwide, the annual

residues are applied to the soil, it can increase the C contents of the soil, because, for example, one ton of cereal residue contains 12–20 kg N, 1–4 kg P, 7–30 kg K, 4–8 kg Ca, and 2–4 kg Mg. Mulching is detached vegetation, which includes wheat straw, compost, or may be plastic sheets, which are spread around plants to protect them from excessive evaporation and cold stress and similarly to promote SOM contents

Crop residues play an important role in the SOC management and improvement of soil quality [76]. Mulching improves soil moisture, reduces soil erosion, and similarly reduces the loss of carbon from the soil and crop residues, which are incorporated into the soil to enhance the soil organic matter. A direct seedling mulch-based cropping system increases soil organic matter, as a result of increased carbon inputs and decreased soil disturbance [27]. Mulch can increase soil organic matter (SOM) and carbon sequestration in the top 0–5 cm soil depth. It improves soil's physical and chemical properties and can increase carbon sequestration in

enhance the buildup of soil organic matter, principally as a result of increased carbon inputs and decreased soil disturbance [27]. Direct seedling straw mulch has the potential to ameliorate the heat stress, and it improves the infiltration rate, reduces evaporation [77, 78], and similarly increases soil organic carbon and N efficiency [79]. Increasing residues inputs to soils entails increasing net primary productivity (NPP). Many agricultural soils, which have been significantly reduced from their original C levels through cultivation, will show C gains in proportion to increases in C inputs. Soil C levels are governed by the balance between the inputs of C through plant residues and the losses of C basically through decomposition. Therefore, C can be increased in soil by increasing residues inputs and or reducing decomposition rates (i.e., heterotrophic soil respiration). Litter quality also affects rates of its decomposition [80]. The results of a 4-month study, which was conducted in a greenhouse controlled condition and in three rates of straw residue and farm yard manure, were added to uncultivated and cropland soils. Two treatments of straw residue and farm yard manure incorporation were used into: a soil surface layer and a 0–20 cm soil depth revealed that the application of organic matter,

tones, and if 15% of these total

per year. Mulch-based cropping systems

*DOI: http://dx.doi.org/10.5772/intechopen.87107*

the application of mineral fertilizers [75].

production of crop residues is about 3.4 × 109

agricultural soils up to 8–16 Mg ha<sup>−</sup><sup>1</sup>

**2.5 Residues management**

in soil.

*Soil Carbon Sequestration through Agronomic Management Practices DOI: http://dx.doi.org/10.5772/intechopen.87107*

NT [70]. Recently, much attention has been given to alternate tillage and cropping systems as a means to mitigate the agricultural emissions of CO2 [27, 71]. Different types of cropping systems, i.e., cover cropping, ratoon cropping, and companion cropping, can be helpful in carbon sequestration. Intercropping which includes row inter cropping, strip inter cropping, mixed cropping, and relay intercropping can increase the income and can also raise soil fertility [72]. Some of the examples of inter cropping are wheat and mustard, cotton and peanut, peanut and sunflower, wheat and chickpea, etc. [73]. Organic farming can also improve soil organic carbon as compared with the conventional farming [68, 74]. Research regarding the restoration of grassland also shows that through their biotic and biotic effects, legume species have more positive effects on the restoration of grasslands as compared with the application of mineral fertilizers [75].

This above shows that keeping in view the economic considerations, selection of appropriate crop rotations according to the soil and environmental conditions can be helpful in the sequestration of carbon, which not only improve soil fertility but also reduce the emissions of CO2 into the atmosphere and increase farmer's income.

#### **2.5 Residues management**

*CO2 Sequestration*

**2.3 Animal manure and compost application**

cropping residues, at 3 t C ha<sup>−</sup><sup>1</sup>

**2.4 Crop rotations**

maize-wheat cropping system [66].

carbon sequestration levels to 5–10 Mg ha<sup>−</sup><sup>1</sup>

It can be concluded that the appropriate use of fertilizers according to the soil condition can be helpful in the maximum sequestration of carbon along with maximum crops production and in the reductions of emissions of different GHGs.

Animal manure is animal's excreta which is collected from livestock farms and barnyards and is used to enrich the soil, while compost is the material which largely consists of decayed organic matter and is used for fertilizing and conditioning of agricultural soil. Application of manures is important for the maintenance of soil health [58, 59] and is the source of C, and its application to different crops fields has effects on C contents [60]. As compared with the application of only NPK, application of FYM along with NPK increased C sequestration in the rice-wheat cropping system [61], while green manuring, as compared with the application of FYM along with green manure, sequestered more C in a Maize-Wheat cropping system [62]. Composting not only increases the net primary production but also enhances the C contents of the soil [63]. It has been reported that decreasing of manures and organic fertilizers application influences not only stable organic compounds but also soil microorganisms and nutrient regimes [64, 65]. Liu et al. [53] supported the positive effect of incorporation of mineral fertilizers with organic manures. Similarly, application of different organic wastes, i.e., municipal solid waste (MSW), farm yard manure (FYM), sugar industry waste (filter cake), and maize

fertilizer showed that the addition of organic wastes (filter cake or MSW) has the best potential for improving SOC retention, WUE, and wheat yield in an irrigated

inorganic fertilizers is beneficial for both soil health and environment.

This all indicates that the use of animal manure, compost, etc. along with other

Crop rotations mean the sequence of crops grown in regularly recurring successions on the same area of land. The succeeding crops may be for 2 or more years. Differences in crop rotations, climates, soils, and different crop-related management practices also affect carbon sequestration. Intensive cropping systems result in the depletion of SOM, but the use of balanced fertilization with NPK, application of organic amendments, and similarly application of crop residues can increase

contain 10.7–18% C, which can also be helpful in the sequestration of carbon [67]. Different legume crops, such as peas, lentils, alfalfa, chickpea, sesbania, etc., can serve as substitute sources for nitrogen. Applications of crop rotations especially by using legume cover crops, which contain carbon compounds that are likely more resistant to microbial metabolism, can make soil carbon more stable [68]. Syswerda et al. [69] reported the results of a long-term study (over a 12-year period) of an organic management system that involved various crop rotations. According to them despite of extensive tillage for weed control, increase in soil carbon sequestration was recorded. The results of a long-term study, which was conducted in Dingxi, Northwest China, during 2013–2015, were shown in-spring wheat-field pea rotation in a rain-fed semi-arid environment. The treatments were: conventional tillage with stubble removed (T); no tillage with stubble removed (NT); no-till with stubble retained (NTS), and conventional tillage with stubble incorporation (TS). The SOC, microbial biomass carbon, and root biomass in NTS increased over T and NT, and similarly, average grain yield across the 3 years in NTS was better than T and

alone and with a full or half dose of NPK mineral

per year because these amendments

**10**

Crop residues are detached vegetative parts of crop plants that are intentionally left to decay in agricultural fields after crop harvesting. Worldwide, the annual production of crop residues is about 3.4 × 109 tones, and if 15% of these total residues are applied to the soil, it can increase the C contents of the soil, because, for example, one ton of cereal residue contains 12–20 kg N, 1–4 kg P, 7–30 kg K, 4–8 kg Ca, and 2–4 kg Mg. Mulching is detached vegetation, which includes wheat straw, compost, or may be plastic sheets, which are spread around plants to protect them from excessive evaporation and cold stress and similarly to promote SOM contents in soil.

Crop residues play an important role in the SOC management and improvement of soil quality [76]. Mulching improves soil moisture, reduces soil erosion, and similarly reduces the loss of carbon from the soil and crop residues, which are incorporated into the soil to enhance the soil organic matter. A direct seedling mulch-based cropping system increases soil organic matter, as a result of increased carbon inputs and decreased soil disturbance [27]. Mulch can increase soil organic matter (SOM) and carbon sequestration in the top 0–5 cm soil depth. It improves soil's physical and chemical properties and can increase carbon sequestration in agricultural soils up to 8–16 Mg ha<sup>−</sup><sup>1</sup> per year. Mulch-based cropping systems enhance the buildup of soil organic matter, principally as a result of increased carbon inputs and decreased soil disturbance [27]. Direct seedling straw mulch has the potential to ameliorate the heat stress, and it improves the infiltration rate, reduces evaporation [77, 78], and similarly increases soil organic carbon and N efficiency [79]. Increasing residues inputs to soils entails increasing net primary productivity (NPP). Many agricultural soils, which have been significantly reduced from their original C levels through cultivation, will show C gains in proportion to increases in C inputs. Soil C levels are governed by the balance between the inputs of C through plant residues and the losses of C basically through decomposition. Therefore, C can be increased in soil by increasing residues inputs and or reducing decomposition rates (i.e., heterotrophic soil respiration). Litter quality also affects rates of its decomposition [80]. The results of a 4-month study, which was conducted in a greenhouse controlled condition and in three rates of straw residue and farm yard manure, were added to uncultivated and cropland soils. Two treatments of straw residue and farm yard manure incorporation were used into: a soil surface layer and a 0–20 cm soil depth revealed that the application of organic matter,

especially the incorporation of farm yard manure, led to significant increase in the final soil organic carbon content, and higher amount of soil organic carbon were stored in the cropland soil than in the uncultivated soil. The results showed that carbon sequestration ranged farm yard manure > straw residue and cropland soil > uncultivated soil. The results revealed paying more attention to the role of organic residue management in carbon sequestration [81].

This all shows that the application of mulch and the use of crop residues can improve soil microbial activity, ameliorate the heat stress, and help in water storage and improvement of soil organic carbon.

#### **2.6 Cover crops**

Cover crop is grown for the benefit of soil rather than the crop yield. Cover crops improve soil quality by increasing soil organic carbon through biomass, by improving soil aggregates and stability, and by protecting the soil from surface runoff. Similarly, green manuring increases the biomass returned to the soil, which results in the form of enlarged soil carbon sink. Studies reveal that the adoption of cover crops is an efficient measure to mitigate climate change [82]. According to Olson 2010 [83], the use of cover crops in intensive row crop rotations with different tillage treatments has been found to sequester soil organic carbon (SOC). Kenneth et al. [84] reported the results of a study which included different kinds of tillages, i.e., no-till (NT), Chisel plow (CP), and moldboard plow (MP) with and without cover crops. The average annual corn and soybean yields were statistically same with or without cover crops. The average annual corn and soybean yields were statistically same for NT, CP, and MP systems with or without cover crops for the same soil depth layer and for tillage treatments. However, all tillage treatments, i.e., NT, CP, and MP, sequestered SOC with cover crops.

Keeping in view the cropping systems, suitable selection and planting of cover crops can be helpful in improving the soil organic carbon.

#### **2.7 Use of improved crop varieties**

Selection of improved varieties of different crops, which can improve both above and below ground biomass, can also improve the soil organic carbon. Machado et al. [85] reported that crop species that have massive rooting systems have the potential to improve SOC in soils under NT. Similarly, according to Kell [86, 87] by improving root growth in agricultural crops, soil carbon storage can match anthropogenic emissions for the next 40 years. This all indicates that the use of improved crop varieties having extensive root systems and better yields can increase both yields and soil fertility.

#### **2.8 Soil biota management**

Soil microbial activities can be helpful in the biological carbon sequestration because microbes improve the soil physical, chemical, and biological properties. The soil biota consists of a large number and a range of micro- and macroorganisms and is the living part of soils. They interact with each other and with plants, directly providing nutrition and other benefits. Their physical structure and products help a large to soil structure. They are also responsible for organic matter decomposition and for the transformations of organically bound nitrogen and minerals that are available to plants. Through biological control mechanisms, these organisms regulate their own populations and as well as those of incoming microorganisms. Micro- and macro-organisms are very crucial in maintaining

**13**

*Soil Carbon Sequestration through Agronomic Management Practices*

that carbon sequestration was higher up to 49.9 g C kg<sup>−</sup><sup>1</sup>

soil carbon sequestration and improve the crops yields.

**2.9 Bio char**

**2.10 Agroforestry**

and 228 Mg ha<sup>−</sup><sup>1</sup>

ecosystem function, and their populations are significantly affected by the different crop management practices. Microorganisms include bacteria, fungi, fungi, protozoa, and some nematodes. These also include a range of invertebrates such as micro- and macro-arthropods, termites, and earthworms. According to an estimate, micro-organisms constitute about one quarter of the total biomass on the Earth [88]. These organisms are affected by the management of soils in the agricultural and forest ecosystems. Soils also differ in their ability to support the survival and growth of different groups of micro- and macro-organisms. Research findings show

soil microbes such as soil bacteria and fungi [89]. Therefore, the use of different kinds of microbes, which are beneficial both for soil and environment, will increase

Bio char is carbonized biomass, which is obtained from sustainable sources and sequestered in soils. It can also be obtained by pyrolysis synthetically. Application of Bio char can also improve the soil health through carbon sequestration, because it improves the crop yield and maintains the cation exchange capacity, water holding, and nutrient retention capacity of the soil. It remains stable for thousands of years and thus reduces the release of terrestrial C to the atmosphere in the form of CO2 [90]. It has been reported that Bio char can improve carbon sequestration in soil due to prolonged residence time [91]. Another study also reveals that the application of Bio char reduces the co-localization of polysaccharides-carbon and aromatic carbon by reducing the carbon metabolism due to carbon stabilization in Bio char-activated soil [92]. It has also been reported that soil management by using different kinds of organic amendments and their incorporation by earthworms can also support

micro-aggregates formation, C, and N retention in agricultural soils [93].

Agroforestry is the combination of agriculture and forestry in which perennial trees and shrubs are grown in combination with agricultural crops. Planting of different kinds of trees, including orchards, fruit plants, and woodlands into the croplands, can improve soil carbon sequestration. Agroforestry has an enormous potential for carbon sequestration in croplands [94] because agroforestry practices accumulate more C than forests and pastures because they have both forest and grassland sequestration and storage patterns active [95–97]. Young [98] have also reported the estimated potential of C gains from agroforestry. Agricultural soils can sequester more quantities of carbon by the adoption of agroforestry. The carbon sequestrations potential of agroforestry systems is estimated between 12

about 1.1–2.2 Pg C can be sequestered in the agricultural soils in the next 50 years [99]. The results of a meta-analysis from 53 published studies, regarding changes in soil organic carbon (SOC) stocks at 0–15, 0–30, 0–60, 0–100, and 0 ≥ 100 cm, after land conversion to agroforestry, revealed a significant decline in the SOC stocks of 26 and 24% in land-use changes from forest to agroforestry at 0–15 and 0–30 cm, respectively. The transition from agriculture to agroforestry significantly enhanced the SOC stock of 26, 40, and 34% at 0–15, 0–30, and 0–100 cm, respectively. The results also showed that conversion from pasture/grassland to agroforestry produced significant SOC stock increases at 0–30 cm (9%) and 0–30 cm (10%). Switching from uncultivated/other land-uses to agroforestry increased SOC by 25%

at 0–30 cm, while a decrease was observed at 0–60 cm (23%) [100].

, so on the Earth's total suitable area for crop production, a total of

in soils which were rich in

*DOI: http://dx.doi.org/10.5772/intechopen.87107*

*Soil Carbon Sequestration through Agronomic Management Practices DOI: http://dx.doi.org/10.5772/intechopen.87107*

ecosystem function, and their populations are significantly affected by the different crop management practices. Microorganisms include bacteria, fungi, fungi, protozoa, and some nematodes. These also include a range of invertebrates such as micro- and macro-arthropods, termites, and earthworms. According to an estimate, micro-organisms constitute about one quarter of the total biomass on the Earth [88]. These organisms are affected by the management of soils in the agricultural and forest ecosystems. Soils also differ in their ability to support the survival and growth of different groups of micro- and macro-organisms. Research findings show that carbon sequestration was higher up to 49.9 g C kg<sup>−</sup><sup>1</sup> in soils which were rich in soil microbes such as soil bacteria and fungi [89]. Therefore, the use of different kinds of microbes, which are beneficial both for soil and environment, will increase soil carbon sequestration and improve the crops yields.

#### **2.9 Bio char**

*CO2 Sequestration*

**2.6 Cover crops**

especially the incorporation of farm yard manure, led to significant increase in the final soil organic carbon content, and higher amount of soil organic carbon were stored in the cropland soil than in the uncultivated soil. The results showed that carbon sequestration ranged farm yard manure > straw residue and cropland soil > uncultivated soil. The results revealed paying more attention to the role of organic

This all shows that the application of mulch and the use of crop residues can improve soil microbial activity, ameliorate the heat stress, and help in water storage

Cover crop is grown for the benefit of soil rather than the crop yield. Cover crops improve soil quality by increasing soil organic carbon through biomass, by improving soil aggregates and stability, and by protecting the soil from surface runoff. Similarly, green manuring increases the biomass returned to the soil, which results in the form of enlarged soil carbon sink. Studies reveal that the adoption of cover crops is an efficient measure to mitigate climate change [82]. According to Olson 2010 [83], the use of cover crops in intensive row crop rotations with different tillage treatments has been found to sequester soil organic carbon (SOC). Kenneth et al. [84] reported the results of a study which included different kinds of tillages, i.e., no-till (NT), Chisel plow (CP), and moldboard plow (MP) with and without cover crops. The average annual corn and soybean yields were statistically same with or without cover crops. The average annual corn and soybean yields were statistically same for NT, CP, and MP systems with or without cover crops for the same soil depth layer and for tillage treatments. However, all tillage treatments, i.e.,

Keeping in view the cropping systems, suitable selection and planting of cover

Selection of improved varieties of different crops, which can improve both above and below ground biomass, can also improve the soil organic carbon. Machado et al. [85] reported that crop species that have massive rooting systems have the potential to improve SOC in soils under NT. Similarly, according to Kell [86, 87] by improving root growth in agricultural crops, soil carbon storage can match anthropogenic emissions for the next 40 years. This all indicates that the use of improved crop varieties having extensive root systems and better yields can

Soil microbial activities can be helpful in the biological carbon sequestration because microbes improve the soil physical, chemical, and biological properties. The soil biota consists of a large number and a range of micro- and macroorganisms and is the living part of soils. They interact with each other and with plants, directly providing nutrition and other benefits. Their physical structure and products help a large to soil structure. They are also responsible for organic matter decomposition and for the transformations of organically bound nitrogen and minerals that are available to plants. Through biological control mechanisms, these organisms regulate their own populations and as well as those of incoming microorganisms. Micro- and macro-organisms are very crucial in maintaining

residue management in carbon sequestration [81].

NT, CP, and MP, sequestered SOC with cover crops.

**2.7 Use of improved crop varieties**

increase both yields and soil fertility.

**2.8 Soil biota management**

crops can be helpful in improving the soil organic carbon.

and improvement of soil organic carbon.

**12**

Bio char is carbonized biomass, which is obtained from sustainable sources and sequestered in soils. It can also be obtained by pyrolysis synthetically. Application of Bio char can also improve the soil health through carbon sequestration, because it improves the crop yield and maintains the cation exchange capacity, water holding, and nutrient retention capacity of the soil. It remains stable for thousands of years and thus reduces the release of terrestrial C to the atmosphere in the form of CO2 [90]. It has been reported that Bio char can improve carbon sequestration in soil due to prolonged residence time [91]. Another study also reveals that the application of Bio char reduces the co-localization of polysaccharides-carbon and aromatic carbon by reducing the carbon metabolism due to carbon stabilization in Bio char-activated soil [92]. It has also been reported that soil management by using different kinds of organic amendments and their incorporation by earthworms can also support micro-aggregates formation, C, and N retention in agricultural soils [93].

#### **2.10 Agroforestry**

Agroforestry is the combination of agriculture and forestry in which perennial trees and shrubs are grown in combination with agricultural crops. Planting of different kinds of trees, including orchards, fruit plants, and woodlands into the croplands, can improve soil carbon sequestration. Agroforestry has an enormous potential for carbon sequestration in croplands [94] because agroforestry practices accumulate more C than forests and pastures because they have both forest and grassland sequestration and storage patterns active [95–97]. Young [98] have also reported the estimated potential of C gains from agroforestry. Agricultural soils can sequester more quantities of carbon by the adoption of agroforestry. The carbon sequestrations potential of agroforestry systems is estimated between 12 and 228 Mg ha<sup>−</sup><sup>1</sup> , so on the Earth's total suitable area for crop production, a total of about 1.1–2.2 Pg C can be sequestered in the agricultural soils in the next 50 years [99]. The results of a meta-analysis from 53 published studies, regarding changes in soil organic carbon (SOC) stocks at 0–15, 0–30, 0–60, 0–100, and 0 ≥ 100 cm, after land conversion to agroforestry, revealed a significant decline in the SOC stocks of 26 and 24% in land-use changes from forest to agroforestry at 0–15 and 0–30 cm, respectively. The transition from agriculture to agroforestry significantly enhanced the SOC stock of 26, 40, and 34% at 0–15, 0–30, and 0–100 cm, respectively. The results also showed that conversion from pasture/grassland to agroforestry produced significant SOC stock increases at 0–30 cm (9%) and 0–30 cm (10%). Switching from uncultivated/other land-uses to agroforestry increased SOC by 25% at 0–30 cm, while a decrease was observed at 0–60 cm (23%) [100].

#### *CO2 Sequestration*

The carbon sequestration potential by agroforestry is estimated up to 9, 21, 50, and 63 Mg Cha<sup>−</sup><sup>1</sup> in semiarid, subhumid, humid, and temperate regions, respectively; however, it has been reported that intensively managed agroforestry practice in combination with annual crops is like conventional agriculture, which does not contribute in carbon sequestration [101].

Agroforestry also helps in the optimization of water use, and similarly, it improves the farmer's income. So, the promotion of agroforestry keeping in view the soil condition, climate, and along with crops production is beneficial for soil, environment, as well as the farmers.

#### **3. Conclusion**

CO2 is increasing at the rate of 2.3 ppm per year, which is resulting in the increase of global warming and environmental pollution. Agriculture sector is responsible for up to 30% emission of GHGs. Sustainable agriculture is essential for the survival of humankind. Adoption of different agronomic management practices can be helpful in the sequestration of carbon. Such practices include no-tillage or reduced tillage, nutrient management, cover crops, crop rotations, green manuring, application of animal manures, agroforestry, etc. Adoption of these different agronomic practices will not only improve the crops yields but will also improve farmer's income.

#### **Author details**

Sikander Khan Tanveer1 \*, Xingli Lu2 , Shamim-Ul-Sibtain Shah3 , Imtiaz Hussain1 and Muhammad Sohail4

1 Wheat Program, Crop Sciences (CSI), PARC–National Agricultural Research Center (NARC), Islamabad, Pakistan

2 College of Agronomy Ningxia Agriculture University, P.R China

3 Directorate of Farm Operations and Services, National Agricultural Research Center (NARC), Islamabad, Pakistan

4 Plant Physiology Program, Crop Sciences (CSI), PARC–National Agricultural Research Center (NARC), Islamabad, Pakistan

\*Address all correspondence to: sikander73@hotmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**15**

pp. 393-408

*Soil Carbon Sequestration through Agronomic Management Practices*

[9] Lal R. Sequestering carbon in soils of agro-ecosystems. Food Policy.

[10] Batjes NH. Total C and N in soils of the world. European Journal of Soil

[11] UNFCCC. Report of the Conference of Parties on its Thirteenth Session, Bali, Indonesia. Geneva: United Nations Framework Convention on Climate

[12] UNFCCC.2012. Land Use, Land Use Change and Forestry (LULUCF). Available from: http:// Unfcccint/ methods\_and\_Science/lulucf/

[13] Lal R, Kimble JK, Levin E, Stewart BA, editors. Advances in Soil Science: Soil Management and Greenhouse Effect. Boca Ratoon, FL:

Lewis Publishers; 1995. p. 93

[14] Plaza- Bonilla D, José Luis A,

[15] Lal R. Enhancing crop yields in the developing counteries through restoration of soil organic carbon pool in agricultural lands. Land Degradation and Development. 2006;**2**(17):197-209.

[16] Sombrero A, de Benito A. Carbon accumulation in soil. Ten-year study of conservation tillage and crop rotation in semi-arid area of castle- Leonion Spain. Soil and Tillage Research.

[17] Lal R. Soil carbon sequestration impacts on global climate change

DOI: 10.1002/Idr-696

2010;**107**:64-70

Cantero-Martinez C, Fanlo R, Iglesias A, Alvaro-Fuentes J. Carbon management in dryland agricultural systems. A review. Agronomy for Sustainable Development. 2015;**35**(4):1319-1334. DOI: 10.10007/s 13593-015-0326-x

2011;**36**:S33-S39

Change; 2007

items/3060.php

Science. 1996;**47**:151-163

*DOI: http://dx.doi.org/10.5772/intechopen.87107*

[1] Lal R. Soil carbon sequestration to mitigate climate change. Geoderma.

[2] Sun Y, Huangs YUX, Zhang W. Stability and saturation of soil organic carbon in rice fields: Evidence from a long-term fertilization experiment in subtropical China. Journal of Soils and Sediments. 2013;**13**(8):1307-1334.

DOI: 10.1007/s 11368-013-0741

[3] Yang R, Y-z S, Wang T, Yang Q. Effect of chemical and organic fertilization on soil carbon and nitrogen accumulation in a newly cultivated farmland. Journal of Integrative Agriculture.

2016;**15**(3):658-666. DOI: 10.1016/S

[4] Post WM, Peng T-H, Emanuel WR, King AW, Dale VH, De Angelis DL. The

global carbon cycles. American Scientist. 1990;**78**:310-326

[5] Eswaran H, Van Den Berg E, Reich PF. Organic carbon in the soils of the world. Soil Science Society of America Journal. 1993;**57**:192-194

[6] IPCC. Climate Change 2007. The Fourth Assessment Report. The Physical Science Basis. Cambridge, United Kingdom: Cambridge University Press; 2007

[7] WMO. Greenhouse Gas Bulletin: The State of the Art Greenhouse Gases in the Atmosphere until December. Geneva: World Meteorological Organization; 2010. p. 2009

[8] Houghton RA, Skole DL. Carbon. In: Turner BL, Clark WC, Kates RW, Richards JF, Mathews JT, Meyer WB, editors. The Earth as Transformed by Human Action. Cambridge UK: Cambridge University Press; 1990.

2095-3119(15)61107-8

**References**

2004;**123**:1-22

*Soil Carbon Sequestration through Agronomic Management Practices DOI: http://dx.doi.org/10.5772/intechopen.87107*

#### **References**

*CO2 Sequestration*

and 63 Mg Cha<sup>−</sup><sup>1</sup>

**3. Conclusion**

contribute in carbon sequestration [101].

environment, as well as the farmers.

**Author details**

farmer's income.

Sikander Khan Tanveer1

and Muhammad Sohail4

Center (NARC), Islamabad, Pakistan

Center (NARC), Islamabad, Pakistan

Research Center (NARC), Islamabad, Pakistan

provided the original work is properly cited.

\*Address all correspondence to: sikander73@hotmail.com

\*, Xingli Lu2

2 College of Agronomy Ningxia Agriculture University, P.R China

1 Wheat Program, Crop Sciences (CSI), PARC–National Agricultural Research

The carbon sequestration potential by agroforestry is estimated up to 9, 21, 50,

tively; however, it has been reported that intensively managed agroforestry practice in combination with annual crops is like conventional agriculture, which does not

Agroforestry also helps in the optimization of water use, and similarly, it improves the farmer's income. So, the promotion of agroforestry keeping in view the soil condition, climate, and along with crops production is beneficial for soil,

CO2 is increasing at the rate of 2.3 ppm per year, which is resulting in the increase of global warming and environmental pollution. Agriculture sector is responsible for up to 30% emission of GHGs. Sustainable agriculture is essential for the survival of humankind. Adoption of different agronomic management practices can be helpful in the sequestration of carbon. Such practices include no-tillage or reduced tillage, nutrient management, cover crops, crop rotations, green manuring, application of animal manures, agroforestry, etc. Adoption of these different agronomic practices will not only improve the crops yields but will also improve

in semiarid, subhumid, humid, and temperate regions, respec-

3 Directorate of Farm Operations and Services, National Agricultural Research

4 Plant Physiology Program, Crop Sciences (CSI), PARC–National Agricultural

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

, Shamim-Ul-Sibtain Shah3

, Imtiaz Hussain1

**14**

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[3] Yang R, Y-z S, Wang T, Yang Q. Effect of chemical and organic fertilization on soil carbon and nitrogen accumulation in a newly cultivated farmland. Journal of Integrative Agriculture. 2016;**15**(3):658-666. DOI: 10.1016/S 2095-3119(15)61107-8

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pp. 194-220

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[19] Sharma PK, Bhushan L, Ladha JK, Naresh RK, Gupta RK, Balasubramanian V, et al. Crop - water relations in rice-wheat systems and water management practices in a marginally sodic, medium textured soil. In: Bouman et al., editors. Waterwise rice production. LOS Banos (Philippines): International Rice Research Institute; 2000. pp. 223-235

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[21] Olson KR. Impacts of tillage, slope and erosion on soil organic carbon retention. Soil Science. 2010;**175**:562- 567. DOI: 10.1097/SS.09o13e3181foc 2837.

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[23] Haas HJ, Evans CE, Miles EF. Nitrogen and carbon changes in Great Plains soils as influenced by cropping and soil treatments. Technical Bulletin No.1164 USDA, State Agricultural

[24] Drury CF, Tan CS, Welacky TW, Oloya TO, Hamil AS, Weaver SE. Red clover and tillage influence on soil temperature, water content, and corn emergence. Agronomy Journal.

Experiment Stations; 1957

1993;**20**:161-164

1999;**19**:101-108

[18] Schlesinger WH. Changes in soil carbon storage and associated properties with disturbance and recovery. In: Trabalha JR, Reichle DE, editors. The changing carboncycle: A global analysis. New York: Springer-Verlag; 1985.

[25] Huchinson JJ, Campbell CA, Desjardins RL. Some perspectives on carbon sequesteration in

[26] Scow KM. Soil microbial

[27] Paustian K, Collins HP, Paul EA. Management controls on soil carbon. In: Paul EA, Paustin K, Elliott ET, Cole CV, editors. Soil Organic Matter in Temperate Agroecosystems. Boca Raton, and FL: CRC Press; 1997.

[28] Bond JJ, Willis WO. Soil water evaporation: Surface residue rate and placement effects. Soil Science Society of America Proceedings.

[29] Smika DE. Soil water change as related to position of wheat straw mulchon soil surface. Soil Science Society of America Journal.

[30] Lal R. Conservation tillage for sustainable agriculture: Tropic Vs. temperate environments. Advances in

[31] Lavelle P, Spain AV. Soil Ecology. Dordrecht, The Netherlands: Kluwer Academic Publishers; 2001. p. 654

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Agronomy. 1989;**42**:84-191

[32] Blanchart E, Albrecht A,

[33] West TO, Post WM. Soil organic carbon by tillage and crop rotation: A global data analysis. Soil Science Society of America Journal.

2002;**66**(6):1930-1946

2007;**142**:288-307

pp. 15-49

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1983;**47**:988-991

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[39] Naveen Kumar BT, Babalad HB. Soil organic carbon, carbon sequestration, soil microbial biomass carbon and nitrogen and soil enzymatic activity as influenced by conservation agriculture in pigeonpea and soybean intercropping system. International Journal of Current Microbiology and Applied Sciences. 2018;**7**(03):323-333. DOI: 10.20546/ ijcmas.2018.703.038

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[43] Ramirez KS, Craine JM, Fierer N. Consistent effects of nitrogen amendments on soil microbial communities and processes across biomes. Global Change Biology. 2012;**18**(6):1918-1927

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[50] Halvorson AD, Reule CA, Follet RF. Nitrogen fertilization effects on soil carbon and nitrogen in a dryland cropping systems. Soil Science Society of America Journal. 1999c;**63**:912-917

[51] Halvorson AD, A-Reule C, Murphy LS. No-tillage and N fertilizer enhance soil carbon sequestration. Journal of Fluid. 2000c;**8**:8-11

[52] Nyborg M, Solberg ED, Malhi SS, Izaaurralde RC. Fertilizer N, crop residue, and tillage after soil C and N contents after a decade. In: Lal R et al., editors. Advances in Soil Science: Soil Management and Greenhouse Effect. Boca Raton FL: Lewis Publishers, CRC Press; 1995. pp. 93-100

[53] Halvorson AD, Weinhold BJ, Black AL. Tillage, nitrogen and cropping systems effects on soil carbon sequestration. Soil Science Society of America Journal. 2002;**66**:906-912

[54] Liu E, Yan C, Mei X, Zhang Y, Fan T. Long-term effect of manure and fertilizer on soil organic carbon pools in dryland farming in Northwest China. PloS One. 2013;**8**(2):e56536. DOI: 10.1371/Journal pone.0056536

[55] Khan S, Mulvaney RL, Ellsworth T, Boast CW. The myth of nitrogen fertilization for soil carbon sequestration. Journal of Environmental Quality. 2007;**36**(6):1821-1832

[56] Nayak AK, Gangwar B, Shukla AK, Muzumdar SP, etal KA. Long-term effect of different integrated nutrient management on soil organic carbon and its fractions on soil organic carbon and its fractions and substainability of rice-wheat systems in indo Gangetic

Plains of India. Field Crops Research. 2012;**127**:129-139

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[58] Schlesinger WH. Carbon sequestration in soils. Science. 1999;**284**:2095

[59] Baker JM, Ochsner TE, Venterea RT, Griffis TJ. Tillage and soil carbon sequestration – What do we really know? Agriculture, Ecosystems and Environment. 2007;**118**:1-5

[60] Stewart CE, Paustian K, Conant RT, Plante AF, Six J. Soil C sequestration: Concept, evidence and evaluation. Biogeochemistry. 2007;**86**:19-31

[61] Naresh RK, Gupta RK, Minhas PS, Rathore RS, Ashish D, Purushottam V. Climate change and challenges of water and food security for smallholder farmers of Uttar Pradesh and mitigation through C sequestration in agricultural lands: An overview. International Journal of Chemical Studies. 2017;**5**(2):221-236

[62] Kukal SS, Rasool R, Benbi DK. Soil organic C sequestration in relation to organic and inorganic fertilization in rice-wheat and maize-wheat systems. Soil and Tillage Research. 2009;**102**:87-92

[63] Baldi E, Cavani L, Margon A, Quartieri M, Sorrenti G, Marzadori C, et al. Effect of compost application on the dynamics of C in a nectarine orchard ecosystem. Science of the Total Environment. 2018;**162**:239-248

[64] Zhang W, Xu M, Wang X, Huang Q, Nie J, Li Z, et al. Effects of organic amendments on soil carbon

**19**

2001;**61**:77-92

*Soil Carbon Sequestration through Agronomic Management Practices*

Cropping. 2009. Available from: http:// archaeology.About.com/od/history of agriculture/qt/mixed cropping.Html

[73] Anon, "Mixed Cropping". Available from: http://Simple.wikipedia.Org/wiki/

[Accessed: 28 March 2010]

Mixed\_Cropping.Html

[74] Kowatsuzali M, Syuaib MF. Comparison of the farming systems and carbon sequestration between conventional and organic rice production in West Java, Indonesia. Sustainability. 2010;**2**:833-843

[75] De Deyn GB, Shiel RS, Ostle NJ, McNamara NP, Oakley S, Young I, et al. Additional carbon sequestration

restoration. Journal of Applied Ecology.

[77] Lal R. Role of Mulching Techniques in Tropical Soil and Water Management. Ibadan, Nigeria: Tech. Bull ITTA; 1975

[78] Lal R. Tillage in lowland rice-based cropping systems. In: Soil Physics and Rice. Philippines: IRRI; 1985.

[79] Hobbs PR, Gupta RK. Sustainable resource management intensively cultivated irrigated rice-wheat cropping systems of the Indo-Gangetic Plains of South Asia. Strategies and options. In: Singh AK, editor. Proceedings of the International Conference on Managing Resources For Sustainable Agricultural Production. In the 21st century. New Delhi, India 14-18 February 2000. New

[76] Chen Zhang-du, Zhang Hai-lin, Dikgwatlhe S-Batsile, Xue Jian-fu, Qiu Kang-Chang, Tang H ai-ming, et al. Soil carbon storage and stratification under different tillage/residue – Management practices in double rice cropping system. Journal of Integrative Agriculture. 2015:1-16. Advance on line publication. DOI: 10.1016/

benefit, of grassland diversity

2011;**48**:600-608

s2095-3119(15)61068-1

pp. 283-307

*DOI: http://dx.doi.org/10.5772/intechopen.87107*

[65] Ren T, Wang J, Chen Q, et al. The effects of manure and nitrogen fertilizer application on soil organic carbon and nitrogen in a high input cropping system. PloS One. 2014;**9**(5):e97732. DOI: 10.1371/journal.pone 0097732

sequestration in paddy fields of subtropical China. Journal of Soils and Sediments. 2012;**12**(4):457-470. DOI:

10.1007/s11368-011-0467-8

[66] Shehzadi S, Shah Z,

2017;**21**(1):36-49

Mohammad W. Impact of organic amendments on soil carbon

sequestration, water use efficiency and yield of irrigated wheat. Biotechnology, Agronomy, Society and Environment.

[67] Manadal B et al. The potential of cropping systems and soil amendments for carbon sequestration in soils under long-term experiments in subtropical India. Global Change Biology;**13**:357-369

[68] Wickings K, Grandy AS, Read SC, Cleveland CC. The origin of litter chemical complexity during decomposition (Njohnson Ed.). Ecology

Letters. 2012;**15**(10):1180-1188

[69] Syswerda SP, Corbin AT, Mokma DL, Kravchenko AN,

Roberson GP. Agricultural management and soil carbon storage in surfaces vs deep layers. Soil Science Society of America Journal. 2011;**75**(1):92

[70] Yeboah S, Zhang R, Cai L, Li L, Xie J, Lou Z, et al. Tillage effect on soil organic carbon, microbial biomass carbon and crop yield in spring wheat – field pea rotation. Plant, Soil and Environment. 2016;**62**(6):279-285

[71] Follet RF. Soil management concepts and carbon sequesteration in cropland soils. Soil and Tillage Research.

[72] Hirts KKK. Mixed Cropping,

Agricultural Techniques Known as Mixed

*Soil Carbon Sequestration through Agronomic Management Practices DOI: http://dx.doi.org/10.5772/intechopen.87107*

sequestration in paddy fields of subtropical China. Journal of Soils and Sediments. 2012;**12**(4):457-470. DOI: 10.1007/s11368-011-0467-8

*CO2 Sequestration*

2000a;**80**:179-192

Blomert B. Organic C accumulation in soil over 30 years in semi-arid southern western Saskatchewan- effect of crop rotations and fertilizers. Canadian Journal of Soil Science.

Plains of India. Field Crops Research.

Bandyopadhyay PK, Gangopadhyay A, Mani PK, et al. Organic amendments influence soil organic carbon pools and rice-wheat productivity. Soil Science Society of America Journal.

[59] Baker JM, Ochsner TE, Venterea RT, Griffis TJ. Tillage and soil carbon sequestration – What do we really know? Agriculture, Ecosystems and

[60] Stewart CE, Paustian K, Conant RT, Plante AF, Six J. Soil C sequestration: Concept, evidence and evaluation. Biogeochemistry. 2007;**86**:19-31

[57] Majumder B, Mandal B,

[58] Schlesinger WH. Carbon sequestration in soils. Science.

Environment. 2007;**118**:1-5

[61] Naresh RK, Gupta RK,

Studies. 2017;**5**(2):221-236

2009;**102**:87-92

Minhas PS, Rathore RS, Ashish D, Purushottam V. Climate change and challenges of water and food security for smallholder farmers of Uttar Pradesh and mitigation through C sequestration in agricultural lands: An overview. International Journal of Chemical

[62] Kukal SS, Rasool R, Benbi DK. Soil organic C sequestration in relation to organic and inorganic fertilization in rice-wheat and maize-wheat systems. Soil and Tillage Research.

[63] Baldi E, Cavani L, Margon A, Quartieri M, Sorrenti G, Marzadori C, et al. Effect of compost application on the dynamics of C in a nectarine orchard ecosystem. Science of the Total

Environment. 2018;**162**:239-248

[64] Zhang W, Xu M, Wang X, Huang Q, Nie J, Li Z, et al. Effects of organic amendments on soil carbon

2012;**127**:129-139

2008;**72**:775-785

1999;**284**:2095

[50] Halvorson AD, Reule CA,

[51] Halvorson AD, A-Reule C,

Press; 1995. pp. 93-100

[53] Halvorson AD, Weinhold BJ,

systems effects on soil carbon

Black AL. Tillage, nitrogen and cropping

sequestration. Soil Science Society of America Journal. 2002;**66**:906-912

[54] Liu E, Yan C, Mei X, Zhang Y, Fan T. Long-term effect of manure and fertilizer on soil organic carbon pools in dryland farming in Northwest China. PloS One. 2013;**8**(2):e56536. DOI: 10.1371/Journal pone.0056536

[55] Khan S, Mulvaney RL,

Quality. 2007;**36**(6):1821-1832

Ellsworth T, Boast CW. The myth of nitrogen fertilization for soil carbon sequestration. Journal of Environmental

[56] Nayak AK, Gangwar B, Shukla AK, Muzumdar SP, etal KA. Long-term effect of different integrated nutrient management on soil organic carbon and its fractions on soil organic carbon and its fractions and substainability of rice-wheat systems in indo Gangetic

Follet RF. Nitrogen fertilization effects on soil carbon and nitrogen in a dryland cropping systems. Soil Science Society of America Journal. 1999c;**63**:912-917

Murphy LS. No-tillage and N fertilizer enhance soil carbon sequestration. Journal of Fluid. 2000c;**8**:8-11

[52] Nyborg M, Solberg ED, Malhi SS, Izaaurralde RC. Fertilizer N, crop residue, and tillage after soil C and N contents after a decade. In: Lal R et al., editors. Advances in Soil Science: Soil Management and Greenhouse Effect. Boca Raton FL: Lewis Publishers, CRC

**18**

[65] Ren T, Wang J, Chen Q, et al. The effects of manure and nitrogen fertilizer application on soil organic carbon and nitrogen in a high input cropping system. PloS One. 2014;**9**(5):e97732. DOI: 10.1371/journal.pone 0097732

[66] Shehzadi S, Shah Z, Mohammad W. Impact of organic amendments on soil carbon sequestration, water use efficiency and yield of irrigated wheat. Biotechnology, Agronomy, Society and Environment. 2017;**21**(1):36-49

[67] Manadal B et al. The potential of cropping systems and soil amendments for carbon sequestration in soils under long-term experiments in subtropical India. Global Change Biology;**13**:357-369

[68] Wickings K, Grandy AS, Read SC, Cleveland CC. The origin of litter chemical complexity during decomposition (Njohnson Ed.). Ecology Letters. 2012;**15**(10):1180-1188

[69] Syswerda SP, Corbin AT, Mokma DL, Kravchenko AN, Roberson GP. Agricultural management and soil carbon storage in surfaces vs deep layers. Soil Science Society of America Journal. 2011;**75**(1):92

[70] Yeboah S, Zhang R, Cai L, Li L, Xie J, Lou Z, et al. Tillage effect on soil organic carbon, microbial biomass carbon and crop yield in spring wheat – field pea rotation. Plant, Soil and Environment. 2016;**62**(6):279-285

[71] Follet RF. Soil management concepts and carbon sequesteration in cropland soils. Soil and Tillage Research. 2001;**61**:77-92

[72] Hirts KKK. Mixed Cropping, Agricultural Techniques Known as Mixed Cropping. 2009. Available from: http:// archaeology.About.com/od/history of agriculture/qt/mixed cropping.Html [Accessed: 28 March 2010]

[73] Anon, "Mixed Cropping". Available from: http://Simple.wikipedia.Org/wiki/ Mixed\_Cropping.Html

[74] Kowatsuzali M, Syuaib MF. Comparison of the farming systems and carbon sequestration between conventional and organic rice production in West Java, Indonesia. Sustainability. 2010;**2**:833-843

[75] De Deyn GB, Shiel RS, Ostle NJ, McNamara NP, Oakley S, Young I, et al. Additional carbon sequestration benefit, of grassland diversity restoration. Journal of Applied Ecology. 2011;**48**:600-608

[76] Chen Zhang-du, Zhang Hai-lin, Dikgwatlhe S-Batsile, Xue Jian-fu, Qiu Kang-Chang, Tang H ai-ming, et al. Soil carbon storage and stratification under different tillage/residue – Management practices in double rice cropping system. Journal of Integrative Agriculture. 2015:1-16. Advance on line publication. DOI: 10.1016/ s2095-3119(15)61068-1

[77] Lal R. Role of Mulching Techniques in Tropical Soil and Water Management. Ibadan, Nigeria: Tech. Bull ITTA; 1975

[78] Lal R. Tillage in lowland rice-based cropping systems. In: Soil Physics and Rice. Philippines: IRRI; 1985. pp. 283-307

[79] Hobbs PR, Gupta RK. Sustainable resource management intensively cultivated irrigated rice-wheat cropping systems of the Indo-Gangetic Plains of South Asia. Strategies and options. In: Singh AK, editor. Proceedings of the International Conference on Managing Resources For Sustainable Agricultural Production. In the 21st century. New Delhi, India 14-18 February 2000. New

Delhi, India: Indian Society of Soil Science; 2000. p. 157

[80] Heal OW, Anderson JM, Swift MJ. Plant litter quality and decomposition: An historical overview. In: Cadisch G, Giller KE, editors. Driven by Nature-Plant Litter Quality and Decomposition. Wallingford: CAB International; 1997. pp. 3-30

[81] Mahmoodabadi M, Heydarpour E. Sequestration of organic carbon influenced by the application of straw residue and farmyard manure in two different soils. International Agrophysics. 2014;**28**:169-176. DOI: 10.2478/intag-2014-0005

[82] Vicente - Vicente JL, Garcia-Ruiz R, Francaviglia R, Aguilera E, Smith P. Soil carbon sequestration rates under Mediterranean woody crops using recommended management practices: A meta-analysis. Agriculture Ecosystems and Environment. 2016;**235**:204-214

[83] Olson KR, Ebelhar SA, Lang JM. Cover crop effects on on crop yields and organic carbon content. Soil Science. 2010;**175**:89-98. DOI: 10.1097/ ss.ob0133e3181cf7959

[84] Olson K, Stephen A, Ebelhar JML. Long-term effects of cover crops on crop yields, soil organic carbon stocks and sequestration. Open Journal of Soil Science. 2014;**4**:284-292

[85] Machado S, Rhinhart K, Petrie S. Longterm cropping systems effects on carbon sequestration in eastern Oregon. Journal of Environmental Quality. 2006;**35**:1548-1553

[86] Kell DB. Breeding crop plants with deep roots: Their role in sustainable carbon, nutrient and water sequestration. Annals of Botany. 2011;**108**(93):407-418

[87] Kell DB. Large scale sequestration of atmospheric via plant roots in

natural and agricultural ecosystems: Why and how. Philosophical Transactions of the Royal Society B. 2012;**367**(1595):1589-1597

[88] Jong SC. Microbial germplasm. In: Knutson L, Stone AK, editors. Biotic Diversity and Germplasm Preservation, Beltsville Symposia in Agricultural Research. Kluwer Academic Publications: Dordrecht; 1988, 1989. pp. 241-273

[89] Bailey VL, Smith JL, Bolton H. Fungal -to- bacterial ratios in soils investigated for enhanced C sequestration. Soil Biology and Biochemistry. 2002;**34**:997-1007

[90] Lehmann J. Bio-energy in the black. Frontiers in Ecology and the Environment. 2007;**5**:381-387

[91] Hemandez-Soriano MC et al. Long-term effect of bio char on the stabilization of recent carbon: Soils with historical inputs of charcoal. GCB Bioenergy. 2016;**8**(2):371-381

[92] Hemandez-Soriano MC et al. Bio char affects carbon composition and stability in soil: A combined spectroscopy-microscopy study. Scientific Reports. 2016;**6**:25127

[93] Pulleman MM, Six J, Uyl A, Marinissen JCY, Jongmans AG. Earthworms and management affect organic matter incorportation and microaggregates formation in agricultural soils. Applied Soil Ecology. 2005;**29**:1-15

[94] Sanches PA, Buresh RJ, Leakey RRB. Trees, soils and food security. Phillosphical Transactions of the Royal Society of London, Series B. 1999;**353**:949-961

[95] Schroeder P. Carbon storage benefits of agroforestry systems. Agroforestry Systems. 1994;**27**:89-97

**21**

*Soil Carbon Sequestration through Agronomic Management Practices*

*DOI: http://dx.doi.org/10.5772/intechopen.87107*

[96] Kort J, Turnock R. Carbon reservoir

[97] Sharrow SH, Ismail S. Carbon and nitrogen storage in agroforests, tree plantations, and pastures in Western Oregon, USA. Aggroforest Systems.

and biomass in Canadian prairie shelterbelts. Agroforestry Systems.

[98] Young A. Agroforestry for Soil Management. 2nd ed. CABI; 1 December 1997. pp. 257-258

[99] Albrecht A, kandji ST. Carbon sequestration in tropical agroforestry systems. Agriculture Ecosystems and

[100] De Stefano A, Jacobson MG. Soil carbon sequestration in agroforestry systems: A meta-analysis. Agroforestry

[101] Montagnini F, Nair PKR. Carbon sequestration: An under exploited

agroforestry systems. In: Nair PKR, Rao MR, Buck LE, editors. New Vistas in Agroforestry: A Compendium for 1st World Congress of Agroforestry. Dordrecht: Springer Netherlands; 2004.

Environment. 2003;**99**:15-27

Systems. 2018;**92**:285-299. DOI: 10.1007/s 10457-017-0147-9

environmental benefit of

pp. 281-295

1999;**44**:175-186

2004;**60**:123-130

*Soil Carbon Sequestration through Agronomic Management Practices DOI: http://dx.doi.org/10.5772/intechopen.87107*

[96] Kort J, Turnock R. Carbon reservoir and biomass in Canadian prairie shelterbelts. Agroforestry Systems. 1999;**44**:175-186

*CO2 Sequestration*

pp. 3-30

Science; 2000. p. 157

Delhi, India: Indian Society of Soil

[80] Heal OW, Anderson JM, Swift MJ. Plant litter quality and decomposition: An historical overview. In: Cadisch G, Giller KE, editors. Driven by Nature-Plant Litter Quality and Decomposition. Wallingford: CAB International; 1997.

natural and agricultural ecosystems:

[88] Jong SC. Microbial germplasm. In: Knutson L, Stone AK, editors. Biotic Diversity and Germplasm Preservation, Beltsville Symposia in Agricultural Research. Kluwer Academic Publications: Dordrecht;

[89] Bailey VL, Smith JL, Bolton H. Fungal -to- bacterial ratios in soils investigated for enhanced C sequestration. Soil Biology and Biochemistry. 2002;**34**:997-1007

[90] Lehmann J. Bio-energy in the black. Frontiers in Ecology and the Environment. 2007;**5**:381-387

[91] Hemandez-Soriano MC et al. Long-term effect of bio char on the stabilization of recent carbon: Soils with historical inputs of charcoal. GCB Bioenergy. 2016;**8**(2):371-381

[92] Hemandez-Soriano MC et al. Bio char affects carbon composition and stability in soil: A combined spectroscopy-microscopy study. Scientific Reports. 2016;**6**:25127

[93] Pulleman MM, Six J, Uyl A, Marinissen JCY, Jongmans AG. Earthworms and management affect organic matter incorportation and microaggregates formation in agricultural soils. Applied Soil Ecology.

[94] Sanches PA, Buresh RJ, Leakey RRB. Trees, soils and food security. Phillosphical Transactions of the Royal Society of London, Series B.

[95] Schroeder P. Carbon storage benefits of agroforestry systems. Agroforestry

2005;**29**:1-15

1999;**353**:949-961

Systems. 1994;**27**:89-97

Why and how. Philosophical Transactions of the Royal Society B.

2012;**367**(1595):1589-1597

1988, 1989. pp. 241-273

[81] Mahmoodabadi M, Heydarpour E. Sequestration of organic carbon influenced by the application of straw residue and farmyard manure in two different soils. International Agrophysics. 2014;**28**:169-176. DOI:

[82] Vicente - Vicente JL, Garcia-Ruiz R, Francaviglia R, Aguilera E, Smith P. Soil carbon sequestration rates under Mediterranean woody crops using recommended management practices: A meta-analysis. Agriculture Ecosystems and Environment. 2016;**235**:204-214

[83] Olson KR, Ebelhar SA, Lang JM. Cover crop effects on on crop yields and organic carbon content. Soil Science. 2010;**175**:89-98. DOI: 10.1097/

[84] Olson K, Stephen A, Ebelhar JML. Long-term effects of cover crops on crop yields, soil organic carbon stocks and sequestration. Open Journal of Soil

[85] Machado S, Rhinhart K, Petrie S. Longterm cropping systems effects on carbon sequestration in eastern Oregon. Journal of Environmental Quality.

[86] Kell DB. Breeding crop plants with deep roots: Their role in sustainable carbon, nutrient and water sequestration. Annals of Botany.

[87] Kell DB. Large scale sequestration of atmospheric via plant roots in

10.2478/intag-2014-0005

ss.ob0133e3181cf7959

Science. 2014;**4**:284-292

2006;**35**:1548-1553

2011;**108**(93):407-418

**20**

[97] Sharrow SH, Ismail S. Carbon and nitrogen storage in agroforests, tree plantations, and pastures in Western Oregon, USA. Aggroforest Systems. 2004;**60**:123-130

[98] Young A. Agroforestry for Soil Management. 2nd ed. CABI; 1 December 1997. pp. 257-258

[99] Albrecht A, kandji ST. Carbon sequestration in tropical agroforestry systems. Agriculture Ecosystems and Environment. 2003;**99**:15-27

[100] De Stefano A, Jacobson MG. Soil carbon sequestration in agroforestry systems: A meta-analysis. Agroforestry Systems. 2018;**92**:285-299. DOI: 10.1007/s 10457-017-0147-9

[101] Montagnini F, Nair PKR. Carbon sequestration: An under exploited environmental benefit of agroforestry systems. In: Nair PKR, Rao MR, Buck LE, editors. New Vistas in Agroforestry: A Compendium for 1st World Congress of Agroforestry. Dordrecht: Springer Netherlands; 2004. pp. 281-295

**23**

**Chapter 3**

**Abstract**

Arkansas

Arkansas (0.02% year<sup>−</sup><sup>1</sup>

cropland, and native prairie

**1. Introduction**

possible.

Landuse and Physiographic

*Marya McKee, Kristofor R. Brye and Lisa Wood*

Region Effects on Soil Carbon

and Nitrogen Sequestration in

Increasing understanding of soil carbon (C) sequestration dynamics and general

year<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

, respectively), than in the Grand

functioning in disappearing native grassland ecosystems, has the potential to enhance soil rehabilitation and ecosystem restoration. The objective of this study was to evaluate the effects of landuse (native tallgrass prairie and managed agriculture) and physiographic region (northwest Arkansas and east-central Arkansas) on the change in soil C and nitrogen (N) storage and other soil properties over a 15-year period. Despite the native prairie losing soil C at a rate of 4.7 Mg ha<sup>−</sup><sup>1</sup>

over the 15-year duration of this study, soil C storage in 2016 was more than 2.5 times greater in the native prairie than in the cultivated agroecosystems in the Grand Prairie. Averaged across landuse, TC concentration (*P* < 0.01) and content (*P* < 0.01) changed more over time in the Ozark Highlands region of northwest

Prairie region of east-central Arkansas. This study demonstrates the value of direct measurements over time for assessing temporal changes in soil properties and results can potentially direct future restoration activities to be as successful as

**Keywords:** carbon sequestration, silt-loam soils, managed grassland, cultivated

Greenhouse gas (GHG) concentrations in the atmosphere have been on the rise since the Industrial Revolution began in the eighteenth century and have led to an enhancement of the greenhouse effect and dramatic increases in global air temperatures. The combined average land and surface air temperatures from 1880 to 2012, calculated from a linear trend with 90% certainty, showed mean warming of 0.85°C, which ranged from 0.65 to 1.06°C, across the globe [1]. This striking increase in air temperature over such a short period of time has evolved into the climatic variations witnessed today that scientists have termed global climate change. The scientific consensus is that the rising air temperatures are the result of an unprecedented rise in GHG emissions over the last 150 years, due primarily to

and 0.28 Mg ha<sup>−</sup><sup>1</sup>

#### **Chapter 3**

## Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas

*Marya McKee, Kristofor R. Brye and Lisa Wood*

#### **Abstract**

Increasing understanding of soil carbon (C) sequestration dynamics and general functioning in disappearing native grassland ecosystems, has the potential to enhance soil rehabilitation and ecosystem restoration. The objective of this study was to evaluate the effects of landuse (native tallgrass prairie and managed agriculture) and physiographic region (northwest Arkansas and east-central Arkansas) on the change in soil C and nitrogen (N) storage and other soil properties over a 15-year period. Despite the native prairie losing soil C at a rate of 4.7 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> over the 15-year duration of this study, soil C storage in 2016 was more than 2.5 times greater in the native prairie than in the cultivated agroecosystems in the Grand Prairie. Averaged across landuse, TC concentration (*P* < 0.01) and content (*P* < 0.01) changed more over time in the Ozark Highlands region of northwest Arkansas (0.02% year<sup>−</sup><sup>1</sup> and 0.28 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> , respectively), than in the Grand Prairie region of east-central Arkansas. This study demonstrates the value of direct measurements over time for assessing temporal changes in soil properties and results can potentially direct future restoration activities to be as successful as possible.

**Keywords:** carbon sequestration, silt-loam soils, managed grassland, cultivated cropland, and native prairie

#### **1. Introduction**

Greenhouse gas (GHG) concentrations in the atmosphere have been on the rise since the Industrial Revolution began in the eighteenth century and have led to an enhancement of the greenhouse effect and dramatic increases in global air temperatures. The combined average land and surface air temperatures from 1880 to 2012, calculated from a linear trend with 90% certainty, showed mean warming of 0.85°C, which ranged from 0.65 to 1.06°C, across the globe [1]. This striking increase in air temperature over such a short period of time has evolved into the climatic variations witnessed today that scientists have termed global climate change. The scientific consensus is that the rising air temperatures are the result of an unprecedented rise in GHG emissions over the last 150 years, due primarily to

human activity in the form of burning fossil fuels, agricultural land conversion and management, and deforestation [1].

Carbon dioxide (CO2) is the most abundant GHG in the atmosphere and has risen from 280 mg L<sup>−</sup><sup>1</sup> before the Industrial Revolution in 1730 to over 400 mg L<sup>−</sup><sup>1</sup> in 2015 and is predicted to continue increasing by 2 mg L<sup>−</sup><sup>1</sup> per year [1]. In 2010, the CO2 derived from burning fossil fuels and industrial processes contributed around 65% of total global GHG emissions, while forestry, land clearing for agriculture, and soil degradation collectively accounted for 11% of the global emissions [1]. In 2015, agricultural production alone accounted for 9% of total US GHG emissions [2]. Fossil fuels are burned during agricultural production, from heavy machinery and equipment, and these emissions account for nearly 25% of the total global GHG emissions originating from fossil fuels [1]. However, other sources of CO2 emissions associated with agricultural production result from the initial conversion and continued tillage of soils that contain substantial amounts of soil organic carbon (SOC).

Carbon flows through the global C cycle between five primary pools: the oceanic pool, geologic pool (fossil fuels), pedologic (soil) pool, atmospheric pool, and biotic pool. Most of the C held within the terrestrial ecosystem is stored within the soil (~2500 Pg), with only a fraction of the total terrestrial C stored within plant biomass (~560 Pg) [3]. The global C cycle and SOC creation are fueled by the photosynthetic activity of plants and other autotrophic organisms, which convert CO2 into glucose (C6H12O6) or energy that is used to develop biomass. Following the decomposition of autotrophic organisms and the heterotrophic organisms that consume them, a portion of the C captured during photosynthesis remains stored in the soil in a process known as soil C sequestration.

Soil C sequestration potential within an ecosystem is dependent on the same factors that lead to pedogenesis: parent material, climate, biota, topography, and time. Climate and biota tend to play a more significant role in the C cycle and therefore are often more important to the soil C sequestration process. Colder climates are more likely to accumulate SOC because soil microbial decomposition of soil organic matter (SOM) is slowed and sometimes paused when temperatures reach below freezing (0°C) [4]. In addition to temperature, the other main climatic factor that affects soil C sequestration is moisture, where a fine line exists between optimal soil moisture and too much or too little soil moisture. Optimal soil moisture contributes to increase in above- and belowground autotrophic productivity, which leads to greater available plant biomass. Too much soil moisture decreases soil microbial decomposition rates of SOC when soil moisture levels reach a point where periodic reducing conditions occur. However, increased moisture levels that do not reach reducing conditions have the potential to increase soil microbial decomposition rates, as microbes gain more access to the soil pores through the movement of water. In contrast, too little soil moisture limits plant productivity, hence the potential production and input of SOM for soil microbes to consume and convert to SOC.

The C compounds returned to the soil during microbial decomposition, in the form of SOM, consist of three separate pools: active, intermediate or slow, and passive. These pools are classified by the amount of time the SOM remains stable before further decomposing and returning to the atmosphere, mostly as CO2, via microbial respiration. Soil organic matter within the active pool consists of labile or easily decomposable particulate organic matter [5]. The active pool of SOM contributes most of the beneficial effects of soil structural stability, which enhances a soil's infiltration capacity and resistance to erosion and can be readily increased by adding fresh plant and animal residues. However, due to the potential instability of the organic material, the active C pool can be easily lost due to reductions in organic additions or increased tillage.

**25**

SOC m<sup>−</sup><sup>2</sup>

year<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

observed for native prairies (0.04 kg SOC m<sup>−</sup><sup>2</sup>

sequestration rate (−0.03 kg SOC m<sup>−</sup><sup>2</sup>

(0.05 kg SOC m<sup>−</sup><sup>2</sup>

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas*

Agricultural production is one of the leading disturbances of the SOC pools because of the management practice of conventional tillage [6]. Over the years, due to reduced C inputs and continual disturbance through conventional tillage, between 40 and 60% of SOC has been lost following the conversion of lands from tallgrass prairie to cultivated agriculture [7]. The decrease can be explained by the initial land conversion to non-native vegetation, followed by the rapid oxidation of SOM from conventional tillage and minimal vegetative cover and biomass inputs back to the soil. Rapid declines in SOC are due partly to the mechanical disintegration of soil aggregates during repeated annual tillage, which exposes organo-mineral surfaces that had otherwise been unavailable for decomposition by microbes when previously undisturbed and the physical loss of SOC due to erosion [8]. However, some level of SOM turnover is necessary to incorporate and protect fresh C inputs from rapid decay and mineralization, whereas SOM turnover that occurs too quickly or too often can lead to decreases in microaggregate stability and

Soil formation and resulting soil properties are inextricably linked with climatic factors and parent material. Arkansas resides in a unique climatic transition zone in the mid-southern United States, with arid to semi-arid grassland to the west and northwest and humid-temperate deciduous forest to the south and southeast. The climate gradient that spans through Arkansas also controls the botanical composition and interacts with distinct topographic and geologic gradients. Consequently, Arkansas is separated into at least two distinct climates and parent material sources. The northwest region of Arkansas, known as the Ozark Highlands [Major Land Resource Area (MLRA) 116A] [10], is relatively warm and wet and dominated by deciduous forest vegetation both presently and as the climax vegetation community. Cherty limestone residuum is the soil parent material for much of the Ozark Highlands. Soils in the Ozark Highlands are typically moderately deep and mediumto fine-textured Udults and Udalfs. The Ozark Highlands also contains remnants of the Osage Prairie, which once extended through south-central and southwestern Missouri, as well as northwest Arkansas [11]. Presently, less than 0.5% of the original Osage prairie exists, due to the conversion to pasture and hay meadows now populated with naturalized (i.e., introduced) species [11]. East-central Arkansas contains the remnants of the tallgrass prairie regionally referred to as the Grand Prairie, within MLRA 134—Southern Mississippi Valley Silty Uplands [10], which is an area

formation, therefore decreasing soil C sequestration potential [9].

that is also relatively warm and wet, with fertile alluvial parent material.

Comparing native prairies across these two physiographic regions in Arkansas, Brye et al. [12] reported that SOM concentrations in the top 10 cm in native prairie ecosystems generally increased south and eastward across Arkansas, due to increasing precipitation in the Grand Prairie region compared to the Ozark Highlands, therefore leading to increase above- and belowground productivity. In contrast, a study conducted by Brye and Gbur [13] reported that, averaged across landuse, soils in the Grand Prairie region had the lowest average SOC sequestration rate (−0.04 kg

physiographic region, soils under agricultural management had a lower average SOC

A study conducted within the Ozark Highlands region evaluating the effects of grassland management on soil physical and chemical properties, including SOC, in the top 10 cm over a 6-year period in silt-loam soil reported that certain management schemes, including grazing and haying, had minimal effect on near-surface soil properties, indicating that contemporary managed forage lands in the Ozark Highlands are not being degraded by agricultural management, but are in fact

year<sup>−</sup><sup>1</sup>

) in the top 10 cm compared to that observed in the Ozark Highlands

 year<sup>−</sup><sup>1</sup> ).

). Brye and Gbur [13] also reported that, averaged across

) in the top 10 cm compared to that

*DOI: http://dx.doi.org/10.5772/intechopen.83783*

#### *Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas DOI: http://dx.doi.org/10.5772/intechopen.83783*

Agricultural production is one of the leading disturbances of the SOC pools because of the management practice of conventional tillage [6]. Over the years, due to reduced C inputs and continual disturbance through conventional tillage, between 40 and 60% of SOC has been lost following the conversion of lands from tallgrass prairie to cultivated agriculture [7]. The decrease can be explained by the initial land conversion to non-native vegetation, followed by the rapid oxidation of SOM from conventional tillage and minimal vegetative cover and biomass inputs back to the soil. Rapid declines in SOC are due partly to the mechanical disintegration of soil aggregates during repeated annual tillage, which exposes organo-mineral surfaces that had otherwise been unavailable for decomposition by microbes when previously undisturbed and the physical loss of SOC due to erosion [8]. However, some level of SOM turnover is necessary to incorporate and protect fresh C inputs from rapid decay and mineralization, whereas SOM turnover that occurs too quickly or too often can lead to decreases in microaggregate stability and formation, therefore decreasing soil C sequestration potential [9].

Soil formation and resulting soil properties are inextricably linked with climatic factors and parent material. Arkansas resides in a unique climatic transition zone in the mid-southern United States, with arid to semi-arid grassland to the west and northwest and humid-temperate deciduous forest to the south and southeast. The climate gradient that spans through Arkansas also controls the botanical composition and interacts with distinct topographic and geologic gradients. Consequently, Arkansas is separated into at least two distinct climates and parent material sources. The northwest region of Arkansas, known as the Ozark Highlands [Major Land Resource Area (MLRA) 116A] [10], is relatively warm and wet and dominated by deciduous forest vegetation both presently and as the climax vegetation community. Cherty limestone residuum is the soil parent material for much of the Ozark Highlands. Soils in the Ozark Highlands are typically moderately deep and mediumto fine-textured Udults and Udalfs. The Ozark Highlands also contains remnants of the Osage Prairie, which once extended through south-central and southwestern Missouri, as well as northwest Arkansas [11]. Presently, less than 0.5% of the original Osage prairie exists, due to the conversion to pasture and hay meadows now populated with naturalized (i.e., introduced) species [11]. East-central Arkansas contains the remnants of the tallgrass prairie regionally referred to as the Grand Prairie, within MLRA 134—Southern Mississippi Valley Silty Uplands [10], which is an area that is also relatively warm and wet, with fertile alluvial parent material.

Comparing native prairies across these two physiographic regions in Arkansas, Brye et al. [12] reported that SOM concentrations in the top 10 cm in native prairie ecosystems generally increased south and eastward across Arkansas, due to increasing precipitation in the Grand Prairie region compared to the Ozark Highlands, therefore leading to increase above- and belowground productivity. In contrast, a study conducted by Brye and Gbur [13] reported that, averaged across landuse, soils in the Grand Prairie region had the lowest average SOC sequestration rate (−0.04 kg SOC m<sup>−</sup><sup>2</sup> year<sup>−</sup><sup>1</sup> ) in the top 10 cm compared to that observed in the Ozark Highlands (0.05 kg SOC m<sup>−</sup><sup>2</sup> year<sup>−</sup><sup>1</sup> ). Brye and Gbur [13] also reported that, averaged across physiographic region, soils under agricultural management had a lower average SOC sequestration rate (−0.03 kg SOC m<sup>−</sup><sup>2</sup> year<sup>−</sup><sup>1</sup> ) in the top 10 cm compared to that observed for native prairies (0.04 kg SOC m<sup>−</sup><sup>2</sup> year<sup>−</sup><sup>1</sup> ).

A study conducted within the Ozark Highlands region evaluating the effects of grassland management on soil physical and chemical properties, including SOC, in the top 10 cm over a 6-year period in silt-loam soil reported that certain management schemes, including grazing and haying, had minimal effect on near-surface soil properties, indicating that contemporary managed forage lands in the Ozark Highlands are not being degraded by agricultural management, but are in fact

*CO2 Sequestration*

risen from 280 mg L<sup>−</sup><sup>1</sup>

soil organic carbon (SOC).

management, and deforestation [1].

in 2015 and is predicted to continue increasing by 2 mg L<sup>−</sup><sup>1</sup>

in the soil in a process known as soil C sequestration.

human activity in the form of burning fossil fuels, agricultural land conversion and

Carbon dioxide (CO2) is the most abundant GHG in the atmosphere and has

Carbon flows through the global C cycle between five primary pools: the oceanic

Soil C sequestration potential within an ecosystem is dependent on the same factors that lead to pedogenesis: parent material, climate, biota, topography, and time. Climate and biota tend to play a more significant role in the C cycle and therefore are often more important to the soil C sequestration process. Colder climates are more likely to accumulate SOC because soil microbial decomposition of soil organic matter (SOM) is slowed and sometimes paused when temperatures reach below freezing (0°C) [4]. In addition to temperature, the other main climatic factor that affects soil C sequestration is moisture, where a fine line exists between optimal soil moisture and too much or too little soil moisture. Optimal soil moisture contributes to increase in above- and belowground autotrophic productivity, which leads to greater available plant biomass. Too much soil moisture decreases soil microbial decomposition rates of SOC when soil moisture levels reach a point where periodic reducing conditions occur. However, increased moisture levels that do not reach reducing conditions have the potential to increase soil microbial decomposition rates, as microbes gain more access to the soil pores through the movement of water. In contrast, too little soil moisture limits plant productivity, hence the potential production and input of SOM for soil microbes to consume and convert to SOC. The C compounds returned to the soil during microbial decomposition, in the form of SOM, consist of three separate pools: active, intermediate or slow, and passive. These pools are classified by the amount of time the SOM remains stable before further decomposing and returning to the atmosphere, mostly as CO2, via microbial respiration. Soil organic matter within the active pool consists of labile or easily decomposable particulate organic matter [5]. The active pool of SOM contributes most of the beneficial effects of soil structural stability, which enhances a soil's infiltration capacity and resistance to erosion and can be readily increased by adding fresh plant and animal residues. However, due to the potential instability of the organic material, the active C pool can be easily lost due to reductions in organic

pool, geologic pool (fossil fuels), pedologic (soil) pool, atmospheric pool, and biotic pool. Most of the C held within the terrestrial ecosystem is stored within the soil (~2500 Pg), with only a fraction of the total terrestrial C stored within plant biomass (~560 Pg) [3]. The global C cycle and SOC creation are fueled by the photosynthetic activity of plants and other autotrophic organisms, which convert CO2 into glucose (C6H12O6) or energy that is used to develop biomass. Following the decomposition of autotrophic organisms and the heterotrophic organisms that consume them, a portion of the C captured during photosynthesis remains stored

the CO2 derived from burning fossil fuels and industrial processes contributed around 65% of total global GHG emissions, while forestry, land clearing for agriculture, and soil degradation collectively accounted for 11% of the global emissions [1]. In 2015, agricultural production alone accounted for 9% of total US GHG emissions [2]. Fossil fuels are burned during agricultural production, from heavy machinery and equipment, and these emissions account for nearly 25% of the total global GHG emissions originating from fossil fuels [1]. However, other sources of CO2 emissions associated with agricultural production result from the initial conversion and continued tillage of soils that contain substantial amounts of

before the Industrial Revolution in 1730 to over 400 mg L<sup>−</sup><sup>1</sup>

per year [1]. In 2010,

**24**

additions or increased tillage.

remaining similar to the remnant prairies from which they were converted [14]. In contrast, a study conducted, within the Grand Prairie region, on a chronosequence of four Typic Albaqualfs in adjacent fields in Prairie County, Arkansas, varying only in time under cultivation with the control as a native, undisturbed tallgrass prairie, reported an exponential decrease in SOC in the top 10 cm as years of cultivation increased [15]. Brye and Pirani [16] showed a significant difference in soil C concentration and content in the top 10 cm between native prairie (2.3–3.2% C; 2.5–3.4 kg C m<sup>−</sup><sup>2</sup> ) and adjacent tilled agricultural systems (1.0–1.7% C, 1.3–2.0 kg C m<sup>−</sup><sup>2</sup> ) in the Grand Prairie region of east-central Arkansas. Specifically, the difference in soil C tended to be greater when the agricultural fields had been tilled for 30 or more years than when the agricultural fields had been tilled for less than 30 years [16]. Following the conversion from native prairie to intensely tilled agriculture, a 17–52% decrease in soil-quality-related parameters was observed, including soil OM, total N, and total C [16].

Many of these examples of losses in SOC, and other resulting soil-quality parameters, can be interpreted positively as the potential to enhance and regain soil C storage in soils affected by long-term agricultural activity. With a combination of site-specific best management practices, like conservation tillage, no-tillage, cover crops, and elimination of fallow periods, which increase C input into the system, agricultural fields have the potential to become C sinks instead of their historic role as C sources. The objective of this study was to evaluate the effects of landuse (i.e., native tallgrass prairie and managed agriculture) and physiographic region on the change in soil C storage and other soil properties over a 15-year period. It was hypothesized that soil C and N storage in the top 10 cm would remain constant or slightly increased within the prairie remnants, while soil under agricultural management (i.e., managed pastureland, and cultivated agriculture) would likely decrease over a 15-year period between 2001 and 2016. Cultivated row-crop agriculture on alluvial soils was hypothesized to have lower C and N storage than managed pastureland on residual soils due to the long history of intensive tillage, despite alluvial soils typically being considered more fertile than residual soils.

#### **2. Materials and methods**

#### **2.1 Site description**

The Stump and Chesney Prairies in Benton County in the Ozark Highlands region of northwest Arkansas have various degrees of disturbed, agricultural landuse adjacent to the prairies in the same soil map unit as exists in the prairies (**Table 1**). Specifically, adjacent to the Stump Prairie resides a managed grassland, dominantly tall fescue (*Lolium arundinaceum* [Schreb.] Darbys.), that has been infrequently cultivated in the last 20 years for cutting and removing the aboveground vegetation (i.e., haying) multiple times a year. In addition, a managed pastureland that has never been cultivated, but has been consistently grazed multiple times per year for the past 20 years with varying head of cattle, also resides adjacent to the Stump Prairie. Adjacent to the Chesney Prairie resides an area that has been periodically cultivated and planted with a row crop [i.e., corn (*Zea mays* L.) or soybean (*Glycine max* L.)] in the last 20 years; however, the area has been left fallow for the past 15 years without a row crop being planted.

The Seidenstricker Prairie, in Prairie County, Arkansas, resides in an area known as the Grand Prairie and has three adjacent agricultural fields, with similar soil mapping units as exists in the prairie, that were once part of the prairie itself

**27**

respectively).

**2.2 Regional characteristics**

*Summary of site characteristics by geographic region.*

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas*

**managed**

**Soil series**

>20 Jay Oxyaquic

>20 Jay Oxyaquic

0 Jay Oxyaquic

>20 Jay Oxyaquic

0 Jay Oxyaquic

31\* Dewitt Typic

42\* Dewitt Typic

60\* Dewitt Typic

0 Dewitt Typic

**Soil taxonomic description**

Fragiudalf

Fragiudalf

Fragiudalf

Fragiudalf

Fragiudalf

Albaqualf

Albaqualf

Albaqualf

Albaqualf

**Slope (%)**

0

0

1

2

2

0

0

0

0

**Site Landuse Years** 

cultivated hayfield

cultivated managed pasture

prairie

prairie

agriculture

agriculture

agriculture

*Indicates years before 2016, therefore native prairie was converted to cultivated agriculture in 1986, 1975, and 1957,* 

prairie

cultivated agriculture

Stump Periodically

Stump Never

Stump Native

Chesney Native

Seidenstricker Cultivated

Seidenstricker Cultivated

Seidenstricker Cultivated

Seidenstricker Native

Chesney Periodically

that have now been consistently annually intensively cultivated and cropped under a rice (*Oryza sativa* L.)-soybean-wheat (*Triticum aestivum* L.) rotation in most years since 1957, 1975, and 1986 (**Table 1**). Consequently, as of 2016, the native prairie and three adjacent agricultural fields represented a chronosequence with varying years under cultivated agriculture (i.e., 0, 31, 42, and 60 years,

The Ozark Highlands (36–38°N lat., 91–95°W long.), MLRA 116A [10], occupies portions of southwest and south-central Missouri, eastern Oklahoma, and northwest and north-central Arkansas. The area is a low-elevation, disjointed mountainous region, covering roughly 2.1 million ha [13]. Soils in the Ozark Highlands are typically Udults and Udalfs with deep, medium- to fine-textured cherty residuum weathered from limestone [17]. Oak (*Quercus* spp.) forests dominate the vegetation in the Ozark Highlands, but a large extent of tallgrass prairie was also historically present. The Chesney and Stump Prairies are located within the Springfield Plateau, a region that extends over 640,000 ha, which consisted of low, undulating plains (240–430 m in elevation) covered in prairie, savannah, hardwood forest, and acidic glade ecosystems [10]. Historic prairie ecosystems covered >30,000 ha within the Springfield Plateau. The Chesney and Stump prairies are the only remnants of a

*DOI: http://dx.doi.org/10.5772/intechopen.83783*

**Region/parent material**

Grand Prairie/ alluvium

*\**

*respectively.*

**Table 1.**

Ozark Highlands/ residuum

**Region/parent material Site Landuse Years managed Soil series Soil taxonomic description Slope (%)** Ozark Highlands/ residuum Stump Periodically cultivated hayfield >20 Jay Oxyaquic Fragiudalf 0 Stump Never cultivated managed pasture >20 Jay Oxyaquic Fragiudalf 0 Stump Native prairie 0 Jay Oxyaquic Fragiudalf 1 Chesney Periodically cultivated agriculture >20 Jay Oxyaquic Fragiudalf 2 Chesney Native prairie 0 Jay Oxyaquic Fragiudalf 2 Grand Prairie/ alluvium Seidenstricker Cultivated agriculture 31\* Dewitt Typic Albaqualf 0 Seidenstricker Cultivated agriculture 42\* Dewitt Typic Albaqualf 0 Seidenstricker Cultivated agriculture 60\* Dewitt Typic Albaqualf 0 Seidenstricker Native prairie 0 Dewitt Typic Albaqualf 0

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas DOI: http://dx.doi.org/10.5772/intechopen.83783*

*\* Indicates years before 2016, therefore native prairie was converted to cultivated agriculture in 1986, 1975, and 1957, respectively.*

#### **Table 1.**

*CO2 Sequestration*

2.5–3.4 kg C m<sup>−</sup><sup>2</sup>

OM, total N, and total C [16].

**2. Materials and methods**

without a row crop being planted.

**2.1 Site description**

C m<sup>−</sup><sup>2</sup>

remaining similar to the remnant prairies from which they were converted [14]. In contrast, a study conducted, within the Grand Prairie region, on a chronosequence of four Typic Albaqualfs in adjacent fields in Prairie County, Arkansas, varying only in time under cultivation with the control as a native, undisturbed tallgrass prairie, reported an exponential decrease in SOC in the top 10 cm as years of cultivation increased [15]. Brye and Pirani [16] showed a significant difference in soil C concentration and content in the top 10 cm between native prairie (2.3–3.2% C;

) and adjacent tilled agricultural systems (1.0–1.7% C, 1.3–2.0 kg

) in the Grand Prairie region of east-central Arkansas. Specifically, the difference in soil C tended to be greater when the agricultural fields had been tilled for 30 or more years than when the agricultural fields had been tilled for less than 30 years [16]. Following the conversion from native prairie to intensely tilled agriculture, a 17–52% decrease in soil-quality-related parameters was observed, including soil

Many of these examples of losses in SOC, and other resulting soil-quality parameters, can be interpreted positively as the potential to enhance and regain soil C storage in soils affected by long-term agricultural activity. With a combination of site-specific best management practices, like conservation tillage, no-tillage, cover crops, and elimination of fallow periods, which increase C input into the system, agricultural fields have the potential to become C sinks instead of their historic role as C sources. The objective of this study was to evaluate the effects of landuse (i.e., native tallgrass prairie and managed agriculture) and physiographic region on the change in soil C storage and other soil properties over a 15-year period. It was hypothesized that soil C and N storage in the top 10 cm would remain constant or slightly increased within the prairie remnants, while soil under agricultural management (i.e., managed pastureland, and cultivated agriculture) would likely decrease over a 15-year period between 2001 and 2016. Cultivated row-crop agriculture on alluvial soils was hypothesized to have lower C and N storage than managed pastureland on residual soils due to the long history of intensive tillage, despite

alluvial soils typically being considered more fertile than residual soils.

The Stump and Chesney Prairies in Benton County in the Ozark Highlands region

of northwest Arkansas have various degrees of disturbed, agricultural landuse adjacent to the prairies in the same soil map unit as exists in the prairies (**Table 1**). Specifically, adjacent to the Stump Prairie resides a managed grassland, dominantly tall fescue (*Lolium arundinaceum* [Schreb.] Darbys.), that has been infrequently cultivated in the last 20 years for cutting and removing the aboveground vegetation (i.e., haying) multiple times a year. In addition, a managed pastureland that has never been cultivated, but has been consistently grazed multiple times per year for the past 20 years with varying head of cattle, also resides adjacent to the Stump Prairie. Adjacent to the Chesney Prairie resides an area that has been periodically cultivated and planted with a row crop [i.e., corn (*Zea mays* L.) or soybean (*Glycine max* L.)] in the last 20 years; however, the area has been left fallow for the past 15 years

The Seidenstricker Prairie, in Prairie County, Arkansas, resides in an area known as the Grand Prairie and has three adjacent agricultural fields, with similar soil mapping units as exists in the prairie, that were once part of the prairie itself

**26**

*Summary of site characteristics by geographic region.*

that have now been consistently annually intensively cultivated and cropped under a rice (*Oryza sativa* L.)-soybean-wheat (*Triticum aestivum* L.) rotation in most years since 1957, 1975, and 1986 (**Table 1**). Consequently, as of 2016, the native prairie and three adjacent agricultural fields represented a chronosequence with varying years under cultivated agriculture (i.e., 0, 31, 42, and 60 years, respectively).

#### **2.2 Regional characteristics**

The Ozark Highlands (36–38°N lat., 91–95°W long.), MLRA 116A [10], occupies portions of southwest and south-central Missouri, eastern Oklahoma, and northwest and north-central Arkansas. The area is a low-elevation, disjointed mountainous region, covering roughly 2.1 million ha [13]. Soils in the Ozark Highlands are typically Udults and Udalfs with deep, medium- to fine-textured cherty residuum weathered from limestone [17]. Oak (*Quercus* spp.) forests dominate the vegetation in the Ozark Highlands, but a large extent of tallgrass prairie was also historically present. The Chesney and Stump Prairies are located within the Springfield Plateau, a region that extends over 640,000 ha, which consisted of low, undulating plains (240–430 m in elevation) covered in prairie, savannah, hardwood forest, and acidic glade ecosystems [10]. Historic prairie ecosystems covered >30,000 ha within the Springfield Plateau. The Chesney and Stump prairies are the only remnants of a

much grander historical prairie that spanned over 4000 ha in northwest Arkansas known as the Lindsley Prairie [18].

The Grand Prairie (34°0′–35°30′ N lat., 91°15′–92°10′ W long.), part of MLRA 134, is in east-central Arkansas and covers roughly 0.5 million ha [10]. Soils in the Grand Prairie are typically deep to very deep Udalfs, with medium texture and mixed mineralogy [17], that are developing in fertile alluvial parent material sourced from the historic flooding of the Mississippi River, with or without a thin loess cover. The historic land cover in the Grand Prairie region was grasslands, which historically covered ~130,000 ha as tallgrass prairie, of which <1% remains today due primarily to the introduction and expansion of mechanized agriculture [19]. Consequently, presently, the predominant landuse within the Grand Prairie region is cultivated, row-crop agriculture, where rice, soybean, and wheat are the dominant crops.

The regions also vary by climate. The climate of the Grand Prairie region is, on average, warmer than the Ozark Highlands, with mean annual temperatures of 16.6 and 14.5°C, respectively [20]. Average annual precipitation in the northwest Arkansas portion of the Ozark Highlands is approximately 116 cm, while that in the Grand Prairie region is 126 cm [20].

#### **2.3 Soil sampling scheme**

Between early August 2001 and mid-April 2002, initial soil samples were collected at Stump and Chesney Prairies in the Ozark Highlands region of northwest Arkansas and at the Seidenstricker Prairie in the Grand Prairie region of east-central Arkansas. Soil property data in the top 10 cm from the initial soil samples collected in 2001/2002 were determined and reported in Brye and West [11] and Brye et al. [21] for the Stump and Chesney prairies and in Brye and Slaton [22] and Brye et al. [12] for the Seidenstricker Prairie. At the same time, between early August 2001 and mid-April 2002, the above-described, adjacent agricultural areas were sampled at all three prairie sites. Between late October and early November 2016, a subsequent set of soil samples were collected in all three prairie sites and in their adjacent agricultural areas. In each soil map unit represented within each prairie and in the same or similar soil map unit in the adjacent agricultural areas, soil samples were collected from the top 10 cm along a 60-m transect at five sampling points spaced 15 m apart (i.e., at the 0-, 15-, 30-, 45-, and 60-m marks). A slide hammer, with a 4.8-cm-diameter, stainless steel core chamber, was used to manually collect the soil samples, which were subsequently oven-dried at 70°C for 48 h, weighed for bulk density determinations, and crushed and sieved to pass through a 2-mm mesh screen for soil chemical property determinations.

Percentages of sand, silt, and clay in the top 10 cm from the initial soil samples collected in 2001/2002 were determined and reported in Brye and West [11] and Brye et al. [21] for the Stump and Chesney prairies and in Brye and Slaton [22] and Brye et al. [12] for the Seidenstricker Prairie. Soil pH was potentiometrically measured using an electrode in a 1:2 (wt/vol) soil-to-water paste. Soil organic matter was determined by weight-loss-on-ignition after 2 h at 360°C. Total C and N were determined by high-temperature combustion (Elementar Variomax CN Analyzer, Elementar Americas, Inc., Mt. Laurel, NJ). No soil among sampled transects effervesced upon treatment with dilute hydrochloric acid, thus all measured soil C was assumed to be SOC. The C:N ratio and fractionation of C and N in the SOM were calculated for each sample using measured concentrations. In addition, for each soil sample, TC, TN, and SOM contents (kg ha<sup>−</sup><sup>1</sup> ) were calculated from

**29**

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas*

interval. To calculate C and N sequestration rates, the 2001/2002 contents were then subtracted from 2016 contents and the differences were divided by the number of

A two-factor analysis of variance (ANOVA) was conducted using SAS 9.4 (SAS Institute, Inc., Cary, NC), based on a completely random design, to evaluate the effects of physiographic region (i.e., Ozark Highlands and Grand Prairie), landuse (i.e., native prairie and managed agriculture), and their interaction on changes in soil bulk density, pH, EC, SOM, C, and N storage, C:N ratio, and C and N fractions of SOM in the top 10 cm over time. A second two-factor ANOVA was conducted using SAS to evaluate the effects of physiographic region, landuse, and their interaction on soil bulk density, pH, EC, SOM, C, and N storage, C:N ratio, and C and N fractions of SOM in the top 10 cm from the 2016 sampling only to assess the current state of soil property differences among treatments. In addition, a linear regression analysis was conducted in Minitab (version 13, Minitab, Inc., State College, PA) using the 2016-measured data only for the Grand Prairie sites to assess soil C storage trends over time under cultivation. For all statistical analyses, significance was judged at *P* < 0.05; thus, when appropriate, means were separated by least signifi-

In 2016, after 15 years of consistent management or natural time progression, all measured soil properties, with the exception of bulk density, C:N ratio, and the C and N fractions of SOM, differed (*P* < 0.05) between regions within landuses (**Table 2**). Soil bulk density and the C and N fractions of SOM differed (*P* < 0.03) between physiographic regions and differed (*P* < 0.04) between landuses, while the soil C:N ratio was unaffected (*P* > 0.05) by region or landuse (**Table 2**), thus was similar and averaged 13.5 across all region-landuse combinations (**Table 3**). **Table 3** also summarizes the means and standard errors among ecosystem-landuse combi-

Soil pH and EC were greatest (*P* < 0.01; **Table 2**) in the Grand Prairie region

but only pH and EC in the agricultural landuse in the Grand Prairie differed from the other region-landuse combinations (**Table 3** and **Figure 1**). Soil pH and EC were likely more regulated in the more conventional agricultural landuses in the Grand Prairie from annual fertilizer additions and irrigation, respectively. Brye and Pirani [16] similarly concluded that soil pH and EC were generally greater under

In 2016, after 15 years of consistent management, SOM concentration and content were both more than two-fold greater in the Ozark Highlands under both landuses and in the Grand Prairie under prairie landuse, which did not differ, than in the Grand Prairie under cultivated agricultural landuse (**Figure 2**). Similarly, TN concentration and content were lowest, by more than 50%, in the Grand Prairie under cultivated agricultural landuse, while TN concentration was greatest under

respectively), and lowest in

respectively),

nations for soil properties from the original 2001/2002 soil sampling.

the native prairie landuse in the same region (4.7 and 0.072 dS m<sup>−</sup><sup>1</sup>

within the agricultural landuse (6.7 and 0.168 dS m<sup>−</sup><sup>1</sup>

tilled agricultural than under native prairie landuse.

), measured bulk densities, and the 10-cm depth

*DOI: http://dx.doi.org/10.5772/intechopen.83783*

measured concentrations (g kg<sup>−</sup><sup>1</sup>

**2.4 Statistical analyses**

years between sampling (~15 years).

cant difference (LSD) at the 0.05 level.

**3.1 Soil property differences after 15 years**

**3. Results and discussion**

measured concentrations (g kg<sup>−</sup><sup>1</sup> ), measured bulk densities, and the 10-cm depth interval. To calculate C and N sequestration rates, the 2001/2002 contents were then subtracted from 2016 contents and the differences were divided by the number of years between sampling (~15 years).

#### **2.4 Statistical analyses**

*CO2 Sequestration*

dominant crops.

known as the Lindsley Prairie [18].

Grand Prairie region is 126 cm [20].

**2.3 Soil sampling scheme**

property determinations.

much grander historical prairie that spanned over 4000 ha in northwest Arkansas

The Grand Prairie (34°0′–35°30′ N lat., 91°15′–92°10′ W long.), part of MLRA 134, is in east-central Arkansas and covers roughly 0.5 million ha [10]. Soils in the Grand Prairie are typically deep to very deep Udalfs, with medium texture and mixed mineralogy [17], that are developing in fertile alluvial parent material sourced from the historic flooding of the Mississippi River, with or without a thin loess cover. The historic land cover in the Grand Prairie region was grasslands, which historically covered ~130,000 ha as tallgrass prairie, of which <1% remains today due primarily to the introduction and expansion of mechanized agriculture [19]. Consequently, presently, the predominant landuse within the Grand Prairie region is cultivated, row-crop agriculture, where rice, soybean, and wheat are the

The regions also vary by climate. The climate of the Grand Prairie region is, on average, warmer than the Ozark Highlands, with mean annual temperatures of 16.6 and 14.5°C, respectively [20]. Average annual precipitation in the northwest Arkansas portion of the Ozark Highlands is approximately 116 cm, while that in the

Between early August 2001 and mid-April 2002, initial soil samples were collected at Stump and Chesney Prairies in the Ozark Highlands region of northwest Arkansas and at the Seidenstricker Prairie in the Grand Prairie region of east-central Arkansas. Soil property data in the top 10 cm from the initial soil samples collected in 2001/2002 were determined and reported in Brye and West [11] and Brye et al. [21] for the Stump and Chesney prairies and in Brye and Slaton [22] and Brye et al. [12] for the Seidenstricker Prairie. At the same time, between early August 2001 and mid-April 2002, the above-described, adjacent agricultural areas were sampled at all three prairie sites. Between late October and early November 2016, a subsequent set of soil samples were collected in all three prairie sites and in their adjacent agricultural areas. In each soil map unit represented within each prairie and in the same or similar soil map unit in the adjacent agricultural areas, soil samples were collected from the top 10 cm along a 60-m transect at five sampling points spaced 15 m apart (i.e., at the 0-, 15-, 30-, 45-, and 60-m marks). A slide hammer, with a 4.8-cm-diameter, stainless steel core chamber, was used to manually collect the soil samples, which were subsequently oven-dried at 70°C for 48 h, weighed for bulk density determinations, and crushed and sieved to pass through a 2-mm mesh screen for soil chemical

Percentages of sand, silt, and clay in the top 10 cm from the initial soil samples collected in 2001/2002 were determined and reported in Brye and West [11] and Brye et al. [21] for the Stump and Chesney prairies and in Brye and Slaton [22] and Brye et al. [12] for the Seidenstricker Prairie. Soil pH was potentiometrically measured using an electrode in a 1:2 (wt/vol) soil-to-water paste. Soil organic matter was determined by weight-loss-on-ignition after 2 h at 360°C. Total C and N were determined by high-temperature combustion (Elementar Variomax CN Analyzer, Elementar Americas, Inc., Mt. Laurel, NJ). No soil among sampled transects effervesced upon treatment with dilute hydrochloric acid, thus all measured soil C was assumed to be SOC. The C:N ratio and fractionation of C and N in the SOM were calculated for each sample using measured concentrations. In addition,

) were calculated from

for each soil sample, TC, TN, and SOM contents (kg ha<sup>−</sup><sup>1</sup>

**28**

A two-factor analysis of variance (ANOVA) was conducted using SAS 9.4 (SAS Institute, Inc., Cary, NC), based on a completely random design, to evaluate the effects of physiographic region (i.e., Ozark Highlands and Grand Prairie), landuse (i.e., native prairie and managed agriculture), and their interaction on changes in soil bulk density, pH, EC, SOM, C, and N storage, C:N ratio, and C and N fractions of SOM in the top 10 cm over time. A second two-factor ANOVA was conducted using SAS to evaluate the effects of physiographic region, landuse, and their interaction on soil bulk density, pH, EC, SOM, C, and N storage, C:N ratio, and C and N fractions of SOM in the top 10 cm from the 2016 sampling only to assess the current state of soil property differences among treatments. In addition, a linear regression analysis was conducted in Minitab (version 13, Minitab, Inc., State College, PA) using the 2016-measured data only for the Grand Prairie sites to assess soil C storage trends over time under cultivation. For all statistical analyses, significance was judged at *P* < 0.05; thus, when appropriate, means were separated by least significant difference (LSD) at the 0.05 level.

### **3. Results and discussion**

#### **3.1 Soil property differences after 15 years**

In 2016, after 15 years of consistent management or natural time progression, all measured soil properties, with the exception of bulk density, C:N ratio, and the C and N fractions of SOM, differed (*P* < 0.05) between regions within landuses (**Table 2**). Soil bulk density and the C and N fractions of SOM differed (*P* < 0.03) between physiographic regions and differed (*P* < 0.04) between landuses, while the soil C:N ratio was unaffected (*P* > 0.05) by region or landuse (**Table 2**), thus was similar and averaged 13.5 across all region-landuse combinations (**Table 3**). **Table 3** also summarizes the means and standard errors among ecosystem-landuse combinations for soil properties from the original 2001/2002 soil sampling.

Soil pH and EC were greatest (*P* < 0.01; **Table 2**) in the Grand Prairie region within the agricultural landuse (6.7 and 0.168 dS m<sup>−</sup><sup>1</sup> respectively), and lowest in the native prairie landuse in the same region (4.7 and 0.072 dS m<sup>−</sup><sup>1</sup> respectively), but only pH and EC in the agricultural landuse in the Grand Prairie differed from the other region-landuse combinations (**Table 3** and **Figure 1**). Soil pH and EC were likely more regulated in the more conventional agricultural landuses in the Grand Prairie from annual fertilizer additions and irrigation, respectively. Brye and Pirani [16] similarly concluded that soil pH and EC were generally greater under tilled agricultural than under native prairie landuse.

In 2016, after 15 years of consistent management, SOM concentration and content were both more than two-fold greater in the Ozark Highlands under both landuses and in the Grand Prairie under prairie landuse, which did not differ, than in the Grand Prairie under cultivated agricultural landuse (**Figure 2**). Similarly, TN concentration and content were lowest, by more than 50%, in the Grand Prairie under cultivated agricultural landuse, while TN concentration was greatest under


#### **Table 2.**

*Analysis of variance summary of the effects of physiographic region (Ozark Highlands and Grand Prairie), landuse (managed agriculture and native prairie), and their interaction on the change in soil bulk density (BD), pH, electrical conductivity (EC), soil organic matter (SOM), total nitrogen (TN), and total carbon (TC) concentration and content, C:N ratio, and the C and N fractions of SOM in the top 10 cm over a 15-year period in silt-loam soils in Arkansas.*

prairie landuse in both regions, which did not differ, and TN content was greatest under prairie landuse in the Grand Prairie (**Table 4** and **Figure 1**). Total N concentration and content were also greater under prairie than managed agricultural landuse in the Ozark Highlands (**Table 4** and **Figure 2**). Similar to TN, TC concentration and content were more than twofold greater under prairie landuse in both regions, which did not differ, than under cultivated agriculture in the Grand Prairie (**Table 4** and **Figure 2**). Total C concentration and content were also greater under prairie than agricultural landuse in the Ozark Highlands (**Figure 2**). Differences in TC and TN content among region-landuse combinations were likely the result of combined differences in TC and TN concentrations and bulk density, where, averaged across landuse, bulk density was 1.1 times greater in the Grand Prairie than in the Ozark Highlands and, averaged across region, was also 1.1 times greater under managed agricultural than native prairie landuse (**Table 3**). However, the differences in TC and TN concentrations alone (**Table 4** and **Figure 2**) clearly demonstrate that there are substantial differences in the net balance between above- and/ or belowground C and N inputs and losses.

Averaged across landuse, TN and TC fractions of SOM were both 1.3 times greater in the Ozark Highlands than in the Grand Prairie (**Table 3**). Averaged across region, TN and TC fractions of SOM were both 1.1 times greater under managed agricultural than native prairie landuse (**Table 3**). The differences in TC and TN fractions of SOM between regions and between landuses indicate that, in the Ozark Highlands and in the managed agricultural landuse use in general, the SOM pool is less diverse with other soil nutrients than in the Grand Prairie and native prairie landuse.

In contrast to the results of this study, Brye and Gbur [13] reported greater SOM, TN, and TC contents under the native prairie in the Grand Prairie, citing warmer and wetter annual climatic conditions that would promote greater belowground root biomass and OM, N, and C inputs compared with the Ozark Highlands.

**31**

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas*

**SOM (Mg ha**<sup>−</sup>**<sup>1</sup> )**

Prairie (PR) 1.11b 4.8 0.082 53.8 1.91 25.9 13.6 3.54b 48.2b

GP-AG 1.27 6.7a 0.168a 26.5b 0.89d 12.2c 13.7 3.38 46.4 GP-PR 1.15 4.7b 0.072b 52.5a 1.59c 21.7b 13.7 3.05 41.7 OZH-AG 1.20 4.9b 0.125b 53.6a 2.44a 31.3a 13.1 4.55 58.9 OZH-PR 1.07 4.8b 0.092b 55.0a 2.23b 30.1a 13.6 4.03 54.7

0.098 (0.01) 32.3 (1.3) 1.37

*Different lower case letters for a soil property within a treatment category indicates a significant difference* 

*††Data reproduced from Brye and West [11], Brye et al. [21], Brye and Slaton [22], and Brye et al. [12].*

*Summary of mean soil property changes by treatment (i.e., physiographic region, landuse and their interaction) over a 15-year sampling period for soil bulk density (BD), pH, electrical conductivity (EC), soil organic matter (SOM), total nitrogen (TN), total carbon (TC), C:N ratio, and the N (N/SOM) and* 

*Ecosystem × landuse combination means (± standard error) from the 2001/2002 sampling*††

0.072 (<0.01)

0.072 (<0.01)

*C (C/SOM) fractions of SOM in the top 10 cm in silt-loam soils in Arkansas.*

5.1 (0.1) 0.104 (0.01) 54.0 (2.7) 2.68

**TN (Mg ha**<sup>−</sup>**<sup>1</sup> )**

1.21 5.7 0.120 39.5 1.24 17.0 13.7 3.22 44.0

1.14 4.9 0.108 54.3 2.33 30.7 13.3 4.29 56.8

1.23a 5.8 0.146 40.0 1.67 21.8 13.4 3.97a 52.6a

(0.03)

(0.07)

(0.17)

(0.11)

58.1 (1.8) 2.33

49.2 (2.1) 2.18

15.1 (0.3)

28.9 (0.8)

26.6 (1.6)

24.1 (1.4)

11.0 (<0.1)

12.4 (0.2)

10.0 (0.3)

11.0 (0.2)

4.34 (0.2)

4.02 (0.1)

4.94 (0.1)

4.43 (0.1)

47.9 (2.3)

49.9 (1.2)

49.0 (1.0)

48.7 (1.0)

**TC (Mg ha**<sup>−</sup>**<sup>1</sup> )** **C:N N/SOM (%)**

**C/SOM (%)**

Similarly, comparing soil properties among only native prairies, Brye et al. [12] concluded that SOM and SOC concentrations and C:N ratio were at least numerically greater in the Grand Prairie than in the Ozark Highlands. However, Brye et al. [12] also reported that, based on a significant linear relationship, both TN and TC increased with increasing SOM concentration faster in the Ozark Highlands than in the Grand Prairie. Brye and West [11] reported that neither TN nor TC concentration differed in the top 10 cm between landuses in 2001/2002 when comparing the same sites used for this study in the Ozark Highlands. However, TN and TC concentration data were obtained through high-temperature combustion, whereas SOM concentration, which is obtained by weight-loss on ignition at a lower temperature, was significantly greater in the grazed than in the ungrazed pasture or native prairie soils [11]. These results indicate that the proportion of SOC within SOM likely differs between management systems, in which the quality of substrate entering

*DOI: http://dx.doi.org/10.5772/intechopen.83783*

**BD (g cm**<sup>−</sup>**<sup>3</sup> )**

*Region* Grand Prairie (GP)

Ozark Highlands (OZH)

*Landuse* Agriculture (AG)

*Ecosystem × landuse*

GP-AG 1.15

GP-PR 1.13

OZH-AG 0.13

OZH-PR 0.06

*†*

*(P < 0.05).*

**Table 3.**

(0.02)

(0.01)

(0.04)

(0.02)

5.9 (0.1)

4.7 (<0.1)

4.8 (<0.1)

**Treatment Soil properties†**

**pH EC (dS m**<sup>−</sup>**<sup>1</sup> )**


*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas DOI: http://dx.doi.org/10.5772/intechopen.83783*

*† Different lower case letters for a soil property within a treatment category indicates a significant difference (P < 0.05).*

*††Data reproduced from Brye and West [11], Brye et al. [21], Brye and Slaton [22], and Brye et al. [12].*

#### **Table 3.**

*CO2 Sequestration*

BD (g cm<sup>−</sup><sup>3</sup>

EC (dS m<sup>−</sup><sup>1</sup>

SOM (Mg ha<sup>−</sup><sup>1</sup>

TN (Mg ha<sup>−</sup><sup>1</sup>

TC (Mg ha<sup>−</sup><sup>1</sup>

*period in silt-loam soils in Arkansas.*

**Table 2.**

prairie landuse in both regions, which did not differ, and TN content was greatest under prairie landuse in the Grand Prairie (**Table 4** and **Figure 1**). Total N concentration and content were also greater under prairie than managed agricultural landuse in the Ozark Highlands (**Table 4** and **Figure 2**). Similar to TN, TC concentration and content were more than twofold greater under prairie landuse in both regions, which did not differ, than under cultivated agriculture in the Grand Prairie (**Table 4** and **Figure 2**). Total C concentration and content were also greater under prairie than agricultural landuse in the Ozark Highlands (**Figure 2**). Differences in TC and TN content among region-landuse combinations were likely the result of combined differences in TC and TN concentrations and bulk density, where, averaged across landuse, bulk density was 1.1 times greater in the Grand Prairie than in the Ozark Highlands and, averaged across region, was also 1.1 times greater under managed agricultural than native prairie landuse (**Table 3**). However, the differences in TC and TN concentrations alone (**Table 4** and **Figure 2**) clearly demonstrate that there are substantial differences in the net balance between above- and/

**Soil property Region Landuse Region × landuse**

pH <0.01 <0.01 <0.01

SOM (%) <0.01 <0.01 <0.01

TN (%) <0.01 0.02 0.04

TC (%) <0.01 < 0.01 0.03

C:N ratio 0.26 0.45 0.32 TN fraction of SOM (%) <0.01 0.04 0.92 TC fraction of SOM (%) <0.01 0.03 0.60

*Analysis of variance summary of the effects of physiographic region (Ozark Highlands and Grand Prairie), landuse (managed agriculture and native prairie), and their interaction on the change in soil bulk density (BD), pH, electrical conductivity (EC), soil organic matter (SOM), total nitrogen (TN), and total carbon (TC) concentration and content, C:N ratio, and the C and N fractions of SOM in the top 10 cm over a 15-year* 

) 0.03 <0.01 0.83

) 0.16 <0.01 <0.01

) <0.01 <0.01 <0.01

) <0.01 0.10 <0.01

) <0.01 < 0.01 <0.01

*P*

Averaged across landuse, TN and TC fractions of SOM were both 1.3 times greater in the Ozark Highlands than in the Grand Prairie (**Table 3**). Averaged across region, TN and TC fractions of SOM were both 1.1 times greater under managed agricultural than native prairie landuse (**Table 3**). The differences in TC and TN fractions of SOM between regions and between landuses indicate that, in the Ozark Highlands and in the managed agricultural landuse use in general, the SOM pool is less diverse with other soil nutrients than in the Grand Prairie and native prairie

In contrast to the results of this study, Brye and Gbur [13] reported greater SOM, TN, and TC contents under the native prairie in the Grand Prairie, citing warmer and wetter annual climatic conditions that would promote greater belowground root biomass and OM, N, and C inputs compared with the Ozark Highlands.

or belowground C and N inputs and losses.

**30**

landuse.

*Summary of mean soil property changes by treatment (i.e., physiographic region, landuse and their interaction) over a 15-year sampling period for soil bulk density (BD), pH, electrical conductivity (EC), soil organic matter (SOM), total nitrogen (TN), total carbon (TC), C:N ratio, and the N (N/SOM) and C (C/SOM) fractions of SOM in the top 10 cm in silt-loam soils in Arkansas.*

Similarly, comparing soil properties among only native prairies, Brye et al. [12] concluded that SOM and SOC concentrations and C:N ratio were at least numerically greater in the Grand Prairie than in the Ozark Highlands. However, Brye et al. [12] also reported that, based on a significant linear relationship, both TN and TC increased with increasing SOM concentration faster in the Ozark Highlands than in the Grand Prairie. Brye and West [11] reported that neither TN nor TC concentration differed in the top 10 cm between landuses in 2001/2002 when comparing the same sites used for this study in the Ozark Highlands. However, TN and TC concentration data were obtained through high-temperature combustion, whereas SOM concentration, which is obtained by weight-loss on ignition at a lower temperature, was significantly greater in the grazed than in the ungrazed pasture or native prairie soils [11]. These results indicate that the proportion of SOC within SOM likely differs between management systems, in which the quality of substrate entering

#### **Figure 1.**

*Landuse effects by physiographic region on the change in soil pH and electrical conductivity (EC) in the top 10 cm over the 15-year sampling period under either agricultural management (AG) or undisturbed prairie (PR) landuse in the Grand Prairie (GP) region of east-central Arkansas or the Ozark Highlands (OZH) region of northwest Arkansas. Different letters associated with mean values on a panel are different at P < 0.05. An asterisk (\*) indicates mean value is greater than 0 (P < 0.05).*

the SOC pool through humification is likely more recalcitrant or physiochemically protected in the native prairie, indicating more C storage is occurring within the passive SOC pool.

#### **3.2 Soil property changes over time**

Most of the soil property differences measured in this study in the top cm over a period of 15 years from 2001/2002 to 2016 were affected by physiographic region, landuse, or both (**Table 5**). Changes in soil pH (*P* < 0.01) and EC (*P* = 0.01) over the 15-year period differed among regions within landuses (**Table 5**). In contrast, changes in SOM content, TC and TN content and concentration, C:N ratio, TC and TN fractions of SOM over time differed (*P* < 0.05; **Table 5**) between regions, while changes in TC content, C:N ratio, and TC fraction of SOM over time also differed (*P* < 0.05; **Table 5**) between landuses. Neither changes in soil bulk density nor SOM concentration over time were affected by region or landuse (*P* > 0.05; **Table 5**).

Soil pH and EC in the top 10 cm increased the most over time under cultivated, row-crop agricultural management in the Grand Prairie, which was a greater change over time than for the other three region-landuse combinations, which did

**33**

acidifying the soil [14].

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas*

**Treatment SOM (%) TN (%) TC (%)**

Grand Prairie (GP) 3.33 0.12 1.44 Ozark Highlands (OZH) 4.88 0.21 2.75

Agriculture (AG) 3.31 0.14 1.81 Prairie (PR) 4.90 0.21 2.39

GP-AG 2.09b 0.07c 0.97c GP-PR 4.58a 0.14b 1.92b OZH-AG 4.53a 0.21a 2.64a OZH-PR 5.23a 0.21a 2.86a

**Soil properties†**

not differ (**Table 6** and **Figure 3**). However, soil pH and EC also decreased the most over time under non-cultivated agricultural landuse in the Ozark Highlands (**Table 6** and **Figure 3**). The differences in soil pH and EC change over time under agricultural landuse likely were due to periodic lime applications and exposure to bicarbonate-rich irrigation water for row-crop production in the Grand Prairie. In contrast, soil pH and EC did not change over time under native prairie landuse in either region, which may have occurred due to already having achieved some level of equilibrium that maintained the soil in a well-buffered state. Similar to the results of this study, based on samples collected in 1987 to a depth of 10 cm, also at the Seidenstricker site in the Grand Prairie, Brye et al. [15] concluded that soil pH levels were greater in the oldest cultivated, agriculturally managed soils, 12- and 30-year-old at the time, than in the native prairie and the youngest (1-year-old) cultivated, agriculturally managed soil. Following a resampling of the same sites in 2001, Brye et al. [15] reported that soil pH was still greater in the cultivated agroecosystems than in the prairie, but that soil pH did not differ among the three cultivated agroecosystems by 14 years later. Brye and Gbur [14], who compared soil property differences in the top 10 cm between native, undisturbed, and managed grasslands in the Ozark Highlands between 2001 and 2008, concluded that, although numerically greater in the agroecosystems, soil pH did not differ in the top 10 cm between native prairie and managed forage landuse, but soil pH levels had decreased by 8% in the 7 years between samplings. The soil pH decrease was attributed to a lack of liming in the managed forage lands and the presence of natural mineralization of the SOM and nitrification processes that had been slowly

*Different lower case letters for a soil property within a treatment category indicates a significant difference* 

*Summary of mean soil property changes by treatment (i.e., physiographic region, landuse, and their interaction) over a 15-year sampling period for soil organic matter (SOM), total nitrogen (TN), total carbon* 

*(TC) concentrations in the top 10 cm in silt-loams soils in Arkansas.*

In contrast to soil pH and EC, averaged across landuse, SOM content in the

not change over time in the Ozark Highlands (**Table 3**). Soil bulk density did not differ over time (**Table 5**), but, despite the change in SOM concentration over time being unaffected (*P* > 0.05) by region (**Table 5**), SOM concentration decreased

year<sup>−</sup><sup>1</sup>

), but did

top 10 cm decreased over time in the Grand Prairie (−0.37 Mg ha<sup>−</sup><sup>1</sup>

*DOI: http://dx.doi.org/10.5772/intechopen.83783*

*Region*

*Landuse*

*†*

*(P < 0.05).*

**Table 4.**

*Region × landuse*

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas DOI: http://dx.doi.org/10.5772/intechopen.83783*


*(P < 0.05).*

#### **Table 4.**

*CO2 Sequestration*

**32**

passive SOC pool.

**Figure 1.**

**3.2 Soil property changes over time**

*An asterisk (\*) indicates mean value is greater than 0 (P < 0.05).*

the SOC pool through humification is likely more recalcitrant or physiochemically protected in the native prairie, indicating more C storage is occurring within the

*Landuse effects by physiographic region on the change in soil pH and electrical conductivity (EC) in the top 10 cm over the 15-year sampling period under either agricultural management (AG) or undisturbed prairie (PR) landuse in the Grand Prairie (GP) region of east-central Arkansas or the Ozark Highlands (OZH) region of northwest Arkansas. Different letters associated with mean values on a panel are different at P < 0.05.* 

Most of the soil property differences measured in this study in the top cm over a period of 15 years from 2001/2002 to 2016 were affected by physiographic region, landuse, or both (**Table 5**). Changes in soil pH (*P* < 0.01) and EC (*P* = 0.01) over the 15-year period differed among regions within landuses (**Table 5**). In contrast, changes in SOM content, TC and TN content and concentration, C:N ratio, TC and TN fractions of SOM over time differed (*P* < 0.05; **Table 5**) between regions, while changes in TC content, C:N ratio, and TC fraction of SOM over time also differed (*P* < 0.05; **Table 5**) between landuses. Neither changes in soil bulk density nor SOM concentration over time were affected by region or landuse (*P* > 0.05; **Table 5**).

Soil pH and EC in the top 10 cm increased the most over time under cultivated,

row-crop agricultural management in the Grand Prairie, which was a greater change over time than for the other three region-landuse combinations, which did *Summary of mean soil property changes by treatment (i.e., physiographic region, landuse, and their interaction) over a 15-year sampling period for soil organic matter (SOM), total nitrogen (TN), total carbon (TC) concentrations in the top 10 cm in silt-loams soils in Arkansas.*

not differ (**Table 6** and **Figure 3**). However, soil pH and EC also decreased the most over time under non-cultivated agricultural landuse in the Ozark Highlands (**Table 6** and **Figure 3**). The differences in soil pH and EC change over time under agricultural landuse likely were due to periodic lime applications and exposure to bicarbonate-rich irrigation water for row-crop production in the Grand Prairie. In contrast, soil pH and EC did not change over time under native prairie landuse in either region, which may have occurred due to already having achieved some level of equilibrium that maintained the soil in a well-buffered state. Similar to the results of this study, based on samples collected in 1987 to a depth of 10 cm, also at the Seidenstricker site in the Grand Prairie, Brye et al. [15] concluded that soil pH levels were greater in the oldest cultivated, agriculturally managed soils, 12- and 30-year-old at the time, than in the native prairie and the youngest (1-year-old) cultivated, agriculturally managed soil. Following a resampling of the same sites in 2001, Brye et al. [15] reported that soil pH was still greater in the cultivated agroecosystems than in the prairie, but that soil pH did not differ among the three cultivated agroecosystems by 14 years later. Brye and Gbur [14], who compared soil property differences in the top 10 cm between native, undisturbed, and managed grasslands in the Ozark Highlands between 2001 and 2008, concluded that, although numerically greater in the agroecosystems, soil pH did not differ in the top 10 cm between native prairie and managed forage landuse, but soil pH levels had decreased by 8% in the 7 years between samplings. The soil pH decrease was attributed to a lack of liming in the managed forage lands and the presence of natural mineralization of the SOM and nitrification processes that had been slowly acidifying the soil [14].

In contrast to soil pH and EC, averaged across landuse, SOM content in the top 10 cm decreased over time in the Grand Prairie (−0.37 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ), but did not change over time in the Ozark Highlands (**Table 3**). Soil bulk density did not differ over time (**Table 5**), but, despite the change in SOM concentration over time being unaffected (*P* > 0.05) by region (**Table 5**), SOM concentration decreased

#### **Figure 2.**

*Landuse effects by physiographic region on soil pH and electrical conductivity (EC) in the top 10 cm from the 2016 sampling only under either agricultural management (AG) or undisturbed prairie (PR) landuse in the Grand Prairie (GP) region of east-central Arkansas and the Ozark Highlands (OZH) region of northwest Arkansas. Different letters associated with mean values on a panel are different at P < 0.05.*

more in the Grand Prairie than in the Ozark Highlands (**Table 6**), which was likely responsible for the decrease in SOM content in the Grand Prairie over time. Furthermore, the Grand Prairie region, on average, is slightly warmer and wetter than in the Ozark Highlands. Consequently, microbial decomposition of SOM was likely somewhat greater over time in the Grand Prairie than in the Ozark Highlands. Brye and Gbur [14] also concluded that SOM content did not change over time in either the native prairies or the managed grasslands in the Ozark Highlands region. In a study comparing landuse effects between the Ozark Highlands and the Grand Prairie regions among silt-loam-textured soils to a depth of 10 cm, between 2001 and 2007, Brye and Gbur [13] also demonstrated that, averaged across landuse, SOM content decreased in the Grand Prairie, but did not change over time in the Ozark Highlands and attributed the results to the regional climate differences. The Grand Prairie region also typically experiences longer durations of warmer temperatures, which stimulate microbial activity and lead to greater microbially mediated SOM decomposition rates.

**35**

year<sup>−</sup><sup>1</sup>

**Table 5.**

−0.01 Mg ha<sup>−</sup><sup>1</sup>

BD (g cm<sup>−</sup><sup>3</sup>

EC (dS m<sup>−</sup><sup>1</sup>

SOM (% yr<sup>−</sup><sup>1</sup>

SOM (Mg ha<sup>−</sup><sup>1</sup>

TN (% yr<sup>−</sup><sup>1</sup>

TN (Mg ha<sup>−</sup><sup>1</sup>

TC (% yr<sup>−</sup><sup>1</sup>

TC (Mg ha<sup>−</sup><sup>1</sup>

C:N ratio (yr<sup>−</sup><sup>1</sup>

pH (yr<sup>−</sup><sup>1</sup>

yr<sup>−</sup><sup>1</sup>

yr<sup>−</sup><sup>1</sup>

yr<sup>−</sup><sup>1</sup>

yr<sup>−</sup><sup>1</sup>

yr<sup>−</sup><sup>1</sup>

TN fraction of SOM (% yr<sup>−</sup><sup>1</sup>

TC fraction of SOM (% yr<sup>−</sup><sup>1</sup>

of 0.04 Mg ha<sup>−</sup><sup>1</sup>

(−0.04 Mg ha<sup>−</sup><sup>1</sup>

content (−0.33 Mg ha<sup>−</sup><sup>1</sup>

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas*

**Soil property Region Landuse Region × landuse**

) 0.55 0.08 0.87

) 0.17 <0.01 0.01

) <0.01 0.59 0.68

) <0.01 0.57 0.16

) <0.01 0.04 0.22

) 0.02 0.99 0.96

) <0.01 0.06 0.76

) 0.04 <0.01 0.37

) 0.08 0.22 0.44

) 0.05 0.76 0.15

) <0.01 0.67 0.19

) <0.01 0.01 <0.01

Similar to SOM content, averaged across landuse, TN concentration (−0.004%

*Analysis of variance summary of the effects of physiographic region, landuse, and their interaction on soil bulk density (BD), pH, electrical conductivity (EC), soil organic matter (SOM), total nitrogen (TN), and total carbon (TC) concentration and content, C:N ratio, and the TN and TC fractions of SOM in the top 10 cm* 

more than a factor of two over time in the Grand Prairie respectively; table than in the Ozark Highlands, which also decreased over time (−0.002% year<sup>−</sup><sup>1</sup>

of fertilizer N for optimal row-crop production in the Grand Prairie, which only meant to meet the crop N requirement, no other mechanisms of N input are enough to overcome the net loss of N over time from the top 10 cm by likely leaching and/or volatilization. In contrast to the results of this study, Brye and Gbur [13] reported that, averaged across landuses, TN content increased over time at a rate

2007. However, in a chronosequence of tallgrass prairie restorations in the Ozark Highlands, TN content in the top 10 cm decreased over time with restoration age and trended toward that in a nearby native prairie, which contained the lowest TN content [23]. The variation in results among studies highlights the multifaceted and

highly limiting nature of N in both natural and cultivated ecosystems. Similar to TN, averaged across landuse, TC concentration (−0.03% year<sup>−</sup><sup>1</sup>

**Table 6**) both increased over time in the Ozark Highlands. There are many complex processes that have been linked to fluctuations and accumulations of C within soils, such as plant physiological responses to atmospheric CO2; light; and environmental stressors, like temperature, nutrients, and water, as well as microbial responses to soil moisture and temperature variations. In the case of this study, all of these factors are potentially at work, with likely a stronger influence stemming from microbial responses to differences in soil moisture and temperature between physiographic regions, where greater microbial decomposition is occurring in the slightly warmer and wetter climate of the Grand Prairie than in the Ozark Highlands. Erosion from wind and water can also play a major role in SOC

year<sup>−</sup><sup>1</sup>

, respectively; **Tables 6** and **7**). Despite the annual input

in the Ozark Highlands, but decreased at the same rate

) in the Grand Prairie in the top 10 cm between 2001 and

; **Table 6**) decreased over time in the Grand Prairie. However,

, **Table 7**) and content (0.28 Mg ha<sup>−</sup><sup>1</sup>

; **Table 6**) decreased by

*P*

and

; **Table 7**) and

 year<sup>−</sup><sup>1</sup> ,

; **Table 4**) and content (−0.04 Mg ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

*from the 2016 sampling in silt-loam soils in Arkansas.*

year<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

in contrast, TC concentration (0.02% year<sup>−</sup><sup>1</sup>

*DOI: http://dx.doi.org/10.5772/intechopen.83783*

**Soil property Region Landuse Region × landuse** *P* BD (g cm<sup>−</sup><sup>3</sup> yr<sup>−</sup><sup>1</sup> ) 0.55 0.08 0.87 pH (yr<sup>−</sup><sup>1</sup> ) <0.01 0.01 <0.01 EC (dS m<sup>−</sup><sup>1</sup> yr<sup>−</sup><sup>1</sup> ) 0.17 <0.01 0.01 SOM (% yr<sup>−</sup><sup>1</sup> ) 0.08 0.22 0.44 SOM (Mg ha<sup>−</sup><sup>1</sup> yr<sup>−</sup><sup>1</sup> ) <0.01 0.59 0.68 TN (% yr<sup>−</sup><sup>1</sup> ) 0.05 0.76 0.15 TN (Mg ha<sup>−</sup><sup>1</sup> yr<sup>−</sup><sup>1</sup> ) <0.01 0.57 0.16 TC (% yr<sup>−</sup><sup>1</sup> ) <0.01 0.67 0.19 TC (Mg ha<sup>−</sup><sup>1</sup> yr<sup>−</sup><sup>1</sup> ) <0.01 0.04 0.22 C:N ratio (yr<sup>−</sup><sup>1</sup> ) 0.04 <0.01 0.37 TN fraction of SOM (% yr<sup>−</sup><sup>1</sup> ) 0.02 0.99 0.96 TC fraction of SOM (% yr<sup>−</sup><sup>1</sup> ) <0.01 0.06 0.76

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas DOI: http://dx.doi.org/10.5772/intechopen.83783*

#### **Table 5.**

*CO2 Sequestration*

**34**

**Figure 2.**

SOM decomposition rates.

more in the Grand Prairie than in the Ozark Highlands (**Table 6**), which was likely responsible for the decrease in SOM content in the Grand Prairie over time. Furthermore, the Grand Prairie region, on average, is slightly warmer and wetter than in the Ozark Highlands. Consequently, microbial decomposition of SOM was likely somewhat greater over time in the Grand Prairie than in the Ozark Highlands. Brye and Gbur [14] also concluded that SOM content did not change over time in either the native prairies or the managed grasslands in the Ozark Highlands region. In a study comparing landuse effects between the Ozark Highlands and the Grand Prairie regions among silt-loam-textured soils to a depth of 10 cm, between 2001 and 2007, Brye and Gbur [13] also demonstrated that, averaged across landuse, SOM content decreased in the Grand Prairie, but did not change over time in the Ozark Highlands and attributed the results to the regional climate differences. The Grand Prairie region also typically experiences longer durations of warmer temperatures, which stimulate microbial activity and lead to greater microbially mediated

*Arkansas. Different letters associated with mean values on a panel are different at P < 0.05.*

*Landuse effects by physiographic region on soil pH and electrical conductivity (EC) in the top 10 cm from the 2016 sampling only under either agricultural management (AG) or undisturbed prairie (PR) landuse in the Grand Prairie (GP) region of east-central Arkansas and the Ozark Highlands (OZH) region of northwest* 

*Analysis of variance summary of the effects of physiographic region, landuse, and their interaction on soil bulk density (BD), pH, electrical conductivity (EC), soil organic matter (SOM), total nitrogen (TN), and total carbon (TC) concentration and content, C:N ratio, and the TN and TC fractions of SOM in the top 10 cm from the 2016 sampling in silt-loam soils in Arkansas.*

Similar to SOM content, averaged across landuse, TN concentration (−0.004% year<sup>−</sup><sup>1</sup> ; **Table 4**) and content (−0.04 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ; **Table 6**) decreased by more than a factor of two over time in the Grand Prairie respectively; table than in the Ozark Highlands, which also decreased over time (−0.002% year<sup>−</sup><sup>1</sup> and −0.01 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> , respectively; **Tables 6** and **7**). Despite the annual input of fertilizer N for optimal row-crop production in the Grand Prairie, which only meant to meet the crop N requirement, no other mechanisms of N input are enough to overcome the net loss of N over time from the top 10 cm by likely leaching and/or volatilization. In contrast to the results of this study, Brye and Gbur [13] reported that, averaged across landuses, TN content increased over time at a rate of 0.04 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> in the Ozark Highlands, but decreased at the same rate (−0.04 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) in the Grand Prairie in the top 10 cm between 2001 and 2007. However, in a chronosequence of tallgrass prairie restorations in the Ozark Highlands, TN content in the top 10 cm decreased over time with restoration age and trended toward that in a nearby native prairie, which contained the lowest TN content [23]. The variation in results among studies highlights the multifaceted and highly limiting nature of N in both natural and cultivated ecosystems.

Similar to TN, averaged across landuse, TC concentration (−0.03% year<sup>−</sup><sup>1</sup> ; **Table 7**) and content (−0.33 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ; **Table 6**) decreased over time in the Grand Prairie. However, in contrast, TC concentration (0.02% year<sup>−</sup><sup>1</sup> , **Table 7**) and content (0.28 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> , **Table 6**) both increased over time in the Ozark Highlands. There are many complex processes that have been linked to fluctuations and accumulations of C within soils, such as plant physiological responses to atmospheric CO2; light; and environmental stressors, like temperature, nutrients, and water, as well as microbial responses to soil moisture and temperature variations. In the case of this study, all of these factors are potentially at work, with likely a stronger influence stemming from microbial responses to differences in soil moisture and temperature between physiographic regions, where greater microbial decomposition is occurring in the slightly warmer and wetter climate of the Grand Prairie than in the Ozark Highlands. Erosion from wind and water can also play a major role in SOC


*\* An asterisk indicates mean value is greater than 0 (P < 0.05).*

*† Units for the soil properties are as follows: BD, g cm<sup>−</sup><sup>3</sup> yr<sup>−</sup><sup>1</sup> ; pH, yr<sup>−</sup><sup>1</sup> ; EC, dS m<sup>−</sup><sup>1</sup> yr<sup>−</sup><sup>1</sup> ; SOM, TN, and TC, Mg ha<sup>−</sup><sup>1</sup> yr<sup>−</sup><sup>1</sup> ; C:N, yr<sup>−</sup><sup>1</sup> ; and N/SOM and C/SOM, % yr<sup>−</sup><sup>1</sup> .*

*††Different lower case letters for a soil property within a treatment category indicate a significant difference (P < 0.05).*

#### **Table 6.**

*Summary of mean soil properties in the top 10 cm by treatment (i.e., physiographic region, landuse and their interaction) for soil bulk density (BD), pH, electrical conductivity (EC), soil organic matter (SOM), total nitrogen (TN), total carbon (TC), C:N ratio, and the N and C fractions of SOM from the 2016 sampling in silt-loam soils in Arkansas.*

loss in soils, as well as the oxidation of SOC associated with cultivation, which could also be contributing to the overall loss of soil C in the Grand Prairie. Conventional tillage is carried out on an annual basis in the agricultural sites from the Grand Prairie used in this study, thereby increasing the potential loss of topsoil and C from erosion and the loss of SOC from oxidation and decomposition. Similar to the results of this study, Brye et al. [15] reported a net loss of SOC from the top 10 cm in the Grand Prairie during a 14-year period from the same Seidenstricker sites used in this study, where, averaged by landuse, SOC decreased at a rate of 0.1 Mg SOC ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> . Over a 6-year period between 2001 and 2007, Brye and Gbur [13] also reported, averaged across landuse, soil C sequestration rates in the top 10 cm were 0.5 and −0.4 Mg SOC ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> in the Ozark Highlands and the Grand Prairie, respectively. Similarly, Brye and Gbur [14] reported that, on average, SOC increased by 0.13 Mg SOC ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> in the top 10 cm in the Ozark Highlands. In contrast to the results of this study, a field experiment conducted on a silt-loam soil under soybean production in the Mississippi River Delta region of eastern Arkansas, approximately 80 km east of the sites in the Grand Prairie used for this study, showed that TC in the top 10 cm increased at an average of 0.6 Mg SOC ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> over a 6-year study period across numerous tillage-burnresidue-level treatment combinations [24]. A study conducted across Texas (e.g., Bushland, Temple, and Corpus Christi) determined the linear relationship between SOC sequestration and average annual temperature was stronger (r2 = 0.99) than with rainfall (r2 = 0.40), where SOC decreased by 0.17 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> for every degree increase in the annual

**37**

Highlands (0.18 year<sup>−</sup><sup>1</sup>

**Figure 3.**

*different at P < 0.05.*

the Grand Prairie (0.25% year<sup>−</sup><sup>1</sup>

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas*

*DOI: http://dx.doi.org/10.5772/intechopen.83783*

temperature, and SOC only decreased by 0.0023 Mg ha<sup>−</sup><sup>1</sup>

more difficult to predict and does not follow a linear relationship.

year<sup>−</sup><sup>1</sup>

) than in Ozark Highlands (−0.04% year<sup>−</sup><sup>1</sup>

Results of the current study support the well-documented pattern that SOC sequestration is greater in cooler (i.e., the Ozark Highlands) compared to warmer climates (i.e., the Grand Prairie); however, the relationship between soil moisture levels and SOC sequestration is

*Landuse effects by physiographic region on soil organic matter (SOM), total nitrogen, and total carbon content and concentration in the top 10 cm from the 2016 sampling only under either agricultural management (AG) or undisturbed prairie (PR) landuse in the Grand Prairie (GP) region of east-central Arkansas and the Ozark Highlands (OZH) region of northwest Arkansas. Different letters associated with mean values on a panel are* 

As a result of decreased TN and increased TC, averaged across landuse, the soil C:N ratio increased in both regions, but increased more over time in the Ozark

Similar to the results of this study, Brye and Gbur [13] concluded that the soil C:N ratio increased between 2001 and 2007, but only under the agricultural landuse in the Grand Prairie and that the soil C:N ratio did not change over time under native prairie in the Grand Prairie and the Ozark Highlands, as well as under agricultural landuse in the Ozark Highlands. In contrast, Brye and Gbur [14] showed that the soil C:N ratio increased by 3.6% between 2002 and 2008 in grasslands in the Ozark Highlands. Averaged across landuse, the TN fraction of SOM changed more over time in

both did not differ from a change of zero (**Table 6**). In contrast, the TC fraction of

) than in the Grand Prairie region (0.13 year<sup>−</sup><sup>1</sup>

as rainfall increased [25].

, **Table 6**).

), but

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas DOI: http://dx.doi.org/10.5772/intechopen.83783*

#### **Figure 3.**

*CO2 Sequestration*

*Region* Grand Prairie (GP)

Ozark Highlands (OZH)

*Landuse* Agriculture (AG)

Prairie (PR)

*\**

*†*

*yr<sup>−</sup><sup>1</sup>*

**Table 6.**

Region × landuse

*; C:N, yr<sup>−</sup><sup>1</sup>*

*silt-loam soils in Arkansas.*

**Treatment Soil properties†**

**BD pH EC SOM TN TC C:N N/SOM C/SOM**

0.005 0.027 0.002 −0.37b\* −0.04b\* −0.33b\* 0.13b\* 0.25 −0.32b\*

0.003 −0.006 0.001 0.04a −0.01a\* 0.28a\* 0.18a\* −0.04 0.52a\*

0.006 0.019 0.003 −0.21 −0.02 0.06a 0.19a\* 0.44 0.29

0.001 0.001 0.000 −0.13 −0.03 −0.12b 0.12b\* 0.05 −0.09

GP-AG 0.008 0.053a\**††* 0.005a\* −0.38 −0.03 −0.19 0.18 −0.09 −0.10 GP-PR 0.001 0.000b −0.000b −0.36 −0.05 −0.47 0.08 0.42 −0.54 OZH-AG 0.005 −0.015b\* 0.001b\* −0.03 −0.02 0.32 0.21 0.03 0.68 OZH-PR 0.000 0.003b 0.000b 0.11 −0.01 0.24 0.16 −0.06 0.35

 *yr<sup>−</sup><sup>1</sup>*

*††Different lower case letters for a soil property within a treatment category indicate a significant difference (P < 0.05).*

*Summary of mean soil properties in the top 10 cm by treatment (i.e., physiographic region, landuse and their interaction) for soil bulk density (BD), pH, electrical conductivity (EC), soil organic matter (SOM), total nitrogen (TN), total carbon (TC), C:N ratio, and the N and C fractions of SOM from the 2016 sampling in* 

*.*

*; pH, yr<sup>−</sup><sup>1</sup>*

*; EC, dS m<sup>−</sup><sup>1</sup>*

 *yr<sup>−</sup><sup>1</sup>*

*; SOM, TN, and TC, Mg ha<sup>−</sup><sup>1</sup>*

**36**

a rate of 0.1 Mg SOC ha<sup>−</sup><sup>1</sup>

0.13 Mg SOC ha<sup>−</sup><sup>1</sup>

were 0.5 and −0.4 Mg SOC ha<sup>−</sup><sup>1</sup>

average of 0.6 Mg SOC ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

and average annual temperature was stronger (r2

where SOC decreased by 0.17 Mg ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

*An asterisk indicates mean value is greater than 0 (P < 0.05).*

*; and N/SOM and C/SOM, % yr<sup>−</sup><sup>1</sup>*

*Units for the soil properties are as follows: BD, g cm<sup>−</sup><sup>3</sup>*

year<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

loss in soils, as well as the oxidation of SOC associated with cultivation, which could also be contributing to the overall loss of soil C in the Grand Prairie. Conventional tillage is carried out on an annual basis in the agricultural sites from the Grand Prairie used in this study, thereby increasing the potential loss of topsoil and C from erosion and the loss of SOC from oxidation and decomposition. Similar to the results of this study, Brye et al. [15] reported a net loss of SOC from the top 10 cm in the Grand Prairie during a 14-year period from the same Seidenstricker sites used in this study, where, averaged by landuse, SOC decreased at

Gbur [13] also reported, averaged across landuse, soil C sequestration rates in the top 10 cm

respectively. Similarly, Brye and Gbur [14] reported that, on average, SOC increased by

of this study, a field experiment conducted on a silt-loam soil under soybean production in the Mississippi River Delta region of eastern Arkansas, approximately 80 km east of the sites in the Grand Prairie used for this study, showed that TC in the top 10 cm increased at an

residue-level treatment combinations [24]. A study conducted across Texas (e.g., Bushland, Temple, and Corpus Christi) determined the linear relationship between SOC sequestration

year<sup>−</sup><sup>1</sup>

. Over a 6-year period between 2001 and 2007, Brye and

in the top 10 cm in the Ozark Highlands. In contrast to the results

in the Ozark Highlands and the Grand Prairie,

over a 6-year study period across numerous tillage-burn-

= 0.99) than with rainfall (r2

for every degree increase in the annual

= 0.40),

*Landuse effects by physiographic region on soil organic matter (SOM), total nitrogen, and total carbon content and concentration in the top 10 cm from the 2016 sampling only under either agricultural management (AG) or undisturbed prairie (PR) landuse in the Grand Prairie (GP) region of east-central Arkansas and the Ozark Highlands (OZH) region of northwest Arkansas. Different letters associated with mean values on a panel are different at P < 0.05.*

temperature, and SOC only decreased by 0.0023 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> as rainfall increased [25]. Results of the current study support the well-documented pattern that SOC sequestration is greater in cooler (i.e., the Ozark Highlands) compared to warmer climates (i.e., the Grand Prairie); however, the relationship between soil moisture levels and SOC sequestration is more difficult to predict and does not follow a linear relationship.

As a result of decreased TN and increased TC, averaged across landuse, the soil C:N ratio increased in both regions, but increased more over time in the Ozark Highlands (0.18 year<sup>−</sup><sup>1</sup> ) than in the Grand Prairie region (0.13 year<sup>−</sup><sup>1</sup> , **Table 6**). Similar to the results of this study, Brye and Gbur [13] concluded that the soil C:N ratio increased between 2001 and 2007, but only under the agricultural landuse in the Grand Prairie and that the soil C:N ratio did not change over time under native prairie in the Grand Prairie and the Ozark Highlands, as well as under agricultural landuse in the Ozark Highlands. In contrast, Brye and Gbur [14] showed that the soil C:N ratio increased by 3.6% between 2002 and 2008 in grasslands in the Ozark Highlands.

Averaged across landuse, the TN fraction of SOM changed more over time in the Grand Prairie (0.25% year<sup>−</sup><sup>1</sup> ) than in Ozark Highlands (−0.04% year<sup>−</sup><sup>1</sup> ), but both did not differ from a change of zero (**Table 6**). In contrast, the TC fraction of


#### **Table 7.**

*Summary of mean soil properties by treatment (i.e., physiographic region, landuse, and their interaction) for soil organic matter (SOM), total nitrogen (TN), total carbon (TC) concentrations in the top 10 cm from the 2016 sampling in silt-loam soils in Arkansas.*

SOM, averaged across landuse, increased over time in the Ozark Highlands (0.52% year<sup>−</sup><sup>1</sup> ), where the TC fraction of SOM decreased over time in the Grand Prairie (−0.32% year<sup>−</sup><sup>1</sup> ) (**Table 6**). Increased TN within the available above- and belowground biomass and the resulting SOM, especially in N-limited ecosystems such as native prairies or agricultural fields, can lead to increased microbial decomposition and therefore loss of C and N within the soil until periods of anaerobic conditions or cooler temperatures slow down decomposition process, therefore resulting in an accumulation of SOC. Brye and Gbur [14] reported that TC and TN fractions of SOM did not change over time in the Ozark Highlands, whereas the difference in results could be the result of the shorter sampling period of only 7 years used by Brye and Gbur [14] compared to the longer 15-year sampling period used in this study.

In contrast to the other measured soil properties, changes in TC content, C:N ratio, and TC fraction of SOM in the top 10 cm differed (*P* < 0.05) over time between landuses (**Table 5**). Averaged across physiographic region, the change in TC content and the TC fraction of SOM over time were greater in the agricultural compared to the native prairie landuse, but neither soil property change over time differed from a change of zero (**Table 6**). In contrast to TC content and the TC fraction of SOM, averaged across physiographic region, the C:N ratio increased more over time in the agricultural (0.19 year<sup>−</sup><sup>1</sup> ) than in the native prairie landuse (0.12 year<sup>−</sup><sup>1</sup> ; **Table 6**).

These results are somewhat contradictory to the stated hypothesis, where greater SOC sequestration was expected to occur in the native prairie landuse over time. However, the disagreement between the results and the stated hypothesis was likely driven by the fact that the largest numeric increase in TC content occurred within the agricultural landuse (0.32 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) in the Ozark Highlands and the greatest numeric decrease occurred in the native prairie in the Grand Prairie (−0.47 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ). Since the agriculturally managed soils in the Ozark Highlands were not tilled on any regular basis and were used as grazed pastureland and mowed hayland, it is within reason that SOC would be increasing within these

**39**

previous studies [11–15].

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas*

ecosystems, as there are likely fertilizers added annually or semi-annually to these agroecosystems in the form of both inorganic fertilizers and/or manure, which would stimulate plant growth and increase above- and belowground biomass to add

Managed grazing practices (i.e., rotational grazing) have also been known to increase SOC storage in soils. A grazing study conducted in a northern mixed-grass prairie in Wyoming under both light and heavy stocking rates reported increased

year<sup>−</sup><sup>1</sup>

rounding exclosures [26]. However, a meta-analysis conducted on C sequestration in native rangelands of the North American Great Plains revealed that, although there was no statistical relationship between the change in SOC content and the longevity of a grazing management practice, the general trend suggested a decrease in SOC sequestration as the age of the grazing management system increased, where the range of years under management were between about 20 and 80 years [27]. The duration under consistent grassland management for the sites in this study within the Ozark Highlands was roughly greater than 20 years, thus was at the younger end

The decrease in TC in the native prairie within the Grand Prairie was unexpected, where the most likely explanation was the combination of severe fragmentation and periodic vehicle traffic and compaction from agricultural machinery in order to reach the cultivated fields surrounding the prairie. Contrary to the results of this study, Brye et al. [15] reported that, in the same native prairie at the Seidenstricker site in this study, a significant increase in SOC concentration occurred from 1987 to 2001. Brye and Gbur [13] also reported that landuse differences in SOC content change over time, averaged across physiographic region,

of the native prairie and agricultural landuse, respectively. The loss of SOC by the conversion of natural vegetation to cultivated landuse, as well as the continued loss of SOC as duration under cultivation increases, is well known, despite varying results due to factors such as soil texture, cropping system, residue management, and climate [6, 8, 28–30]. Tillage can have one of the greatest influences on SOC loss over time due the disturbance of the macroaggregates that form around and protect particles of undecomposed SOM, leading to the mineralization of that SOM, and consequently a loss of SOC. A study conducted on a silty-clay-loam soil in southcentral Texas reported an average 50% increase in SOC storage in the top 5 cm over a 20-year sampling period under a no-tillage management plan compared to a

Jones and Donnelly [31] conducted a meta-analysis study among landuses ranging from native undisturbed grasslands to poorly managed rangelands and concluded global soil C sequestration rates in the top 15 and/or 30 cm ranged

est mean soil C sequestration rate was measured in the agriculturally managed

sequestration rates were expected to occur in the native prairies compared to the agricultural landuse and greater accumulation of SOM, TC, and TN was expected in the Grand Prairie region compared to the Ozark Highlands based on results of previous studies conducted at these sites [11–15]. Differences between studies conducted previously at these sites could stem from variations in sampling and analytical methods over time; however, differences are more likely the result of actual changes over time, identified by direct measurements, over a longer period (i.e., 15 years) in this study instead of using regression analyses or linear relationships and shorter study periods (i.e., ≤8 years) that were used in several of the

year<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

) compared to the non-grazed sur-

year<sup>−</sup><sup>1</sup>

. In the current study, the larg-

). However, greater SOC

in the top 10 cm

*DOI: http://dx.doi.org/10.5772/intechopen.83783*

SOC in the top 30 cm (0.30 Mg C ha<sup>−</sup><sup>1</sup>

conventional tillage practice [30].

from 0 to approximately 8 Mg SOC ha<sup>−</sup><sup>1</sup>

soils within the Ozark Highlands (0.32 Mg C ha<sup>−</sup><sup>1</sup>

of the age range evaluated by Derner and Schuman [27].

equated to SOC sequestration rates of 0.4 and −0.3 Mg ha<sup>−</sup><sup>1</sup>

to the SOM and SOC pools.

#### *Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas DOI: http://dx.doi.org/10.5772/intechopen.83783*

ecosystems, as there are likely fertilizers added annually or semi-annually to these agroecosystems in the form of both inorganic fertilizers and/or manure, which would stimulate plant growth and increase above- and belowground biomass to add to the SOM and SOC pools.

Managed grazing practices (i.e., rotational grazing) have also been known to increase SOC storage in soils. A grazing study conducted in a northern mixed-grass prairie in Wyoming under both light and heavy stocking rates reported increased SOC in the top 30 cm (0.30 Mg C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) compared to the non-grazed surrounding exclosures [26]. However, a meta-analysis conducted on C sequestration in native rangelands of the North American Great Plains revealed that, although there was no statistical relationship between the change in SOC content and the longevity of a grazing management practice, the general trend suggested a decrease in SOC sequestration as the age of the grazing management system increased, where the range of years under management were between about 20 and 80 years [27]. The duration under consistent grassland management for the sites in this study within the Ozark Highlands was roughly greater than 20 years, thus was at the younger end of the age range evaluated by Derner and Schuman [27].

The decrease in TC in the native prairie within the Grand Prairie was unexpected, where the most likely explanation was the combination of severe fragmentation and periodic vehicle traffic and compaction from agricultural machinery in order to reach the cultivated fields surrounding the prairie. Contrary to the results of this study, Brye et al. [15] reported that, in the same native prairie at the Seidenstricker site in this study, a significant increase in SOC concentration occurred from 1987 to 2001. Brye and Gbur [13] also reported that landuse differences in SOC content change over time, averaged across physiographic region, equated to SOC sequestration rates of 0.4 and −0.3 Mg ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> in the top 10 cm of the native prairie and agricultural landuse, respectively. The loss of SOC by the conversion of natural vegetation to cultivated landuse, as well as the continued loss of SOC as duration under cultivation increases, is well known, despite varying results due to factors such as soil texture, cropping system, residue management, and climate [6, 8, 28–30]. Tillage can have one of the greatest influences on SOC loss over time due the disturbance of the macroaggregates that form around and protect particles of undecomposed SOM, leading to the mineralization of that SOM, and consequently a loss of SOC. A study conducted on a silty-clay-loam soil in southcentral Texas reported an average 50% increase in SOC storage in the top 5 cm over a 20-year sampling period under a no-tillage management plan compared to a conventional tillage practice [30].

Jones and Donnelly [31] conducted a meta-analysis study among landuses ranging from native undisturbed grasslands to poorly managed rangelands and concluded global soil C sequestration rates in the top 15 and/or 30 cm ranged from 0 to approximately 8 Mg SOC ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> . In the current study, the largest mean soil C sequestration rate was measured in the agriculturally managed soils within the Ozark Highlands (0.32 Mg C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ). However, greater SOC sequestration rates were expected to occur in the native prairies compared to the agricultural landuse and greater accumulation of SOM, TC, and TN was expected in the Grand Prairie region compared to the Ozark Highlands based on results of previous studies conducted at these sites [11–15]. Differences between studies conducted previously at these sites could stem from variations in sampling and analytical methods over time; however, differences are more likely the result of actual changes over time, identified by direct measurements, over a longer period (i.e., 15 years) in this study instead of using regression analyses or linear relationships and shorter study periods (i.e., ≤8 years) that were used in several of the previous studies [11–15].

*CO2 Sequestration*

*Region*

*Landuse*

*Region × landuse*

**Treatment SOM (% yr<sup>−</sup><sup>1</sup>**

*An asterisk indicates mean value is greater than 0 (P < 0.05).*

*2016 sampling in silt-loam soils in Arkansas.*

SOM, averaged across landuse, increased over time in the Ozark Highlands (0.52%

*Summary of mean soil properties by treatment (i.e., physiographic region, landuse, and their interaction) for soil organic matter (SOM), total nitrogen (TN), total carbon (TC) concentrations in the top 10 cm from the* 

Grand Prairie (GP) −0.04b\* −0.004b\* −0.03b\* Ozark Highlands (OZH) −0.01a −0.002a\* 0.02a\*

Agriculture (AG) −0.04 −0.003 −0.00 Prairie (PR) −0.01 −0.003 −0.01

GP-AG −0.05 −0.003 −0.02 GP-PR −0.04 −0.004 −0.04 OZH-AG −0.03 −0.003 0.01 OZH-PR −0.01 −0.001 0.02

ground biomass and the resulting SOM, especially in N-limited ecosystems such as native prairies or agricultural fields, can lead to increased microbial decomposition and therefore loss of C and N within the soil until periods of anaerobic conditions or cooler temperatures slow down decomposition process, therefore resulting in an accumulation of SOC. Brye and Gbur [14] reported that TC and TN fractions of SOM did not change over time in the Ozark Highlands, whereas the difference in results could be the result of the shorter sampling period of only 7 years used by Brye and Gbur [14] compared to the longer 15-year sampling period used in this

In contrast to the other measured soil properties, changes in TC content, C:N ratio, and TC fraction of SOM in the top 10 cm differed (*P* < 0.05) over time between landuses (**Table 5**). Averaged across physiographic region, the change in TC content and the TC fraction of SOM over time were greater in the agricultural compared to the native prairie landuse, but neither soil property change over time differed from a change of zero (**Table 6**). In contrast to TC content and the TC fraction of SOM, averaged across physiographic region, the C:N ratio increased

These results are somewhat contradictory to the stated hypothesis, where greater SOC sequestration was expected to occur in the native prairie landuse over time. However, the disagreement between the results and the stated hypothesis was likely driven by the fact that the largest numeric increase in TC content occurred

the greatest numeric decrease occurred in the native prairie in the Grand Prairie

Highlands were not tilled on any regular basis and were used as grazed pastureland and mowed hayland, it is within reason that SOC would be increasing within these

year<sup>−</sup><sup>1</sup>

). Since the agriculturally managed soils in the Ozark

more over time in the agricultural (0.19 year<sup>−</sup><sup>1</sup>

within the agricultural landuse (0.32 Mg ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

; **Table 6**).

), where the TC fraction of SOM decreased over time in the Grand Prairie

) (**Table 6**). Increased TN within the available above- and below-

**Soil properties**

**) TC (% yr<sup>−</sup><sup>1</sup>**

**)**

**) TN (% yr<sup>−</sup><sup>1</sup>**

) than in the native prairie landuse

) in the Ozark Highlands and

**38**

year<sup>−</sup><sup>1</sup>

**Table 7.**

*\**

study.

(0.12 year<sup>−</sup><sup>1</sup>

(−0.47 Mg ha<sup>−</sup><sup>1</sup>

(−0.32% year<sup>−</sup><sup>1</sup>

Considering only the Grand Prairie sites consisting of a native tallgrass prairie and three agroecosystems that varied in duration under cultivation that originated as part of the native prairie tract, regression analysis revealed no significant relationship between soil C sequestration rate in the top 10 cm over the 15-year period from 2001 to 2016 (*P* > 0.05) or TC storage from 2016 alone (*P* > 0.05) and duration of years of annual cultivation. Severe fragmentation and mismanagement of the native tallgrass prairie could be the cause of this lack of a significant linear relationship. Brye et al. [15] somewhat similarly concluded that the relationship between SOC and years of cultivation did not change significantly over a 14-year period between 1987 and 2001 in the same study sites within the Seidenstricker site.

#### **4. Conclusions**

Changes in near-surface soil C and N and related properties, assessed by direct measurement, over a 15-year period in silt-loam soils in Arkansas differed between physiographic regions and landuse and among their treatment combinations. Similar to that hypothesized, averaged across region, SOM, TC, and TN in the native prairie landuse did not change over time, indicating some degree of equilibrium exists in the less-disturbed, more natural ecosystems. However, in contrast to that hypothesized, SOM, TC, and TN also did not change over time in the managed agricultural landuse when averaged across region. Though not significant, cultivated row-crop agriculture on alluvial soils was shown to have at least numerically lower C and N storage and C and N decreased more over time than that in managed pastureland on residual soils, likely due to the long history of intensive tillage, despite alluvial soils typically being generally considered more fertile than residual soils.

Results of this study demonstrate how the combination of climate and soil parent material, which constituted the major differences between physiographic regions that were investigated in this study, can have a large influence on SOM, C and N storage, and change over time. Despite differing types of managed agricultural landuse between the two regions, physiographic region clearly had a greater influence than landuse, as evidenced by more soil property changes over time evaluated in this study differing between regions when averaged across landuse than differed between landuses when averaged across regions.

Results also showed that more numerous differences between regions and landuses were identified when only a single measurement set in time was considered compared to much fewer differences between regions and landuses recognized when assessing change over time based on direct measurements. In the absence of direct measurements, any inferences drawn about temporal trends in soil properties, particularly those like SOM, C, and N, that are key to improving understanding about the effects of rising mean annual air temperatures, rising atmospheric greenhouse gas concentrations, and global climate change in general must be tempered with numerous caveats because those inferences could be misleading.

Many types of ecosystems are resilient and conditioned to resist change. Though inconvenient for numerous reasons, direct measurement over time in long-term studies, as were conducted in this study, perhaps offers the most appropriate methodology to assess temporal variation in soil properties and ecosystem characteristics toward understanding global climate change. Therefore, long-term, direct-measurement studies should be maintained and expanded to increase the accuracy of cataloging important ecosystem processes, such as soil C sequestration and other beneficial soil properties, particularly in disappearing native prairie ecosystems in Arkansas and elsewhere. The results of long-term studies will provide more useful and effective guidance for rehabilitating and/or restoring areas of

**41**

**Author details**

provided the original work is properly cited.

Marya McKee, Kristofor R. Brye\* and Lisa Wood University of Arkansas, Fayetteville, AR, USA

\*Address all correspondence to: kbrye@uark.edu

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas*

degraded land and/or minimally productive agricultural land. Ecosystem restoration projects will not only likely increase soil health and sustainability, but applying similar restoration principles to agricultural lands may increase productivity and collectively contribute to slowing, or potentially reversing, the global threat of

This research study was partially funded by the Arkansas Natural Resources

rising greenhouse gases in the atmosphere and climate change.

There are no conflicts of interest to declare.

*DOI: http://dx.doi.org/10.5772/intechopen.83783*

**Acknowledgements**

Conservation Service.

**Conflict of interest**

*Landuse and Physiographic Region Effects on Soil Carbon and Nitrogen Sequestration in Arkansas DOI: http://dx.doi.org/10.5772/intechopen.83783*

degraded land and/or minimally productive agricultural land. Ecosystem restoration projects will not only likely increase soil health and sustainability, but applying similar restoration principles to agricultural lands may increase productivity and collectively contribute to slowing, or potentially reversing, the global threat of rising greenhouse gases in the atmosphere and climate change.

#### **Acknowledgements**

*CO2 Sequestration*

**4. Conclusions**

Considering only the Grand Prairie sites consisting of a native tallgrass prairie and three agroecosystems that varied in duration under cultivation that originated as part of the native prairie tract, regression analysis revealed no significant relationship between soil C sequestration rate in the top 10 cm over the 15-year period from 2001 to 2016 (*P* > 0.05) or TC storage from 2016 alone (*P* > 0.05) and duration of years of annual cultivation. Severe fragmentation and mismanagement of the native tallgrass prairie could be the cause of this lack of a significant linear relationship. Brye et al. [15] somewhat similarly concluded that the relationship between SOC and years of cultivation did not change significantly over a 14-year period between 1987 and 2001 in the same study sites within the Seidenstricker site.

Changes in near-surface soil C and N and related properties, assessed by direct measurement, over a 15-year period in silt-loam soils in Arkansas differed between physiographic regions and landuse and among their treatment combinations. Similar to that hypothesized, averaged across region, SOM, TC, and TN in the native prairie landuse did not change over time, indicating some degree of equilibrium exists in the less-disturbed, more natural ecosystems. However, in contrast to that hypothesized, SOM, TC, and TN also did not change over time in the managed agricultural landuse when averaged across region. Though not significant, cultivated row-crop agriculture on alluvial soils was shown to have at least numerically lower C and N storage and C and N decreased more over time than that in managed pastureland on residual soils, likely due to the long history of intensive tillage, despite alluvial soils typically

Results of this study demonstrate how the combination of climate and soil parent material, which constituted the major differences between physiographic regions that were investigated in this study, can have a large influence on SOM, C and N storage, and change over time. Despite differing types of managed agricultural landuse between the two regions, physiographic region clearly had a greater influence than landuse, as evidenced by more soil property changes over time evaluated in this study differing between regions when averaged across landuse

Results also showed that more numerous differences between regions and landuses were identified when only a single measurement set in time was considered compared to much fewer differences between regions and landuses recognized when assessing change over time based on direct measurements. In the absence of direct measurements, any inferences drawn about temporal trends in soil properties, particularly those like SOM, C, and N, that are key to improving understanding about the effects of rising mean annual air temperatures, rising atmospheric greenhouse gas concentrations, and global climate change in general must be tempered

Many types of ecosystems are resilient and conditioned to resist change. Though inconvenient for numerous reasons, direct measurement over time in long-term studies, as were conducted in this study, perhaps offers the most appropriate methodology to assess temporal variation in soil properties and ecosystem characteristics toward understanding global climate change. Therefore, long-term, direct-measurement studies should be maintained and expanded to increase the accuracy of cataloging important ecosystem processes, such as soil C sequestration and other beneficial soil properties, particularly in disappearing native prairie ecosystems in Arkansas and elsewhere. The results of long-term studies will provide more useful and effective guidance for rehabilitating and/or restoring areas of

being generally considered more fertile than residual soils.

than differed between landuses when averaged across regions.

with numerous caveats because those inferences could be misleading.

**40**

This research study was partially funded by the Arkansas Natural Resources Conservation Service.

### **Conflict of interest**

There are no conflicts of interest to declare.

### **Author details**

Marya McKee, Kristofor R. Brye\* and Lisa Wood University of Arkansas, Fayetteville, AR, USA

\*Address all correspondence to: kbrye@uark.edu

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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[27] Derner JD, Shuman GE. Carbon sequestration and rangelands: A synthesis of land management and precipitation effects. Journal of Soil and Water Conservation. 2007;**62**:77-65

[28] Lal R. Carbon sequestration impacts on global climate change and food security. Science. 2004;**304**:1623-1627

[29] Lal R. Soil carbon sequestration to mitigate climate change. Geoderma. 2004;**123**:1-22

[30] Wright AL, Hons FM. Tillage impacts on soil aggregation and carbon and nitrogen sequestration under wheat cropping sequences. Soil and Tillage Research. 2005;**84**:67-75

[31] Jones MB, Donnelly A. Carbon sequestration in temperate grassland ecosystems and the influence of management, climate and elevated CO2. New Phytologist. 2004;**164**:423-439

**42**

*CO2 Sequestration*

**References**

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2007;**80**:1-3

2001;**4**:237-139

Biology. 2000;**6**:317-327

Publication; 2009. p. 410

[1] International Panel on Climate Change (IPCC). Carbon and Other Biogeochemical Cycles. Climate Change 2014—The Physical Science Basis [Online]. 2014. pp. 465-514. Available from: http://ipcc.ch/index.htm [Accessed: 25 May 2018]

[9] Six J, Bossuyt H, Degryze S, Denef K.

A history of research on the link between (micro)aggregates, soil biota, and soil organic matter dynamics. Soil and Tillage Research. 2004;**79**:7-31

[10] United States Department of Agriculture, Soil Conservation Service (USDA-SCS). Land resource regions and major land resource areas of the United States, the Caribbean, and the Pacific Basin. In: Agriculture Handbook 296. Washington DC: USDA-SCS; 1981.

[11] Brye KR, West CP. Grassland management effects on soil surface properties in the Ozark Highlands. Soil

[12] Brye KR, West CP, Gbur EE. Soil quality differences under native tallgrass prairie across a climosequence in Arkansas. The American Midland

Science. 2005;**170**:63-73

Naturalist. 2004;**152**:214-230

2010;**175**:339-348

2011;**176**:129-135

2004;**34**:177-192

[13] Brye KR, Gbur EE. Regional differences in soil carbon and nitrogen storage as affected by land use and soil moisture regime. Soil Science.

[14] Brye KR, Gbur EE. Near-surface soil property changes over time as affected by grassland management in the Ozark Highlands. Soil Science.

[15] Brye KR, Gbur EE, Miller DM. Relationships among soil carbon and physiochemical properties of a Typic Albaqualf as affected by years under cultivation. Communications in Soil Science and Plant Analysis.

[16] Brye KR, Pirani AL. Native soil quality and the effects of tillage in the Grand Prairie region of eastern Arkansas. The American Midland

Naturalist. 2005;**154**:28-41

p. 682

[2] Environmental Protection Agency (EPA). Greenhouse gas emissions: Sources of greenhouse gas emissions [Internet]. 2017. Available from: https:// www.epa.gov/ghgemissions/sourcesgreenhouse-gas-emissions [Accessed:

[3] Stevenson FJ. Carbon balance of the soil and role of organic matter in soil fertility. In: Stevenson FJ, editor. Cycles of Soil: Carbon, Nitrogen, Phosphorus, Sulfur, Micronutrients. New York, NY: John Wiley and Sons; 1986. pp. 45-77

[4] Brady NC, Weil RR. The Nature and Properties of Soils. 14th ed. Upper Saddle River, NJ: Pearson Education Inc;

[5] Lal R, Follett RF, editors. Soil Carbon Sequestration and the Greenhouse Effect. 2nd ed. Vol. 57. Madison, WI: Soil Science Society of America Special

[6] McCarl BA, Metting FB, Rice C. Soil carbon sequestration. Climate Change.

agroecosystems of southern Wisconsin:

[7] Kucharik CJ, Brye KR, Norman JM, Foley JA, Gower ST, Bundy LG. Measurements and modeling of carbon and nitrogen cycling in

Potential for SOC sequestration during the next 50 years. Ecosystems.

[8] Post WM, Kwon KC. Soil carbon sequestration and land-use change: Process and potential. Global Change

**45**

**Chapter 4**

Soils

*Rainer Nerger*

**Abstract**

Strategic Management of Grazing

Grassland Systems to Maintain

and Increase Organic Carbon in

*Beverley Henry, Katja Klumpp, Peter Koncz, Mireia Llorente,* 

Understanding management-induced C sequestration potential in soils under

agriculture, forestry, and other land use systems and their quantification to offset increasing greenhouse gases are of global concern. This chapter reviews management-induced changes in C storage in soils of grazing grassland systems, their impacts on ecosystem functions, and their adaptability and needs of protection across socio-economic and cultural settings. In general, improved management of grassland/pasture such as manuring/slurry application, liming and rotational grazing, and low to medium livestock units could sequester C more than under high intensity grazing conditions. Converting cultivated land to pasture, restoration of degraded land, and maximizing pasture phases in mixed-cropping, pasture with mixed-livestock, integrated forestry-pasturage of livestock (silvopastoral) and crop-forestry-pasturage of livestock (agro-silvopastoral) systems could also maintain and enhance soil organic C density (SOCρ). In areas receiving low precipitation and having high erodibility, grazing exclusion might restore degraded grasslands and increase SOCρ. Yet, optimizing C sequestration rates, sowing of more productive grass varieties, judicial inorganic and organic fertilization, rotational grazing, and other climate-resilient approaches could improve overall farm productivity and

profitability and attain sustainability in livestock farming systems.

integrated land uses, livestock farming

**1. Introduction**

**Keywords:** carbon sequestration, grazing grassland, silvopastoralism,

Soil stores 2–3 times more carbon (C) than the atmosphere. Soil organic carbon (SOC) pools under contrasting long-term management systems provide insights into the potential for sequestering C, sustaining soil productivity and maintaining functions in the biosphere-atmosphere interface. The broadest division of grassland, both

*Mohammad Ibrahim Khalil, Rosa Francaviglia,* 

*Beata Emoke Madari, Miriam Muñoz-Rojas and* 

### **Chapter 4**

## Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon in Soils

*Mohammad Ibrahim Khalil, Rosa Francaviglia, Beverley Henry, Katja Klumpp, Peter Koncz, Mireia Llorente, Beata Emoke Madari, Miriam Muñoz-Rojas and Rainer Nerger*

### **Abstract**

Understanding management-induced C sequestration potential in soils under agriculture, forestry, and other land use systems and their quantification to offset increasing greenhouse gases are of global concern. This chapter reviews management-induced changes in C storage in soils of grazing grassland systems, their impacts on ecosystem functions, and their adaptability and needs of protection across socio-economic and cultural settings. In general, improved management of grassland/pasture such as manuring/slurry application, liming and rotational grazing, and low to medium livestock units could sequester C more than under high intensity grazing conditions. Converting cultivated land to pasture, restoration of degraded land, and maximizing pasture phases in mixed-cropping, pasture with mixed-livestock, integrated forestry-pasturage of livestock (silvopastoral) and crop-forestry-pasturage of livestock (agro-silvopastoral) systems could also maintain and enhance soil organic C density (SOCρ). In areas receiving low precipitation and having high erodibility, grazing exclusion might restore degraded grasslands and increase SOCρ. Yet, optimizing C sequestration rates, sowing of more productive grass varieties, judicial inorganic and organic fertilization, rotational grazing, and other climate-resilient approaches could improve overall farm productivity and profitability and attain sustainability in livestock farming systems.

**Keywords:** carbon sequestration, grazing grassland, silvopastoralism, integrated land uses, livestock farming

#### **1. Introduction**

Soil stores 2–3 times more carbon (C) than the atmosphere. Soil organic carbon (SOC) pools under contrasting long-term management systems provide insights into the potential for sequestering C, sustaining soil productivity and maintaining functions in the biosphere-atmosphere interface. The broadest division of grassland, both natural and anthropogenic, is between temperate and tropical grasslands. Globally, grasslands (pasture, silage and hay) dominate major agricultural areas and contribute 20–30% to the SOC pool by sequestering atmospheric CO2, thus mitigating climate change [1, 2]. Livestock graze mostly on pasture and meadows, and the production systems are highly diverse, ranging from low-input grasslands in arid and semiarid regions to highly intensive pasture in more mesic environments, integrating livestockcrop-forage systems. Grazing is one of the most important factors that could change the soil C density in grassland systems. Understanding the impacts of grazing intensity and livestock types under different management systems on SOC sequestration is a key to providing the most effective soil C management strategies.

Soil C storage depends on the C input mainly through the root biomass, added C, and its release mediated by soil processes. Belowground processes may respond differently from aboveground vegetation to grazing whereas change of plant community structure induced by grazing does not necessarily lead to decreased soil C storage [3]. Although grazing in some cases decreases vegetation growth, good management can improve its growth on many degraded lands [4]. In addition to biogeochemical processes and environmental factors, SOC storage under grasslands and the associated land uses is regulated importantly by biotic factors, e.g., livestock type, grazing intensity, grass species, and their heterogeneity [1]. Some recent studies show that intensification of livestock management could enhance C losses in association with emissions of GHGs [5]. Others show that intense grazing pressure and large additions of manure over short periods (e.g., rotational grazing) increase soil C and water infiltration and retention, and eventually enhance plant production [4]. Soil C sequestration in grasslands varies between 0.03 and 1 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> , depending on land type, land use, climatic factors, and treatments [6].

Grazing intensity and management may modify soil physical structure, function, and SOC storage capacity that could reduce or increase nutrient retention, water storage, pollutant attenuation, soil fertility, plant productivity, and species composition [7]. For sustainable management of pastures and rehabilitation of degraded lands, tailoring flexible and site-specific grazing management, depending on climate conditions and the availability of local resources, and avoidance of the extreme process of land degradation that may deteriorate further with climate change are in need. Carbon balance is controlled by the nature, frequency, and intensity of disturbances in grassland ecosystems [8]. However, the relationship between grazing intensity and SOC is generally nonlinear [9]. Previous studies have found mixed results [10], with some showing increases [11], no effect [12], or decreases [13] in SOCρ. Other recent reviews [10] state that high grazing intensity significantly decreases belowground C and N pools, and those effects depend on livestock type and climatic conditions. However, some mechanisms are not well understood, and mixed results are common. Animal manure and other offsite organic applications have significant potential for sequestering C in soils, but the proportion stabilized may depend on local climatic and edaphic conditions and the decomposability/degradability of the materials added [14]. Grazing also accelerates N cycling and promotes N losses through NH3 from urine and dung patches [15] which, in nutrient limited systems, may constrain C inputs and humification rates.

Globally, most soils are responsive to management changes to increase SOCρ. The greatest response comes from retirement and restoration of degraded agricultural lands, manure/bio-solid applications [10], improvements of pasture lands, adaptive grazing management systems, inclusion of woody species into the pasture system, and conversion from cropland to pasture [6]. This chapter advances evidence-based C sequestration potential in soils of pasture and associated lands under various livestock systems (**Figure 1**). The main aims are to (a) improve the knowledge base and understanding of

**47**

**Figure 1.**

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon…*

management practices and technologies to increase and maintain SOC while reducing climate change footprint and achieving productivity and environmental benefits; (b) identify region/biome-specific management practices to enhance/maintain SOC and combat environmental degradation without sacrificing food security; and (c) outline

*Livestock grazing in grassland and other related land uses. (a) Grazing grassland in Temperate regions (Source: ARC 2020), (b) Grazing grassland in Tropical regions (Source: SLU), (c) Grazing grassland in Mediterranean regions (Source: Dreamstime), (d) Grazing grassland in Arid regions (Source: NMSU), (e) Integrated croplivestock system (Source: People Food & Nature) and (f) Integrated silvo-pastural system (Source: Aftaweb).*

**2. Carbon sequestration potential in soils under livestock-associated** 

Adjustment of grazing/management intensity to climate and soil type could increase SOC. Positive and negative impacts of grazing on SOC storage compared to unharvested rangeland have been reported for semi-arid regions of the USA [5], Western Canada [16], the Netherlands [17] and the United Kingdom [18]. In many cases, grazing favors C sequestration via animal returns and heterogeneity of vegetation with the exception of very intensive systems. This can be considered as a mosaic of patches of variable vegetation height, with or without the presence of

economic, ecological, social, and policy options for storing additional SOC.

**pasture management practices**

**2.1 Grazing grassland/pasture management**

*DOI: http://dx.doi.org/10.5772/intechopen.84341*

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon… DOI: http://dx.doi.org/10.5772/intechopen.84341*

**Figure 1.**

*CO2 Sequestration*

natural and anthropogenic, is between temperate and tropical grasslands. Globally, grasslands (pasture, silage and hay) dominate major agricultural areas and contribute 20–30% to the SOC pool by sequestering atmospheric CO2, thus mitigating climate change [1, 2]. Livestock graze mostly on pasture and meadows, and the production systems are highly diverse, ranging from low-input grasslands in arid and semiarid regions to highly intensive pasture in more mesic environments, integrating livestockcrop-forage systems. Grazing is one of the most important factors that could change the soil C density in grassland systems. Understanding the impacts of grazing intensity and livestock types under different management systems on SOC sequestration is

Soil C storage depends on the C input mainly through the root biomass, added C, and its release mediated by soil processes. Belowground processes may respond differently from aboveground vegetation to grazing whereas change of plant community structure induced by grazing does not necessarily lead to decreased soil C storage [3]. Although grazing in some cases decreases vegetation growth, good management can improve its growth on many degraded lands [4]. In addition to biogeochemical processes and environmental factors, SOC storage under grasslands and the associated land uses is regulated importantly by biotic factors, e.g., livestock type, grazing intensity, grass species, and their heterogeneity [1]. Some recent studies show that intensification of livestock management could enhance C losses in association with emissions of GHGs [5]. Others show that intense grazing pressure and large additions of manure over short periods (e.g., rotational grazing) increase soil C and water infiltration and retention, and eventually enhance plant production

a key to providing the most effective soil C management strategies.

[4]. Soil C sequestration in grasslands varies between 0.03 and 1 t C ha<sup>−</sup><sup>1</sup>

Grazing intensity and management may modify soil physical structure, function, and SOC storage capacity that could reduce or increase nutrient retention, water storage, pollutant attenuation, soil fertility, plant productivity, and species composition [7]. For sustainable management of pastures and rehabilitation of degraded lands, tailoring flexible and site-specific grazing management, depending on climate conditions and the availability of local resources, and avoidance of the extreme process of land degradation that may deteriorate further with climate change are in need. Carbon balance is controlled by the nature, frequency, and intensity of disturbances in grassland ecosystems [8]. However, the relationship between grazing intensity and SOC is generally nonlinear [9]. Previous studies have found mixed results [10], with some showing increases [11], no effect [12], or decreases [13] in SOCρ. Other recent reviews [10] state that high grazing intensity significantly decreases belowground C and N pools, and those effects depend on livestock type and climatic conditions. However, some mechanisms are not well understood, and mixed results are common. Animal manure and other offsite organic applications have significant potential for sequestering C in soils, but the proportion stabilized may depend on local climatic and edaphic conditions and the decomposability/degradability of the materials added [14]. Grazing also accelerates N cycling and promotes N losses through NH3 from urine and dung patches [15] which, in nutrient limited systems, may constrain C inputs

Globally, most soils are responsive to management changes to increase SOCρ. The greatest response comes from retirement and restoration of degraded agricultural lands, manure/bio-solid applications [10], improvements of pasture lands, adaptive grazing management systems, inclusion of woody species into the pasture system, and conversion from cropland to pasture [6]. This chapter advances evidence-based C sequestration potential in soils of pasture and associated lands under various livestock systems (**Figure 1**). The main aims are to (a) improve the knowledge base and understanding of

depending on land type, land use, climatic factors, and treatments [6].

 year<sup>−</sup><sup>1</sup> ,

**46**

and humification rates.

*Livestock grazing in grassland and other related land uses. (a) Grazing grassland in Temperate regions (Source: ARC 2020), (b) Grazing grassland in Tropical regions (Source: SLU), (c) Grazing grassland in Mediterranean regions (Source: Dreamstime), (d) Grazing grassland in Arid regions (Source: NMSU), (e) Integrated croplivestock system (Source: People Food & Nature) and (f) Integrated silvo-pastural system (Source: Aftaweb).*

management practices and technologies to increase and maintain SOC while reducing climate change footprint and achieving productivity and environmental benefits; (b) identify region/biome-specific management practices to enhance/maintain SOC and combat environmental degradation without sacrificing food security; and (c) outline economic, ecological, social, and policy options for storing additional SOC.

#### **2. Carbon sequestration potential in soils under livestock-associated pasture management practices**

#### **2.1 Grazing grassland/pasture management**

Adjustment of grazing/management intensity to climate and soil type could increase SOC. Positive and negative impacts of grazing on SOC storage compared to unharvested rangeland have been reported for semi-arid regions of the USA [5], Western Canada [16], the Netherlands [17] and the United Kingdom [18]. In many cases, grazing favors C sequestration via animal returns and heterogeneity of vegetation with the exception of very intensive systems. This can be considered as a mosaic of patches of variable vegetation height, with or without the presence of

urine and dung. In contrast, very intense grazing, or short periods between successive grazing can lead to a trade-off between biomass production and C inputs to soil (i.e., root production and litter), and subsequent C sequestration [8].

Even so, managed grasslands have the potential to act as C sinks, sequestrating on average 0.7 ± 0.16 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> [19]. However, there is a large variability in soil C accrual due to differences in climate, soil, and vegetation conditions as well as due to varying biomass removal. Under low biomass removal [~30% of present biomass], soil C sequestration of European grasslands may reach up to 1.27 ± 0.40 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> , while at medium biomass removal (30–70%) to high (>70%) values are lower, depending on fertilization level and climate (**Table 1**). Indeed, high biomass removal (>70%) may lead to SOC losses. In North Dakota, USA, a long-term study in three mixed prairie sites (mainly Blue grama: *Bouteloua gracilis*) found that the moderately grazed pasture (2.6 ha steer<sup>−</sup><sup>1</sup> ) contained 17% less SOC than the exclosure treatment, but heavy grazing (0.9 ha steer<sup>−</sup><sup>1</sup> ) did not reduce it further (**Table 1**) [5, 18]. For 12 years, the annual rate of change in SOC (0–90 cm) followed the order: low grazing pressure (1.17 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) > unharvested (0.64) = high grazing pressure (0.51) > hayed (0.22). Moreover, grazed (cattle) tall fescue-common bermudagrass pasture (20 years old) had greater SOC (31%) at a depth of 0–20 cm than adjacent 24-year old conservation-tillage cropland [19]. Improved C sequestration for extensive grazing, showing a sink of C (0.86 ± 0.74 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ), vs. mown systems was also confirmed for Hungarian sandy grasslands, during which the mowing management (cut once per year) became a source of C (−1.22 ± 0.35 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) [20]. These C losses were attributed to a higher herbage use intensity of the mowed grassland compared to the grazed one. In addition to intensive biomass removal, soil erosion can contribute to reducing SOC in pastures heavily grazed by cattle.

Even so, under some conditions, high biomass removal may improve C sequestration. Such as the semi-arid grasslands in Colorado (shortgrass steppe), where changes in SOC were higher with heavy grazing (60–75% utilization; 2.27 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) compared to light grazing (20–35% utilization; 0.55 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) (**Table 1**) [21]. Significantly higher soil C (0–30 cm) was measured in grazed pastures (1.06 ± 0.03 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) compared to nongrazed exclosures (0.20 ± 0.14). In fact, heavy stocking rates in shortgrass steppe resulted in a plant community dominated by the C4 grass, blue grama, while exclusion of livestock grazing increased the production of C3 grasses and prickly pear cactus (*Opuntia polyacantha*) [22]. In addition to plant community changes, grazing exclusion leads to an immobilization of C in excessive aboveground plant litter of forbs and grasses and lack of dense fibrous rooting systems conducive to SOM formation and accumulation. Accordingly, outcomes indicate that stimulation of annual shoot turnover and redistribution of C within the plant-soil system contributes to an increase in SOC. Furthermore, the higher SOC in heavily grazed grassland may be attributable to higher inorganic C (SIC), than the nongrazed treatment, and longterm grazing could decrease the readily mineralizable fraction of SOM. These effects emphasize the importance of inorganic C in assessing the mass and distribution of plant-soil C, and in evaluating the impacts of grazing management on C sequestration particularly in semiarid and arid ecosystems.

C sequestration, of course, should not be the only priority when making decision of pasture-based livestock farming systems located in less productive areas, (e.g., southern Europe and mountainous regions), which are highly relevant in both environmental and social terms. Although, C sequestration should be promoted to mitigate climate change and improve soil quality (water holding capacity and nutrient turnover). Solutions such as adaptive multi-paddock grazing or rotational grazing systems may increase carrying capacity and restore soil C. In other systems

**49**

**Table 1.**

*practices.*

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon…*

Cattle L = LSU <0.6; HUI

**Livestock density (LSU: L, M, and H) \* and management practices**

<0.3

M = LSU 0.6–1.3, HUI 0.3–0.7

Density = 0%, L to H = 50–200%

L = 0.64 NLSU, HUE: 0.4

goat, and horses)

L = 0.7–2.5 ewe eq ha<sup>−</sup><sup>1</sup> (cattle, sheep, pigs, and goats)

Steers H + M Inorg. (N:

L H

H

L = YH (20–35% utilization) H = YH (60–75% utilization)

**Fertilization (N, P) and liming (kg ha<sup>−</sup><sup>1</sup> )**

> Zero and ≥100 N

> Zero and ≥100 N

H = HUI 0.7–1 Zero −0.57 ± nd

M — 0.50 ± nd Liming ± nutrients

> Liming ± phosphate

M — 0.35 ± nd

L = HUE 0.6 — −1.23 ± 0.35

200–270), inorg-org. (73.6), and broiler litter

M — 0.65 ± nd

Long-term grazing Heavy grazing

*); L = Low; M = Medium; H = High; nd = Not determined; YH = Yearling* 

*) in grazing grassland/pasture and the associated management* 

>100 kg N 0.74 ± 0.30

— 0.10 ± 0.10

— 0.86 ± 0.74

— 0.0013 ± nd

— 0.05–0.10

— 1.17 ± nd

— 0.20 ± nd\*

**SOCρ changes (t C ha<sup>−</sup><sup>1</sup>**

1.27 ± 0.40\*

1.12 ± 0.32\*

0.40 ± 0.06\*

0.35 ± nd\*

−0.45 ± 0.53\*

0.03 ± 0.00

0.51 ± nd

1.51 ± nd\*

0.55 ± nd 2.27 ± nd

 **year<sup>−</sup><sup>1</sup> )**

*DOI: http://dx.doi.org/10.5772/intechopen.84341*

**category**

Mixed (cattle/ sheep)

> Cattle (mowed)

Hungary [30] Mixed L (Cattle, sheep,

Cattle Angus Steers

 *year<sup>−</sup><sup>1</sup>*

 *year<sup>−</sup><sup>1</sup>*

Sheep L

**Biomes/regions Livestock** 

The EU and France (managed grassland) [23]

Australia (perennial and annual pasture) [24–28]

Rotational grazing

Hungary (extensive

Mediterranean, Spain (extensive grazing)

USA (mixed prairie) [5] (Grazed Bermuda grass) [31, 32] -Mixed prairie - Short-grass steppe

[21, 22]

*LSU = Livestock density unit (ha<sup>−</sup><sup>1</sup>*

*Annual SOC density changes (t C ha<sup>−</sup><sup>1</sup>*

*heifers; SOCρ = SOC density; \* = Pooled/Averaged.*

[29]

[20]

grazing) (Grazing +1 cut)


*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon… DOI: http://dx.doi.org/10.5772/intechopen.84341*

*LSU = Livestock density unit (ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ); L = Low; M = Medium; H = High; nd = Not determined; YH = Yearling heifers; SOCρ = SOC density; \* = Pooled/Averaged.*

#### **Table 1.**

*CO2 Sequestration*

1.27 ± 0.40 t C ha<sup>−</sup><sup>1</sup>

(0.86 ± 0.74 t C ha<sup>−</sup><sup>1</sup>

C ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

ing on average 0.7 ± 0.16 t C ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

reducing SOC in pastures heavily grazed by cattle.

compared to light grazing (20–35% utilization; 0.55 t C ha<sup>−</sup><sup>1</sup>

became a source of C (−1.22 ± 0.35 t C ha<sup>−</sup><sup>1</sup>

particularly in semiarid and arid ecosystems.

urine and dung. In contrast, very intense grazing, or short periods between successive grazing can lead to a trade-off between biomass production and C inputs to soil

Even so, managed grasslands have the potential to act as C sinks, sequestrat-

in soil C accrual due to differences in climate, soil, and vegetation conditions as well as due to varying biomass removal. Under low biomass removal [~30% of present biomass], soil C sequestration of European grasslands may reach up to

(>70%) values are lower, depending on fertilization level and climate (**Table 1**). Indeed, high biomass removal (>70%) may lead to SOC losses. In North Dakota, USA, a long-term study in three mixed prairie sites (mainly Blue grama: *Bouteloua* 

reduce it further (**Table 1**) [5, 18]. For 12 years, the annual rate of change in SOC

vested (0.64) = high grazing pressure (0.51) > hayed (0.22). Moreover, grazed (cattle) tall fescue-common bermudagrass pasture (20 years old) had greater SOC (31%) at a depth of 0–20 cm than adjacent 24-year old conservation-tillage cropland [19]. Improved C sequestration for extensive grazing, showing a sink of C

sandy grasslands, during which the mowing management (cut once per year)

uted to a higher herbage use intensity of the mowed grassland compared to the grazed one. In addition to intensive biomass removal, soil erosion can contribute to

in SOC were higher with heavy grazing (60–75% utilization; 2.27 t C ha<sup>−</sup><sup>1</sup>

Even so, under some conditions, high biomass removal may improve C sequestration. Such as the semi-arid grasslands in Colorado (shortgrass steppe), where changes

Significantly higher soil C (0–30 cm) was measured in grazed pastures (1.06 ± 0.03 t

rates in shortgrass steppe resulted in a plant community dominated by the C4 grass, blue grama, while exclusion of livestock grazing increased the production of C3 grasses and prickly pear cactus (*Opuntia polyacantha*) [22]. In addition to plant community changes, grazing exclusion leads to an immobilization of C in excessive aboveground plant litter of forbs and grasses and lack of dense fibrous rooting systems conducive to SOM formation and accumulation. Accordingly, outcomes indicate that stimulation of annual shoot turnover and redistribution of C within the plant-soil system contributes to an increase in SOC. Furthermore, the higher SOC in heavily grazed grassland may be attributable to higher inorganic C (SIC), than the nongrazed treatment, and longterm grazing could decrease the readily mineralizable fraction of SOM. These effects emphasize the importance of inorganic C in assessing the mass and distribution of plant-soil C, and in evaluating the impacts of grazing management on C sequestration

C sequestration, of course, should not be the only priority when making decision of pasture-based livestock farming systems located in less productive areas, (e.g., southern Europe and mountainous regions), which are highly relevant in both environmental and social terms. Although, C sequestration should be promoted to mitigate climate change and improve soil quality (water holding capacity and nutrient turnover). Solutions such as adaptive multi-paddock grazing or rotational grazing systems may increase carrying capacity and restore soil C. In other systems

year<sup>−</sup><sup>1</sup>

) compared to nongrazed exclosures (0.20 ± 0.14). In fact, heavy stocking

[19]. However, there is a large variability

) contained 17%

 year<sup>−</sup><sup>1</sup> )

) (**Table 1**) [21].

year<sup>−</sup><sup>1</sup>

) [20]. These C losses were attrib-

year<sup>−</sup><sup>1</sup>

) did not

) > unhar-

, while at medium biomass removal (30–70%) to high

), vs. mown systems was also confirmed for Hungarian

(i.e., root production and litter), and subsequent C sequestration [8].

*gracilis*) found that the moderately grazed pasture (2.6 ha steer<sup>−</sup><sup>1</sup>

(0–90 cm) followed the order: low grazing pressure (1.17 t C ha<sup>−</sup><sup>1</sup>

less SOC than the exclosure treatment, but heavy grazing (0.9 ha steer<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

**48**

*Annual SOC density changes (t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) in grazing grassland/pasture and the associated management practices.*

such as marginal grasslands, introducing perennial grasses can increase pasture productivity [33] and build SOC storage, while minimizing surface erosion. Perennial grasses, compared to annuals, generally allocate a greater fraction of productivity to the maintenance of a deeper and more extensive root system [24, 25], resulting in an average increase of 0.15–0.50 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> . Also, the introduction of more productive species [34], improved grazing regimes, fertilization practices, and irrigation management has been proposed for intensively managed pastures in North America for further potential C gains of 0.2 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> .

Practices, including liming, gypsum amendment (e.g., 125 kg ha<sup>−</sup><sup>1</sup> ), and nutrient managements, could increase SOC within a range of 0.29–0.55 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> (e.g., Australia). These gains are primarily attributed to increased plant production. In general, mineral phosphate fertilizers are applied to pastures on granite-derived soil, while gypsum is applied to address inherent deficiencies on basalt-derived soil. The application of P either alone or coupled with lime sequestrated C in soils at 0.41 and 0.29 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> . However, for land occupied by low to medium intensity grazing (~90% of Australia's agricultural land), soil and climate conditions are not suitable for other more intensive agricultural practices. Given the large area occupied by these lands, a small gain in SOC per hectare would translate to a high total sequestration [26].

#### **2.2 Integrated farming with grazing**

Adoption of sustainable practices is needed to maintain soil fertility and subsequent productivity, and to avoid soil degradation and SOC depletion. Integrated farming systems often provide a combination of good management practices. The success of integrated system in promoting SOC accumulation largely depends on successful maintenance of good management practices over time. Besides, C accumulation and the capacity of the soil to maintain its levels depend on a variety of factors such as clay soils contribute to higher SOCρ and its maintenance [35, 36] and above-ground species diversity such as co-existence of shallow and deep-rooting species [37] influence below-ground diversity [38] and provide a constant soil cover and biomass inputs to combat erosion and maintain nutrient inputs balance at various soil depths through.

Incorporating legumes into grazed grasslands and woodlands/savannas can address the N deficiency as common in mature, unfertilized rangeland soils. This practice has been used in tropical/subtropical regions of northeastern Australia [39] and in areas of Western Australia with a temperate climate. Here, growing *Leucaena leucocephala* in rows in C4 grassland in subtropical regions increased SOC by 17–30% over 40 years (sequestration rate of 0.28 t ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> , **Table 2**). Also, improved management practices (fertilization, liming, irrigation, seeding legumes, planting more productive grasses, and using appropriate grazing regimes) have been reported to increase C sequestration (0.72 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) in 22 municipalities of the Brazilian states of Rondônia and Mato Grosso [40].

A number of integrated farming systems (IS) such as crop-livestock (agropastoral system, ICL), crop-forestry (silvoarable system, ICF), forestry-pasturage of livestock (silvopastoral system, ILF), and crop-forestry-pasturage of livestock (agro-silvopastoral system, ICLF) are reported to improve C sequestration. For IS in Southern Amazon and Cerrado (neo-tropical savanna) of Brazil, C sequestration rates of 0.60 and 1.30 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> were reported for 0–30 and 0–100 cm soil depth, respectively (**Table 2**) [37]. In the Mediterranean area of Italy with Dystric Cambisols, the conversion of cork oak forests to grasslands (i.e., silvopastoral ecosystems) showed that the C sequestration rate in topsoil (20 cm depth) was 0.71 ± 0.13 under frequent crop rotation (with 5 years of cereals or legumes, oats,

**51**

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon…*

Italian ryegrass, and annual clovers or vetch followed by spontaneous herbaceous

In agrosilvopastoral system of the Iberian Peninsula (Mediterranean woodlands, Dehesas or Montados in Spain and Portugal, respectively), the improvement of C sequestration was mainly attributed to permanent pastures with mixed livestock raising at low stocking densities without external fodder inputs, exploitation of holm and/or cork oaks and arable systems with long rotations, and closed nutrient cycles. This was in opposite to soil tillage required in many Mediterranean soil/climate conditions to allow production of arable crops likely to reduce C sequestration.

> **Livestock density and/or No. LSU\***

AE ha<sup>−</sup><sup>1</sup> ; 1 AE = 400 kg steer

Cattle H = 21.27 AU ha<sup>−</sup><sup>1</sup> 370 NPK; 318

Beef cattle M — −0.03 to

Sheep L = 3–4 sheep ha<sup>−</sup><sup>1</sup> 50–39 (N-P) 0.71 ± 0.13

L Season long

M 0–30 cm

*); L = Low; M = Medium and H = High; SOCρ = SOC density change; nd:* 

*) in integrated farming with grazing grassland, shrublands, and* 

Cattle L to M = 0.45

pasture (5 years of spontaneous herbaceous vegetation and 1 year of hay crop),

year<sup>−</sup><sup>1</sup>

**Fertilization (N and P) and liming (kg ha<sup>−</sup><sup>1</sup> )**

> P = 22 S = 28

SP; 105 KCl; 324; NPK; 86 urea +10 KCl; 400 SP + 69 KCl; Pasture: 30 SP

> Fertilization, lime, and irrigation

L = 6 sheep ha<sup>−</sup><sup>1</sup> 50–39 (N-P) 1.20 ± 0.07

grazing

0–100 cm

M — 0.10 ± 0.00

H — 1.43 ± 0.00

**SOCρ changes (t C ha<sup>−</sup><sup>1</sup>**

0.28 ± 0.00

0.60 ± 0.12 1.30 ± 0.23

0.72 ± nd

0.61 ± nd

0.10 ± 0.00

0.23 ± 0.03 0.19 ± 0.04

 **year<sup>−</sup><sup>1</sup> )**

, under temporary

*DOI: http://dx.doi.org/10.5772/intechopen.84341*

respectively (**Table 2**) [41].

**Biomes/regions Livestock** 

Queensland, Australia (grassland and planted tree legumes mixed) [39]

Southern Amazon,

(integrated croplivestock-forestry)

Amazon, Brazil (nominal)

Improved with legume and productive varieties

Mediterranean, Italy (silvopasture) [41]

Inner Mongolia (semi-arid steppe)

Northern China (semi-arid, grassland) [43]

(desert steppe) [44]

*LSU = Livestock density unit (ha<sup>−</sup><sup>1</sup>*

*Annual SOC density changes (t C ha<sup>−</sup><sup>1</sup>*

*the associated management practices.*

Brazil

[37]

[40]

[9]

China (degraded grassland) [42]

China

*Not determined.*

**Table 2.**

vegetation in the sixth year), and 1.20 ± 0.07 t C ha<sup>−</sup><sup>1</sup>

**category**

Cattle/sheep grazing exclusion

 *year<sup>−</sup><sup>1</sup>*

 *year<sup>−</sup><sup>1</sup>*

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon… DOI: http://dx.doi.org/10.5772/intechopen.84341*

Italian ryegrass, and annual clovers or vetch followed by spontaneous herbaceous vegetation in the sixth year), and 1.20 ± 0.07 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> , under temporary pasture (5 years of spontaneous herbaceous vegetation and 1 year of hay crop), respectively (**Table 2**) [41].

In agrosilvopastoral system of the Iberian Peninsula (Mediterranean woodlands, Dehesas or Montados in Spain and Portugal, respectively), the improvement of C sequestration was mainly attributed to permanent pastures with mixed livestock raising at low stocking densities without external fodder inputs, exploitation of holm and/or cork oaks and arable systems with long rotations, and closed nutrient cycles. This was in opposite to soil tillage required in many Mediterranean soil/climate conditions to allow production of arable crops likely to reduce C sequestration.


*LSU = Livestock density unit (ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ); L = Low; M = Medium and H = High; SOCρ = SOC density change; nd: Not determined.*

#### **Table 2.**

*Annual SOC density changes (t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) in integrated farming with grazing grassland, shrublands, and the associated management practices.*

*CO2 Sequestration*

and 0.29 t C ha<sup>−</sup><sup>1</sup>

sequestration [26].

ous soil depths through.

rates of 0.60 and 1.30 t C ha<sup>−</sup><sup>1</sup>

in an average increase of 0.15–0.50 t C ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

**2.2 Integrated farming with grazing**

North America for further potential C gains of 0.2 t C ha<sup>−</sup><sup>1</sup>

such as marginal grasslands, introducing perennial grasses can increase pasture productivity [33] and build SOC storage, while minimizing surface erosion. Perennial grasses, compared to annuals, generally allocate a greater fraction of productivity to the maintenance of a deeper and more extensive root system [24, 25], resulting

productive species [34], improved grazing regimes, fertilization practices, and irrigation management has been proposed for intensively managed pastures in

(e.g., Australia). These gains are primarily attributed to increased plant production. In general, mineral phosphate fertilizers are applied to pastures on granite-derived soil, while gypsum is applied to address inherent deficiencies on basalt-derived soil. The application of P either alone or coupled with lime sequestrated C in soils at 0.41

grazing (~90% of Australia's agricultural land), soil and climate conditions are not suitable for other more intensive agricultural practices. Given the large area occupied by these lands, a small gain in SOC per hectare would translate to a high total

Adoption of sustainable practices is needed to maintain soil fertility and subsequent productivity, and to avoid soil degradation and SOC depletion. Integrated farming systems often provide a combination of good management practices. The success of integrated system in promoting SOC accumulation largely depends on successful maintenance of good management practices over time. Besides, C accumulation and the capacity of the soil to maintain its levels depend on a variety of factors such as clay soils contribute to higher SOCρ and its maintenance [35, 36] and above-ground species diversity such as co-existence of shallow and deep-rooting species [37] influence below-ground diversity [38] and provide a constant soil cover and biomass inputs to combat erosion and maintain nutrient inputs balance at vari-

Incorporating legumes into grazed grasslands and woodlands/savannas can address the N deficiency as common in mature, unfertilized rangeland soils. This practice has been used in tropical/subtropical regions of northeastern Australia [39] and in areas of Western Australia with a temperate climate. Here, growing *Leucaena leucocephala* in rows in C4 grassland in subtropical regions increased SOC

improved management practices (fertilization, liming, irrigation, seeding legumes, planting more productive grasses, and using appropriate grazing regimes) have

A number of integrated farming systems (IS) such as crop-livestock (agropastoral system, ICL), crop-forestry (silvoarable system, ICF), forestry-pasturage of livestock (silvopastoral system, ILF), and crop-forestry-pasturage of livestock (agro-silvopastoral system, ICLF) are reported to improve C sequestration. For IS in Southern Amazon and Cerrado (neo-tropical savanna) of Brazil, C sequestration

depth, respectively (**Table 2**) [37]. In the Mediterranean area of Italy with Dystric Cambisols, the conversion of cork oak forests to grasslands (i.e., silvopastoral ecosystems) showed that the C sequestration rate in topsoil (20 cm depth) was 0.71 ± 0.13 under frequent crop rotation (with 5 years of cereals or legumes, oats,

by 17–30% over 40 years (sequestration rate of 0.28 t ha<sup>−</sup><sup>1</sup>

been reported to increase C sequestration (0.72 t C ha<sup>−</sup><sup>1</sup>

of the Brazilian states of Rondônia and Mato Grosso [40].

year<sup>−</sup><sup>1</sup>

Practices, including liming, gypsum amendment (e.g., 125 kg ha<sup>−</sup><sup>1</sup>

ent managements, could increase SOC within a range of 0.29–0.55 t C ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

. However, for land occupied by low to medium intensity

. Also, the introduction of more

), and nutri-

year<sup>−</sup><sup>1</sup>

 year<sup>−</sup><sup>1</sup> .

year<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

were reported for 0–30 and 0–100 cm soil

, **Table 2**). Also,

) in 22 municipalities

**50**

#### **2.3 Grazing shrublands and exclusions**

Overgrazing is one of the main causes of desertification in semiarid grasslands, and grazing exclusion (GE) is an effective management practice globally, to restore degraded grasslands and improve SOCρ significantly via plant biomass and soil microbial biomass compared to grazing management [44]. The C dynamics in grassland ecosystems with GE showed a positive impact of GE on vegetation and SOCρ at most sites [42]. The mean values for SOCρ change were 0.23 ± 0.03 and 0.19 ± 0.04 t C ha<sup>−</sup> 1 year− 1 in 0–30 and 0–100 cm, respectively. Changes in SOCρ rates showed an exponential decay trend since GE and reached steady state at a later stage. Also, reduction in grazing pressure was reported (medium grazing, cattle/sheep) to result in a considerable increase of SOC and that the rate due to GE (10 years) was 0.10 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> (**Table 2**), suggesting that degradation of the grassland is being reversed [43].

For instance, the Alexa desert steppe has been strongly degraded by overgrazing, contributing around 22% of the total springtime dust originating from Asia. The effects of 7 years of GE on C dynamics showed lower SOC and higher SIC pools in areas with GE [44]. The total C pool in the GE plant-soil system was 10% greater than that in the area grazed over that time period (primarily due to 21% greater SIC), with a sequestration of 1.43 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> (**Table 2**). In semiarid steppes, recovery of heavily declined SOC caused by overgrazing is difficult and influences of long-term grazing on depression of nutrient cycling could be observed. For instance, in the semiarid steppes typical of Inner Mongolia, SOCρ was found comparable between grazed sites (average of 3 locations with sheep) and nongrazed GE sites at 0.1 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> (**Table 2**) [9]. Soil organic C levels in *Artemisia frigida* grassland was about 70% of that in *Leymus chinensis*, and in *A. frigida* grassland, it was significantly lower in grazing compared to nongrazing sites.

However, contrasting effects of overgrazing have also been reported [43, 45]. Soil IC pools could markedly contribute to the total C pool following GE, possibly due to the enhanced formation of pedogenic carbonates, higher soil water content, or increased carbonate capture in dust by recovering vegetation. On the other hand, the pool of SOC can be decreased by 11.5% in exclosure soils compared with the grazed site [46], linked mainly to the decrease in surface soil bulk density. These findings are potentially important because the Inner Mongolia grassland is the largest in the world and its degradation under heavy grazing is a source of dust storms that have major regional and global impacts. The positive impact of GE on vegetation and SOCρ [42] could improve enzyme activities and basal soil respiration in degraded sandy grassland, suggesting that degradation of the grassland is being reversed [13, 43]. A viable option for sandy grassland management could be to adopt proper exclosure in a rotation grazing system in the initial stage of degradation.

In Mediterranean regions, livestock take advantage of shrubs and grass during grazing while producing and dispersing manure. This represents the acceleration of transformation of plant OM into SOM, leading to an increase in SOCρ and makes them more resilient to future scenarios of global change [14]. Revegetation is very important especially to stop desertification processes and thereby increase SOC storage and improve soil health. Grazing management and cultivation of fodder have a high level of structural diversity both on a within and between habitat scale [47]. Greater SOCρ directly underneath the tree canopy suggests that maintaining or increasing tree cover may increase long term storage of soil C in Mediterranean silvopastoral systems.

**53**

*a*

*b*

*c*

*d*

*e*

*f*

**Table 3.**

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon…*

Multiple factors such as soil properties, land management, vegetation types, LUC, and climatic conditions influence soil C sequestration. Overall, the conversion of pasture into arable land leads to SOC loses with a balance up to 50 Pg [6] and up to 59% [48]. In the humid temperate zone of Europe, conversion of permanent grassland/pasture to arable land by plowing is associated with high SOC losses,

Carbon loss after grassland conversion to cropland are often rapid (−36 ± 5%;

after 17 years [50]. Conversely, grassland establishment on cropland can be a longlasting C sink with a relative density change of 128 ± 23% with no new equilibrium reached within 120 years (**Table 3**). Comparing sites, SOC increased with temperature and precipitation but decreased with depth and clay content. Regarding depth, top and subsoil SOC changes follow the same trend, but changes are often smaller in subsoil (25 ± 5% of the total SOC changes). Results of a meta-analysis from 74 publications indicate that overall, SOCρ declines after land use change from pasture to

> **Livestock density (LSU\*)**

> > 0–1 cut

M = 1.9; 2–3 cuts

Temperate zone [50] — — — −1.81 ± 0.55d Europe [52] — — — −19.00 ± 7.00

Cattle M = 2.2,

Ireland [51] — — 87–316 N (mineral and

) with a new SOC equilibrium being reached

) and increases when converting crop to pasture (+19%;

**Fertilization (N and P); liming (kg ha<sup>−</sup><sup>1</sup>**

> **and slurry (t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> )**

~46 N, ~7 P (7 yrs); Slurry: ~0.1–0.2 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup>

~64 N (1 year); Slurry: ~0.2–0.4

organic fertilizers)

— — — 1.99 ± 0.55e

— — — 0.33–0.70 ± nd

*); L = Low; M = Medium and H = High; SOCρ = SOC density change;* 

*) in land uses change from grazing grassland/pasture to cropland,* 

of 32 years; **Table 4**) [48, 50], while mean SOC

**)** 

**SOCρ changes (t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> )**

−2.77 ± 1.79a

−27.2 ± 11.70b

−12.88c

0.56 ± 0.34f 0.22 ± nd

**2.4 Land use change from pasture to cropland and vice-versa**

especially in the first year after conversion (**Table 4**) [49].

; on average 0.56 t ha<sup>−</sup><sup>1</sup>

**category**

 *year<sup>−</sup><sup>1</sup>*

 *year<sup>−</sup><sup>1</sup>*

*from cropland to grazing grassland/pasture, and the associated management practices.*

*20-year average but reaching an equilibrium may take >100 years.*

changes mostly occurred in the upper 30 cm.

year<sup>−</sup><sup>1</sup>

*DOI: http://dx.doi.org/10.5772/intechopen.84341*

on average estimated 1.81 t ha<sup>−</sup><sup>1</sup>

crop (−59%; −19 ± 7 t ha<sup>−</sup><sup>1</sup>

Germany (grassland to cropland) [49]

Europe (cropland to pasture) [50–53]

Australia (cropland to pasture) [2, 37, 54]

*nd: Not determined.*

*7-year average.*

*1-year average.*

*2.5-year average.*

*20-year average.*

*LSU = Livestock density unit (ha<sup>−</sup><sup>1</sup>*

*32-year average, yet to reach equilibrium.*

*Annual SOC density changes (t C ha<sup>−</sup><sup>1</sup>*

**Biomes/regions Livestock** 

18 ± 11 t ha<sup>−</sup><sup>1</sup>

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon… DOI: http://dx.doi.org/10.5772/intechopen.84341*

#### **2.4 Land use change from pasture to cropland and vice-versa**

Multiple factors such as soil properties, land management, vegetation types, LUC, and climatic conditions influence soil C sequestration. Overall, the conversion of pasture into arable land leads to SOC loses with a balance up to 50 Pg [6] and up to 59% [48]. In the humid temperate zone of Europe, conversion of permanent grassland/pasture to arable land by plowing is associated with high SOC losses, especially in the first year after conversion (**Table 4**) [49].

Carbon loss after grassland conversion to cropland are often rapid (−36 ± 5%; on average estimated 1.81 t ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) with a new SOC equilibrium being reached after 17 years [50]. Conversely, grassland establishment on cropland can be a longlasting C sink with a relative density change of 128 ± 23% with no new equilibrium reached within 120 years (**Table 3**). Comparing sites, SOC increased with temperature and precipitation but decreased with depth and clay content. Regarding depth, top and subsoil SOC changes follow the same trend, but changes are often smaller in subsoil (25 ± 5% of the total SOC changes). Results of a meta-analysis from 74 publications indicate that overall, SOCρ declines after land use change from pasture to crop (−59%; −19 ± 7 t ha<sup>−</sup><sup>1</sup> ) and increases when converting crop to pasture (+19%; 18 ± 11 t ha<sup>−</sup><sup>1</sup> ; on average 0.56 t ha<sup>−</sup><sup>1</sup> of 32 years; **Table 4**) [48, 50], while mean SOC changes mostly occurred in the upper 30 cm.


*LSU = Livestock density unit (ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ); L = Low; M = Medium and H = High; SOCρ = SOC density change; nd: Not determined.*

*a 7-year average.*

*CO2 Sequestration*

**2.3 Grazing shrublands and exclusions**

(10 years) was 0.10 t C ha<sup>−</sup><sup>1</sup>

grassland is being reversed [43].

year<sup>−</sup><sup>1</sup>

significantly lower in grazing compared to nongrazing sites.

Overgrazing is one of the main causes of desertification in semiarid grasslands, and grazing exclusion (GE) is an effective management practice globally, to restore degraded grasslands and improve SOCρ significantly via plant biomass and soil microbial biomass compared to grazing management [44]. The C dynamics in grassland ecosystems with GE showed a positive impact of GE on vegetation and SOCρ at most sites [42]. The mean values for SOCρ change were 0.23 ± 0.03 and 0.19 ± 0.04 t C ha<sup>−</sup> 1 year− 1 in 0–30 and 0–100 cm, respectively. Changes in SOCρ rates showed an exponential decay trend since GE and reached steady state at a later stage. Also, reduction in grazing pressure was reported (medium grazing, cattle/sheep) to result in a considerable increase of SOC and that the rate due to GE

For instance, the Alexa desert steppe has been strongly degraded by overgrazing, contributing around 22% of the total springtime dust originating from Asia. The effects of 7 years of GE on C dynamics showed lower SOC and higher SIC pools in areas with GE [44]. The total C pool in the GE plant-soil system was 10% greater than that in the area grazed over that time period (primarily due to 21% greater SIC), with a sequestration of 1.43 t C ha<sup>−</sup><sup>1</sup>

(**Table 2**). In semiarid steppes, recovery of heavily declined SOC caused by overgrazing is difficult and influences of long-term grazing on depression of nutrient cycling could be observed. For instance, in the semiarid steppes typical of Inner Mongolia, SOCρ was found comparable between grazed sites (average of 3 locations with sheep) and nongrazed GE sites at 0.1 t C

was about 70% of that in *Leymus chinensis*, and in *A. frigida* grassland, it was

However, contrasting effects of overgrazing have also been reported [43, 45]. Soil IC pools could markedly contribute to the total C pool following GE, possibly due to the enhanced formation of pedogenic carbonates, higher soil water content, or increased carbonate capture in dust by recovering vegetation. On the other hand, the pool of SOC can be decreased by 11.5% in exclosure soils compared with the grazed site [46], linked mainly to the decrease in surface soil bulk density. These findings are potentially important because the Inner Mongolia grassland is the largest in the world and its degradation under heavy grazing is a source of dust storms that have major regional and global impacts. The positive impact of GE on vegetation and SOCρ [42] could improve enzyme activities and basal soil respiration in degraded sandy grassland, suggesting that degradation of the grassland is being reversed [13, 43]. A viable option for sandy grassland management could be to adopt proper exclosure in a rotation grazing system in the initial stage of

In Mediterranean regions, livestock take advantage of shrubs and grass during grazing while producing and dispersing manure. This represents the acceleration of transformation of plant OM into SOM, leading to an increase in SOCρ and makes them more resilient to future scenarios of global change [14]. Revegetation is very important especially to stop desertification processes and thereby increase SOC storage and improve soil health. Grazing management and cultivation of fodder have a high level of structural diversity both on a within and between habitat scale [47]. Greater SOCρ directly underneath the tree canopy suggests that maintaining or increasing tree cover may increase long term storage of soil C in Mediterranean

(**Table 2**) [9]. Soil organic C levels in *Artemisia frigida* grassland

(**Table 2**), suggesting that degradation of the

year<sup>−</sup><sup>1</sup>

**52**

ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

degradation.

silvopastoral systems.

*b 1-year average.*

*c 2.5-year average.*

*d 20-year average.*

*e 20-year average but reaching an equilibrium may take >100 years.*

*f 32-year average, yet to reach equilibrium.*

**Table 3.**

*Annual SOC density changes (t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) in land uses change from grazing grassland/pasture to cropland, from cropland to grazing grassland/pasture, and the associated management practices.*

#### **2.5 Degraded and other grassland areas**

Soil carbon can be lost from grassland areas due to degradation, sometimes in association with management for grazing. For example, evaluation of the effects of management on SOCρ in grasslands compared to native vegetation in 22 municipalities of the Brazilian states of Rondônia and Mato Grosso showed that in degraded grassland, SOCρ declined by about 0.27–0.28 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> [39]. This indicates that degraded unmanaged grasslands in tropical regions lose C from the system (**Table 4**). Similar losses were found in temperate regions. In a shortgrass steppe, 28% less SOC was measured at locations with little or no plant input for about 45 years [55].

To assess the impact of animal trampling on soil properties, a study was conducted at a sub-alpine pasture in the Canton of Fribourg, Switzerland that had been used for summer grazing for over 150 years with a livestock density of about 4 cattle ha<sup>−</sup><sup>1</sup> (**Table 4**) [56]. The SOCρ in the 0–25 cm depth for areas of intensive trampling ("Bare steps") was 60 t C ha<sup>−</sup><sup>1</sup> , vegetated shoulder between trampled areas 74 t C ha<sup>−</sup><sup>1</sup> , and unaffected slope 76 t C ha<sup>−</sup><sup>1</sup> . The loss of SOC by trampling accounted for about 15 t C ha<sup>−</sup><sup>1</sup> , 20% of the total stock in this layer, or 30% on an equivalent soil mass basis (16 t C ha<sup>−</sup><sup>1</sup> over 150 years = 0.11 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ). In the bare steps, physical protection and aggregate stability are reduced, exposing soils to the eroding power of raindrops, making them susceptible to overland waterflow, and depletion of organic C and N. Decrease in SOCρ is most probably the result of three different processes, (i) erosion of the unprotected bare soils, (ii) reduced C input due to the lack of vegetation, and (iii) soil aggregate disruption through trampling.

Sequestration estimates for more marginal and less-managed rangelands generally fall below 0.5 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> [7]. With recommended management, it was assessed that rangelands could sequester SOC at a rate of 0.1 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> with an additional 0.2–0.3 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> mitigation through avoided emissions [57]. In addition to a general increase in sequestration rates, planting of permanent vegetation in degraded and marginal lands could act as larger C sinks with sequestration rates in soils from nil to 1.1 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> depending on the use of manure/bio-solid applications [7, 15]. In summary, sequestration potential for numerous management practices could be 0.44 ± 0.20 t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> [15]. While most studies have shown increased sequestration rates with improved grassland management, nil or negative effects on C sequestration in soils have been reported, possibly associated with poor experimental design or climate and soil limitations [2].


#### **Table 4.**

*Examples of SOC density changes (t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> ) in degraded and other land areas and the associated management practices.*

**55**

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon…*

**3. Challenges and opportunities to improve SOC storage in pasture** 

**3.1 Livestock management impacts on soil carbon sequestration potential**

a negative effect on SOC storage in areas like Southern Spain.

**3.2 Cultural and socio-economic views of grassland management**

Livestock farming systems differ widely in terms of their use of resources, degree of intensification, species and orientation of production, local/regional socio-economic and market context, cultural roles, etc. [15]. Pasture-based livestock farming systems in the European Mediterranean basin play a key role in the management and conservation of large high nature value lands and that are highly relevant in both environmental and social terms, with great ecological, landscape, and cultural diversity. Accordingly, agricultural policies have begun to recognize their productive, environmental, and societal functions [62]. In the second half of the twentieth century, modernization and intensification of agriculture and the

Anthropogenic land use decreases soil C storage worldwide and often contributes to soil degradation and erosion. Loss of SOC occurs due to reduced organic matter inputs, deforestation, plowing, and sealing and animal impacts such as trampling. Globally, grazing lands comprise the largest and most diverse single land resource and represent an important component of terrestrial C cycling and sequestration [1]. Trade-offs among productivity, GHG emissions and SOC sequestration should be considered for the management of livestock farming to ensure sustainable production and climate mitigation. Climatic variables, particularly rainfall and temperature, and soil characteristics are major factors in determining potential storage of C in soils under managed livestock systems [58]. The data available suggest that C content varies widely among different grassland types as well as livestock management practices. The effects of grazing management on the ecosystem processes that control C cycling and distribution have not been sufficiently evaluated in native grassland ecosystems. Current literature suggests no clear general relationships between grazing management and C sequestration. Some studies have reported no effect of grazing on SOC [43] while several others reported increases [13, 59] and a few reported decreases [42] as a result of grazing. Land use change is a major factor in determining SOC density in agricultural systems [52]. Conversion of permanent grassland or pasture into cropland results in loss of SOC, with the rate of decline dependent mainly on soil type, climate, ecosystem productivity, plant species, and intensity of management [60]. In addition, ecosystem function is affected through altered biodiversity and soil quality, with impacts differing across biomes and continents. In the tropics, the extent of degradation is normally greater due to higher temperature and often less sustainable soil management practices that accelerate decomposition and nutrient loss [60]. Similarly, conversion of native pasture and forest soils into cropland may increase soil bulk density (16%), plasticity index (30%), and soil erodibility (51%), as well as decrease SOC (50%), total N (50%), tilth index (40%), and available water capacity (40%) for surface soils [61]. There is a potential for restoration to a higher SOC level over time if arable lands are reverted to pasture. In the Mediterranean region, the recent dramatic changes in the development of industrial and tourism economies, with alteration of the composition and spatial structure of the traditional landscape, have had critical consequences for soil processes and management. European agricultural policies and the growing population have promoted intensive production systems, showing

*DOI: http://dx.doi.org/10.5772/intechopen.84341*

**management systems**

#### **3. Challenges and opportunities to improve SOC storage in pasture management systems**

#### **3.1 Livestock management impacts on soil carbon sequestration potential**

Anthropogenic land use decreases soil C storage worldwide and often contributes to soil degradation and erosion. Loss of SOC occurs due to reduced organic matter inputs, deforestation, plowing, and sealing and animal impacts such as trampling. Globally, grazing lands comprise the largest and most diverse single land resource and represent an important component of terrestrial C cycling and sequestration [1]. Trade-offs among productivity, GHG emissions and SOC sequestration should be considered for the management of livestock farming to ensure sustainable production and climate mitigation. Climatic variables, particularly rainfall and temperature, and soil characteristics are major factors in determining potential storage of C in soils under managed livestock systems [58]. The data available suggest that C content varies widely among different grassland types as well as livestock management practices.

The effects of grazing management on the ecosystem processes that control C cycling and distribution have not been sufficiently evaluated in native grassland ecosystems. Current literature suggests no clear general relationships between grazing management and C sequestration. Some studies have reported no effect of grazing on SOC [43] while several others reported increases [13, 59] and a few reported decreases [42] as a result of grazing. Land use change is a major factor in determining SOC density in agricultural systems [52]. Conversion of permanent grassland or pasture into cropland results in loss of SOC, with the rate of decline dependent mainly on soil type, climate, ecosystem productivity, plant species, and intensity of management [60]. In addition, ecosystem function is affected through altered biodiversity and soil quality, with impacts differing across biomes and continents. In the tropics, the extent of degradation is normally greater due to higher temperature and often less sustainable soil management practices that accelerate decomposition and nutrient loss [60]. Similarly, conversion of native pasture and forest soils into cropland may increase soil bulk density (16%), plasticity index (30%), and soil erodibility (51%), as well as decrease SOC (50%), total N (50%), tilth index (40%), and available water capacity (40%) for surface soils [61]. There is a potential for restoration to a higher SOC level over time if arable lands are reverted to pasture. In the Mediterranean region, the recent dramatic changes in the development of industrial and tourism economies, with alteration of the composition and spatial structure of the traditional landscape, have had critical consequences for soil processes and management. European agricultural policies and the growing population have promoted intensive production systems, showing a negative effect on SOC storage in areas like Southern Spain.

#### **3.2 Cultural and socio-economic views of grassland management**

Livestock farming systems differ widely in terms of their use of resources, degree of intensification, species and orientation of production, local/regional socio-economic and market context, cultural roles, etc. [15]. Pasture-based livestock farming systems in the European Mediterranean basin play a key role in the management and conservation of large high nature value lands and that are highly relevant in both environmental and social terms, with great ecological, landscape, and cultural diversity. Accordingly, agricultural policies have begun to recognize their productive, environmental, and societal functions [62]. In the second half of the twentieth century, modernization and intensification of agriculture and the

*CO2 Sequestration*

years [55].

4 cattle ha<sup>−</sup><sup>1</sup>

areas 74 t C ha<sup>−</sup><sup>1</sup>

through trampling.

limitations [2].

Switzerland (summer grazing pasture) [56]

*LSU = Livestock density unit (ha<sup>−</sup><sup>1</sup>*

*Examples of SOC density changes (t C ha<sup>−</sup><sup>1</sup>*

**2.5 Degraded and other grassland areas**

trampling ("Bare steps") was 60 t C ha<sup>−</sup><sup>1</sup>

equivalent soil mass basis (16 t C ha<sup>−</sup><sup>1</sup>

accounted for about 15 t C ha<sup>−</sup><sup>1</sup>

generally fall below 0.5 t C ha<sup>−</sup><sup>1</sup>

with an additional 0.2–0.3 t C ha<sup>−</sup><sup>1</sup>

**Biomes/regions Livestock** 

sequestration rates in soils from nil to 1.1 t C ha<sup>−</sup><sup>1</sup>

grassland, SOCρ declined by about 0.27–0.28 t C ha<sup>−</sup><sup>1</sup>

Soil carbon can be lost from grassland areas due to degradation, sometimes in association with management for grazing. For example, evaluation of the effects of management on SOCρ in grasslands compared to native vegetation in 22 municipalities of the Brazilian states of Rondônia and Mato Grosso showed that in degraded

that degraded unmanaged grasslands in tropical regions lose C from the system (**Table 4**). Similar losses were found in temperate regions. In a shortgrass steppe, 28% less SOC was measured at locations with little or no plant input for about 45

To assess the impact of animal trampling on soil properties, a study was conducted at a sub-alpine pasture in the Canton of Fribourg, Switzerland that had been used for summer grazing for over 150 years with a livestock density of about

bare steps, physical protection and aggregate stability are reduced, exposing soils to the eroding power of raindrops, making them susceptible to overland waterflow, and depletion of organic C and N. Decrease in SOCρ is most probably the result of three different processes, (i) erosion of the unprotected bare soils, (ii) reduced C input due to the lack of vegetation, and (iii) soil aggregate disruption

Sequestration estimates for more marginal and less-managed rangelands

[57]. In addition to a general increase in sequestration rates, planting of permanent vegetation in degraded and marginal lands could act as larger C sinks with

manure/bio-solid applications [7, 15]. In summary, sequestration potential for

most studies have shown increased sequestration rates with improved grassland management, nil or negative effects on C sequestration in soils have been reported, possibly associated with poor experimental design or climate and soil

year<sup>−</sup><sup>1</sup>

numerous management practices could be 0.44 ± 0.20 t C ha<sup>−</sup><sup>1</sup>

**category**

 *year<sup>−</sup><sup>1</sup>*

was assessed that rangelands could sequester SOC at a rate of 0.1 t C ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

, and unaffected slope 76 t C ha<sup>−</sup><sup>1</sup>

(**Table 4**) [56]. The SOCρ in the 0–25 cm depth for areas of intensive

year<sup>−</sup><sup>1</sup>

, vegetated shoulder between trampled

[7]. With recommended management, it

mitigation through avoided emissions

, 20% of the total stock in this layer, or 30% on an

over 150 years = 0.11 t C ha<sup>−</sup><sup>1</sup>

year<sup>−</sup><sup>1</sup>

**Livestock density (LSU\*) and management practices**

L = Vegetated shoulder = 4 cattle ha<sup>−</sup><sup>1</sup> L = Unaffected slope = 4 cattle ha<sup>−</sup><sup>1</sup>

*) in degraded and other land areas and the associated* 

Cattle L = Bare steps = 4 cattle ha<sup>−</sup><sup>1</sup>

Brazil (Amazon) [40] Beef cattle — −0.28 ± nd

*); L = Low; nd: Not determined.*

 *year<sup>−</sup><sup>1</sup>*

. The loss of SOC by trampling

year<sup>−</sup><sup>1</sup>

depending on the use of

year<sup>−</sup><sup>1</sup>

). In the

year<sup>−</sup><sup>1</sup>

[15]. While

**SOCρ changes (t C ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> )**

> −0.10 ± nd 0.09 ± nd 0.11 ± nd

[39]. This indicates

**54**

**Table 4.**

*management practices.*

establishment of new economic and commercial relationships with urban areas have caused depopulation and a continuous reduction or abandonment of livestock farming in rural areas across Europe [63]. Within this context, the continuity of small family farms is a key aspect when assessing the sustainability of agropastoral systems. Within the EU, approximately 74 M ha of permanent grassland (including 17 M ha in upland areas), 10 M ha of temporary grassland, and 35 M ha of land in forage cereal crops (equal to 60% of the total planted area) are dedicated to feeding the European livestock herd [64]. Though grass-based systems require more land area than poultry or swine, ruminants can make use of grasslands and rangelands or land unsuitable for cultivation, thus not competing with biomass production for human food.

There are potential risks and benefits of diverse grazing land management due to the numerous episodes of land degradation associated with drought and overgrazing [27]. There is strong need for adopting sustainable practices at lower intensification management to prevent and avoid further soil degradation [65]. Implementation of land management practices with positive C storage outcomes may have a large impact on the economic factors of livestock production and can be limited by social and cultural issues. It has been suggested that reducing stocking rates to improve perennial grass basal cover could sequester 315 M t of C in the top 10 cm of soil over a 30-year period [66]. Besides, allocation of more time to grazing in pastures, rather than to feeding on mown herbage could be beneficial. Possibilities to expand grazing areas and period should also be explored. Abandonment of grasslands should be avoided to enrich biodiversity and limit the spread of invasive species [67].

Moreover, many farms are technically producing organic meat, although not yet officially accredited due to the high administrative procedures required [68]. Expansion of grazing management is possible but its feasibility and the full climate change mitigation potential in time and space on broader ecological, socioeconomic, and political aspects should be evaluated [20]. The achievement of integrated systems promoting SOC accumulation and maintenance largely depends on good management practices successfully followed over time. Grasslands are among the ecosystems with the highest SOC density and stocks, and that serious concern is imperative [69]. Indeed, the EC Regulation1782/03 has introduced the concept of cross-compliance, with direct payments for farmers if they meet specific environmental requirements (Good Agricultural Environmental Conditions—GAEC).

#### **3.3 Possible synergies and co-benefits or conflicts of livestock management with other practices**

The emerging environmental and resource vulnerabilities may help adjustments in land use and farm practices, motivation and application of cultural beliefs, and a broader understanding of economic value associated with markets, technology, and administrative and policy frameworks. Importantly, we should consider the SOC stock in permanent grassland and the losses due to land use change and allocate C emission to milk and to the other products and ecosystem services to reduce the emission of GHGs from extensive systems [15]. Extensive livestock farming and pastoralism is a synergistic practice with the FAO recommendations to reduce meat consumption per capita, that is, to eat less meat but of higher quality and in the context of environmental sustainability [15]. On average, carbon emission is 4 times higher and erosion prevention is 10% lower in areas with a high grazing intensity compared to areas with a low grazing intensity [70].

Site-specific management practices could play a key role to moderate intensification of grassland production systems [71], and to mitigate some environmental

**57**

erodibility.

phases.

**4. Conclusions**

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon…*

impacts resulting from intensive agriculture. There are enormous opportunities across landscape mosaics to achieve an equilibrium between crops and grasslands to optimize trade-offs between food production and environment preservation as well as for offsetting unavoidable enteric CH4 by C sequestration in grassland soils [72]. Integration of livestock systems with other agricultural activities (e.g., production of grain crops or biomass for energy) increases diversity within agricultural systems, better regulates biogeochemical cycles, decreases environmental fluxes, and supports diverse habitats and trophic networks. Thus, modern integrated crop-livestock-forestry systems could improve many ecosystem services, such as C

Trampling by livestock may reduce the cover and connectivity of plant, litter, and biocrust cover [73] and make soil vulnerable to wind and water erosion [74]. Strategic integration of crops, livestock, forage, and agroforestry increases the complexity of production systems, thus reducing problems of specialization, captures economic and ecological synergies, and offers a range of novel opportunities to conduit natural processes, from carbon sequestration and site remediation to nonchemical vegetation management. Mixed cropping-pasture rotation systems are likely to be significant in increasing SOC at low N application during cropping

While increased complexity likely brings about ecological and economic benefits over highly specialized production systems, it may hamper its adoption and long-term maintenance. Land tenure, common property, and privatization issues also control competition from cropping, including biofuels and other land uses that limit grazing patterns and areas. Technical support for producers is imperative for the continued practice of mixed production, particularly for small- and mediumscale farmers, as well as sound complementary policies and good governance so that a "rebound effect" does not lead to any social and environmental impacts. Public extension services, in collaboration with the private sector, that strengthen information flow and enable investment in infrastructure have been and remain crucial

Globally, grazing is the largest anthropogenic land use, and a clear understanding of potential impacts of livestock management practices is essential to sequester C in the soils. Over-grazing decreases productivity, feeding efficiency, and C sequestration and increases GHG emissions from the systems. To enhance SOCρ and attain environmental sustainability in the systems, improved livestock management and the associated measures to cover soils, maintain biodiversity, select appropriate grazing time, control animal density and trampling, distribute dung and urine properly, keep soil moisture favorable, and improve livestock quality and productivity could have huge benefits. Further measures to make the system a C sink to offset any increased GHGs are to (i) optimize stocking rates to reduce land degradation, (ii) introduce improved pasture species and legumes to increase biomass production and SOCρ, (iii) apply recommended rate of inorganic fertilizers and manure to stimulate biomass production, and (iv) bring degraded land under pasture to reduce

It is vital to understand the spatial pattern of livestock grazing intensity and its effects on ecosystem functions, address the range of natural resources and social dimensions, and encourage holistic approaches and partnership processes to achieve effective sustainable livestock-based systems. These include adaptation to climate change, promotion of technically advanced management options,

*DOI: http://dx.doi.org/10.5772/intechopen.84341*

sequestration, and environmental sustainability.

to the success of integrated systems [37].

#### *Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon… DOI: http://dx.doi.org/10.5772/intechopen.84341*

impacts resulting from intensive agriculture. There are enormous opportunities across landscape mosaics to achieve an equilibrium between crops and grasslands to optimize trade-offs between food production and environment preservation as well as for offsetting unavoidable enteric CH4 by C sequestration in grassland soils [72]. Integration of livestock systems with other agricultural activities (e.g., production of grain crops or biomass for energy) increases diversity within agricultural systems, better regulates biogeochemical cycles, decreases environmental fluxes, and supports diverse habitats and trophic networks. Thus, modern integrated crop-livestock-forestry systems could improve many ecosystem services, such as C sequestration, and environmental sustainability.

Trampling by livestock may reduce the cover and connectivity of plant, litter, and biocrust cover [73] and make soil vulnerable to wind and water erosion [74]. Strategic integration of crops, livestock, forage, and agroforestry increases the complexity of production systems, thus reducing problems of specialization, captures economic and ecological synergies, and offers a range of novel opportunities to conduit natural processes, from carbon sequestration and site remediation to nonchemical vegetation management. Mixed cropping-pasture rotation systems are likely to be significant in increasing SOC at low N application during cropping phases.

While increased complexity likely brings about ecological and economic benefits over highly specialized production systems, it may hamper its adoption and long-term maintenance. Land tenure, common property, and privatization issues also control competition from cropping, including biofuels and other land uses that limit grazing patterns and areas. Technical support for producers is imperative for the continued practice of mixed production, particularly for small- and mediumscale farmers, as well as sound complementary policies and good governance so that a "rebound effect" does not lead to any social and environmental impacts. Public extension services, in collaboration with the private sector, that strengthen information flow and enable investment in infrastructure have been and remain crucial to the success of integrated systems [37].

#### **4. Conclusions**

*CO2 Sequestration*

human food.

spread of invasive species [67].

**with other practices**

compared to areas with a low grazing intensity [70].

establishment of new economic and commercial relationships with urban areas have caused depopulation and a continuous reduction or abandonment of livestock farming in rural areas across Europe [63]. Within this context, the continuity of small family farms is a key aspect when assessing the sustainability of agropastoral systems. Within the EU, approximately 74 M ha of permanent grassland (including 17 M ha in upland areas), 10 M ha of temporary grassland, and 35 M ha of land in forage cereal crops (equal to 60% of the total planted area) are dedicated to feeding the European livestock herd [64]. Though grass-based systems require more land area than poultry or swine, ruminants can make use of grasslands and rangelands or land unsuitable for cultivation, thus not competing with biomass production for

There are potential risks and benefits of diverse grazing land management due to the numerous episodes of land degradation associated with drought and overgrazing [27]. There is strong need for adopting sustainable practices at lower intensification management to prevent and avoid further soil degradation [65]. Implementation of land management practices with positive C storage outcomes may have a large impact on the economic factors of livestock production and can be limited by social and cultural issues. It has been suggested that reducing stocking rates to improve perennial grass basal cover could sequester 315 M t of C in the top 10 cm of soil over a 30-year period [66]. Besides, allocation of more time to grazing in pastures, rather than to feeding on mown herbage could be beneficial. Possibilities to expand grazing areas and period should also be explored. Abandonment of grasslands should be avoided to enrich biodiversity and limit the

Moreover, many farms are technically producing organic meat, although not yet officially accredited due to the high administrative procedures required [68]. Expansion of grazing management is possible but its feasibility and the full climate

economic, and political aspects should be evaluated [20]. The achievement of integrated systems promoting SOC accumulation and maintenance largely depends on good management practices successfully followed over time. Grasslands are among the ecosystems with the highest SOC density and stocks, and that serious concern is imperative [69]. Indeed, the EC Regulation1782/03 has introduced the concept of cross-compliance, with direct payments for farmers if they meet specific environmental requirements (Good Agricultural Environmental Conditions—GAEC).

**3.3 Possible synergies and co-benefits or conflicts of livestock management** 

The emerging environmental and resource vulnerabilities may help adjustments in land use and farm practices, motivation and application of cultural beliefs, and a broader understanding of economic value associated with markets, technology, and administrative and policy frameworks. Importantly, we should consider the SOC stock in permanent grassland and the losses due to land use change and allocate C emission to milk and to the other products and ecosystem services to reduce the emission of GHGs from extensive systems [15]. Extensive livestock farming and pastoralism is a synergistic practice with the FAO recommendations to reduce meat consumption per capita, that is, to eat less meat but of higher quality and in the context of environmental sustainability [15]. On average, carbon emission is 4 times higher and erosion prevention is 10% lower in areas with a high grazing intensity

Site-specific management practices could play a key role to moderate intensifica-

tion of grassland production systems [71], and to mitigate some environmental

change mitigation potential in time and space on broader ecological, socio-

**56**

Globally, grazing is the largest anthropogenic land use, and a clear understanding of potential impacts of livestock management practices is essential to sequester C in the soils. Over-grazing decreases productivity, feeding efficiency, and C sequestration and increases GHG emissions from the systems. To enhance SOCρ and attain environmental sustainability in the systems, improved livestock management and the associated measures to cover soils, maintain biodiversity, select appropriate grazing time, control animal density and trampling, distribute dung and urine properly, keep soil moisture favorable, and improve livestock quality and productivity could have huge benefits. Further measures to make the system a C sink to offset any increased GHGs are to (i) optimize stocking rates to reduce land degradation, (ii) introduce improved pasture species and legumes to increase biomass production and SOCρ, (iii) apply recommended rate of inorganic fertilizers and manure to stimulate biomass production, and (iv) bring degraded land under pasture to reduce erodibility.

It is vital to understand the spatial pattern of livestock grazing intensity and its effects on ecosystem functions, address the range of natural resources and social dimensions, and encourage holistic approaches and partnership processes to achieve effective sustainable livestock-based systems. These include adaptation to climate change, promotion of technically advanced management options, introduction of consistent policies to enhance development capacity, and minimization of desertification, drought, and loss of biodiversity. Besides, recognition, awareness, behavioral change, and investments with due worldwide pro-extensive livestock policies are essential. Involvement of stakeholders, various organizations, development agencies/practitioners, community donors, relevant networks, and researchers is desirable to fully exploit the opportunities lying within the systems. Emphasis on spatially explicit global studies should be given to explore the impacts of livestock managements, adopt better technologies, and quantify trade-offs/ off-setting potential and synergies among ecosystems. Further research should be targeted to value natural grasslands and livestock-based ecosystems, developing quantifiable methods for SOC measurement, strategic monitoring and verification of management-induced C sequestration. This is to ensure full GHG accounting and balance while generating improved understanding of the economic and institutional aspects of C sequestration involving people engaged in livestock farming.

### **Acknowledgements**

The authors thank the Environmental Protection Agency (EPA), Ireland, for funding (2015 CCRP-FS.21) to publish this chapter; Department of Agriculture, Food and the Marine (DAFM), Ireland for funding the lead author through Irish Land UsES (15/S/650); and Dr. Ciniro Costa-Junior, Institute for Agriculture and Forestry Certification and Management, Piracicaba-SP, Brazil for his initial contribution.

**59**

provided the original work is properly cited.

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon…*

, Beata Emoke Madari9

1 School of Biology and Environmental Science, University College Dublin, Ireland

4 Science and Engineering Faculty, Queensland University of Technology, Brisbane,

2 Climate-Resilient Agri-Environmetal Systems (CRAES)-Earth Institute,

3 Council for Agricultural Research and Economics, Research Centre for

5 Grassland Ecosystem Research Unit, INRA, Clermont-Ferrand, France

8 Forest Department, University of Extremadura, Plasencia Campus, Spain

10 School of Biological, Earth and Environmental Sciences, The University of New

11 School of Biological Sciences, The University of Western Australia, Crawley,

, Beverley Henry4

, Katja Klumpp5

, Miriam Muñoz-Rojas10,11

,

*DOI: http://dx.doi.org/10.5772/intechopen.84341*

Mohammad Ibrahim Khalil1,2\*, Rosa Francaviglia3

Agriculture and Environment (CREA-AA), Rome, Italy

6 Duna-Ipoly National Park Directorate, Budapest, Hungary

7 MTA–SZIE Plant Ecology Research Group, Gödöllő, Hungary

9 Embrapa Rice and Beans, Santo Antônio de Goiás, GO, Brazil

12 Soil and More Impacts B.V., German Office, Hamburg, Germany

\*Address all correspondence to: ibrahim.khalil@ucd.ie

**Author details**

and Rainer Nerger12

Australia

Australia

Peter Koncz6,7, Mireia Llorente8

University College Dublin, Ireland

South Wales, Sydney, Australia

### **Author details**

*CO2 Sequestration*

**Acknowledgements**

contribution.

introduction of consistent policies to enhance development capacity, and minimization of desertification, drought, and loss of biodiversity. Besides, recognition, awareness, behavioral change, and investments with due worldwide pro-extensive livestock policies are essential. Involvement of stakeholders, various organizations, development agencies/practitioners, community donors, relevant networks, and researchers is desirable to fully exploit the opportunities lying within the systems. Emphasis on spatially explicit global studies should be given to explore the impacts of livestock managements, adopt better technologies, and quantify trade-offs/ off-setting potential and synergies among ecosystems. Further research should be targeted to value natural grasslands and livestock-based ecosystems, developing quantifiable methods for SOC measurement, strategic monitoring and verification of management-induced C sequestration. This is to ensure full GHG accounting and balance while generating improved understanding of the economic and institutional aspects of C sequestration involving people engaged in livestock farming.

The authors thank the Environmental Protection Agency (EPA), Ireland, for funding (2015 CCRP-FS.21) to publish this chapter; Department of Agriculture, Food and the Marine (DAFM), Ireland for funding the lead author through Irish Land UsES (15/S/650); and Dr. Ciniro Costa-Junior, Institute for Agriculture and Forestry Certification and Management, Piracicaba-SP, Brazil for his initial

**58**

Mohammad Ibrahim Khalil1,2\*, Rosa Francaviglia3 , Beverley Henry4 , Katja Klumpp5 , Peter Koncz6,7, Mireia Llorente8 , Beata Emoke Madari9 , Miriam Muñoz-Rojas10,11 and Rainer Nerger12

1 School of Biology and Environmental Science, University College Dublin, Ireland

2 Climate-Resilient Agri-Environmetal Systems (CRAES)-Earth Institute, University College Dublin, Ireland

3 Council for Agricultural Research and Economics, Research Centre for Agriculture and Environment (CREA-AA), Rome, Italy

4 Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia

5 Grassland Ecosystem Research Unit, INRA, Clermont-Ferrand, France

6 Duna-Ipoly National Park Directorate, Budapest, Hungary

7 MTA–SZIE Plant Ecology Research Group, Gödöllő, Hungary

8 Forest Department, University of Extremadura, Plasencia Campus, Spain

9 Embrapa Rice and Beans, Santo Antônio de Goiás, GO, Brazil

10 School of Biological, Earth and Environmental Sciences, The University of New South Wales, Sydney, Australia

11 School of Biological Sciences, The University of Western Australia, Crawley, Australia

12 Soil and More Impacts B.V., German Office, Hamburg, Germany

\*Address all correspondence to: ibrahim.khalil@ucd.ie

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **References**

[1] Lal R. Soil carbon sequestration impacts on global climate change and food security. Science. 2004;**304**:1623-1627

[2] Conant RT, Paustian K, Elliot ET. Grassland management and conversion into grassland: Effects on soil carbon. Ecological Applications. 2001;**11**:343-355

[3] Allard V et al. The role of grazing management for the net biome productivity and greenhouse gas budget (CO2, N2O, and CH4) of semi-natural grassland. Agriculture, Ecosystems and Environment. 2007;**121**:47-58

[4] Roser M, Ritchie H. Yields and Land Use in Agriculture [Internet]. 2018. Available from: https://ourworldindata. org/yields-and-land-use-in-agriculture [Accessed: 01 May 2018]

[5] Frank AB, Tanaka DL, Hoffman L, Follet RF. Soil carbon and nitrogen of northern Great Plains grasslands as influenced by longterm grazing. Journal of Range Management. 1995;**48**:470-474

[6] Janzen HH. The soil carbon dilemma: Shall we hoard it or use it? Soil Biology and Biochemistry. 2006;**38**:419-424

[7] Smith P et al. Greenhouse gas mitigation in agriculture. Philosophical Transactions of the Royal Society B: Biological Sciences. 2008;**363**:789-813

[8] Soussana J-F, Lemaire G. Coupling carbon and nitrogen cycles for environmentally sustainable intensification of grasslands and crop–livestock systems. Agriculture, Ecosystems and Environment. 2014;**190**:9-17

[9] Cui XY et al. Effect of long-term grazing on soil organic carbon content in semiarid steppes in Inner Mongolia. Ecological Research. 2005;**20**:519-527

[10] Savory A. A Global Strategy for Addressing Climate Change. 2008. Available from: https:// soilcarboncoalition.org/files/ globalstrategy.pdf [Accessed: 01 May 2018]

[11] Soussana J-F, Fuhrer J, Jones M, Van Amstel A. The greenhouse gas balance of grasslands in Europe. Agriculture, Ecosystems and Environment. 2007;**121**:1-4

[12] Eldridge DJ, Delgado-Baquerizo M. Continental-scale impacts of livestock grazing on ecosystem supporting and regulating services. Land Degradation and Development. 2017;**28**:1473-1481

[13] Golluscio RA et al. Sheep grazing decreases organic carbon and nitrogen pools in the Patagonian Steppe: Combination of direct and indirect effects. Ecosystems. 2009;**12**:686-697

[14] Piñeiro G et al. Pathways of grazing effects on soil organic carbon and nitrogen. Rangeland Ecology & Management. 2010;**63**:109-119

[15] Hutchinson JJ, Campbell CA, Desjardins RL. Some perspectives on carbon sequestration in agriculture. Agricultural and Forest Meteorology. 2007;**142**:288-302

[16] Naeth MA et al. Grazing impacts on litter and soil organic matter in mixed prairie and fescue grassland ecosystems in Alberta. Journal of Range Management. 1991;**44**:7-12

[17] Hassink J. Effects of soil texture and grassland management on soil organic C and N and rates of C and N mineralization. Soil Biology and Biochemistry. 1994;**26**:1221-1231

[18] Bardgett RD, Leemans DK, Cook R, Hobbs PJ. Seasonality of the soil biota

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Results of three long-term experiments.

Soil Research. 2011;**49**:320-328

[27] Hill MJ et al. Analysis of soil carbon outcomes from interaction between climate and grazing pressure in Australian rangelands using Range-ASSESS. Environmental Modelling &

[28] Segoli M et al. Managing cattle grazing intensity: Effects on soil organic matter and soil nitrogen. Soil Research.

[29] Fulkerson WJ, Slack K, Moore K, Rolfe C. Management of *Loliumperenne Trifolium-repens* pastures in the subtropics. 1. Effect of

defoliation interval, seeding rate and application of N and lime. Australian Journal of Agricultural Research.

[30] Kis-Kovács G et al. National Inventory Report for 1985-2015. Budapest: Hungarian Meteorological

[31] Franzluebbers AJ, Stuedemann JA. Soil-profile organic carbon and total nitrogen during 12 years of pasture management in the Southern Piedmont USA. Agriculture, Ecosystems and Environment. 2009;**129**:28-36

[32] Franzluebbers AJ, Stuedemann JA, Schomberg HH, Wilkinson SR. Soil organic C and N pools under long-term pasture management in the Southern Piedmont, USA. Soil Biology and Biochemistry. 2000;**32**:469-478

[33] Witham N et al. Evaluating Perennial Pastures: A Case Study of Perennial Pasture Use in the South Coast Region of Western Australia. Esperance, W.A.: Esperance Regional Forum; 2007. p. 86

[34] Bruce JP, Frome M, Haites E, Janzen H, Lal R, Paustian K. Carbon sequestration in soils. Journal of Soil and Water Conservation. 1999;**54**:382-389

Software. 2006;**21**:779-801

2015;**53**:677-682

1993;**44**:1947-1958

Service; 2017

*DOI: http://dx.doi.org/10.5772/intechopen.84341*

of grazed and ungrazed hill grasslands.

[19] Franzluebbers AJ, Stuedemann JA, Schomberg HH, Wilkinson SR. Soil organic C and N pools under long-term pasture management in the Southern Piedmont, USA. Soil Biology and Biochemistry. 2000;**32**:469-478

[20] Koncz P et al. Extensive grazing in contrast to mowing is climate friendly based on the farm-scale greenhouse gas balance. Agriculture, Ecosystems and Environment. 2017;**240**:121-134

[21] Reeder JD, Schuman GE. Influence of livestock grazing on C sequestration in semi-arid mixed-grass and shortgrass rangelands. Environmental Pollution. 2002;**116**:457-463

[22] Reeder JD, Schuman GE, Morgan JA, Lecain DR. Response of organic and inorganic carbon and nitrogen to long-term grazing of the shortgrass steppe. Environmental Management.

[23] EFDC (European Fluxes Database Cluster). European Fluxes Database Cluster [Internet]. 2018. Available from: http://www.europe-fluxdata.eu/

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2010. p. 81

[Accessed: 15 April 2018]

[24] Sanderman J, Farquharson R, Baldock J. Soil Carbon Sequestration Potential: A Review for Australian Agriculture. A Report Prepared for Department of Climate Change and Energy Efficiency. Canberra: CSIRO;

[25] Chan KY et al. Soil carbon stocks under different pastures and pasture management in the higher rainfall areas of south-eastern Australia. Australian Journal of Soil Research. 2010;**48**:7-15

[26] Chan KY et al. Soil carbon dynamics under different cropping and pasture management in temperate Australia:

Soil Biology and Biochemistry.

1997;**29**:1285-1294

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon… DOI: http://dx.doi.org/10.5772/intechopen.84341*

of grazed and ungrazed hill grasslands. Soil Biology and Biochemistry. 1997;**29**:1285-1294

[19] Franzluebbers AJ, Stuedemann JA, Schomberg HH, Wilkinson SR. Soil organic C and N pools under long-term pasture management in the Southern Piedmont, USA. Soil Biology and Biochemistry. 2000;**32**:469-478

[20] Koncz P et al. Extensive grazing in contrast to mowing is climate friendly based on the farm-scale greenhouse gas balance. Agriculture, Ecosystems and Environment. 2017;**240**:121-134

[21] Reeder JD, Schuman GE. Influence of livestock grazing on C sequestration in semi-arid mixed-grass and shortgrass rangelands. Environmental Pollution. 2002;**116**:457-463

[22] Reeder JD, Schuman GE, Morgan JA, Lecain DR. Response of organic and inorganic carbon and nitrogen to long-term grazing of the shortgrass steppe. Environmental Management. 2004;**33**:485-495

[23] EFDC (European Fluxes Database Cluster). European Fluxes Database Cluster [Internet]. 2018. Available from: http://www.europe-fluxdata.eu/ [Accessed: 15 April 2018]

[24] Sanderman J, Farquharson R, Baldock J. Soil Carbon Sequestration Potential: A Review for Australian Agriculture. A Report Prepared for Department of Climate Change and Energy Efficiency. Canberra: CSIRO; 2010. p. 81

[25] Chan KY et al. Soil carbon stocks under different pastures and pasture management in the higher rainfall areas of south-eastern Australia. Australian Journal of Soil Research. 2010;**48**:7-15

[26] Chan KY et al. Soil carbon dynamics under different cropping and pasture management in temperate Australia:

Results of three long-term experiments. Soil Research. 2011;**49**:320-328

[27] Hill MJ et al. Analysis of soil carbon outcomes from interaction between climate and grazing pressure in Australian rangelands using Range-ASSESS. Environmental Modelling & Software. 2006;**21**:779-801

[28] Segoli M et al. Managing cattle grazing intensity: Effects on soil organic matter and soil nitrogen. Soil Research. 2015;**53**:677-682

[29] Fulkerson WJ, Slack K, Moore K, Rolfe C. Management of *Loliumperenne Trifolium-repens* pastures in the subtropics. 1. Effect of defoliation interval, seeding rate and application of N and lime. Australian Journal of Agricultural Research. 1993;**44**:1947-1958

[30] Kis-Kovács G et al. National Inventory Report for 1985-2015. Budapest: Hungarian Meteorological Service; 2017

[31] Franzluebbers AJ, Stuedemann JA. Soil-profile organic carbon and total nitrogen during 12 years of pasture management in the Southern Piedmont USA. Agriculture, Ecosystems and Environment. 2009;**129**:28-36

[32] Franzluebbers AJ, Stuedemann JA, Schomberg HH, Wilkinson SR. Soil organic C and N pools under long-term pasture management in the Southern Piedmont, USA. Soil Biology and Biochemistry. 2000;**32**:469-478

[33] Witham N et al. Evaluating Perennial Pastures: A Case Study of Perennial Pasture Use in the South Coast Region of Western Australia. Esperance, W.A.: Esperance Regional Forum; 2007. p. 86

[34] Bruce JP, Frome M, Haites E, Janzen H, Lal R, Paustian K. Carbon sequestration in soils. Journal of Soil and Water Conservation. 1999;**54**:382-389

**60**

2014;**190**:9-17

*CO2 Sequestration*

**References**

2001;**11**:343-355

[1] Lal R. Soil carbon sequestration impacts on global climate change and food security. Science. 2004;**304**:1623-1627

[10] Savory A. A Global Strategy for Addressing Climate Change. 2008. Available from: https:// soilcarboncoalition.org/files/

2018]

2007;**121**:1-4

2017;**28**:1473-1481

2007;**142**:288-302

globalstrategy.pdf [Accessed: 01 May

[11] Soussana J-F, Fuhrer J, Jones M, Van Amstel A. The greenhouse gas balance of grasslands in Europe. Agriculture, Ecosystems and Environment.

[12] Eldridge DJ, Delgado-Baquerizo M. Continental-scale impacts of livestock grazing on ecosystem supporting and regulating services. Land Degradation and Development.

[13] Golluscio RA et al. Sheep grazing decreases organic carbon and nitrogen pools in the Patagonian Steppe: Combination of direct and indirect effects. Ecosystems. 2009;**12**:686-697

[14] Piñeiro G et al. Pathways of grazing effects on soil organic carbon and nitrogen. Rangeland Ecology & Management. 2010;**63**:109-119

[15] Hutchinson JJ, Campbell CA, Desjardins RL. Some perspectives on carbon sequestration in agriculture. Agricultural and Forest Meteorology.

[16] Naeth MA et al. Grazing impacts on litter and soil organic matter in mixed prairie and fescue grassland ecosystems in Alberta. Journal of Range

[17] Hassink J. Effects of soil texture and grassland management on soil organic C and N and rates of C and N mineralization. Soil Biology and Biochemistry. 1994;**26**:1221-1231

[18] Bardgett RD, Leemans DK, Cook R, Hobbs PJ. Seasonality of the soil biota

Management. 1991;**44**:7-12

[2] Conant RT, Paustian K, Elliot ET.

conversion into grassland: Effects on soil carbon. Ecological Applications.

[3] Allard V et al. The role of grazing management for the net biome

productivity and greenhouse gas budget (CO2, N2O, and CH4) of semi-natural grassland. Agriculture, Ecosystems and

[4] Roser M, Ritchie H. Yields and Land Use in Agriculture [Internet]. 2018. Available from: https://ourworldindata. org/yields-and-land-use-in-agriculture

[5] Frank AB, Tanaka DL, Hoffman L, Follet RF. Soil carbon and nitrogen of northern Great Plains grasslands as influenced by longterm grazing. Journal of Range Management. 1995;**48**:470-474

[6] Janzen HH. The soil carbon dilemma: Shall we hoard it or use it? Soil Biology and Biochemistry. 2006;**38**:419-424

[7] Smith P et al. Greenhouse gas mitigation in agriculture. Philosophical Transactions of the Royal Society B: Biological Sciences. 2008;**363**:789-813

[8] Soussana J-F, Lemaire G. Coupling carbon and nitrogen cycles for environmentally sustainable intensification of grasslands and crop–livestock systems. Agriculture, Ecosystems and Environment.

[9] Cui XY et al. Effect of long-term grazing on soil organic carbon content in semiarid steppes in Inner Mongolia. Ecological Research. 2005;**20**:519-527

Grassland management and

Environment. 2007;**121**:47-58

[Accessed: 01 May 2018]

[35] Zinn YL, Lal R, Bigham JM, Resck DVS. Edaphic controls on soil organic carbon retention in the Brazilian Cerrado: Texture and mineralogy. Soil Science Society of America Journal. 2007;**71**:1204

[36] Cardinael R et al. Increased soil organic carbon stocks under agroforestry: A survey of six different sites in France. Agriculture, Ecosystems and Environment. 2017;**236**:243-255

[37] Oliveira JM et al. Integrated farming systems for improving soil carbon balance in the southern Amazon of Brazil. Regional Environmental Change. 2018;**18**:105-116

[38] Lisboa FJG et al. The match between microbial community structure and soil properties is modulated by land use types and sample origin within an integrated agroecosystem. Soil Biology and Biochemistry. 2014;**78**:97-108

[39] Conrad KA et al. The sequestration and turnover of soil organic carbon in subtropical leucaena-grass pastures. Agriculture, Ecosystems and Environment. 2017;**248**:38-47

[40] Maia SMF, Ogle SM, Cerri CEP, Cerri CC. Soil organic carbon stock change due to land use activity along the agricultural frontier of the Southwestern Amazon, Brazil, between 1970 and 2002. Global Change Biology. 2009;**16**:2775-2788

[41] Francaviglia R, Renzi G, Ledda L, Benedetti A. Organic carbon pools and soil biological fertility are affected by land use intensity in Mediterranean ecosystems of Sardinia, Italy. Science of the Total Environment. 2017;**599-600**:789-796

[42] Deng L, Zhou-Ping S, Wu G-L, Xiao-Feng C. Effects of grazing exclusion on carbon sequestration in China's grassland. Earth-Science Reviews. 2017;**173**:84-95

[43] Su YZ, Li YL, Cui JY, Zhao WZ. Influences of continuous grazing and livestock exclusion on soil properties in a degraded sandy grassland, Inner Mongolia, Northern China. Catena. 2005;**59**:267-278

[44] Niu D et al. Grazing exclusion alters ecosystem carbon pools in Alxa desert steppe. New Zealand Journal of Agricultural Research. 2011;**54**:127-142

[45] Steffens M, Kölb A, Totsche KU, Kögel-Knabner I. Grazing effects on soil chemical and physical properties in a semiarid steppe of Inner Mongolia (P.R. China). Geoderma. 2008;**143**:63-72

[46] Berg WA, Bradford JA, Sims PL. Long-term soil nitrogen and vegetation change on Sandhill rangeland. Journal of Range Management. 1997;**50**:482-486

[47] Aguilera E, Lassaletta L, Gattinger A, Gimeno BS. Managing soil carbon for climate change mitigation and adaptation in Mediterranean cropping systems: A meta-analysis. Agriculture, Ecosystems and Environment. 2013;**168**:25-36

[48] Guo LB, Gifford RM. Soil carbon stocks and land use change: A metaanalysis. Global Change Biology. 2002;**8**:345-360

[49] Nerger R, Beylich A, Fohrer N. Long-term monitoring of soil quality changes in Northern Germany. Geoderma Regional. 2016;**7**:239-249

[50] Poeplau C et al. Temporal dynamics of soil organic carbon after land-use change in the temperate zone–carbon response functions as a model approach. Global Change Biology. 2011;**17**:2415-2427

[51] Necpalova M, Li D, Lanigan G, Casey IA, Burchill W, Humphreys J. Changes in soil organic carbon in a clay loam soil following ploughing

**63**

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon…*

semiarid ecosystem. Biology and Fertility of Soils. 2006;**43**:76-82

[60] Khalil MI, Haque MA, Sattar MA, Schmidhalter U. Relative contribution of crop residue bound-N to irrigated rice and carbon storage in a subtropical soil. In: Bernal et al., editors. Proceedings of the 11th International Conference of the FAO ESCORENA Network on Recycling of Agricultural, Municipal and Industrial Residues in Agriculture; Murcia, Spain; 2004. pp. 169-172

[61] Emadi M, Baghernejad M, Fathi H, Saffari M. Effect of land use change on selected soil physical and chemical properties in north highlands of Iran. Journal of Applied Sciences.

[62] Gibon A. Managing grassland for production, the environment and the landscape. Challenges at the farm and the landscape level. Livestock Production Science. 2005;**96**:11-31

[63] MacDonald D et al. Agricultural abandonment in mountain areas of Europe: Environmental consequences and policy response. Journal of Environmental Management.

[64] Dumont B et al. Rôles, Impacts et Services Issus des Élevages en Europe. Synthèse de L'expertise Scientifique Collective. France: INRA; 2016. p. 127.

[65] Pereira P, Brevik E, Muñoz-Miriam M, Miller B. Soil Mapping and Process Modeling for Sustainable Land Use Management. Elsevier; 2017. p. 398.

[66] Allen DE et al. What determines soil organic carbon stocks in the grazing lands of north-eastern Australia? Soil

[67] Molnár ZS et al. Common and conflicting objectives and practices of

eBook ISBN: 9780128052013

Research. 2014;**51**:695-706

2008;**8**:496-502

2000;**59**:47-69

auto-saisine

*DOI: http://dx.doi.org/10.5772/intechopen.84341*

and reseeding of permanent grassland under temperate moist climatic conditions. Grass and Forage Science.

[52] Poeplau C, Don A. Sensitivity of soil organic carbon stocks and fractions to different land-use changes across Europe. Geoderma. 2013;**192**:189-201

[53] Jones MB. Potential for carbon sequestration in temperate grassland soils. In: Abberton M et al, editors. Proceedings of the Workshop on the Role of Grassland Carbon Sequestration in the Mitigation of Climate Change.

[54] Young RR, Wilson B, Harden S, Bernardi A. Accumulation of soil carbon under zero tillage cropping and perennial vegetation on the Liverpool Plains, eastern Australia. Australian Journal of Soil Research.

[55] Kelly RH, Burke IC, Lauenroth WK. Soil organic matter and nutrient availability responses to reduced plant inputs in shortgrass steppe. Ecology.

[56] Hiltbrunner D et al. Cattle trampling alters soil properties and changes soil microbial communities in a Swiss sub-alpine pasture. Geoderma.

[57] Schuman GE, Janzen HH,

[58] Albaladejo J et al. Land use and climate change impacts on soil organic carbon stocks in semi-arid Spain. Journal of Soils and Sediments.

[59] Raiesi F, Asadi E. Soil microbial activity and litter turnover in native grazed and ungrazed rangelands in

Herrick JE. Soil carbon dynamics and potential carbon sequestration by rangelands. Environmental Pollution.

2014;**69**:611-624

Rome: FAO. 2010

2009;**47**:273-285

1996;**77**:2516-2527

2012;**170**:369-377

2002;**116**:391-396

2013;**13**:265-277

*Strategic Management of Grazing Grassland Systems to Maintain and Increase Organic Carbon… DOI: http://dx.doi.org/10.5772/intechopen.84341*

and reseeding of permanent grassland under temperate moist climatic conditions. Grass and Forage Science. 2014;**69**:611-624

*CO2 Sequestration*

2007;**71**:1204

2018;**18**:105-116

[35] Zinn YL, Lal R, Bigham JM, Resck DVS. Edaphic controls on soil organic carbon retention in the Brazilian Cerrado: Texture and mineralogy. Soil Science Society of America Journal.

[43] Su YZ, Li YL, Cui JY, Zhao WZ. Influences of continuous grazing and livestock exclusion on soil properties in a degraded sandy grassland, Inner Mongolia, Northern China. Catena.

[44] Niu D et al. Grazing exclusion alters ecosystem carbon pools in Alxa desert steppe. New Zealand Journal of Agricultural Research. 2011;**54**:127-142

[45] Steffens M, Kölb A, Totsche KU, Kögel-Knabner I. Grazing effects on soil chemical and physical properties in a semiarid steppe of Inner Mongolia (P.R. China). Geoderma. 2008;**143**:63-72

[46] Berg WA, Bradford JA, Sims PL.

[47] Aguilera E, Lassaletta L, Gattinger A, Gimeno BS. Managing soil carbon for climate change mitigation and adaptation in Mediterranean cropping systems: A meta-analysis. Agriculture,

Long-term soil nitrogen and vegetation change on Sandhill rangeland. Journal of Range Management. 1997;**50**:482-486

Ecosystems and Environment.

[49] Nerger R, Beylich A, Fohrer N. Long-term monitoring of soil quality changes in Northern Germany. Geoderma Regional. 2016;**7**:239-249

response functions as a model approach. Global Change Biology.

[51] Necpalova M, Li D, Lanigan G, Casey IA, Burchill W, Humphreys J. Changes in soil organic carbon in a clay loam soil following ploughing

2011;**17**:2415-2427

[50] Poeplau C et al. Temporal dynamics of soil organic carbon after land-use change in the temperate zone–carbon

[48] Guo LB, Gifford RM. Soil carbon stocks and land use change: A metaanalysis. Global Change Biology.

2013;**168**:25-36

2002;**8**:345-360

2005;**59**:267-278

[36] Cardinael R et al. Increased soil organic carbon stocks under agroforestry: A survey of six different sites in France. Agriculture, Ecosystems and Environment. 2017;**236**:243-255

[37] Oliveira JM et al. Integrated farming systems for improving soil carbon balance in the southern Amazon of Brazil. Regional Environmental Change.

[38] Lisboa FJG et al. The match between microbial community structure and soil properties is modulated by land use types and sample origin within an integrated agroecosystem. Soil Biology and Biochemistry. 2014;**78**:97-108

[39] Conrad KA et al. The sequestration and turnover of soil organic carbon in subtropical leucaena-grass

pastures. Agriculture, Ecosystems and

[40] Maia SMF, Ogle SM, Cerri CEP, Cerri CC. Soil organic carbon stock change due to land use activity along the agricultural frontier of the Southwestern Amazon, Brazil, between 1970 and 2002. Global Change Biology.

[41] Francaviglia R, Renzi G, Ledda L, Benedetti A. Organic carbon pools and soil biological fertility are affected by land use intensity in Mediterranean ecosystems of Sardinia, Italy. Science of the Total Environment.

[42] Deng L, Zhou-Ping S, Wu G-L, Xiao-Feng C. Effects of grazing exclusion on carbon sequestration in China's grassland. Earth-Science

Environment. 2017;**248**:38-47

2009;**16**:2775-2788

2017;**599-600**:789-796

Reviews. 2017;**173**:84-95

**62**

[52] Poeplau C, Don A. Sensitivity of soil organic carbon stocks and fractions to different land-use changes across Europe. Geoderma. 2013;**192**:189-201

[53] Jones MB. Potential for carbon sequestration in temperate grassland soils. In: Abberton M et al, editors. Proceedings of the Workshop on the Role of Grassland Carbon Sequestration in the Mitigation of Climate Change. Rome: FAO. 2010

[54] Young RR, Wilson B, Harden S, Bernardi A. Accumulation of soil carbon under zero tillage cropping and perennial vegetation on the Liverpool Plains, eastern Australia. Australian Journal of Soil Research. 2009;**47**:273-285

[55] Kelly RH, Burke IC, Lauenroth WK. Soil organic matter and nutrient availability responses to reduced plant inputs in shortgrass steppe. Ecology. 1996;**77**:2516-2527

[56] Hiltbrunner D et al. Cattle trampling alters soil properties and changes soil microbial communities in a Swiss sub-alpine pasture. Geoderma. 2012;**170**:369-377

[57] Schuman GE, Janzen HH, Herrick JE. Soil carbon dynamics and potential carbon sequestration by rangelands. Environmental Pollution. 2002;**116**:391-396

[58] Albaladejo J et al. Land use and climate change impacts on soil organic carbon stocks in semi-arid Spain. Journal of Soils and Sediments. 2013;**13**:265-277

[59] Raiesi F, Asadi E. Soil microbial activity and litter turnover in native grazed and ungrazed rangelands in

semiarid ecosystem. Biology and Fertility of Soils. 2006;**43**:76-82

[60] Khalil MI, Haque MA, Sattar MA, Schmidhalter U. Relative contribution of crop residue bound-N to irrigated rice and carbon storage in a subtropical soil. In: Bernal et al., editors. Proceedings of the 11th International Conference of the FAO ESCORENA Network on Recycling of Agricultural, Municipal and Industrial Residues in Agriculture; Murcia, Spain; 2004. pp. 169-172

[61] Emadi M, Baghernejad M, Fathi H, Saffari M. Effect of land use change on selected soil physical and chemical properties in north highlands of Iran. Journal of Applied Sciences. 2008;**8**:496-502

[62] Gibon A. Managing grassland for production, the environment and the landscape. Challenges at the farm and the landscape level. Livestock Production Science. 2005;**96**:11-31

[63] MacDonald D et al. Agricultural abandonment in mountain areas of Europe: Environmental consequences and policy response. Journal of Environmental Management. 2000;**59**:47-69

[64] Dumont B et al. Rôles, Impacts et Services Issus des Élevages en Europe. Synthèse de L'expertise Scientifique Collective. France: INRA; 2016. p. 127. auto-saisine

[65] Pereira P, Brevik E, Muñoz-Miriam M, Miller B. Soil Mapping and Process Modeling for Sustainable Land Use Management. Elsevier; 2017. p. 398. eBook ISBN: 9780128052013

[66] Allen DE et al. What determines soil organic carbon stocks in the grazing lands of north-eastern Australia? Soil Research. 2014;**51**:695-706

[67] Molnár ZS et al. Common and conflicting objectives and practices of herders and conservation managers: The need for a conservation herder. Ecosystem Health and Sustainability. 2016;**2**:e01215

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[74] Aubault H et al. Grazing impacts on the susceptibility of rangelands to wind erosion: The effects of stocking rate, stocking strategy and land condition. Aeolian Research. 2015;**17**:89-99

**65**

**Chapter 5**

**Abstract**

(R2

mitigations.

**1. Introduction**

Leaf Litter Decomposition and

Mitigation of CO2 Emissions in

*Askia M. Mohammed, James S. Robinson, David J. Midmore* 

Studies simultaneously quantifying litter weight losses and rates of CO2-C evolved are few, though essential for accurate estimates of forest carbon budgets. A 120-day dry matter loss and a 130-day carbon emission experiments were concurrently conducted at the soil laboratory of the University of Reading, UK. Leaf litters of tree species comprising cocoa (*Theobroma cacao*), *Newbouldia laevis* (dominant shade tree in Eastern region (ER)) and *Persea americana* (dominant shade tree in Western region (WR)) of Ghana were incubated using a single tree leaf litter and/or a 1:1 mixed species leaf litters to determine and predict the litter decomposition and C dynamics in cocoa systems with or without the shade trees. Decomposition and C release trends in the ER systems followed: shade > mixed cocoa-shade = predicted mixed litter > cocoa; and in the WR, the order was: cocoa = mixed cocoa-shade > predicted mixed > shade. Differences between released C estimated from litter weight loss and CO2-C evolution measurement methods were not consistent. Regression analysis revealed a strong

 = 0.71) relationship between loss of litter C and the CO2-C evolution during litter decomposition. The large C pool for shaded cocoa systems indicates the potential to store more C and thus, its promotion could play a significant role in atmospheric CO2

Soil organic matter is the main source of plant nutrients in low input agriculture [1], whilst the primary regenerative source of soil organic matter on agricultural lands is the decomposition of retained plant residues. Therefore, sustainable agricultural production based on nutrient cycling would operate only in systems where enough plant biomass is generated and retained on agricultural land. Hence, the success of forest ecosystems lies on their ability to store large amounts of organic matter aboveground in woody plant tissue and fibrous litter. Conceivably, biomass production, leaf litter decomposition and root biomass turnover in forest ecosystems have much influence on agro ecosystems' nutrient cycling and sustainability [2]. Nutrients are returned to soil through leaf falls and decomposition processes. Thus, their nutrient cycling starts during litter decomposition, where organically bound nutrients are released as free ions to the soil solution that then become

**Keywords:** cocoa system, mineralization, mineralizable C, oxidizable C

Cocoa Ecosystems

*and Anne Verhoef*

#### **Chapter 5**

*CO2 Sequestration*

2016;**2**:e01215

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herders and conservation managers: The need for a conservation herder. Ecosystem Health and Sustainability.

[68] Dezsény Z, Drexler D. Organic agriculture in Hungary. Ecology and

[70] Petz K et al. Mapping and modelling trade-offs and synergies between grazing intensity and ecosystem services in rangelands using global-scale datasets and models. Global Environmental

[71] Soussana J-F, Tallec T, Blanfort V. Mitigating the greenhouse gas balance of ruminant production systems through carbon sequestration in grasslands. Animal. 2010;**4**:334-350

[72] Khalil MI, Osborne B. Improving estimates of soil organic carbon (SOC) stocks and their long-term temporal changes in agricultural soils in Ireland.

[73] Daryanto S, Eldridge DJ, Throop HL. Managing semi-arid woodlands for carbon storage: Grazing and shrub effects on above- and belowground carbon. Agriculture, Ecosystems and

[74] Aubault H et al. Grazing impacts on the susceptibility of rangelands to wind erosion: The effects of stocking rate, stocking strategy and land condition. Aeolian Research. 2015;**17**:89-99

Geoderma. 2018;**322**:172-183

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**64**

## Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems

*Askia M. Mohammed, James S. Robinson, David J. Midmore and Anne Verhoef*

#### **Abstract**

Studies simultaneously quantifying litter weight losses and rates of CO2-C evolved are few, though essential for accurate estimates of forest carbon budgets. A 120-day dry matter loss and a 130-day carbon emission experiments were concurrently conducted at the soil laboratory of the University of Reading, UK. Leaf litters of tree species comprising cocoa (*Theobroma cacao*), *Newbouldia laevis* (dominant shade tree in Eastern region (ER)) and *Persea americana* (dominant shade tree in Western region (WR)) of Ghana were incubated using a single tree leaf litter and/or a 1:1 mixed species leaf litters to determine and predict the litter decomposition and C dynamics in cocoa systems with or without the shade trees. Decomposition and C release trends in the ER systems followed: shade > mixed cocoa-shade = predicted mixed litter > cocoa; and in the WR, the order was: cocoa = mixed cocoa-shade > predicted mixed > shade. Differences between released C estimated from litter weight loss and CO2-C evolution measurement methods were not consistent. Regression analysis revealed a strong (R2 = 0.71) relationship between loss of litter C and the CO2-C evolution during litter decomposition. The large C pool for shaded cocoa systems indicates the potential to store more C and thus, its promotion could play a significant role in atmospheric CO2 mitigations.

**Keywords:** cocoa system, mineralization, mineralizable C, oxidizable C

#### **1. Introduction**

Soil organic matter is the main source of plant nutrients in low input agriculture [1], whilst the primary regenerative source of soil organic matter on agricultural lands is the decomposition of retained plant residues. Therefore, sustainable agricultural production based on nutrient cycling would operate only in systems where enough plant biomass is generated and retained on agricultural land. Hence, the success of forest ecosystems lies on their ability to store large amounts of organic matter aboveground in woody plant tissue and fibrous litter. Conceivably, biomass production, leaf litter decomposition and root biomass turnover in forest ecosystems have much influence on agro ecosystems' nutrient cycling and sustainability [2].

Nutrients are returned to soil through leaf falls and decomposition processes. Thus, their nutrient cycling starts during litter decomposition, where organically bound nutrients are released as free ions to the soil solution that then become

available for uptake by plants. As the bulk of cocoa farmers are poor and therefore, do not apply external fertilizers to their croplands because of its high cost, litter decomposition from both cocoa and non-cocoa (or shade) trees plays a central role in the nutrition of the system. Although cocoa systems accumulate less leaf biomass than native forests, several studies have reported sizeable leaf litter-falls per hectare in cocoa systems (**Table 1**). The high biomass of leaf litter in cocoa systems indicates a high potential source of nutrient cycling when retained to undergo decomposition on the floor of the ecosystem but also a lot of CO2 emissions.

Land use change is arguably the most common anthropogenic activity that interferes greatly with most biogeochemical cycles. Its impact on C and nutrient cycling in the soil has been the subject of much attention [3–6]. Understanding the effects of land use/land cover change on ecosystem functions is often derived by quantifying changes in C and nutrient stocks and fluxes. Indeed, changes in forest cover have been implicated in the rising levels of carbon dioxide (CO2), the main greenhouse gas (GHG), in the atmosphere [4, 7, 8]. This is because large amounts of organic C are often stored in forest trees and which upon clear-felling, decompose and release the stored C to the atmosphere [9].

Since plant litter decomposition involves carbon dioxide (CO2) emissions, and fragmentation and leaching of organic matter to the soil, many studies have been conducted to investigate the factors controlling litter decomposition. These studies have often followed one of three approaches. The first approach simply measures the annual litter-fall in vegetation and equates that to the amount of organic material being decomposed. This approach acknowledges that the soil organic matter level in most natural vegetation types attains an equilibrium state where the amount of material being decomposed annually is equal to the amount of annual litter-fall. The second approach is the weight loss of buried litter over time, whilst the third approach measures the microbial activity on litter via CO2 evolution.

Using weight loss of buried litter contained in nylon mesh bags over time, many studies concluded that the rate of leaf litter decomposition depended on tree species, the chemical composition of the leaves, and environmental factors such as temperature and soil moisture [2, 10, 11]. Hitherto, several researchers considered the C/N ratio of plants as the main plant composition factor that controls decomposition rates [10]. Increasingly, other litter constituents such as lignin and polyphenol concentration, especially in the tropics, are considered to play important roles in the decomposition process [11–14].


**67**

mitigate CO2 emissions.

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

Although the use of litter bags makes it possible for buried litter recovery, their use for decomposition studies has been criticized for creating unrealistic 'microclimate' conditions; e.g. moisture may be elevated to levels not found in unconfined conditions and can contribute to litter decomposition [15, 16]. Losses due to earthworm consumption or litter fragmentation overestimate those mediated by microbial activities. Frankland [23] studied the weight loss pattern of *Bracken rachids* through the unconfined method i.e., using plastic labels to mark the litter before placing it on the soil surface. The study noted that retrieval of decomposing litter under this method is tedious and presents large potential errors in estimating the decomposition rates. Also, it does not protect the litter from the interferences of larger organisms and fragmentation. Therefore methods to overcome these drawbacks are imperative when investigating the factors that control leaf litter

As an alternative, numerous studies have measured decomposition rates of litter by the CO2 evolution or carbon mineralization method [14, 24–29]. This method has the advantage of measuring decomposition during shorter periods (hour scale); i.e., through early decomposition stages when weight loss cannot be accurately quantified [30]. However, the CO2 evolution method requires an experimental set-up that often deviates farther from the natural conditions than weight loss measurement. Studies simultaneously quantifying litter weight losses and investigating rates of CO2-C evolved are few; however they are essential for accurate estimates of forest nutrient cycling. Nonetheless, results from the few studies on litter decomposition studies using the CO2 releasing method have been comparable to the weight loss

Many litter decomposition studies have focused on individual plant species when

This chapter reports on the findings from laboratory incubation experiments carried out on separate leaf samples of cocoa and shade species and 1:1 mixed cocoa-shade leaf litters. Dry mass loss and C emission from unconfined leaf samples were analyzed to (i) determine the decomposition dynamics of cocoa litter, and of the dominant shade species in cocoa ecosystems, (ii) investigate the effects of leaf interactions on decomposition (iii) assess the relationship between decomposition rates and C release patterns, (iv) determine the C emission rates during leaf decomposition, and (v) assess the relationship between leaf weight loss and C emissions during decomposition, and (vi) determine the CO2 mitigation potentials of cocoa systems. The study hypothesized that the decomposition rates of the mixed leaves of cocoa-shade systems would (1) differ from the rates of decomposition of the separate litter components decomposing alone (i.e., separate cocoa and shade leaves), (2) be equal to the pooled rates of the separate litter components decomposing alone, (3) the amount of C in the litter loss is the same as the C emitted during litter decomposition and (4) cocoa systems have the potential to

investigating the factors influencing litter decay [33–38]. However, leaf litters in ecosystems with more than one dominant plant species do not fall separately, either in time or space, but create an admixture of litters. Although the potential of litter interactions was hypothesized to have a marked effects on their decomposition in agro ecosystems many years ago by Thomas [39], Staaf [40], Seastedt [41] and many others, studies on potential interactions in mixed leaf litter decomposition are still few and not well understood, and so require further investigations to aid planning for nutrient management through decomposition and nutrient release in agroforestry and similar systems [42]. Hansen and Coleman [43] noted some changes in the chemical environment (increased nutrient availability) due to litter mixing during decomposition studies of mixed litters of yellow birch (*Betula alleganiensis* Britton),

red oak (*Quercus rubra* L.) and sugar maple (*Acer saccharum* Marsh).

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

decomposition.

method [27, 31, 32].

*a Cocoa with* Cordia alliodora *as shade tree.*

*b No data.*

*c Cocoa with* Erythrina poeppigiana *as shade tree.*

*Source: from [22].*

#### **Table 1.**

*Annual litter-fall of cocoa ecosystems (in kg dry matter (DM)/ha).*

#### *Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

Although the use of litter bags makes it possible for buried litter recovery, their use for decomposition studies has been criticized for creating unrealistic 'microclimate' conditions; e.g. moisture may be elevated to levels not found in unconfined conditions and can contribute to litter decomposition [15, 16]. Losses due to earthworm consumption or litter fragmentation overestimate those mediated by microbial activities. Frankland [23] studied the weight loss pattern of *Bracken rachids* through the unconfined method i.e., using plastic labels to mark the litter before placing it on the soil surface. The study noted that retrieval of decomposing litter under this method is tedious and presents large potential errors in estimating the decomposition rates. Also, it does not protect the litter from the interferences of larger organisms and fragmentation. Therefore methods to overcome these drawbacks are imperative when investigating the factors that control leaf litter decomposition.

As an alternative, numerous studies have measured decomposition rates of litter by the CO2 evolution or carbon mineralization method [14, 24–29]. This method has the advantage of measuring decomposition during shorter periods (hour scale); i.e., through early decomposition stages when weight loss cannot be accurately quantified [30]. However, the CO2 evolution method requires an experimental set-up that often deviates farther from the natural conditions than weight loss measurement. Studies simultaneously quantifying litter weight losses and investigating rates of CO2-C evolved are few; however they are essential for accurate estimates of forest nutrient cycling. Nonetheless, results from the few studies on litter decomposition studies using the CO2 releasing method have been comparable to the weight loss method [27, 31, 32].

Many litter decomposition studies have focused on individual plant species when investigating the factors influencing litter decay [33–38]. However, leaf litters in ecosystems with more than one dominant plant species do not fall separately, either in time or space, but create an admixture of litters. Although the potential of litter interactions was hypothesized to have a marked effects on their decomposition in agro ecosystems many years ago by Thomas [39], Staaf [40], Seastedt [41] and many others, studies on potential interactions in mixed leaf litter decomposition are still few and not well understood, and so require further investigations to aid planning for nutrient management through decomposition and nutrient release in agroforestry and similar systems [42]. Hansen and Coleman [43] noted some changes in the chemical environment (increased nutrient availability) due to litter mixing during decomposition studies of mixed litters of yellow birch (*Betula alleganiensis* Britton), red oak (*Quercus rubra* L.) and sugar maple (*Acer saccharum* Marsh).

This chapter reports on the findings from laboratory incubation experiments carried out on separate leaf samples of cocoa and shade species and 1:1 mixed cocoa-shade leaf litters. Dry mass loss and C emission from unconfined leaf samples were analyzed to (i) determine the decomposition dynamics of cocoa litter, and of the dominant shade species in cocoa ecosystems, (ii) investigate the effects of leaf interactions on decomposition (iii) assess the relationship between decomposition rates and C release patterns, (iv) determine the C emission rates during leaf decomposition, and (v) assess the relationship between leaf weight loss and C emissions during decomposition, and (vi) determine the CO2 mitigation potentials of cocoa systems. The study hypothesized that the decomposition rates of the mixed leaves of cocoa-shade systems would (1) differ from the rates of decomposition of the separate litter components decomposing alone (i.e., separate cocoa and shade leaves), (2) be equal to the pooled rates of the separate litter components decomposing alone, (3) the amount of C in the litter loss is the same as the C emitted during litter decomposition and (4) cocoa systems have the potential to mitigate CO2 emissions.

*CO2 Sequestration*

available for uptake by plants. As the bulk of cocoa farmers are poor and therefore, do not apply external fertilizers to their croplands because of its high cost, litter decomposition from both cocoa and non-cocoa (or shade) trees plays a central role in the nutrition of the system. Although cocoa systems accumulate less leaf biomass than native forests, several studies have reported sizeable leaf litter-falls per hectare in cocoa systems (**Table 1**). The high biomass of leaf litter in cocoa systems indicates a high potential source of nutrient cycling when retained to undergo decom-

Land use change is arguably the most common anthropogenic activity that interferes greatly with most biogeochemical cycles. Its impact on C and nutrient cycling in the soil has been the subject of much attention [3–6]. Understanding the effects of land use/land cover change on ecosystem functions is often derived by quantifying changes in C and nutrient stocks and fluxes. Indeed, changes in forest cover have been implicated in the rising levels of carbon dioxide (CO2), the main greenhouse gas (GHG), in the atmosphere [4, 7, 8]. This is because large amounts of organic C are often stored in forest trees and which upon clear-felling, decompose

Since plant litter decomposition involves carbon dioxide (CO2) emissions, and fragmentation and leaching of organic matter to the soil, many studies have been conducted to investigate the factors controlling litter decomposition. These studies have often followed one of three approaches. The first approach simply measures the annual litter-fall in vegetation and equates that to the amount of organic material being decomposed. This approach acknowledges that the soil organic matter level in most natural vegetation types attains an equilibrium state where the amount of material being decomposed annually is equal to the amount of annual litter-fall. The second approach is the weight loss of buried litter over time, whilst the third

position on the floor of the ecosystem but also a lot of CO2 emissions.

approach measures the microbial activity on litter via CO2 evolution.

**Country Annual litter-fall**

Using weight loss of buried litter contained in nylon mesh bags over time, many studies concluded that the rate of leaf litter decomposition depended on tree species, the chemical composition of the leaves, and environmental factors such as temperature and soil moisture [2, 10, 11]. Hitherto, several researchers considered the C/N ratio of plants as the main plant composition factor that controls decomposition rates [10]. Increasingly, other litter constituents such as lignin and polyphenol concentration, especially in the tropics, are considered to play important roles in the

Malaysia 8–10 5460 2660 8120 [17] Venezuela 30 7630 13,571 21,201 [18] Costa Ricaa 10 ndb nd 7071 [19] Costa Ricac 10 nd nd 8906 [19] Brazil nd nd nd 9000–14,000 [20] Ghana nd nd nd 5000 [21]

**Age cocoa (years) Cocoa tree Shade tree Total Reference**

and release the stored C to the atmosphere [9].

decomposition process [11–14].

*Cocoa with* Cordia alliodora *as shade tree.*

*Cocoa with* Erythrina poeppigiana *as shade tree.*

*Annual litter-fall of cocoa ecosystems (in kg dry matter (DM)/ha).*

**66**

**Table 1.**

*a*

*b No data. c*

*Source: from [22].*

#### **2. Materials and methods**

#### **2.1 Leaf sampling and site**

Leaf samples from three tree species (cocoa, *Newbouldia laevis* dominant species in Eastern Region (ER) and *Persea americana* dominant in Western Region (WR)) were collected from cocoa ecosystems in ER and WR of Ghana. Farms were selected in the ER at the Duodukrom community within the Suhum District (6°2′ N, 0°27′ W), and the in WR at Anyinabrim found in the Sefwi-Wiawso District (6°57′ N, 2°35′ W).

The ER covers a land area of 19,323 km<sup>2</sup> representing 8.1% of the total land area of Ghana [44]. It lies between latitude 6° and 7° N and longitude 1°30′ W and 0°30′ E. The region has been producing cocoa long before cultivations started in the Western region. The WR occupies a land area of 23,921 km<sup>2</sup> which is approximately 10% of the total land area of Ghana [44]. The region is the wettest part of Ghana and harbors about 24 forest reserves that account for about 40% of the forest reserves in Ghana. The sampled leaf litters from these regions were transported to the Soil Research Centre of the University of Reading, UK, where the following experiments were conducted.

#### **2.2 Initial chemical properties of the oven-dried leaf litters**

#### *2.2.1 Total carbon*

The total carbon (C) in the samples was determined using the Europa Roboprep connected to a VG 622 Mass Spectrophotometer. Weights of 0.90–1.10 mg (oven dry) of plant components (root, stem, branch, leaf and litter), and 8.00–12.00 mg (air dry) of soil samples, in triplicate, were put into small pre-weighed aluminum cups and pressed to seal completely using forceps. The sealed samples were arranged in a labeled sample holder and transferred to the Mass Spectrometry System for analysis. The analytical output was in % C of the samples.

#### *2.2.2 Total nitrogen*

The total N in the leaf and soil samples was determined using the Europa Scientific ANCA System. Samples of 5–6 mg leaf and 8–12 mg soil were weighed into small aluminum cups and pressed to seal using forceps. The sealed samples were transferred to the Europa system for analysis. The analyzed data were expressed as % N (w/w).

#### *2.2.3 Total P, K, Ca, Mg and S*

Approximately 0.5 g oven dry plant samples (i.e., root, stem, branch, leaf) were accurately weighed and transferred into 100 mL Kjeldahl digestion tubes. About 10 mL of concentrated AnalaR nitric acid were added to each tube in a fume hood. Each tube was then covered with a glass marble and left to stand overnight. The tubes were placed on a digestion block the next day and cautiously heated to 60°C for 3 h followed by a gradual increase to 110°C and allowed to digest for 6 h. The digestion tubes were then removed, allowed to cool and the digest filtered through prewashed No. 540 (12.5 cm diameter) filter papers into 100 mL volumetric flasks. The flasks were made up to volume with ultra-pure water. Aliquots of 5 mL from each flask were diluted by a factor of two and

**69**

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

analyzed for concentrations of P, K, Ca, Mg and S using the inductively coupled

Standards of multi-element solution (0.5, 1, 50 and 100 mg/L K, Ca, Mg, Mn, Zn, Fe, and Al), sulfur (50 mg/L) and phosphorus (50 mg/L), as well as a blank (0 mg/L) were prepared to contain the same nitric acid concentration as in the digest to calibrate the ICP-OES. The data generated by the ICP-OES were reported in concentrations (μg/L) which, after correcting for the blank reading, was converted to mg/kg dry weight based on the sample weights digested, volume of extract

As outlined in Anderson and Ingram [46], a 1 ± 0.001 g sample of leaf for each tree species was weighed (W1) into 200 mL Berzelius beaker. A 100 mL of acid detergent solution (20 g of cetyltrimethyl ammonium bromide (CTAB) was dissolved in 27.84 mL of sulfuric acid (98% purity) in a 1000 mL volumetric flask and brought to the mark with distilled water and to form a clear solution by heating) was then added and heated to boil for 1 h. The content was filtered hot through a vitreosil crucible (No. 1) of known weights (W2). The residue was washed with 3 × 50 mL aliquots of hot water and then with acetone until no more color was removed. The residue was then oven-dried at 105°C for 2 h, cooled in a desiccator and weighed whilst still in the crucible (W3). The sample remaining expressed as a percentage of the initial weight of the sample, estimated the acid detergent fiber

ADF(%) <sup>=</sup> (W3 <sup>−</sup> W2) <sup>×</sup> <sup>100</sup> \_\_\_\_\_\_\_\_\_\_\_\_\_ W1 (1)

A saturated potassium permanganate solution was prepared by dissolving 50 g KMnO4 and 0.05 g Ag2SO4 in a 1000 mL volumetric flask and brought to the mark with distilled water. Lignin buffer solution was also prepared by dissolving 6 g Fe(NO3)3·9H2O and 0.15 g AgNO3 in water followed by addition of 400 mL methylpropan-2-ol and diluted to 1000 mL with distilled water. A combined solution of the saturated KMnO4 and lignin buffer solution in the ratio of 2:1 was prepared. The crucible containing the ADF was then placed in a shallow enamel containing cold water carefully without wetting the fiber and 25 mL of the combined KMnO4/buffer added. The content was stirred with a glass rod to break up lumps and to wet all the fiber particles in the crucible with the solution and allowed to stand for 3 h. The content in the crucible was then filtered under suction and washed with demineralizing solution (50 g oxalic acid dehydrate dissolved in 700 mL 95% ethanol, followed with addition of 50 mL conc. HCl and diluted to 1000 mL with distilled water) until white. This was filtered and washed thoroughly with ethanol under continuous suction and washed in a similar manner with acetone. The crucible was then oven-dried at 105°C for 2 h, cooled in a desiccator and weighed (W4). The

*Lignin*(%) <sup>=</sup> (*W*<sup>3</sup> <sup>−</sup> *<sup>W</sup>*4) <sup>×</sup> <sup>100</sup> \_\_\_\_\_\_\_\_\_\_\_\_\_ *W*1 (2)

Approximately 100 g each of 2-mm sieved air-dried plant materials (viz. cocoa, *N. laevis* and *P. Americana,* 1:1 (w/w) mixture of cocoa: *N. laevis* and cocoa:

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

and the dilution factor [45].

(ADF) content of the sample:

percentage lignin in the sample was then calculated as:

**2.3 Sample preparation for experimentation**

*2.2.4 Lignin concentration*

plasma-optical emission spectrometry (ICP-OES).

#### *Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

analyzed for concentrations of P, K, Ca, Mg and S using the inductively coupled plasma-optical emission spectrometry (ICP-OES).

Standards of multi-element solution (0.5, 1, 50 and 100 mg/L K, Ca, Mg, Mn, Zn, Fe, and Al), sulfur (50 mg/L) and phosphorus (50 mg/L), as well as a blank (0 mg/L) were prepared to contain the same nitric acid concentration as in the digest to calibrate the ICP-OES. The data generated by the ICP-OES were reported in concentrations (μg/L) which, after correcting for the blank reading, was converted to mg/kg dry weight based on the sample weights digested, volume of extract and the dilution factor [45].

#### *2.2.4 Lignin concentration*

*CO2 Sequestration*

2°35′ W).

**2. Materials and methods**

experiments were conducted.

*2.2.1 Total carbon*

*2.2.2 Total nitrogen*

expressed as % N (w/w).

*2.2.3 Total P, K, Ca, Mg and S*

The ER covers a land area of 19,323 km<sup>2</sup>

Western region. The WR occupies a land area of 23,921 km<sup>2</sup>

**2.2 Initial chemical properties of the oven-dried leaf litters**

System for analysis. The analytical output was in % C of the samples.

The total N in the leaf and soil samples was determined using the Europa Scientific ANCA System. Samples of 5–6 mg leaf and 8–12 mg soil were weighed into small aluminum cups and pressed to seal using forceps. The sealed samples were transferred to the Europa system for analysis. The analyzed data were

Approximately 0.5 g oven dry plant samples (i.e., root, stem, branch, leaf) were accurately weighed and transferred into 100 mL Kjeldahl digestion tubes. About 10 mL of concentrated AnalaR nitric acid were added to each tube in a fume hood. Each tube was then covered with a glass marble and left to stand overnight. The tubes were placed on a digestion block the next day and cautiously heated to 60°C for 3 h followed by a gradual increase to 110°C and allowed to digest for 6 h. The digestion tubes were then removed, allowed to cool and the digest filtered through prewashed No. 540 (12.5 cm diameter) filter papers into 100 mL volumetric flasks. The flasks were made up to volume with ultra-pure water. Aliquots of 5 mL from each flask were diluted by a factor of two and

Leaf samples from three tree species (cocoa, *Newbouldia laevis* dominant species in Eastern Region (ER) and *Persea americana* dominant in Western Region (WR)) were collected from cocoa ecosystems in ER and WR of Ghana. Farms were selected in the ER at the Duodukrom community within the Suhum District (6°2′ N, 0°27′ W), and the in WR at Anyinabrim found in the Sefwi-Wiawso District (6°57′ N,

of Ghana [44]. It lies between latitude 6° and 7° N and longitude 1°30′ W and 0°30′ E. The region has been producing cocoa long before cultivations started in the

10% of the total land area of Ghana [44]. The region is the wettest part of Ghana and harbors about 24 forest reserves that account for about 40% of the forest reserves in Ghana. The sampled leaf litters from these regions were transported to the Soil Research Centre of the University of Reading, UK, where the following

The total carbon (C) in the samples was determined using the Europa Roboprep connected to a VG 622 Mass Spectrophotometer. Weights of 0.90–1.10 mg (oven dry) of plant components (root, stem, branch, leaf and litter), and 8.00–12.00 mg (air dry) of soil samples, in triplicate, were put into small pre-weighed aluminum cups and pressed to seal completely using forceps. The sealed samples were arranged in a labeled sample holder and transferred to the Mass Spectrometry

representing 8.1% of the total land area

which is approximately

**2.1 Leaf sampling and site**

**68**

As outlined in Anderson and Ingram [46], a 1 ± 0.001 g sample of leaf for each tree species was weighed (W1) into 200 mL Berzelius beaker. A 100 mL of acid detergent solution (20 g of cetyltrimethyl ammonium bromide (CTAB) was dissolved in 27.84 mL of sulfuric acid (98% purity) in a 1000 mL volumetric flask and brought to the mark with distilled water and to form a clear solution by heating) was then added and heated to boil for 1 h. The content was filtered hot through a vitreosil crucible (No. 1) of known weights (W2). The residue was washed with 3 × 50 mL aliquots of hot water and then with acetone until no more color was removed. The residue was then oven-dried at 105°C for 2 h, cooled in a desiccator and weighed whilst still in the crucible (W3). The sample remaining expressed as a percentage of the initial weight of the sample, estimated the acid detergent fiber (ADF) content of the sample:

## 1\textsuperscript{5}\$\\
\*\*Contium or une sampue.\*\*

$$\text{ADF(\%)} = \frac{(\text{W3} - \text{W2}) \times 100}{\text{W1}}\tag{1}$$

A saturated potassium permanganate solution was prepared by dissolving 50 g KMnO4 and 0.05 g Ag2SO4 in a 1000 mL volumetric flask and brought to the mark with distilled water. Lignin buffer solution was also prepared by dissolving 6 g Fe(NO3)3·9H2O and 0.15 g AgNO3 in water followed by addition of 400 mL methylpropan-2-ol and diluted to 1000 mL with distilled water. A combined solution of the saturated KMnO4 and lignin buffer solution in the ratio of 2:1 was prepared. The crucible containing the ADF was then placed in a shallow enamel containing cold water carefully without wetting the fiber and 25 mL of the combined KMnO4/buffer added. The content was stirred with a glass rod to break up lumps and to wet all the fiber particles in the crucible with the solution and allowed to stand for 3 h. The content in the crucible was then filtered under suction and washed with demineralizing solution (50 g oxalic acid dehydrate dissolved in 700 mL 95% ethanol, followed with addition of 50 mL conc. HCl and diluted to 1000 mL with distilled water) until white. This was filtered and washed thoroughly with ethanol under continuous suction and washed in a similar manner with acetone. The crucible was then oven-dried at 105°C for 2 h, cooled in a desiccator and weighed (W4). The percentage lignin in the sample was then calculated as:

 $\rightarrow$ ]ignin in the sample was then calculated as: 
$$Lignin(\text{\textquotedbl{}6}) = \frac{(W3 - W4) \times 100}{W1} \tag{2}$$

#### **2.3 Sample preparation for experimentation**

Approximately 100 g each of 2-mm sieved air-dried plant materials (viz. cocoa, *N. laevis* and *P. Americana,* 1:1 (w/w) mixture of cocoa: *N. laevis* and cocoa: *P. americana* leaf litters) were weighed into a 500 mL beaker. Water (300 mL) was gradually added to each weighed litter sample with continuous stirring to produce a moist litter treatment that was not saturated [27]. They were kept in a fridge at a temperature of 4°C for 72 h to attain an equilibrated moisture status in all treatments. Three weighed sub samples (6 g) of each treatment were oven-dried at 80°C for 24 h and used to determine a conversion factor to an oven dry basis.

#### **2.4 Leaf decomposition experiment**

A known weight (approx. 6 g) of each leaf treatment was transferred into a labeled 15 mL beaker separately. Soil (~5 mg) from the region specific to the leaf treatment was added to the beaker to serve as an inoculant. Each beaker unit was replicated 12 times to give the total of 72 experimental units. These units were weighed and randomly arranged for incubation in a 30°C controlled dark room located in the Soil Chemistry laboratory of the Soil Research Centre, University of Reading, UK. Three (3) replicates of each treatment were retrieved after 0, 20, 50, 80 and 120 days of incubation. The beakers so retrieved following each incubation period, were oven-dried at 80°C for 24 h and weighed. The residual oven-dried litters were appropriately labeled and stored for chemical analysis.

#### **2.5 CO2-C emission experiment**

A sample (3 g) of each litter treatment was transferred into a 250 mL conical flask. As shown in **Figure 1**, the neck of the flask was closed with a rubber bung from which was suspended a vial containing 20 mL of 1 M NaOH solution to trap CO2 evolved as outlined by Rowell [47]. A similar conical flask was set-up without leaf treatment as a blank. Each flask unit was replicated 3 times to give a total of 21 experimental units comprising 18 litter treatments and 3 blanks. Also, the treated conical flasks were randomly arranged for incubation in a 30°C controlled dark room located in the Soil Chemistry Laboratory of Soil Research Centre, University of Reading, UK. At 0, 3, 5, 11, 16, 28, 43, 60, 75, 90, 103 and 130 days of incubation, the vials were removed, and the NaOH was carefully transferred quantitatively (with rinsing) into an empty 50 mL conical flask for titration. Ten milliliters (10 mL) of 1 M BaCl2 was added to precipitate the carbonate compounds (NaHCO3) formed as a result of reaction between NaOH and CO2 (**Figure 1**). The vials were thus, removed 12 times and replaced after refilling with fresh NaOH solution before closing the incubation beaker to continue the capture of released CO2 from the decomposing leaves. The amount of CO2 captured was determined by titrating the unreacted NaOH in the 50 mL flask with 0.5 M HCl using phenolphthalein as the indicator.

#### **2.6 Data analysis**

The data on per cent mass remaining, carbon and nutrient concentrations of pure cocoa leaf and shade species leaf decomposing alone were used to estimate expected data for mixed cocoa and shade litter denoted as predicted mixture, using the simplified form of similar relations used by others as:

$$\text{simplified form of similar relations used by others as:}$$

$$\text{predicted}(\text{x}) = \frac{\text{Cocoa}(\text{x}) + \text{Shade}(\text{x})}{2} \tag{3}$$

**71**

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

cocoa-shade leaves treatment indicated an interaction in the decomposition of the mixed leaves, either negative or positive [49]. The data on % residual leaf were fitted to the exponential decay Eq. (2) that was proposed first by Olson [50] to

*Rt* = *Ro* ∗ exp(−*kd t*) (4)

The data on C emission were fitted to the single exponential rise-to-maximum

*Ct* = *Co* ∗ [1 − exp(−*km t*)] (5)

where *Ct* = amount of C emitted after time *t* of the incubation; *Co*= amount of C that can be potentially emitted within the period of incubation; and *km* = mineral-

The amounts of C accompanying the loss leaves during the decomposition

[*C*]*loss*(*t*) <sup>=</sup> (100 <sup>−</sup> %*leafremained*(*t*)) \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ 100 <sup>×</sup> [*C*]*<sup>i</sup>* (6)

where [*C*]loss(t) is amount of C in the leaf loss (g/kg) at time *t* (i.e., 0, 20 40, 80

The comparison was carried out statistically using ANOVA to test for significant differences of all data parameters (% residual litter mass, C and nutrient concentrations and release, C emission, *Co*, and *kd*). Tukey's mean separation procedure at the 0.05 level of significance was used for all data. All figures were produced with SigmaPlot 10.0 using the means of % residual litter mass, C and nutrient concentrations and release and also C emission. Also the fitted model parameters were

and 120 days), and [*C*]i is the initial carbon concentration in the litter (g/kg).

estimated using the SigmaPlot 10.0 regression analysis module.

where *Rt* = % residual weight at time *t*, *Ro*= initial litter per cent at day zero

describe the decomposition rates of the leaf litter treatments:

(i.e 100%) and *kd* = decomposition rate constant.

(growth) model.

**Figure 1.**

*Photograph of CO2-C emission experiment.*

ization rate constant.

processes were calculated as:

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

where *x* = per cent mass remaining, carbon or nutrient concentration, and C emission of the leaf treatments at each retrieval day [28, 48, 49]. Any significant difference between the estimated predicted mixture value and the actual mixed

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

**Figure 1.** *Photograph of CO2-C emission experiment.*

*CO2 Sequestration*

**2.4 Leaf decomposition experiment**

**2.5 CO2-C emission experiment**

phthalein as the indicator.

**2.6 Data analysis**

*P. americana* leaf litters) were weighed into a 500 mL beaker. Water (300 mL) was gradually added to each weighed litter sample with continuous stirring to produce a moist litter treatment that was not saturated [27]. They were kept in a fridge at a temperature of 4°C for 72 h to attain an equilibrated moisture status in all treatments. Three weighed sub samples (6 g) of each treatment were oven-dried at 80°C

A known weight (approx. 6 g) of each leaf treatment was transferred into a labeled 15 mL beaker separately. Soil (~5 mg) from the region specific to the leaf treatment was added to the beaker to serve as an inoculant. Each beaker unit was replicated 12 times to give the total of 72 experimental units. These units were weighed and randomly arranged for incubation in a 30°C controlled dark room located in the Soil Chemistry laboratory of the Soil Research Centre, University of Reading, UK. Three (3) replicates of each treatment were retrieved after 0, 20, 50, 80 and 120 days of incubation. The beakers so retrieved following each incubation period, were oven-dried at 80°C for 24 h and weighed. The residual oven-dried

A sample (3 g) of each litter treatment was transferred into a 250 mL conical flask. As shown in **Figure 1**, the neck of the flask was closed with a rubber bung from which was suspended a vial containing 20 mL of 1 M NaOH solution to trap CO2 evolved as outlined by Rowell [47]. A similar conical flask was set-up without leaf treatment as a blank. Each flask unit was replicated 3 times to give a total of 21 experimental units comprising 18 litter treatments and 3 blanks. Also, the treated conical flasks were randomly arranged for incubation in a 30°C controlled dark room located in the Soil Chemistry Laboratory of Soil Research Centre, University of Reading, UK. At 0, 3, 5, 11, 16, 28, 43, 60, 75, 90, 103 and 130 days of incubation, the vials were removed, and the NaOH was carefully transferred quantitatively (with rinsing) into an empty 50 mL conical flask for titration. Ten milliliters (10 mL) of 1 M BaCl2 was added to precipitate the carbonate compounds (NaHCO3) formed as a result of reaction between NaOH and CO2 (**Figure 1**). The vials were thus, removed 12 times and replaced after refilling with fresh NaOH solution before closing the incubation beaker to continue the capture of released CO2 from the decomposing leaves. The amount of CO2 captured was determined by titrating the unreacted NaOH in the 50 mL flask with 0.5 M HCl using phenol-

The data on per cent mass remaining, carbon and nutrient concentrations of pure cocoa leaf and shade species leaf decomposing alone were used to estimate expected data for mixed cocoa and shade litter denoted as predicted mixture, using

*predicted*(*x*) <sup>=</sup> *Cocoa*(*x*) <sup>+</sup> *Shade*(*x*) \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ 2 (3)

where *x* = per cent mass remaining, carbon or nutrient concentration, and C emission of the leaf treatments at each retrieval day [28, 48, 49]. Any significant difference between the estimated predicted mixture value and the actual mixed

the simplified form of similar relations used by others as:

for 24 h and used to determine a conversion factor to an oven dry basis.

litters were appropriately labeled and stored for chemical analysis.

**70**

cocoa-shade leaves treatment indicated an interaction in the decomposition of the mixed leaves, either negative or positive [49]. The data on % residual leaf were fitted to the exponential decay Eq. (2) that was proposed first by Olson [50] to describe the decomposition rates of the leaf litter treatments:

$$R\_t = R\_o \* \exp\left(-k\_d t\right) \tag{4}$$

where *Rt* = % residual weight at time *t*, *Ro*= initial litter per cent at day zero (i.e 100%) and *kd* = decomposition rate constant.

The data on C emission were fitted to the single exponential rise-to-maximum (growth) model.

$$\mathbf{C}\_t = \mathbf{C}\_o \ast \begin{bmatrix} \mathbf{1} \ -\exp\left(-k\_m t\right) \end{bmatrix} \tag{5}$$

where *Ct* = amount of C emitted after time *t* of the incubation; *Co*= amount of C that can be potentially emitted within the period of incubation; and *km* = mineralization rate constant.

The amounts of C accompanying the loss leaves during the decomposition processes were calculated as:

$$\begin{array}{l} \text{excess were calculated as:}\\\\ \text{[C]}\_{low(t)} = \frac{\text{(100 - 9dage}\_{reminal(t)})}{100} \times \text{[C]}\_{i} \end{array} \tag{6}$$

where [*C*]loss(t) is amount of C in the leaf loss (g/kg) at time *t* (i.e., 0, 20 40, 80 and 120 days), and [*C*]i is the initial carbon concentration in the litter (g/kg).

The comparison was carried out statistically using ANOVA to test for significant differences of all data parameters (% residual litter mass, C and nutrient concentrations and release, C emission, *Co*, and *kd*). Tukey's mean separation procedure at the 0.05 level of significance was used for all data. All figures were produced with SigmaPlot 10.0 using the means of % residual litter mass, C and nutrient concentrations and release and also C emission. Also the fitted model parameters were estimated using the SigmaPlot 10.0 regression analysis module.

### **3. Results and discussion**

#### **3.1 Chemical characteristics of the leaf sample**

#### *3.1.1 Eastern region of Ghana*

Literature is replete with the important role that litter chemistry plays in decomposition and nutrient release in top soils [14, 26, 51–53]. The initial concentrations of some elemental nutrients of the leaf litter samples are presented in **Table 2**. The leaf litter treatments did not differ significantly (*P* > 0.05) in their C and S concentrations in the Eastern region (ER). The leaf litters generally had low oxidizable carbon concentration by weight with less variability as indicated by the narrow range of 337.0–382.6 g/kg. The cocoa-shade mixture had the highest C and the leaf litter of shade tree contained the least (**Table 2**). Honeycutt et al. [54], Woomer et al. [55], and Kuo et al. [56] noted that plant residues have stable carbon concentration of about 40% by weight. Other studies have used a constant value from 450 to 500 g/kg as the C concentration for all parts of a tree biomass including the leaves [57–60]. Thus, the present C concentrations of the leaf litters from cocoa ecosystems in the ER of Ghana are lower than the commonly used ranges. The C concentration of 357.2 g/kg for the leaf litter of cocoa is lower than that reported by Anglaaere [16] as 413 g/kg for cocoa leaf samples from Atwima District in the same Eastern region of Ghana where the present study was carried out. However, the present litter C ranged confirmed the reported C data of 364 to 400 g/kg on similar cocoa leaf litter by Ofori-Frimpong and Rowell [27].

Among the nutrients that varied significantly between the leaf samples, that of the shade tree *Newbouldia laevis*, had significantly (*P* < 0.05) higher K, Ca and lignin but lower Mg concentration than the cocoa leaf litter (**Table 2**). The N, P and S concentrations in the leaf litters of the cocoa and shade trees did not differ significantly (*P* > 0.05). The predicted mixture contained higher P and Mg concentrations than


*1* Newbouldia laevis *in Eastern region,* Persea americana *in Western region.*

*2 Different letters within same region and column indicate significant difference at* P *< 0.05 using Tukey's method.*

#### **Table 2.**

*Initial chemical composition and lignin (L) content (mean) and nutrient ratios of the leaf litters of cocoa, shade (*Newbouldia laevis*,* Persea americana*)1 and mixed cocoa-shade under cocoa ecosystems in eastern and Western regions and the predicted mixed litter in Ghana.2*

**73**

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

the analyzed mixture of cocoa-shade leaf litter. The lower P and Mg concentrations in mixed cocoa-shade litter than expected or predicted is an indication of nonadditive response or negative interaction when cocoa and shade leaves are mixed together. The other nutrient elements, however, were similar in the mixed cocoashade and predicted mixed litters, indicating an additive response for those nutrient elements in mixed litter systems such as shaded or agroforestry systems (**Table 2**). The initial N concentrations of all the leaf litters were higher than the critical level for cocoa foliage N concentration (9.0 g/kg), below which point net N immobilization would be expected [61]. Thus, with the high N concentration of the leaves, net N mineralization is highly possible during the leaf decomposition. Several researchers have considered the N and/or its ratios such as C/N, lignin/N and polyphenol/N of residues as major factors controlling decomposition processes [14, 34, 52]. The C/N and lignin/N ratios of the leaf litters from ER ranged from 19.4 to 25.2 and 11.7 to 21.8, respectively (**Table 2**). Thus, the C/N ratios of the litters are so close to the critical level of 25 noted for decomposition and N mineral-

Where nutrient ratios are used as indices of nutrient status to microbial growth,

**Table 2** revealed that the P, K and Mg concentrations of all the leaves from the ER were less than the critical range of 2.0 to 2.5 g/kg, 20 and 5 g/kg respectively. As such, P, K and Mg immobilization would be expected during decomposition [61, 66–68]. The Ca concentrations of the litters were higher than the critical 6 g/kg value. The lignin content of the leaf litters from the ER ranged from 220.0 to 289.1 g/kg dry matter (DM). The cocoa leaf litter had significantly (P < 0.05) lower lignin status when compared with the shade and the mixed cocoa-shade leaf litters, as well as the predicted mixture (**Table 2**). However, the lignin concentration (215.7 g/kg DM) in the cocoa leaf litter in this study is higher than the data (141–146 g/kg DM) of Dawoe [69] on cocoa leaf lignin status in Ghana. The lignin concentration in mixed cocoa-shade litter was similar to the predicted mixed litters (**Table 2**). Lignin has been considered a determinant of litter quality and a predictor of decomposition by previous researchers [34, 70, 71].

The leaf litters from the Western region (WR) varied considerably in their initial nutrient and lignin concentrations (**Table 2**). The variations in the C, N and P concentrations did not however, differ significantly (*P* > 0.05) among the leaf litter treatments (**Table 2**). The C concentration of cocoa leaves in the present study was lower than the reported data by Anglaaere [16]. This study found the N (1.74%) in leaf litter of cocoa to corroborate previous studies in other parts of Ghana [16, 69]. Anglaaere [16] reported N of 18.5 g/kg for cocoa leaves, whilst Dawoe [69] found an N range of 9.5 to 14.8 g/kg for cocoa leaves from 3 to 30 year old cocoa trees. It thus appears that foliar N concentration for cocoa is highly variable. With the N concentration of all the leaf litters being lower than the critical N level of 20 g/kg, net N

immobilization would be expected during decomposition [29, 62, 63].

Differences in total P concentration of the leaf litters from the WR were not significant (*P* > 0.05) and were all low when compared to the leaf litters from ER

Girisha et al. [64] put forward that nutrient retention during decomposition depends on their initial status in the litter. The C-element ratio has been commonly used to explain nutrient status where a nutrient element, *say* R, is said to be limiting when the C/R ratio is above a certain critical level set for microbial growth. In this case, nutrient element R will be retained resulting in immobilization but where C/R ratio is below the critical level, the nutrient element R is released during decomposition of the litter [65]. The C/N ratios were statistically similar in the leaf litter

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

ization to occur [62, 63].

treatments under ER (**Table 2**).

*3.1.2 Western region of Ghana*

#### *Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

the analyzed mixture of cocoa-shade leaf litter. The lower P and Mg concentrations in mixed cocoa-shade litter than expected or predicted is an indication of nonadditive response or negative interaction when cocoa and shade leaves are mixed together. The other nutrient elements, however, were similar in the mixed cocoashade and predicted mixed litters, indicating an additive response for those nutrient elements in mixed litter systems such as shaded or agroforestry systems (**Table 2**).

The initial N concentrations of all the leaf litters were higher than the critical level for cocoa foliage N concentration (9.0 g/kg), below which point net N immobilization would be expected [61]. Thus, with the high N concentration of the leaves, net N mineralization is highly possible during the leaf decomposition. Several researchers have considered the N and/or its ratios such as C/N, lignin/N and polyphenol/N of residues as major factors controlling decomposition processes [14, 34, 52]. The C/N and lignin/N ratios of the leaf litters from ER ranged from 19.4 to 25.2 and 11.7 to 21.8, respectively (**Table 2**). Thus, the C/N ratios of the litters are so close to the critical level of 25 noted for decomposition and N mineralization to occur [62, 63].

Where nutrient ratios are used as indices of nutrient status to microbial growth, Girisha et al. [64] put forward that nutrient retention during decomposition depends on their initial status in the litter. The C-element ratio has been commonly used to explain nutrient status where a nutrient element, *say* R, is said to be limiting when the C/R ratio is above a certain critical level set for microbial growth. In this case, nutrient element R will be retained resulting in immobilization but where C/R ratio is below the critical level, the nutrient element R is released during decomposition of the litter [65]. The C/N ratios were statistically similar in the leaf litter treatments under ER (**Table 2**).

**Table 2** revealed that the P, K and Mg concentrations of all the leaves from the ER were less than the critical range of 2.0 to 2.5 g/kg, 20 and 5 g/kg respectively. As such, P, K and Mg immobilization would be expected during decomposition [61, 66–68]. The Ca concentrations of the litters were higher than the critical 6 g/kg value. The lignin content of the leaf litters from the ER ranged from 220.0 to 289.1 g/kg dry matter (DM). The cocoa leaf litter had significantly (P < 0.05) lower lignin status when compared with the shade and the mixed cocoa-shade leaf litters, as well as the predicted mixture (**Table 2**). However, the lignin concentration (215.7 g/kg DM) in the cocoa leaf litter in this study is higher than the data (141–146 g/kg DM) of Dawoe [69] on cocoa leaf lignin status in Ghana. The lignin concentration in mixed cocoa-shade litter was similar to the predicted mixed litters (**Table 2**). Lignin has been considered a determinant of litter quality and a predictor of decomposition by previous researchers [34, 70, 71].

#### *3.1.2 Western region of Ghana*

The leaf litters from the Western region (WR) varied considerably in their initial nutrient and lignin concentrations (**Table 2**). The variations in the C, N and P concentrations did not however, differ significantly (*P* > 0.05) among the leaf litter treatments (**Table 2**). The C concentration of cocoa leaves in the present study was lower than the reported data by Anglaaere [16]. This study found the N (1.74%) in leaf litter of cocoa to corroborate previous studies in other parts of Ghana [16, 69]. Anglaaere [16] reported N of 18.5 g/kg for cocoa leaves, whilst Dawoe [69] found an N range of 9.5 to 14.8 g/kg for cocoa leaves from 3 to 30 year old cocoa trees. It thus appears that foliar N concentration for cocoa is highly variable. With the N concentration of all the leaf litters being lower than the critical N level of 20 g/kg, net N immobilization would be expected during decomposition [29, 62, 63].

Differences in total P concentration of the leaf litters from the WR were not significant (*P* > 0.05) and were all low when compared to the leaf litters from ER

*CO2 Sequestration*

and Rowell [27].

*Eastern region*

*Western region*

**3. Results and discussion**

*3.1.1 Eastern region of Ghana*

**3.1 Chemical characteristics of the leaf sample**

Literature is replete with the important role that litter chemistry plays in decomposition and nutrient release in top soils [14, 26, 51–53]. The initial concentrations of some elemental nutrients of the leaf litter samples are presented in **Table 2**. The leaf litter treatments did not differ significantly (*P* > 0.05) in their C and S concentrations in the Eastern region (ER). The leaf litters generally had low oxidizable carbon concentration by weight with less variability as indicated by the narrow range of 337.0–382.6 g/kg. The cocoa-shade mixture had the highest C and the leaf litter of shade tree contained the least (**Table 2**). Honeycutt et al. [54], Woomer et al. [55], and Kuo et al. [56] noted that plant residues have stable carbon concentration of about 40% by weight. Other studies have used a constant value from 450 to 500 g/kg as the C concentration for all parts of a tree biomass including the leaves [57–60]. Thus, the present C concentrations of the leaf litters from cocoa ecosystems in the ER of Ghana are lower than the commonly used ranges. The C concentration of 357.2 g/kg for the leaf litter of cocoa is lower than that reported by Anglaaere [16] as 413 g/kg for cocoa leaf samples from Atwima District in the same Eastern region of Ghana where the present study was carried out. However, the present litter C ranged confirmed the reported C data of 364 to 400 g/kg on similar cocoa leaf litter by Ofori-Frimpong

Among the nutrients that varied significantly between the leaf samples, that of the shade tree *Newbouldia laevis*, had significantly (*P* < 0.05) higher K, Ca and lignin but lower Mg concentration than the cocoa leaf litter (**Table 2**). The N, P and S concentrations in the leaf litters of the cocoa and shade trees did not differ significantly (*P* > 0.05). The predicted mixture contained higher P and Mg concentrations than

**Leaf litter C N P K Ca Mg S L C/N**

Cocoa 357.2a 18.4ab 1.13a 4.58c 12.9c 5.94a 1.89a 215.7c 19.4a Shade 337.0a 13.8b 1.07a 7.36a 16.3a 3.00d 1.89a 288.0a 25.2a Coc-shade 382.6a 19.5a 0.99b 5.61b 14.1b 4.12c 1.83a 256.9b 19.6a Predicted 347.1a 16.1b 1.10a 5.97b 14.6b 4.47b 1.89a 251.8b 22.3a

Cocoa 378.7a 17.4a 0.85a 8.57a 11.0a 5.25a 1.65b 220.0c 21.9a Shade 342.4a 15.2a 0.79a 4.43b 9.1b 2.67b 1.78a 289.1a 23.6a Coc-shade 360.2a 18.5a 0.85a 6.55c 10.0c 3.96c 1.72ab 265.4b 19.5a Predicted 360.6a 16.3a 0.82a 6.50b 10.0b 3.96b 1.72ab 254.5b 22.7a

*Different letters within same region and column indicate significant difference at* P *< 0.05 using Tukey's method.*

*Initial chemical composition and lignin (L) content (mean) and nutrient ratios of the leaf litters of cocoa,* 

Newbouldia laevis *in Eastern region,* Persea americana *in Western region.*

*shade (*Newbouldia laevis*,* Persea americana*)<sup>1</sup>*

*Western regions and the predicted mixed litter in Ghana.2*

**g/kg ratio**

 *and mixed cocoa-shade under cocoa ecosystems in eastern and* 

**72**

*1*

*2*

**Table 2.**

(**Table 2**). Anglaaere [16] also found the P to be low, at 1.3 g/kg in Ghanaian cocoa leaf, confirming the low P status of cocoa litters in Ghana found in the two regions by this study. Compared with critical levels of nutrient elements, the cocoa leaf litter in this study is deficient in P, K and Mg concentrations [61]. It is thus expected that during decomposition of the leaf litters from WR, as with ER, the deficient elements would not be released easily resulting in temporal nutrient immobilization [61, 66, 67].

The K, Ca and Mg concentrations in the leaf litter of the WR shade tree *P. americana* were significantly (*P* < 0.05) lower than those in the cocoa litter but higher in lignin concentration (**Table 2**). With respect to K and Mg, the leaf litter of the cocoa in the WR contained approximately twice as much as that in the shade tree litter. Compared with data on cocoa foliar nutrients in Anglaaere [16], the cocoa leaf nutrients from the WR appeared to be similar.

The initial chemical composition of the leaf litter of mixed cocoa-shade was generally similar to that of the predicted mixture treatment with the exception of P and Mg in the ER; and K, Ca and Mg in the WR, suggesting a high predictability of mixed litter nutrients from the single component species nutrient concentrations (**Table 2**). Overall, there were significant variations in the nutrient balance of the leaf litters and also high variability in nutrient ratios as shown in **Table 2**. These nutrient variations were more pronounced in the single litter treatments than the mixed and predicted mixed litters.

#### **3.2 Decomposition trends of the leaf samples**

**Figure 2a** presents the decomposition patterns of leaf litters of cocoa ecosystems in the ER obtained during a 120-day laboratory incubation experiment. During the first 20 days of incubation, the shade litter lost approximately 9% of its initial weight whereas the cocoa leaf litter lost only 2.8% of its weight, indicating a lag phase in the decomposition of the cocoa leaf litter (**Figure 2a**). Anglaaere [16] reported mass loss of 3.45% of cocoa leaf litter within the first one month of initial decomposition. However, the % leaf litter of cocoa and shade trees that remained did not differ significantly during the first 20 days of incubation. Thereafter, significant differences occurred in the per cent mass remaining between the leaf litters of cocoa and shade trees, with the leaf litter of the latter continuously decomposing at a higher rate than the former as incubation time progressed (**Figure 2a**). At the end of the 120 days of incubation, the leaf litter losses were 17.6 and 30.7% in the cocoa and shade litters, respectively. These litter loss percentages compared well with the reported losses between 16 and 33% of cocoa leaf litters within 80 days of incubation by Ofori-Frimpong and Rowell [27].

Overall, the decomposition pattern of the mixed cocoa-shade litter treatment indicated an additive response and thus, appeared predictable from the decomposition patterns of the component litters decomposing alone. Although the litter remains of the mixed cocoa-shade litter could not be separated into the individual components at any stage of the incubation, both the predicted and the actual mixed cocoa-shade litter treatments indicated higher (*P* < 0.05) decomposition rates than the pure cocoa leaf litter treatment (**Figure 2a**); this indicates that mixing leaf litter has the potential to enhance litter decomposition in the cocoa ecosystems in the ER.

The decomposition patterns of the leaf litter gathered from the cocoa farms in the WR is presented in **Figure 2b**. The decomposition pattern of the leaf litter of the shade species (*P. americana*) displayed a lag phase within the first 20 days of incubation where only about 3.6% had undergone decomposition (**Figure 2b**). The leaf litter of cocoa had significantly lower % remaining when compared with the

**75**

**Figure 2.**

*indicate standard error (n = 3).*

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

leaf litter decomposition pattern of the shade species as the incubation progressed. By the end of 120 days of incubation, the mass loss of cocoa was 29.1% of the initial weight whilst the shade litter decomposed by only 15.1% of its initial dry weight (**Figure 2b**). The mass loss of 29.1% for cocoa leaf litter from WR is greater than that (17.6%) from ER and, also, the reported mass loss of 22.35% by the 4th month

*Decomposition patterns of leaf litters in cocoa ecosystems: (a) Eastern region and (b) Western region. Bars* 

Comparison between the decomposition patterns of mixed cocoa-shade and the predicted mixed litter treatments showed no significant (*P* > 0.05) difference up to the first 20 days of incubation. Thereafter, there was a clear difference in the decomposition patterns between them for the next 100 days of incubation with the mixed cocoa-shade litter treatment decomposing at faster rates. As the time for decomposition progressed beyond 50 days, the cocoa-shade mixed litter decomposition pattern tended to behave like the pure cocoa leaf litter (**Figure 2b**). Thus, the mixed cocoa-shade treatment showed a non-additive response with positive interaction after 20 days of incubation and therefore, its decomposition is not predictable from the component species of the mixture. Over the 120-day incubation period, the amounts of leaf litter that decomposed were 26 and 20% for the mixed cocoashade litter and predicted mixed litter, respectively. The implication is that shaded

of incubation of cocoa leaf litter from the Ashanti region of Ghana [16].

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

#### **Figure 2.**

*CO2 Sequestration*

(**Table 2**). Anglaaere [16] also found the P to be low, at 1.3 g/kg in Ghanaian cocoa leaf, confirming the low P status of cocoa litters in Ghana found in the two regions by this study. Compared with critical levels of nutrient elements, the cocoa leaf litter in this study is deficient in P, K and Mg concentrations [61]. It is thus expected that during decomposition of the leaf litters from WR, as with ER, the deficient elements would not be released easily resulting in temporal nutrient immobilization [61, 66, 67]. The K, Ca and Mg concentrations in the leaf litter of the WR shade tree *P. americana* were significantly (*P* < 0.05) lower than those in the cocoa litter but higher in lignin concentration (**Table 2**). With respect to K and Mg, the leaf litter of the cocoa in the WR contained approximately twice as much as that in the shade tree litter. Compared with data on cocoa foliar nutrients in Anglaaere [16], the cocoa

The initial chemical composition of the leaf litter of mixed cocoa-shade was generally similar to that of the predicted mixture treatment with the exception of P and Mg in the ER; and K, Ca and Mg in the WR, suggesting a high predictability of mixed litter nutrients from the single component species nutrient concentrations (**Table 2**). Overall, there were significant variations in the nutrient balance of the leaf litters and also high variability in nutrient ratios as shown in **Table 2**. These nutrient variations were more pronounced in the single litter treatments than the

**Figure 2a** presents the decomposition patterns of leaf litters of cocoa ecosystems

Overall, the decomposition pattern of the mixed cocoa-shade litter treatment indicated an additive response and thus, appeared predictable from the decomposition patterns of the component litters decomposing alone. Although the litter remains of the mixed cocoa-shade litter could not be separated into the individual components at any stage of the incubation, both the predicted and the actual mixed cocoa-shade litter treatments indicated higher (*P* < 0.05) decomposition rates than the pure cocoa leaf litter treatment (**Figure 2a**); this indicates that mixing leaf litter has the potential to enhance litter decomposition in the cocoa

The decomposition patterns of the leaf litter gathered from the cocoa farms in the WR is presented in **Figure 2b**. The decomposition pattern of the leaf litter of the shade species (*P. americana*) displayed a lag phase within the first 20 days of incubation where only about 3.6% had undergone decomposition (**Figure 2b**). The leaf litter of cocoa had significantly lower % remaining when compared with the

in the ER obtained during a 120-day laboratory incubation experiment. During the first 20 days of incubation, the shade litter lost approximately 9% of its initial weight whereas the cocoa leaf litter lost only 2.8% of its weight, indicating a lag phase in the decomposition of the cocoa leaf litter (**Figure 2a**). Anglaaere [16] reported mass loss of 3.45% of cocoa leaf litter within the first one month of initial decomposition. However, the % leaf litter of cocoa and shade trees that remained did not differ significantly during the first 20 days of incubation. Thereafter, significant differences occurred in the per cent mass remaining between the leaf litters of cocoa and shade trees, with the leaf litter of the latter continuously decomposing at a higher rate than the former as incubation time progressed (**Figure 2a**). At the end of the 120 days of incubation, the leaf litter losses were 17.6 and 30.7% in the cocoa and shade litters, respectively. These litter loss percentages compared well with the reported losses between 16 and 33% of cocoa leaf litters within 80 days of

leaf nutrients from the WR appeared to be similar.

**3.2 Decomposition trends of the leaf samples**

incubation by Ofori-Frimpong and Rowell [27].

mixed and predicted mixed litters.

**74**

ecosystems in the ER.

*Decomposition patterns of leaf litters in cocoa ecosystems: (a) Eastern region and (b) Western region. Bars indicate standard error (n = 3).*

leaf litter decomposition pattern of the shade species as the incubation progressed. By the end of 120 days of incubation, the mass loss of cocoa was 29.1% of the initial weight whilst the shade litter decomposed by only 15.1% of its initial dry weight (**Figure 2b**). The mass loss of 29.1% for cocoa leaf litter from WR is greater than that (17.6%) from ER and, also, the reported mass loss of 22.35% by the 4th month of incubation of cocoa leaf litter from the Ashanti region of Ghana [16].

Comparison between the decomposition patterns of mixed cocoa-shade and the predicted mixed litter treatments showed no significant (*P* > 0.05) difference up to the first 20 days of incubation. Thereafter, there was a clear difference in the decomposition patterns between them for the next 100 days of incubation with the mixed cocoa-shade litter treatment decomposing at faster rates. As the time for decomposition progressed beyond 50 days, the cocoa-shade mixed litter decomposition pattern tended to behave like the pure cocoa leaf litter (**Figure 2b**). Thus, the mixed cocoa-shade treatment showed a non-additive response with positive interaction after 20 days of incubation and therefore, its decomposition is not predictable from the component species of the mixture. Over the 120-day incubation period, the amounts of leaf litter that decomposed were 26 and 20% for the mixed cocoashade litter and predicted mixed litter, respectively. The implication is that shaded

cocoa system in the WR would be more efficient in nutrient cycling than expected. However, decomposition of cocoa leaf litter alone (unshaded system) was similar to that of mixed cocoa-shade litter (shaded systems).

#### *3.2.1 Decay constant*

The leaf decomposition patterns shown in **Figure 2a** and **b**, conformed well (*R*<sup>2</sup> = 0.81–0.99) to the single exponential decay model proposed by Olson [50] for similar mass loss studies. However, the plots of the model were observed not to go through 100% weight remaining at the start (i.e., day zero) of the incubation, indicating some degree of deficiency associated with the model [2]. Notwithstanding, the same model has been used by other researchers in recent times to fit similar litter decomposition data [46, 72–74]. From the fitted model for the % leaf litter remaining, the decomposition rate constants (*k*d) of the leaf litter treatments were estimated for a period of 120 days of decomposition and are presented in **Table 3**. The *k*d measures the proportion of the material that decays per unit time. Therefore, the lower the *k*d of a decomposing organic material, the slower it decomposes.

In the Eastern region (ER), the decomposition rate constants varied considerably and ranged from 1.65 × 10−3/day for the leaf litter of cocoa to 2.72 × 10−3/day for leaf litter of shade tree (**Table 3**). The *k*d for the mixed cocoa-shade and predicted mixture treatments were intermediate between that of the cocoa and the shade, in support of their decomposition patterns described earlier (**Figure 2a**). The leaf litter of the shade species had a much higher (*P* < 0.05) decay rate constant than the cocoa leaf litter treatment. Anim-Kwapong and Osei-Bonsu [75] found a similar high *k*d value of 2.51 × 10−3/day (recalculated from authors' half-life value of 9.22 for *N. laevis*) for *N. laevis* also collected from the same ER of Ghana. In respect of the decomposition rate of cocoa leaf litter in the present study, comparable leaf litter decay rates have been reported by Owusu-Sekyere et al. [76] and for some forest tree species [77]. The decomposition rate of the predicted mixed leaves and the actual mixed cocoa-shade treatments (2.14 × 10−3/day) were exactly the same; this agrees with the earlier assertion of additive response for mixed leaf decomposition


*1* Newbouldia laevis *in Eastern region,* Persea americana *in Western region. 2*

*Different letters within same region and column indicate significant difference at* P *< 0.05 using Tukey's method.*

#### **Table 3.**

*Decomposition constants and potential mineralizable C (% of initial oxidizable C) of cocoa, shade (*Newbouldia laevis*,* Persea americana*)1 , mixed cocoa-shade and predicted cocoa-shade mixture under cocoa ecosystems in eastern and Western regions of Ghana.*

**77**

*\**

**Table 4.**

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

values, the order of the leaf litter decomposition in the ER followed: Shade > mixed cocoa-shade = predicted mixed litter > cocoa.

the forest species exhibited a significantly higher decay rate.

simulating the litter state of shaded cocoa ecosystems in the ER. Based on the *k*<sup>d</sup>

The higher rate of decomposition in mixed leaves of cocoa-shade than pure leaves of cocoa suggests that nutrient cycling in cocoa ecosystems of the ER would be favored by shaded cocoa ecosystems. Owusu-Sekyere et al. [76] attributed the slow decomposition rate constant of cocoa to high lignin and polyphenol concentrations in the cocoa leaves. However, in their case the data showed no significant difference between leaves of forest species and cocoa with respect to C/N ratios, yet

Indeed, several works on litter decomposition have reported significant correlation between initial chemical composition of decomposing materials and the decay constants. Some of the litter constituents that have indicated significant correlations with *k*d in previous studies included the initial C, N, P, Ca concentrations, lignin, polyphenols and ratios of C/N, lignin/N and polyphenol/N of decomposing organic materials [10–14, 32, 76]. In contrast, the *k*d values estimated for the leaf litters from ER did not show significant correlations with C, N, P, S and C/N (**Table 4**). Rather, the *k*d values correlated positively (*P* < 0.05) with K, Ca, and negatively (*P* < 0.05) with Mg (**Table 4**). The cations; K, Ca and Mg are known to activate enzymes that promote metabolism [78] implicating their role to driving litter decomposition. Similar correlations between decomposition rates and initial concentrations of K, Ca, and Mg have previously been observed by Briones and Ineson [31]. The lack of correlations between *k*d values and N concentration or C/N ratios could partly be due to the narrow ranges of the C and N concentrations of the leaf litters under study and/or partly indicates the insensitivity of the *k*d to assess the decomposability of the litters [79–82]. The current study agreed with McTiernan et al. [83] who found a significant correlation between *k*d and Ca, and none for *k*d and N concentration for a mixture of tree leaf litter during decomposition. Elsewhere, others also found C/P ratios to correlate

In the Western region (WR), decomposition rate constants of leaf litters under cocoa ecosystems ranged from 0.00127 to 0.00259/day (**Table 3**). The estimated *k*<sup>d</sup> values for cocoa systems are higher than the *k*d values ranging from 0.221 to 0.227/y (i.e., 0.00060 to 0.00062/day) in Dawoe [69] for cocoa systems in the Ashanti

**Element Eastern region Western region** C 0.359 0.362 N −0.549 0.301 P −0.390 0.799\*\* K 0.766\*\* 0.726\*\* Ca 0.726\*\* 0.689\* Mg −0.763\*\* 0.715\* S −0.392 −0.496 L 0.766\*\* −0.591\* C/N 0.664\* −0.195

*Correlation coefficients (*r*) between initial chemical composition and lignin (L) of leaf litter and decay* 

*constant (*kd*) from cocoa ecosystems in the Eastern and Western regions of Ghana.*

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

with litter decomposition [84].

*Correlation is significant at the 0.05 level (2-tailed). \*\*Correlation is significant at the 0.01 level (2-tailed).*

#### *Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

simulating the litter state of shaded cocoa ecosystems in the ER. Based on the *k*<sup>d</sup> values, the order of the leaf litter decomposition in the ER followed:

Shade > mixed cocoa-shade = predicted mixed litter > cocoa.

The higher rate of decomposition in mixed leaves of cocoa-shade than pure leaves of cocoa suggests that nutrient cycling in cocoa ecosystems of the ER would be favored by shaded cocoa ecosystems. Owusu-Sekyere et al. [76] attributed the slow decomposition rate constant of cocoa to high lignin and polyphenol concentrations in the cocoa leaves. However, in their case the data showed no significant difference between leaves of forest species and cocoa with respect to C/N ratios, yet the forest species exhibited a significantly higher decay rate.

Indeed, several works on litter decomposition have reported significant correlation between initial chemical composition of decomposing materials and the decay constants. Some of the litter constituents that have indicated significant correlations with *k*d in previous studies included the initial C, N, P, Ca concentrations, lignin, polyphenols and ratios of C/N, lignin/N and polyphenol/N of decomposing organic materials [10–14, 32, 76]. In contrast, the *k*d values estimated for the leaf litters from ER did not show significant correlations with C, N, P, S and C/N (**Table 4**). Rather, the *k*d values correlated positively (*P* < 0.05) with K, Ca, and negatively (*P* < 0.05) with Mg (**Table 4**). The cations; K, Ca and Mg are known to activate enzymes that promote metabolism [78] implicating their role to driving litter decomposition. Similar correlations between decomposition rates and initial concentrations of K, Ca, and Mg have previously been observed by Briones and Ineson [31]. The lack of correlations between *k*d values and N concentration or C/N ratios could partly be due to the narrow ranges of the C and N concentrations of the leaf litters under study and/or partly indicates the insensitivity of the *k*d to assess the decomposability of the litters [79–82]. The current study agreed with McTiernan et al. [83] who found a significant correlation between *k*d and Ca, and none for *k*d and N concentration for a mixture of tree leaf litter during decomposition. Elsewhere, others also found C/P ratios to correlate with litter decomposition [84].

In the Western region (WR), decomposition rate constants of leaf litters under cocoa ecosystems ranged from 0.00127 to 0.00259/day (**Table 3**). The estimated *k*<sup>d</sup> values for cocoa systems are higher than the *k*d values ranging from 0.221 to 0.227/y (i.e., 0.00060 to 0.00062/day) in Dawoe [69] for cocoa systems in the Ashanti


#### **Table 4.**

*Correlation coefficients (*r*) between initial chemical composition and lignin (L) of leaf litter and decay constant (*kd*) from cocoa ecosystems in the Eastern and Western regions of Ghana.*

*CO2 Sequestration*

*3.2.1 Decay constant*

*Eastern region*

*Western region*

*(*Newbouldia laevis*,* Persea americana*)1*

*ecosystems in eastern and Western regions of Ghana.*

(*R*<sup>2</sup>

cocoa system in the WR would be more efficient in nutrient cycling than expected. However, decomposition of cocoa leaf litter alone (unshaded system) was similar to

The leaf decomposition patterns shown in **Figure 2a** and **b**, conformed well

 = 0.81–0.99) to the single exponential decay model proposed by Olson [50] for similar mass loss studies. However, the plots of the model were observed not to go through 100% weight remaining at the start (i.e., day zero) of the incubation, indicating some degree of deficiency associated with the model [2]. Notwithstanding, the same model has been used by other researchers in recent times to fit similar litter decomposition data [46, 72–74]. From the fitted model for the % leaf litter remaining, the decomposition rate constants (*k*d) of the leaf litter treatments were estimated for a period of 120 days of decomposition and are presented in **Table 3**. The *k*d measures the proportion of the material that decays per unit time. Therefore, the lower the *k*d of a decomposing organic material, the slower it decomposes. In the Eastern region (ER), the decomposition rate constants varied considerably and ranged from 1.65 × 10−3/day for the leaf litter of cocoa to 2.72 × 10−3/day for leaf litter of shade tree (**Table 3**). The *k*d for the mixed cocoa-shade and predicted mixture treatments were intermediate between that of the cocoa and the shade, in support of their decomposition patterns described earlier (**Figure 2a**). The leaf litter of the shade species had a much higher (*P* < 0.05) decay rate constant than the cocoa leaf litter treatment. Anim-Kwapong and Osei-Bonsu [75] found a similar high *k*d value of 2.51 × 10−3/day (recalculated from authors' half-life value of 9.22 for *N. laevis*) for *N. laevis* also collected from the same ER of Ghana. In respect of the decomposition rate of cocoa leaf litter in the present study, comparable leaf litter decay rates have been reported by Owusu-Sekyere et al. [76] and for some forest tree species [77]. The decomposition rate of the predicted mixed leaves and the actual mixed cocoa-shade treatments (2.14 × 10−3/day) were exactly the same; this agrees with the earlier assertion of additive response for mixed leaf decomposition

**Leaf litter treatment Decomposition constant,** *k***d/day Potential C mineralizable,** *C***o g/kg**

Cocoa litter 0.00165b2 107.7b Shade litter 0.00272a 114.8ab Mixed cocoa-shade 0.00214ab 118.5a Predicted mixed litter 0.00214ab 111.2ab

Cocoa litter 0.00240a 119.9b Shade litter 0.00127b 61.10d Mixed cocoa-shade 0.00259a 209.7a Predicted mixed litter 0.00187ab 90.40c

*Different letters within same region and column indicate significant difference at* P *< 0.05 using Tukey's method.*

*, mixed cocoa-shade and predicted cocoa-shade mixture under cocoa* 

*Decomposition constants and potential mineralizable C (% of initial oxidizable C) of cocoa, shade* 

Newbouldia laevis *in Eastern region,* Persea americana *in Western region.*

that of mixed cocoa-shade litter (shaded systems).

**76**

*1*

*2*

**Table 3.**

region of Ghana. The author used data on monthly litter fall to estimate the *k*<sup>d</sup> values using the annual litter-fall over litter-stock formulae, which has a greater source of variability due to seasonal effects on monthly litter-fall. Depending on the season, particularly during wet seasons, less litter fall may be recorded leading to lower estimates for *k*d values. Anglaaere [16] reported much lower litter-fall biomass from April to November which coincided with the wet season period in the cocoa cultivation regions of Ghana.

The decomposition of the cocoa leaf treatment was significantly faster than that of the shade species (**Table 3**). The difference in the decomposition rates of leaves from cocoa and the shade species is attributable to the differences in the biochemical composition of their leaf structures as similar attributions have been made by many workers to explain variations in decomposing organic materials [28, 64, 81, 82]. Indeed, the present study found significant (*P* < 0.05) positive correlations between *k*d values and K, Ca, and Mg but negative correlations with C and S (**Table 4**). Briones and Ineson [31] also reported significant correlations between *k*d and K, Ca, and Mg in decomposition of eucalyptus, ash and birch individually, and as litter mixtures during decomposition. Of the initial concentrations of chemical parameters, the cocoa leaf litter was significantly higher in all the positively correlated parameters and lower in all the negatively correlated parameters than the leaf litter of the shade tree, hence the higher estimate of its decomposition rate constant (**Table 3**).

The decomposition rate appeared faster in leaf litter treatments of mixed cocoashade than the predicted mixture from the single decomposition rates of the components, but the difference was not significant (*P* > 0.05, **Table 3**). The observed faster rate of decomposition in the mixed cocoa-shade is an indication of a possible synergistic effect under shaded cocoa systems in the WR during litter decomposition. Compared with the single plant species leaf litter decomposition rate constant, the mixed leaf litter decomposed at a rate similar to leaf litter of pure cocoa, both of which were faster (*P* < 0.05) than the pure leaf litter of the shade tree. The significance of the above finding is that, litter decomposition and nutrient release patterns would not differ between shaded cocoa and unshaded cocoa ecosystems in the WR but will be lower in a forest of only *P. americana* trees.

#### *3.2.2 Carbon release patterns*

The carbon and nutrient contents of the residual litters were determined as the product of their concentration and the litter dry mass; this allowed C and nutrient release to be plotted as a percentage of the initial C and nutrient contents of the litters. Similar plots have been provided by other researchers [48, 49]. **Figure 3** presents the C release patterns for the various litters during the course of decomposition. Leaf litters from the ER all released C in the course of the decomposition. The C release patterns were similar and linear except in the mixed cocoa-shade where the pattern was curvilinear with an initial faster C release within the first 20 days, then a gentle release between 20 to 80 days, and a slow release followed thereafter to 120 days (**Figure 3**ER: (C)). However, the amount of carbon released among the litters did not differ significantly (*F*12, 40 = 0.64, *P* = 0.797) during the decomposition. Released C during litter decomposition has been attributed to losses of soluble C and mineralization [65]. After 120 days of incubation, the C released from litters of ER varied between 23.3 and 26.8% of the initial litter C contents.

With regard to decomposition of litter from WR, the C release patterns showed significant (*F*12, 40 = 3.67, *P* < 0.001) differences among the decomposed litters during the course of the incubation. The C released from mixed cocoa-shade was the slowest and the cocoa litter released the greatest amount of C during the decomposition process (**Figure 3**WR: (C)). However, the % C released from the cocoa

**79**

**Figure 3.**

*at various stages.*

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

litters were not significantly (*P* > 0.05) different from those of shade and predicted mixture. The % carbon emitted after the 120 days of incubation varied from 11.5% in the mixed cocoa-shade litter to 27.4% in cocoa leaf litters. The implication of the slower C releasing rate of mixed litter than the expected is that, nutrient cycling through decomposition under shaded cocoa system would lead to nutrient limita-

*Carbon released patterns (% of initial C) during a 120-day decomposition of leaf litters from cocoa ecosystems* 

Decomposition processes in agro-ecosystems have been implicated as enriching the atmosphere with carbon dioxide (CO2). During leaf litter decomposition, the decomposing litter is accompanied with losses of carbon. Although the amount of litter decomposed would be expected to be proportional to the C loss, considerable variations do occur due to different biochemical composition of different plant species [83]. There have not been many studies to monitor the fate of the C loss through the decomposed litter. This requires a method that will capture the C released as litter undergoes decomposition. If C loss data from such a method tends to be comparable to those from the litterbag technique, then the problem of having

tion and, most likely, could cause nutrient deficiency for growing crops.

**3.3 Carbon emission patterns during leaf decomposition**

to retrieve decomposing litter is overcome.

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

#### **Figure 3.**

*CO2 Sequestration*

cocoa cultivation regions of Ghana.

region of Ghana. The author used data on monthly litter fall to estimate the *k*<sup>d</sup> values using the annual litter-fall over litter-stock formulae, which has a greater source of variability due to seasonal effects on monthly litter-fall. Depending on the season, particularly during wet seasons, less litter fall may be recorded leading to lower estimates for *k*d values. Anglaaere [16] reported much lower litter-fall biomass from April to November which coincided with the wet season period in the

The decomposition of the cocoa leaf treatment was significantly faster than that of the shade species (**Table 3**). The difference in the decomposition rates of leaves from cocoa and the shade species is attributable to the differences in the biochemical composition of their leaf structures as similar attributions have been made by many workers to explain variations in decomposing organic materials [28, 64, 81, 82]. Indeed, the present study found significant (*P* < 0.05) positive correlations between *k*d values and K, Ca, and Mg but negative correlations with C and S (**Table 4**). Briones and Ineson [31] also reported significant correlations between *k*d and K, Ca, and Mg in decomposition of eucalyptus, ash and birch individually, and as litter mixtures during decomposition. Of the initial concentrations of chemical parameters, the cocoa leaf litter was significantly higher in all the positively correlated parameters and lower in all the negatively correlated parameters than the leaf litter of the shade tree,

The decomposition rate appeared faster in leaf litter treatments of mixed cocoashade than the predicted mixture from the single decomposition rates of the components, but the difference was not significant (*P* > 0.05, **Table 3**). The observed faster rate of decomposition in the mixed cocoa-shade is an indication of a possible synergistic effect under shaded cocoa systems in the WR during litter decomposition. Compared with the single plant species leaf litter decomposition rate constant, the mixed leaf litter decomposed at a rate similar to leaf litter of pure cocoa, both of which were faster (*P* < 0.05) than the pure leaf litter of the shade tree. The significance of the above finding is that, litter decomposition and nutrient release patterns would not differ between shaded cocoa and unshaded cocoa ecosystems in the WR

The carbon and nutrient contents of the residual litters were determined as the product of their concentration and the litter dry mass; this allowed C and nutrient release to be plotted as a percentage of the initial C and nutrient contents of the litters. Similar plots have been provided by other researchers [48, 49]. **Figure 3** presents the C release patterns for the various litters during the course of decomposition. Leaf litters from the ER all released C in the course of the decomposition. The C release patterns were similar and linear except in the mixed cocoa-shade where the pattern was curvilinear with an initial faster C release within the first 20 days, then a gentle release between 20 to 80 days, and a slow release followed thereafter to 120 days (**Figure 3**ER: (C)). However, the amount of carbon released among the litters did not differ significantly (*F*12, 40 = 0.64, *P* = 0.797) during the decomposition. Released C during litter decomposition has been attributed to losses of soluble C and mineralization [65]. After 120 days of incubation, the C released from litters of ER varied between 23.3 and 26.8% of the initial litter C contents. With regard to decomposition of litter from WR, the C release patterns showed significant (*F*12, 40 = 3.67, *P* < 0.001) differences among the decomposed litters during the course of the incubation. The C released from mixed cocoa-shade was the slowest and the cocoa litter released the greatest amount of C during the decomposition process (**Figure 3**WR: (C)). However, the % C released from the cocoa

hence the higher estimate of its decomposition rate constant (**Table 3**).

but will be lower in a forest of only *P. americana* trees.

*3.2.2 Carbon release patterns*

**78**

*Carbon released patterns (% of initial C) during a 120-day decomposition of leaf litters from cocoa ecosystems at various stages.*

litters were not significantly (*P* > 0.05) different from those of shade and predicted mixture. The % carbon emitted after the 120 days of incubation varied from 11.5% in the mixed cocoa-shade litter to 27.4% in cocoa leaf litters. The implication of the slower C releasing rate of mixed litter than the expected is that, nutrient cycling through decomposition under shaded cocoa system would lead to nutrient limitation and, most likely, could cause nutrient deficiency for growing crops.

#### **3.3 Carbon emission patterns during leaf decomposition**

Decomposition processes in agro-ecosystems have been implicated as enriching the atmosphere with carbon dioxide (CO2). During leaf litter decomposition, the decomposing litter is accompanied with losses of carbon. Although the amount of litter decomposed would be expected to be proportional to the C loss, considerable variations do occur due to different biochemical composition of different plant species [83]. There have not been many studies to monitor the fate of the C loss through the decomposed litter. This requires a method that will capture the C released as litter undergoes decomposition. If C loss data from such a method tends to be comparable to those from the litterbag technique, then the problem of having to retrieve decomposing litter is overcome.

#### **Figure 4.**

*Carbon mineralization patterns of leaf litters in cocoa ecosystems: (a) Eastern region and (b) Western region. Bars indicate standard error (n = 3).*

As a response to the above concern, **Figure 4a** and **b** present the patterns and cumulative amounts of CO2-C emissions measured during the decomposition of leaf litters collected under cocoa ecosystems of ER and WR of Ghana. The patterns of C emitted from the decomposing leaf litter were somewhat similar. Overall, C emissions increased rapidly during the first 16 days followed by a relatively slow rate as time progressed (**Figure 4a** and **b**). Previous works have also shown double-phase patterns for CO2-C emissions during soil organic carbon mineralization [82, 85–88]. Even though the C emission patterns were similar, the litter treatments differed significantly (*P* < 0.05) in the amounts of C released at all times during the incubation.

Among the litter treatments from the ER, the mixed cocoa-shade consistently released significantly more C than the other treatments which did not differ in their C emissions (**Figure 4a**). Thus, whilst there was no difference between the pure cocoa and shade treatments, the C emission of their mixture was higher than expected and could not be predicted from the separate litter treatments as indicated by the significantly (*P* < 0.05) lower C emission pattern of the predicted mixture. At 130 days of incubation, the amounts of C emitted from the litter treatments ranged from 106.0 to 119.2 g/kg for cocoa and mixed cocoa-shade treatments, respectively (**Figure 4a**). The higher C mineralization in mixed cocoa-shade appeared to be the effect of P which is the only nutrient element that differed between the mixed cocoa-shade and the other samples from ER (**Table 2**).

**81**

biochemical quality.

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

25 below which mineralization would be expected [62, 63].

*3.3.1 Potential mineralizable C for 130 days incubation*

Leaf treatments from the WR exhibited similar C release patterns as earlier stated; each showing a double phase comprising of an initial rapid rate and a subsequent decreasing rate as the incubation advanced (**Figure 4b**). However, in the case of the litter treatments from WR, the cocoa leaf treatment emitted significantly (*P* < 0.05) more C than the other treatments until 43 days of incubation when there was no longer significant difference from the C emissions of mixed cocoa-shade treatment (**Figure 4b**). The lowest C emission pattern was observed from the treatment with shade leaf litter. The C emission patterns of the mixed cocoa-shade and predicted mixture treatments exhibited fluctuations such that higher C emission was estimated by the predicted mixture from 5 to 16 days. The C emitted from both did not differ between 28 and 75 days, and thereafter, the C emissions of the mixed cocoa-shade treatment exceeded the predicted emissions towards the end of the

At 130 days, the range of C emitted from the treatment with leaf litters from WR was 64.3 to 135.8 g/kg for the shade and mixed cocoa-shade treated litters. Previous works on soil carbon mineralization reported that the initial biochemical composition plays a major role in driving the process and C/N ratio of decomposing organic material is said to be a good indicator of its mineralization potential [89]. However, the findings herein are unable to confirm or deny the importance of C/N ratio since the litters did not differ significantly and were all less than the critical C/N ratio of

The potential mineralizable C pools from the leaf litters at the end of 130 days of incubation were estimated by fitting the C emission patterns (**Figure 4**) to a single exponential rise-to-maximum (growth) model (Eq. (6)). The same model has been used previously on similar data by others [82, 87, 90]. The data on emitted C con-

estimates of potential mineralizable C and the mineralization rate constants of the

There were considerable variations in the estimated mineralizable C among the leaf litter obtained from the WR (**Table 3**). The results indicated a wider range of mineralizable C pools of 61.10–209.70 g/kg respectively for the shade and mixed cocoa-shade litter treatments. The estimated potential mineralizable C range for the WR litters represented a potential C loss range of 13.4–49.6% of the

The potential mineralizable C (*C*o) estimated for the litters from ER during the 130-day incubation had a narrow range of 107.7–118.5 g/kg for cocoa and mixed cocoa-shade treatments, respectively (**Table 3**). The estimated potential mineralizable C represents approximately 26.4–29.6% of the oxidizable C in leaf litters of cocoa and mixed cocoa-shade, respectively. This indicates that the leaf litters had close potential for releasing similar amounts of C. However, these estimated mineralizable carbon values differed significantly (*F*3, 4 = 11.50, *P* = 0.020) according to the litter treatments. The differences in amount of estimated mineralizable C appear to reflect the quality of the oxidizable carbon source. Indeed, a correlation analysis indicated the presence of significant relationships between the estimated mineralizable C of leaf litters from ER and some initial chemical properties of the litter treatment as follows: N (*r* = 0.713, *P* = 0.047), P (*r* = −0.784, *P* = 0.021), and C/N (*r* = −0.883, *P* = 0.004). However, other researchers found high mineralizable C from decomposing *Mucuna* litter and attributed this to its low lignin content rather than its C/N ratio [85, 87]. This means that the amount of potential mineralizable C from decomposing organic material is partly controlled by its

= 98.0–99.9) and the estimated parameters provided

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

observation (**Figure 4b**).

formed well to the model (*R*<sup>2</sup>

litter treatments as presented in **Table 3**.

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

Leaf treatments from the WR exhibited similar C release patterns as earlier stated; each showing a double phase comprising of an initial rapid rate and a subsequent decreasing rate as the incubation advanced (**Figure 4b**). However, in the case of the litter treatments from WR, the cocoa leaf treatment emitted significantly (*P* < 0.05) more C than the other treatments until 43 days of incubation when there was no longer significant difference from the C emissions of mixed cocoa-shade treatment (**Figure 4b**). The lowest C emission pattern was observed from the treatment with shade leaf litter. The C emission patterns of the mixed cocoa-shade and predicted mixture treatments exhibited fluctuations such that higher C emission was estimated by the predicted mixture from 5 to 16 days. The C emitted from both did not differ between 28 and 75 days, and thereafter, the C emissions of the mixed cocoa-shade treatment exceeded the predicted emissions towards the end of the observation (**Figure 4b**).

At 130 days, the range of C emitted from the treatment with leaf litters from WR was 64.3 to 135.8 g/kg for the shade and mixed cocoa-shade treated litters. Previous works on soil carbon mineralization reported that the initial biochemical composition plays a major role in driving the process and C/N ratio of decomposing organic material is said to be a good indicator of its mineralization potential [89]. However, the findings herein are unable to confirm or deny the importance of C/N ratio since the litters did not differ significantly and were all less than the critical C/N ratio of 25 below which mineralization would be expected [62, 63].

#### *3.3.1 Potential mineralizable C for 130 days incubation*

The potential mineralizable C pools from the leaf litters at the end of 130 days of incubation were estimated by fitting the C emission patterns (**Figure 4**) to a single exponential rise-to-maximum (growth) model (Eq. (6)). The same model has been used previously on similar data by others [82, 87, 90]. The data on emitted C conformed well to the model (*R*<sup>2</sup> = 98.0–99.9) and the estimated parameters provided estimates of potential mineralizable C and the mineralization rate constants of the litter treatments as presented in **Table 3**.

The potential mineralizable C (*C*o) estimated for the litters from ER during the 130-day incubation had a narrow range of 107.7–118.5 g/kg for cocoa and mixed cocoa-shade treatments, respectively (**Table 3**). The estimated potential mineralizable C represents approximately 26.4–29.6% of the oxidizable C in leaf litters of cocoa and mixed cocoa-shade, respectively. This indicates that the leaf litters had close potential for releasing similar amounts of C. However, these estimated mineralizable carbon values differed significantly (*F*3, 4 = 11.50, *P* = 0.020) according to the litter treatments. The differences in amount of estimated mineralizable C appear to reflect the quality of the oxidizable carbon source. Indeed, a correlation analysis indicated the presence of significant relationships between the estimated mineralizable C of leaf litters from ER and some initial chemical properties of the litter treatment as follows: N (*r* = 0.713, *P* = 0.047), P (*r* = −0.784, *P* = 0.021), and C/N (*r* = −0.883, *P* = 0.004). However, other researchers found high mineralizable C from decomposing *Mucuna* litter and attributed this to its low lignin content rather than its C/N ratio [85, 87]. This means that the amount of potential mineralizable C from decomposing organic material is partly controlled by its biochemical quality.

There were considerable variations in the estimated mineralizable C among the leaf litter obtained from the WR (**Table 3**). The results indicated a wider range of mineralizable C pools of 61.10–209.70 g/kg respectively for the shade and mixed cocoa-shade litter treatments. The estimated potential mineralizable C range for the WR litters represented a potential C loss range of 13.4–49.6% of the

*CO2 Sequestration*

**80**

**Figure 4.**

*Bars indicate standard error (n = 3).*

As a response to the above concern, **Figure 4a** and **b** present the patterns and cumulative amounts of CO2-C emissions measured during the decomposition of leaf litters collected under cocoa ecosystems of ER and WR of Ghana. The patterns of C emitted from the decomposing leaf litter were somewhat similar. Overall, C emissions increased rapidly during the first 16 days followed by a relatively slow rate as time progressed (**Figure 4a** and **b**). Previous works have also shown double-phase patterns for CO2-C emissions during soil organic carbon mineralization [82, 85–88]. Even though the C emission patterns were similar, the litter treatments differed significantly (*P* < 0.05) in the amounts of C released at all times during the incubation. Among the litter treatments from the ER, the mixed cocoa-shade consistently released significantly more C than the other treatments which did not differ in their C emissions (**Figure 4a**). Thus, whilst there was no difference between the pure cocoa and shade treatments, the C emission of their mixture was higher than expected and could not be predicted from the separate litter treatments as indicated by the significantly (*P* < 0.05) lower C emission pattern of the predicted mixture. At 130 days of incubation, the amounts of C emitted from the litter treatments ranged from 106.0 to 119.2 g/kg for cocoa and mixed cocoa-shade treatments, respectively (**Figure 4a**). The higher C mineralization in mixed cocoa-shade appeared to be the effect of P which is the only nutrient element that differed between the mixed cocoa-shade and the other samples from ER (**Table 2**).

*Carbon mineralization patterns of leaf litters in cocoa ecosystems: (a) Eastern region and (b) Western region.* 

initial oxidizable C content of the litters within 130 days of incubation. The present estimate for C loss relative to the period is much higher when compared with Saffigna et al. [91] who reported a decline in mineralizable C by 29% when sorghum residues were removed for 6 years from a hitherto amended soil. However the lower C loss associated with sorghum residue partly reflects its lower oxidizable carbon content relative to cocoa litter. The cocoa litter contained approximately twice as much mineralizable C as contained in the shade litter, but the mixed cocoa-shade contained more than twice as much potential mineralizable C as expected by the predicted mixture capacity (**Table 3**).

There were no significant correlations between the estimated mineralizable C pools from the WR leaf litter treatments and the biochemical composition of the decomposing litter although there were indications of moderate relationship with each one of the following: C (*r* = −0.672, *P* = 0.068), N (*r* = −0.564, *P* = 0.145), and P (*r* = 0.530, *P* = 0.176). It thus confirms that the amount of potential mineralizable C estimated from the litter incubation partly reflected the initial chemical composition and the amount of oxidizable C in the decomposing litter.

#### **3.4 Comparison of C from leaf weight loss and CO2-C evolution methods**

Although leaf decomposition is generally measured by weight loss, it is also measured by carbon dioxide release in numerous studies [24, 25]. These methods have several sources of variations as mentioned in the introductory section that potentially could confound the results and cause deviations from litter decomposition under natural vegetation types. Comparison of methods is an option through which interference from the methods with the results can be isolated.

**Table 5** presents the measured amounts of C released from cocoa systems in ER and WR during leaf litter decomposition averaged over the incubation period (120 days) by the weight loss and carbon dioxide evolution methods. Under the cocoa systems in the Eastern region, the C released measured by the CO2 evolution method was significantly higher than measured by the weight loss method in cocoa leaf (*F*1, 3 = 38.1, *P* = 0.009), mixed litter (*F*1, 3 = 23.5, *P* = 0.017) and predicted mixed litter (*F*1, 3 = 18.4, *P* = 0.023) decomposition but their difference was not significant (*F*1, 3 = 0.07, *P* = 0.810) with respect to shade tree leaf decomposition (**Table 5**). These higher amounts of C from the released CO2 measurements are usually unexpected under natural unconfined environments since the release of CO2


#### **Table 5.**

*Cumulative C released (g/kg) over 120 days during litter decomposition under cocoa systems in Eastern and Western regions as measured by the weight loss and CO2-C evolution methods.1*

**83**

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

during litter decomposition is but one of several ways including fragmentation and organic matter leaching that contributes to the weight loss of buried litter [24, 25]. However, the confinement of the current experiment as described earlier meant that weight losses through fragmentation and leaching of organic matter were disallowed. Therefore, the litter weight loss solely depended on the release amounts of CO2-C during the period. Thus, the expected weight loss from decomposing litters must at most, be equivalent to the amounts of CO2 released in the absence of leaching of other organic material. The many steps such as initial total C determination of the decomposing litter, weighing litter remains that have not been dried well or have attached soil particles to determine weight loss and the use of larger time intervals are all sources of variations associated with the determination of C release by the weight loss method. These steps have the potential of being over estimated and might explain the lower amounts C losses by the weight loss method when compared to the CO2-C evolution method. On the other hand, the short time intervals of the CO2-C evolution methods with regard to the frequent replacement of the adsorbent creates room for atmospheric CO2-C to interfere with the decomposition and consequently leads to over estimation of release C from the litter decomposition alone. Apparently, the above sources of deviations associated with the two methods were minimal under the litter treatments of WR cocoa systems. Hence, the expectation of equality between litter weight loss C and CO2-C released was confirmed in all but the shade tree leaf litter decomposition. Differences between released C estimated from litter weight loss and CO2-C evolution measurement methods were not statistically significant under decomposing cocoa litter (*F*1, 3 = 3.9, *P* = 0.143), mixed litter (*F*1, 3 = 0.008, *P* = 0.933) and predicted litter (*F*1, 3 = 0.008, *P* = 0.934) in the WR (**Table 5**). In contrast, the shade tree leaf litter decomposition from WR released significantly (*F*1, 3 = 11.5, *P* = 0.043) different amounts of C, where the measured C by CO2-C evolved was higher than that in loss litter (**Table 5**).

Although the measured differences varied between regions, regression analysis of pooled data from the two regions indicated the existence of a strong relationship between weight loss of litter C and the CO2-C evolution during litter decomposition (**Figure 5**). The line of best fit to the scatter suggests that CO2-C emission is proportional to litter decomposition in the cocoa ecosystems. Quantitatively, litter decomposition accounts for 70.9% of the variations in measured CO2-C emissions from the cocoa ecosystems (**Figure 5**). Other researchers have also found strong agreements between the two methods with respect to measuring the C released

The quantity of carbon released from the decomposition of dead materials into the atmosphere contributes significantly to the global carbon budget. It is estimated that about 70% total annual carbon flux (this is equivalent to 68 Pg C/y) derives from the decomposition of plant materials [92]. Forests are recognized as an important component for climate mitigation and adaptation. Conceivably, promoting agroforestry practices such as cocoa ecosystems in the tropics on cleared lands would mitigate the atmospheric CO2 loads through photosynthesis and C storage in their tissues. The amount of C stored is proportional to the biomass of the tree components and consequently the amount of

In comparing the C stored in cocoa systems with annual crops, many studies have reported higher C storage in the cocoa systems [22, 93, 94]. Lavelle and Pashanasi [95] noted that forest ecosystems and pastures contain more biomass C than cropland. On a vertisol in Ethiopia, Lulu and Insam [96] observed positive

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

during decomposition [27, 31, 32].

**3.5 Mitigation of CO2 emissions**

CO2 removed from the atmosphere.

#### *Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

during litter decomposition is but one of several ways including fragmentation and organic matter leaching that contributes to the weight loss of buried litter [24, 25].

However, the confinement of the current experiment as described earlier meant that weight losses through fragmentation and leaching of organic matter were disallowed. Therefore, the litter weight loss solely depended on the release amounts of CO2-C during the period. Thus, the expected weight loss from decomposing litters must at most, be equivalent to the amounts of CO2 released in the absence of leaching of other organic material. The many steps such as initial total C determination of the decomposing litter, weighing litter remains that have not been dried well or have attached soil particles to determine weight loss and the use of larger time intervals are all sources of variations associated with the determination of C release by the weight loss method. These steps have the potential of being over estimated and might explain the lower amounts C losses by the weight loss method when compared to the CO2-C evolution method. On the other hand, the short time intervals of the CO2-C evolution methods with regard to the frequent replacement of the adsorbent creates room for atmospheric CO2-C to interfere with the decomposition and consequently leads to over estimation of release C from the litter decomposition alone.

Apparently, the above sources of deviations associated with the two methods were minimal under the litter treatments of WR cocoa systems. Hence, the expectation of equality between litter weight loss C and CO2-C released was confirmed in all but the shade tree leaf litter decomposition. Differences between released C estimated from litter weight loss and CO2-C evolution measurement methods were not statistically significant under decomposing cocoa litter (*F*1, 3 = 3.9, *P* = 0.143), mixed litter (*F*1, 3 = 0.008, *P* = 0.933) and predicted litter (*F*1, 3 = 0.008, *P* = 0.934) in the WR (**Table 5**). In contrast, the shade tree leaf litter decomposition from WR released significantly (*F*1, 3 = 11.5, *P* = 0.043) different amounts of C, where the measured C by CO2-C evolved was higher than that in loss litter (**Table 5**).

Although the measured differences varied between regions, regression analysis of pooled data from the two regions indicated the existence of a strong relationship between weight loss of litter C and the CO2-C evolution during litter decomposition (**Figure 5**). The line of best fit to the scatter suggests that CO2-C emission is proportional to litter decomposition in the cocoa ecosystems. Quantitatively, litter decomposition accounts for 70.9% of the variations in measured CO2-C emissions from the cocoa ecosystems (**Figure 5**). Other researchers have also found strong agreements between the two methods with respect to measuring the C released during decomposition [27, 31, 32].

#### **3.5 Mitigation of CO2 emissions**

The quantity of carbon released from the decomposition of dead materials into the atmosphere contributes significantly to the global carbon budget. It is estimated that about 70% total annual carbon flux (this is equivalent to 68 Pg C/y) derives from the decomposition of plant materials [92]. Forests are recognized as an important component for climate mitigation and adaptation. Conceivably, promoting agroforestry practices such as cocoa ecosystems in the tropics on cleared lands would mitigate the atmospheric CO2 loads through photosynthesis and C storage in their tissues. The amount of C stored is proportional to the biomass of the tree components and consequently the amount of CO2 removed from the atmosphere.

In comparing the C stored in cocoa systems with annual crops, many studies have reported higher C storage in the cocoa systems [22, 93, 94]. Lavelle and Pashanasi [95] noted that forest ecosystems and pastures contain more biomass C than cropland. On a vertisol in Ethiopia, Lulu and Insam [96] observed positive

*CO2 Sequestration*

predicted mixture capacity (**Table 3**).

initial oxidizable C content of the litters within 130 days of incubation. The present estimate for C loss relative to the period is much higher when compared with Saffigna et al. [91] who reported a decline in mineralizable C by 29% when sorghum residues were removed for 6 years from a hitherto amended soil. However the lower C loss associated with sorghum residue partly reflects its lower oxidizable carbon content relative to cocoa litter. The cocoa litter contained approximately twice as much mineralizable C as contained in the shade litter, but the mixed cocoa-shade contained more than twice as much potential mineralizable C as expected by the

There were no significant correlations between the estimated mineralizable C pools from the WR leaf litter treatments and the biochemical composition of the decomposing litter although there were indications of moderate relationship with each one of the following: C (*r* = −0.672, *P* = 0.068), N (*r* = −0.564, *P* = 0.145), and P (*r* = 0.530, *P* = 0.176). It thus confirms that the amount of potential mineralizable C estimated from the litter incubation partly reflected the initial chemical composi-

tion and the amount of oxidizable C in the decomposing litter.

**3.4 Comparison of C from leaf weight loss and CO2-C evolution methods**

which interference from the methods with the results can be isolated.

**Region Litter**

*Western regions as measured by the weight loss and CO2-C evolution methods.1*

**Cocoa leaf litter**

Although leaf decomposition is generally measured by weight loss, it is also measured by carbon dioxide release in numerous studies [24, 25]. These methods have several sources of variations as mentioned in the introductory section that potentially could confound the results and cause deviations from litter decomposition under natural vegetation types. Comparison of methods is an option through

**Table 5** presents the measured amounts of C released from cocoa systems in ER and WR during leaf litter decomposition averaged over the incubation period (120 days) by the weight loss and carbon dioxide evolution methods. Under the cocoa systems in the Eastern region, the C released measured by the CO2 evolution method was significantly higher than measured by the weight loss method in cocoa leaf (*F*1, 3 = 38.1, *P* = 0.009), mixed litter (*F*1, 3 = 23.5, *P* = 0.017) and predicted mixed litter (*F*1, 3 = 18.4, *P* = 0.023) decomposition but their difference was not significant (*F*1, 3 = 0.07, *P* = 0.810) with respect to shade tree leaf decomposition (**Table 5**). These higher amounts of C from the released CO2 measurements are usually unexpected under natural unconfined environments since the release of CO2

> **Shade leaf litter**

Loss litter C 167.7b 329.0a 230.8b 248.4b Evolved CO2-C 304.0a 326.4a 371.1a 315.2a

Loss litter C 371.3a 153.8b 324.7a 262.5a Evolved CO2-C 338.3a 185.1a 326.9a 261.8a

*Different letters within same region and column indicate significant difference at* P *< 0.05 using Tukey's method.*

*Cumulative C released (g/kg) over 120 days during litter decomposition under cocoa systems in Eastern and* 

**Mixed leaf litter**

**Predicted mixed litter**

**82**

*1*

**Table 5.**

*Eastern region*

*Western region*

#### **Figure 5.**

*Relationship between measurements of C released during litter decomposition by the litter weight loss and the CO2-C evolution methods.*

effects of agroforestry practice with Sesbania on soil organic carbon (SOC) pool. Dowuona et al. [97] reported a 25.6 g/kg SOC on a ferric acrisol under *Leucaena leucocephala* woodlot in Ghana compared to the 15.6 g/kg SOC for its *Chromolaena odorata* native fallow adjacent soil.

The recognition of the potential of sequestering carbon in plantations has attracted the attention of many researchers on C sequestration projects. These researchers have predicted a potential market for C in developing nations as a result of the investments from companies and governments wishing to offset their emissions of greenhouse gases as directed by the Kyoto Protocol's Clean Development Mechanism [98, 99].

Whether the soil acts as a source or sink of carbon gases depends greatly on the type and intensity of activities of human management on the land. Soil management practices have been documented to have tremendous effects on soil organic matter (SOM) storage. In a study from adjacent forested and cultivated soils in eight agro-ecosystems from the Ethiopian highlands and Nigerian lowlands, SOM content was two to four times higher in the forested than in the cultivated soils [100]. In an 11-year experiment to assess the potential of different cropping systems to sequester C in the soils, Bostick et al. [101] noted significant reductions of soil organic carbon from a continuous fallow of 0.53% C to 0.46, 0.37, 0.35 and 0.33% C for sorghum-fallow, continuous cotton, continuous sorghum and cottonmaize-sorghum rotations, respectively, in Burkina Faso. Haynes and Francis [102] have reported high amounts of C under pasture relative to cultivated soils. Pichot et al. [103] observed that average soil C increased between 116 and 377 kg/ha/y in a 10-year study in Burkina Faso when soils were amended with low and high levels of inorganic and organic fertilizer, respectively.

#### **4. Conclusions**

Litter decomposition helps to replenish soil nutrient pools. Therefore, plant litter decomposition plays a key role in biogeochemical nutrient cycling, the rate of which

**85**

**Author details**

Askia M. Mohammed1

2 University of Reading, UK

\*, James S. Robinson2

1 CSIR-Savanna Agricultural Research Institute, Tamale, Ghana

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

\*Address all correspondence to: mamusah@yahoo.com

provided the original work is properly cited.

, David J. Midmore2

and Anne Verhoef<sup>2</sup>

*Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems*

determines the productivity of natural and in part agro ecosystems. The findings of this study have contributed to our understanding of litter decomposition and C

Trends of leaf litter decomposition and C mineralization indicated that mixed cocoa-shade litter treatments decomposed faster than the cocoa leaf litter alone; this suggests that litter mixing has a positive interaction effect in cocoa ecosystems. The management implication of this finding is that if the release of nutrients into the soil is a consequence of litter decomposition, then the mixed litter systems as in shaded cocoa ecosystems would be more effective in releasing plant nutrients than

*DOI: http://dx.doi.org/10.5772/intechopen.86520*

dynamics in cocoa ecosystems of Ghana.

the single tree species litter systems.

#### *Leaf Litter Decomposition and Mitigation of CO2 Emissions in Cocoa Ecosystems DOI: http://dx.doi.org/10.5772/intechopen.86520*

determines the productivity of natural and in part agro ecosystems. The findings of this study have contributed to our understanding of litter decomposition and C dynamics in cocoa ecosystems of Ghana.

Trends of leaf litter decomposition and C mineralization indicated that mixed cocoa-shade litter treatments decomposed faster than the cocoa leaf litter alone; this suggests that litter mixing has a positive interaction effect in cocoa ecosystems. The management implication of this finding is that if the release of nutrients into the soil is a consequence of litter decomposition, then the mixed litter systems as in shaded cocoa ecosystems would be more effective in releasing plant nutrients than the single tree species litter systems.

### **Author details**

*CO2 Sequestration*

effects of agroforestry practice with Sesbania on soil organic carbon (SOC) pool. Dowuona et al. [97] reported a 25.6 g/kg SOC on a ferric acrisol under *Leucaena leucocephala* woodlot in Ghana compared to the 15.6 g/kg SOC for its *Chromolaena* 

*Relationship between measurements of C released during litter decomposition by the litter weight loss and the* 

The recognition of the potential of sequestering carbon in plantations has attracted the attention of many researchers on C sequestration projects. These researchers have predicted a potential market for C in developing nations as a result of the investments from companies and governments wishing to offset their emissions of greenhouse gases as directed by the Kyoto Protocol's Clean Development

Whether the soil acts as a source or sink of carbon gases depends greatly on the type and intensity of activities of human management on the land. Soil management practices have been documented to have tremendous effects on soil organic matter (SOM) storage. In a study from adjacent forested and cultivated soils in eight agro-ecosystems from the Ethiopian highlands and Nigerian lowlands, SOM content was two to four times higher in the forested than in the cultivated soils [100]. In an 11-year experiment to assess the potential of different cropping systems to sequester C in the soils, Bostick et al. [101] noted significant reductions of soil organic carbon from a continuous fallow of 0.53% C to 0.46, 0.37, 0.35 and 0.33% C for sorghum-fallow, continuous cotton, continuous sorghum and cottonmaize-sorghum rotations, respectively, in Burkina Faso. Haynes and Francis [102] have reported high amounts of C under pasture relative to cultivated soils. Pichot et al. [103] observed that average soil C increased between 116 and 377 kg/ha/y in a 10-year study in Burkina Faso when soils were amended with low and high levels

Litter decomposition helps to replenish soil nutrient pools. Therefore, plant litter decomposition plays a key role in biogeochemical nutrient cycling, the rate of which

*odorata* native fallow adjacent soil.

of inorganic and organic fertilizer, respectively.

Mechanism [98, 99].

*CO2-C evolution methods.*

**Figure 5.**

**84**

**4. Conclusions**

Askia M. Mohammed1 \*, James S. Robinson2 , David J. Midmore2 and Anne Verhoef<sup>2</sup>

1 CSIR-Savanna Agricultural Research Institute, Tamale, Ghana

2 University of Reading, UK

\*Address all correspondence to: mamusah@yahoo.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Soils. 1998;**27**:143-148

s11104-009-0173-0

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[84] Vitousek PM, Turner DR, Parton WJ, Sanford RL. Litter decomposition on the Mauna Loa environmental matrix, Hawai'i: Patterns, mechanisms, and models. Ecology. 1994;**75**:418-429

[85] Nourbakhsh F. Fate of carbon and nitrogen from plant residue decomposition in a calcareous soil. Plant, Soil and Environment. 2006;**52**:137-146

[86] Bonde TA, Rosswall T. Seasonal variation of potentially mineralizable nitrogen in four cropping systems. Soil Science Society of America Journal. 1987;**51**:1508-1514

[87] Ajwa H, Tabatabai M. Decomposition of different organic materials in soils. Biology and Fertility of Soils. 1994;**18**:175-182

[88] Riffaldi R, Saviozzi A, Levi-Minzi R. Carbon mineralization kinetics as influenced by soil properties. Biology and Fertility of Soils. 1996;**22**:293-298

[89] Cheruiyot E, Mwonga S, Mumera L, Macharia J, Tabu I, Ngugi J. Rapid decay of dolichos [*Lablab purpureus* (L.) Sweet] residue leads to loss of nitrogen benefit to succeeding maize (*Zea mays* L.). Animal Production Science. 2007;**47**:1000-1007

[90] Martinez C, Tabatabai M. Decomposition of biotechnology by-products in soils. Journal of Environmental Quality. 1997;**26**:625-632

[91] Saffigna P, Powlson D, Brookes P, Thomas G. Influence of sorghum residues and tillage on soil organic matter and soil microbial biomass in an Australian vertisol. Soil Biology and Biochemistry. 1989;**21**:759-765

[92] Raich JW, Schlesinger WH. The global carbon dioxide flux in soil

respiration and its relationship to vegetation and climate. Tellus B. 1992;**44**:81-99. Available from: http:// www.blackwell-synergy.com/links/ doi/10.1034%2Fj.1600-0889.1992. t01-1-00001.x

[93] Kotto-same J, Woomer PL, Appolinaire M, Louis Z. Carbon dynamics in slash-and-bum agriculture and land use alternatives of the humid forest zone in Cameroon. Science (80-). 1997;**809**:97

[94] Duguma B, Gockowski J, Bakala J. Smallholder cacao (*Theobroma cacao* Linn.) cultivation in agroforestry systems of West and Central Africa: Challenges and opportunities. Agroforestry Systems. 2001;**51**:177-188

[95] Lavelle P, Pashanasi B. Soil macrofauna and land management in Peruvian Amazonia. Pedobiologia (Jena). 1989;**33**:283-291

[96] Lulu B, Insam H. Effects of cropping systems and manuring on soil microbial and carbon status of a vertisol in Ethiopia. Bodenkultur. 2000;**51**:107-114

[97] Dowuona GN, Mermut AR, Adiku SGK, Nartey E, Tete-Mensah I. Improvements in the quality of soils under agroforestry practice in Ghana. Soil fertility management in West African land use systems. 1997;**34**:251-258

[98] Fearnside PM. Forests and global warming mitigation in Brazil: Opportunities in the Brazilian forest sector for responses to global warming. Biomass and Bioenergy. 1999;**16**:171-189

[99] Wise R, Cacho O. A bioeconomic analysis of carbon sequestration in farm forestry: A simulation study of *Gliricidia sepium*. Agroforestry Systems [Internet]. 2005;**64**(3):237-250. Available from: http://www. springerlink.com/index/10.1007/ s10457-004-3938-8

[100] Spaccini R, Zena A, Igwe CA, Mbagwu JSC, Piccolo A. Carbohydrate in water-stable aggregates and particle size fractions of forested and cultivated soils in two contrasting tropical ecosystems. Biogeochemistry. 2001;**53**:1-22

[101] Bostick WM, Bado VB, Bationo A, Soler CT, Hoogenboom G, Jones JW. Soil carbon dynamics and crop residue yields of cropping systems in Northern Guinea Savanna of Burkina Faso. Soil and Tillage Research. 2006;**2257**:1-14

[102] Haynes RJ, Francis GS. Changes in microbial biomass C, soil carbohydrate composition and aggregate stability induced by growth of selected crop and forage species under field conditions. Journal of Soil Science. 1993;**44**:665-675

[103] Pichot J, Sedogo M, Poulain J, Arrivets J. Fertility evolution in a tropical ferruginous soil under the effect of organic manure and inorganic fertilizer applications [ploughed-in green manure, crop residues, straw; rotating sorghum-legume crops; aluminium toxicity allelopathy; Upper Volta]. Agronomia Tropical. 1981;**36**:122-133

**93**

**Chapter 6**

**Abstract**

GHG emissions.

**1. Introduction**

nitrous oxide, palm oil mill effluent

Greenhouse Gas Assessment

and Strategies to Achieve CO2

Sequestration in the Brazilian

*Leidivan Almeida Frazão, Guilherme Silva Raucci,* 

*João Luis Nunes Carvalho, Marcelo Valadares Galdos,* 

*Cindy Silva Moreira, Carlos Eduardo Pellegrino Cerri* 

**Keywords:** carbon dioxide, crude palm oil, fresh fruit bunches, methane,

Oil palm (*Elaeis guineensis* Jacq.) is the most produced oil crop in the world due to its high productivity in relation to other oleaginous crops (e.g., soybean, sunflower, and rapeseed), and could meet growing global demand that is estimated to reach 240 million tons of palm oil by 2050 [1]. In Brazil, the cultivated area with oil palm is about 236,000 ha, including areas of agro-industries, small- and mediumsized farmers, family farmers and members of agrarian reform. It is estimated that

As the palm oil production is expanding in Brazilian Amazon region, this study aimed to determinate the greenhouse gas (GHG) emissions since the agricultural phase to transportation of crude palm oil (CPO) and then indicate strategies to achieve the CO2 sequestration. The scope of this study comprised since the stage of oil palm seedlings production until the transportation of CPO. Inventory data for the year of 2009 included the agricultural production of fresh fruit bunches (FFB) and the extraction and transportation of CPO. The management of palm oil mill effluent (POME), use of fertilizers, fuels, pesticides, and electricity contributed to 66.5, 17.9, 15.1, 0.4, and 0.1% of the total emissions, respectively. Agricultural phase, CPO extraction, and transportation emitted 32,131, 79,590, and 1,104 t CO2-eq, respectively. The carbon (C) footprint was 0.79 t CO2-eq / t CPO, and the highest GHG emissions were associated to the management of POME. On the other hand, the use of all residues from the mill as fertilizer substitute can minimize the GHG emissions and increase soil C stocks. In addition, the methane (CH4) from POME captured and used for steam or electricity is also a viable alternative to reduce the

Palm Oil Life Cycle

*and Carlos Clemente Cerri*

#### **Chapter 6**

*CO2 Sequestration*

2001;**53**:1-22

[100] Spaccini R, Zena A, Igwe CA, Mbagwu JSC, Piccolo A. Carbohydrate

[101] Bostick WM, Bado VB, Bationo A, Soler CT, Hoogenboom G, Jones JW. Soil carbon dynamics and crop residue yields of cropping systems in Northern Guinea Savanna of Burkina Faso. Soil and Tillage Research. 2006;**2257**:1-14

[102] Haynes RJ, Francis GS. Changes in microbial biomass C, soil carbohydrate composition and aggregate stability induced by growth of selected crop and forage species under field conditions. Journal of Soil Science. 1993;**44**:665-675

[103] Pichot J, Sedogo M, Poulain J, Arrivets J. Fertility evolution in a tropical ferruginous soil under the effect of organic manure and inorganic fertilizer applications [ploughed-in green manure, crop residues, straw; rotating sorghum-legume crops; aluminium toxicity allelopathy; Upper Volta]. Agronomia Tropical.

1981;**36**:122-133

in water-stable aggregates and particle size fractions of forested and cultivated soils in two contrasting tropical ecosystems. Biogeochemistry.

**92**

## Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm Oil Life Cycle

*Leidivan Almeida Frazão, Guilherme Silva Raucci, João Luis Nunes Carvalho, Marcelo Valadares Galdos, Cindy Silva Moreira, Carlos Eduardo Pellegrino Cerri and Carlos Clemente Cerri*

#### **Abstract**

As the palm oil production is expanding in Brazilian Amazon region, this study aimed to determinate the greenhouse gas (GHG) emissions since the agricultural phase to transportation of crude palm oil (CPO) and then indicate strategies to achieve the CO2 sequestration. The scope of this study comprised since the stage of oil palm seedlings production until the transportation of CPO. Inventory data for the year of 2009 included the agricultural production of fresh fruit bunches (FFB) and the extraction and transportation of CPO. The management of palm oil mill effluent (POME), use of fertilizers, fuels, pesticides, and electricity contributed to 66.5, 17.9, 15.1, 0.4, and 0.1% of the total emissions, respectively. Agricultural phase, CPO extraction, and transportation emitted 32,131, 79,590, and 1,104 t CO2-eq, respectively. The carbon (C) footprint was 0.79 t CO2-eq / t CPO, and the highest GHG emissions were associated to the management of POME. On the other hand, the use of all residues from the mill as fertilizer substitute can minimize the GHG emissions and increase soil C stocks. In addition, the methane (CH4) from POME captured and used for steam or electricity is also a viable alternative to reduce the GHG emissions.

**Keywords:** carbon dioxide, crude palm oil, fresh fruit bunches, methane, nitrous oxide, palm oil mill effluent

#### **1. Introduction**

Oil palm (*Elaeis guineensis* Jacq.) is the most produced oil crop in the world due to its high productivity in relation to other oleaginous crops (e.g., soybean, sunflower, and rapeseed), and could meet growing global demand that is estimated to reach 240 million tons of palm oil by 2050 [1]. In Brazil, the cultivated area with oil palm is about 236,000 ha, including areas of agro-industries, small- and mediumsized farmers, family farmers and members of agrarian reform. It is estimated that

88% of Brazilian palm oil production was located at Pará State, while and Bahia and Roraima States account for 11 and 1% of production, respectively [2].

There is a great potential for development of palm oil chain in Brazil. The Brazilian government envisions a 35% expansion of oil palm production in the Amazon region due to its favorable soil and climate conditions and large amount of available lands. The Program for Sustainable Production of Palm Oil in Brazil has been promoting oil palm plantations but limiting the expansion only to degraded lands [3]. There was an encouragement for the cultivation of oil palm in the northern region due to its high productivity and potential for inclusion in the biodiesel agenda. Pará State continued to be targeted as the largest potential producer, and there was an estimated expansion of 330,000 ha until 2020 [4].

The environmental impacts of palm oil production can be accessed from a life cycle point of view, where the greenhouse gas (GHG) emissions can be accounted since from oil palm cultivation, crude palm oil (CPO) extraction, CPO transportation, and recycling or disposal of residues from the mill [5, 6]. According to Menichetti and Otto [7], the impacts depend on the consumption of conventional fuels, fertilizers, and the wastes generated. We hypothesized that the main source of GHG emissions in the palm oil production is related do CPO extraction and disposal of liquid waste from the mill.

Therefore, the aim of this study was to access the GHG emissions derived from the agricultural production, CPO extraction and transportation in an agro-industry farm located at Pará State, Amazon region, Brazil. Additionally, we aim to propose strategies for reducing GHG emissions and for promoting the CO2 sequestration.

#### **2. Materials and methods**

#### **2.1 Location of the study area**

The study was carried out in 2009 in a commercial farm located in the municipality of Tailândia (48°46′W, 2°27′S), Pará State, Brazil (**Figure 1**). The company had a total area of 107,000 ha, where 60% is occupied with native vegetation, 36% with oil palm plantation, and 4% with infrastructure. The native vegetation is tropical rainforest. According to Köppen classification, the climate is Afi (tropical monsoonal). The rainfall for 2009 was 2705 mm year<sup>−</sup><sup>1</sup> and the mean temperature was 26.5°C. The temperature ranged from 22.6 to 33.4°C and the mean of annual relative humidity was higher throughout the year. The mean altitude of the region is 30 m, and the soil is well drained with medium clay content (18–29%), and classified as "Latossolo Amarelo distrófico típico" in the Brazilian System of Soil Classification [8] and as Oxisol (Xanthic Hapludox) in the USDA classification [9].

#### **2.2 Palm oil system description**

The palm oil supply chain consists of three subsystems (**Figure 2**): seedlings production, fresh fruit bunches (FFBs) production, and crude palm oil (CPO) extraction. Several processes are involved in the production of FFB, including planning, nursery establishment (seedlings cultivation), soil preparation, field establishment, field maintenance, harvesting and collection of FFB and replanting [10]. Considering all steps, the agricultural phase of oil palm production lasts for around 25–30 years [1].

The industrial phase consists of CPO extraction. The palm oil mill is located near to the oil palm plantations to facilitate the timely transportation and effective processing of FFB. Processing in the palm oil mill involves four major unit operations: sterilization, threshing and stripping of fruits, digestion, and oil extraction [11].

**95**

**Figure 2.**

**Figure 1.**

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm…*

Subsequently, the CPO, the main product from the palm oil mill, is transported to a refinery aiming to produce refined palm oil (RPO). Although it is possible to use CPO as raw material, the biodiesel production is based on fatty acids extracted

from palm oil fruit through the refining process [12].

*Description of the CPO production system in the Brazilian Amazon region.*

*Location map of the study area in the Brazilian Amazon region.*

*DOI: http://dx.doi.org/10.5772/intechopen.92772*

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm… DOI: http://dx.doi.org/10.5772/intechopen.92772*

**Figure 1.**

*CO2 Sequestration*

of liquid waste from the mill.

**2. Materials and methods**

**2.1 Location of the study area**

**2.2 Palm oil system description**

monsoonal). The rainfall for 2009 was 2705 mm year<sup>−</sup><sup>1</sup>

88% of Brazilian palm oil production was located at Pará State, while and Bahia and

The environmental impacts of palm oil production can be accessed from a life cycle point of view, where the greenhouse gas (GHG) emissions can be accounted since from oil palm cultivation, crude palm oil (CPO) extraction, CPO transportation, and recycling or disposal of residues from the mill [5, 6]. According to Menichetti and Otto [7], the impacts depend on the consumption of conventional fuels, fertilizers, and the wastes generated. We hypothesized that the main source of GHG emissions in the palm oil production is related do CPO extraction and disposal

Therefore, the aim of this study was to access the GHG emissions derived from the agricultural production, CPO extraction and transportation in an agro-industry farm located at Pará State, Amazon region, Brazil. Additionally, we aim to propose strategies for reducing GHG emissions and for promoting the CO2 sequestration.

The study was carried out in 2009 in a commercial farm located in the municipality of Tailândia (48°46′W, 2°27′S), Pará State, Brazil (**Figure 1**). The company had a total area of 107,000 ha, where 60% is occupied with native vegetation, 36% with oil palm plantation, and 4% with infrastructure. The native vegetation is tropical rainforest. According to Köppen classification, the climate is Afi (tropical

was 26.5°C. The temperature ranged from 22.6 to 33.4°C and the mean of annual relative humidity was higher throughout the year. The mean altitude of the region is 30 m, and the soil is well drained with medium clay content (18–29%), and classified as "Latossolo Amarelo distrófico típico" in the Brazilian System of Soil Classification [8] and as Oxisol (Xanthic Hapludox) in the USDA classification [9].

The palm oil supply chain consists of three subsystems (**Figure 2**): seedlings production, fresh fruit bunches (FFBs) production, and crude palm oil (CPO) extraction. Several processes are involved in the production of FFB, including planning, nursery establishment (seedlings cultivation), soil preparation, field establishment, field maintenance, harvesting and collection of FFB and replanting [10]. Considering all steps, the agricultural phase of oil palm production lasts for around 25–30 years [1]. The industrial phase consists of CPO extraction. The palm oil mill is located near to the oil palm plantations to facilitate the timely transportation and effective processing of FFB. Processing in the palm oil mill involves four major unit operations: sterilization, threshing and stripping of fruits, digestion, and oil extraction [11].

and the mean temperature

There is a great potential for development of palm oil chain in Brazil. The Brazilian government envisions a 35% expansion of oil palm production in the Amazon region due to its favorable soil and climate conditions and large amount of available lands. The Program for Sustainable Production of Palm Oil in Brazil has been promoting oil palm plantations but limiting the expansion only to degraded lands [3]. There was an encouragement for the cultivation of oil palm in the northern region due to its high productivity and potential for inclusion in the biodiesel agenda. Pará State continued to be targeted as the largest potential producer, and

Roraima States account for 11 and 1% of production, respectively [2].

there was an estimated expansion of 330,000 ha until 2020 [4].

**94**

*Location map of the study area in the Brazilian Amazon region.*

#### **Figure 2.**

*Description of the CPO production system in the Brazilian Amazon region.*

Subsequently, the CPO, the main product from the palm oil mill, is transported to a refinery aiming to produce refined palm oil (RPO). Although it is possible to use CPO as raw material, the biodiesel production is based on fatty acids extracted from palm oil fruit through the refining process [12].

#### *2.2.1 Agricultural phase*

In the oil palm cultivation, the first stage in the agricultural phase is the seedlings production. In prenursery, seeds are sown in small polyethylene bags (0.5 L) where the seedlings are kept under the shade to protect them from direct sunlight until they are 3 months old. In the subsequent main nursery stage, the seedlings are transferred to large polyethylene bags (18 L) and grown without a protective shade until they are 12 months old, when they are considered ready to be shifted to the plantations. Sprinkler systems are used to provide sufficient water in prenursery and nursery (8 mm day<sup>−</sup><sup>1</sup> ). The seedlings are supplied with nutrients by fertilizer applications.

The palms from nursery are transferred to oil palm plantations and planted at a density of 143 plants/ha on a mineral soil with low and medium clay content. About some time after palm plantation, a legume used as cover crop (*Pueraria phaseoloides*) is sown. The cover crop prevents erosion and fixes nitrogen from the atmosphere in their root nodules, especially during the stage when the palms are young. A circle with no vegetation is established around each plant, preventing competition of weeds. The circle allows the herbicide application and the easy access for harvesting and picking of loose fruits.

The fertilizers applied in the oil palm plantations are potassium chloride, ammonium sulfate, kieserite, and rock phosphate. The herbicide glyphosate is used mainly to make the circles around the plant. The insecticide acephate is used in a small quantity due to use of integrated pest management, where natural enemies are used instead of pesticides.

The harvest operations start at 3 years of age and continue until the oil palm plantations are 25 years old. Harvesting of ripe FFB is manually carried out every 12 days using a sickle mounted on an aluminum pole. Normally, two fronds beneath the fruit bunch are pruned before harvesting. The pruned fronds are placed in the field between the palm rows for mulching. Detached FFBs are placed by the roadside, collected and disposed in dumpsters, and later taken by truck to a palm oil mill.

Replanting of oil palm is carried out after 25 years due to difficulty in harvesting tall palms and to low FFB yield. So, the palms are felled, chipped, and left in the plantation as a nutrient source for the new palm plants.

#### *2.2.2 CPO production*

In the palm oil mill, the FFBs are transferred into the sterilizer. The fruits are sterilized by steam (135°C) under a pressure of 3 kg cm<sup>−</sup><sup>2</sup> for 80–90 min. The sterilization process avoids loosens of the individual fruits from the bunch and also deactivates the enzyme which the breakdown of the oil into FFA.

The sterilized FFBs are sent to a thresher where the fruits are separated from the bunch. The empty fruit bunches (EFBs), which are abundant, may be used to produce steam and power, and the ashes used as fertilizers [13]. However, in the Agropalma farm, the EFBs also are applied on the organic plantations as organic fertilizer.

The fruits from the thresher are then sent to a digester that converts the fruits into a homogeneous oily mash by means of a mechanical stirring process. The digested mash is then pressed using a screw press to remove the major portion of the CPO. At this point, the CPO comprises a mixture of oil, water, and fruit solids, which are screened through a vibrating screen to remove as much solids as possible. The oil is then clarified in a continuous settling tank whose decanted CPO is then passed through a centrifugal purifier to remove remaining solids and then sent to

**97**

of 21.2 t ha<sup>−</sup><sup>1</sup>

production system.

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm…*

the vacuum dryer to remove moisture. The CPO is then pumped to storage tanks

The nuts with the pressed mesocarp fibers are separated at the fiber cyclone and then cracked to produce kernels and shells. The kernels are shipped to kernel crushing plants to be processed into crude palm kernel oil (CPKO), while the shell

The main solid residues from the milling process are EFBs, pressed mesocarp fiber, shell, and boiler ash, while the liquid waste is palm oil mill effluent (POME) (**Figure 2**). In the studied plantations, the POME is conveyed from the mill and disposed in anaerobic ponds and later is used for palm tree irrigation purposes. All the residues from the palm oil extraction process are reused in the oil palm cultiva-

The CPO stored in tanks is transported by trucks to the barge docks 24 km away from the mills and then is taken by barge to the refinery located 200 km from the farm. Each barge carries 1100 t of CPO. Besides being cheaper due to geographical conditions of the palm oil mill, the CPO transportation by the waterway is easier

The scope of this study comprised since the stage of oil palm seedling production until the transportation of CPO. Inventory data included the main steps of the palm oil supply chain: agricultural production of FFB, extraction of CPO, and transportation of CPO to a refinery. We considered the year of 2009 (January 1 to December 31) to evaluate the carbon footprint of CPO production and transportation at Agropalma farm. In this study, the functional unit (FU) is 1 t of CPO.

We evaluated the GHG emissions related to seedlings production, planting and cultivation of juvenile and mature oil palm plantations, considering a FFB yield

fuels, fertilizers (i.e., nitrogen, phosphorous, and potassium) and defensives in the

The GHG emissions from industrial processes (by the use of fossil fuels, biofuels, biomass, and electricity) and FFB transportation from the field to the palm oil mill (by the use of fossil fuels) were calculated. In addition, we evaluated the GHG emissions from CPO transportation by trucks to the barge docks and then to the refinery. The GHG sources associated to inputs and outputs from the palm oil production, extraction, and transportation are described in **Figure 2**. The input data used to calculate the GHG emissions are listed in **Table 1**. **Table 2** presents the

The international standards ISO 14040 and ISO 14044 on life cycle assessments

were used in this study to determine the GHG emissions from CPO production based in the methodology proposed by IPCC [18]. When allocation could not be avoided in the treatment of coproducts and residues, the resulting emissions of a process were portioned between its different products in a way that reflected the underlying physical relations between then. The rationale in using mass allocation is that physical portioning is most consistent as it contains the least uncertainties. According to the production at Agropalma in 2009, the weight allocation was 92% of CPO and 8% of PKO. To measure GHG emissions, we have used the inputs presented in the inventory data (**Table 1**) and their respective emission factors (**Table 2**). The EFB and POME are used in the plantations as fertilizers, while the

. The study measured direct and indirect emissions from the use of

*DOI: http://dx.doi.org/10.5772/intechopen.92772*

before it is sent off to the refining process.

and pressed mesocarp fiber are used as boiler fuel.

*2.2.3 Transportation of CPO from palm oil mill*

than it is by road in the region of study.

**2.3 Scope definition and data collection**

emission factors (EFs) used in this study.

tion (EFB, ashes, and POME) or palm oil mill (fiber and shell).

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm… DOI: http://dx.doi.org/10.5772/intechopen.92772*

the vacuum dryer to remove moisture. The CPO is then pumped to storage tanks before it is sent off to the refining process.

The nuts with the pressed mesocarp fibers are separated at the fiber cyclone and then cracked to produce kernels and shells. The kernels are shipped to kernel crushing plants to be processed into crude palm kernel oil (CPKO), while the shell and pressed mesocarp fiber are used as boiler fuel.

The main solid residues from the milling process are EFBs, pressed mesocarp fiber, shell, and boiler ash, while the liquid waste is palm oil mill effluent (POME) (**Figure 2**). In the studied plantations, the POME is conveyed from the mill and disposed in anaerobic ponds and later is used for palm tree irrigation purposes. All the residues from the palm oil extraction process are reused in the oil palm cultivation (EFB, ashes, and POME) or palm oil mill (fiber and shell).

#### *2.2.3 Transportation of CPO from palm oil mill*

*CO2 Sequestration*

*2.2.1 Agricultural phase*

and nursery (8 mm day<sup>−</sup><sup>1</sup>

are used instead of pesticides.

access for harvesting and picking of loose fruits.

plantation as a nutrient source for the new palm plants.

sterilized by steam (135°C) under a pressure of 3 kg cm<sup>−</sup><sup>2</sup>

deactivates the enzyme which the breakdown of the oil into FFA.

applications.

oil mill.

*2.2.2 CPO production*

In the oil palm cultivation, the first stage in the agricultural phase is the seedlings production. In prenursery, seeds are sown in small polyethylene bags (0.5 L) where the seedlings are kept under the shade to protect them from direct sunlight until they are 3 months old. In the subsequent main nursery stage, the seedlings are transferred to large polyethylene bags (18 L) and grown without a protective shade until they are 12 months old, when they are considered ready to be shifted to the plantations. Sprinkler systems are used to provide sufficient water in prenursery

The palms from nursery are transferred to oil palm plantations and planted at a density of 143 plants/ha on a mineral soil with low and medium clay content. About some time after palm plantation, a legume used as cover crop (*Pueraria phaseoloides*) is sown. The cover crop prevents erosion and fixes nitrogen from the atmosphere in their root nodules, especially during the stage when the palms are young. A circle with no vegetation is established around each plant, preventing competition of weeds. The circle allows the herbicide application and the easy

The fertilizers applied in the oil palm plantations are potassium chloride, ammonium sulfate, kieserite, and rock phosphate. The herbicide glyphosate is used mainly to make the circles around the plant. The insecticide acephate is used in a small quantity due to use of integrated pest management, where natural enemies

The harvest operations start at 3 years of age and continue until the oil palm plantations are 25 years old. Harvesting of ripe FFB is manually carried out every 12 days using a sickle mounted on an aluminum pole. Normally, two fronds beneath the fruit bunch are pruned before harvesting. The pruned fronds are placed in the field between the palm rows for mulching. Detached FFBs are placed by the roadside, collected and disposed in dumpsters, and later taken by truck to a palm

Replanting of oil palm is carried out after 25 years due to difficulty in harvesting tall palms and to low FFB yield. So, the palms are felled, chipped, and left in the

In the palm oil mill, the FFBs are transferred into the sterilizer. The fruits are

sterilization process avoids loosens of the individual fruits from the bunch and also

The sterilized FFBs are sent to a thresher where the fruits are separated from the bunch. The empty fruit bunches (EFBs), which are abundant, may be used to produce steam and power, and the ashes used as fertilizers [13]. However, in the Agropalma farm, the EFBs also are applied on the organic plantations as organic

The fruits from the thresher are then sent to a digester that converts the fruits into a homogeneous oily mash by means of a mechanical stirring process. The digested mash is then pressed using a screw press to remove the major portion of the CPO. At this point, the CPO comprises a mixture of oil, water, and fruit solids, which are screened through a vibrating screen to remove as much solids as possible. The oil is then clarified in a continuous settling tank whose decanted CPO is then passed through a centrifugal purifier to remove remaining solids and then sent to

for 80–90 min. The

). The seedlings are supplied with nutrients by fertilizer

**96**

fertilizer.

The CPO stored in tanks is transported by trucks to the barge docks 24 km away from the mills and then is taken by barge to the refinery located 200 km from the farm. Each barge carries 1100 t of CPO. Besides being cheaper due to geographical conditions of the palm oil mill, the CPO transportation by the waterway is easier than it is by road in the region of study.

#### **2.3 Scope definition and data collection**

The scope of this study comprised since the stage of oil palm seedling production until the transportation of CPO. Inventory data included the main steps of the palm oil supply chain: agricultural production of FFB, extraction of CPO, and transportation of CPO to a refinery. We considered the year of 2009 (January 1 to December 31) to evaluate the carbon footprint of CPO production and transportation at Agropalma farm. In this study, the functional unit (FU) is 1 t of CPO.

We evaluated the GHG emissions related to seedlings production, planting and cultivation of juvenile and mature oil palm plantations, considering a FFB yield of 21.2 t ha<sup>−</sup><sup>1</sup> . The study measured direct and indirect emissions from the use of fuels, fertilizers (i.e., nitrogen, phosphorous, and potassium) and defensives in the production system.

The GHG emissions from industrial processes (by the use of fossil fuels, biofuels, biomass, and electricity) and FFB transportation from the field to the palm oil mill (by the use of fossil fuels) were calculated. In addition, we evaluated the GHG emissions from CPO transportation by trucks to the barge docks and then to the refinery. The GHG sources associated to inputs and outputs from the palm oil production, extraction, and transportation are described in **Figure 2**. The input data used to calculate the GHG emissions are listed in **Table 1**. **Table 2** presents the emission factors (EFs) used in this study.

The international standards ISO 14040 and ISO 14044 on life cycle assessments were used in this study to determine the GHG emissions from CPO production based in the methodology proposed by IPCC [18]. When allocation could not be avoided in the treatment of coproducts and residues, the resulting emissions of a process were portioned between its different products in a way that reflected the underlying physical relations between then. The rationale in using mass allocation is that physical portioning is most consistent as it contains the least uncertainties. According to the production at Agropalma in 2009, the weight allocation was 92% of CPO and 8% of PKO. To measure GHG emissions, we have used the inputs presented in the inventory data (**Table 1**) and their respective emission factors (**Table 2**). The EFB and POME are used in the plantations as fertilizers, while the


#### **Table 1.**

*Fertilizers, pesticides, fossil fuel and energy inputs, and waste generated in the crude palm oil (CPO) production in Pará State, Brazil.*


#### **Table 2.**

*Emission factors used to calculate the GHG emissions from crude palm oil (CPO) production in Pará State, Brazil.*

**99**

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm…*

pressed fiber and shell are burnt as fuel in the palm oil mill boiler. Nevertheless, the savings for the use of solid residues and POME are not included in this study.

Based on the input data, it was possible to estimate GHG emissions in terms of equivalent CO2 (CO2-eq). Emissions of N2O and CH4 are compared based on the global warming potential (GWP), since CH4 and N2O have a GWP 25 and 298 times

The total GHG emissions resulting from the production of FFB, extraction and transportation of CPO were 112,825 t CO2-eq (**Figure 3**). The main source of GHG was the management of POME, followed by fertilizer application, fuel combustion, pesticide application, and electricity use. The high CH4 emissions in the anaerobic ponds, when converted into CO2-eq represented 66.5% of the total emissions. The use of fertilizers and fuels contributed to 17.9 and 15.1% of the total emissions, respectively. The application and electricity use represented less than 1% of the total

The highest GHG amount emitted from POME is related to CH4 emissions in the anaerobic ponds. The anaerobic ponds located in Agropalma farm are over 2 m deep and the POME has a large amount of C available and, consequently, high COD (chemical oxygen demand). In this study, the COD had an average of 21.65 kg m<sup>−</sup><sup>3</sup>

which is considered a high value by the standards of the Intergovernmental Panel on

Similar results were found by Choo et al. [19] determining the GHG contribution by subsystems in the oil palm supply chain at Malaysia. The highest emissions were associated to POME without biogas capture. After POME disposal into the ponds, the CH4 content is higher in the outlet region [20]. This is explained by excess concentration of organic matter in the inlet region that would influence the methanogenic activities [21]. As a result, lower CH4 and higher CO2 are emitted

The fertilizers applied in the seedlings production and oil palm plantations resulted in the second largest GHG emission source. It is important to notice that GHG emissions are released both during the industrial production of fertilizer and through the application of these fertilizers on the field. The cultivation of oil palm requires high inputs of nitrogen fertilizer, which can create high soil emissions due

The oil palm cultivation in Agropalma farm uses small amount of pesticides, resulting in low GHG emissions due to the use of these products (**Figure 3**). In 2009, glyphosate (herbicide) and acephate (insecticide) were used, so that GHG emissions were lower than other results previously reported in Malaysia [13, 19] and

The measured fuel combustion was related to agricultural operations, FFB transportation, extraction and transportation of CPO to a refinery. According to previous studies [13, 23], GHG emissions associated to use of diesel in plantations,

8.5–19.1 kg CO2-eq/t FFB. We found a total emission of 23.08 kg CO2-eq/t FFB and this value can be attributed to the highest number of mechanized operations at Agropalma farm compared with the most part of palm oil companies in Southeast Asia. Moreover, we also include the emissions from the combustion of fibers and

, the total emissions would be in order of

internal transport and machinery are in order of 180–404 kg CO2-eq ha<sup>−</sup><sup>1</sup>

Climate Change [18] for effluents generated in the vegetable oil industry.

,

 yr.<sup>−</sup><sup>1</sup> .

*DOI: http://dx.doi.org/10.5772/intechopen.92772*

larger than CO2, respectively [18].

**3. Results and discussion**

**3.1 Total GHG emissions**

GHG emissions (**Figure 4**).

from the inlet region.

in Brazil [12].

to a conversion into N2O [22].

If the FFB yield is set at 21.2 t ha<sup>−</sup><sup>1</sup>

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm… DOI: http://dx.doi.org/10.5772/intechopen.92772*

pressed fiber and shell are burnt as fuel in the palm oil mill boiler. Nevertheless, the savings for the use of solid residues and POME are not included in this study.

Based on the input data, it was possible to estimate GHG emissions in terms of equivalent CO2 (CO2-eq). Emissions of N2O and CH4 are compared based on the global warming potential (GWP), since CH4 and N2O have a GWP 25 and 298 times larger than CO2, respectively [18].

#### **3. Results and discussion**

#### **3.1 Total GHG emissions**

*CO2 Sequestration*

**Pesticides (L)**

**Fossil fuel (L)1**

**Energy**

**Residue**

*1*

**Table 1.**

POME at anaerobic ponds (m3

*production in Pará State, Brazil.*

**Source Unit Emission factor Reference**

) — 693,193 —

**GHG source Production stage**

Nitrogen (N) 362 — — Phosphate (P) 256 — — Potassium (K) 3634 — —

Glyphosate 52,745 — — Organophosphate 6678 — —

Diesel 3,708,216 854,458 365,909 Gasoline 124,834 64,476 —

Electricity energy (kW/h) — 1,685,636 — Biomass (fiber + shell) (t) — 80,064 —

*The quantities of biodiesel and ethanol mixed in diesel and gasoline, respectively, were computed.*

*Fertilizers, pesticides, fossil fuel and energy inputs, and waste generated in the crude palm oil (CPO)* 

**Agricultural Industrial Transportation**

Diesel kg CO2/L diesel 3.11 [14] Gasoline kg CO2/L gasoline 2.85 [14] Ethanol kg CO2/L ethanol 0.46 [15] Biodiesel kg CO2/L biodiesel 0.39 [15]

Nitrogen kg CO2/kg N 3.14 [16] Phosphate kg CO2/kg P 0.61 [16] Potassium kg CO2/kg K 0.44 [16]

2009 (medium value) t CO2/MWh 0.0245 [17]

Glyphosate kg CO2 eq/kg A.I.1 15.95 [14]

Organophosphate kg CO2 e/kg A.I. 7.68 [14]

POME at anaerobic ponds kg CO2 e/kg DQO 5.00 [14] Biomass (fiber + shell) kg CO2 e/t 22.53 [18]

*Emission factors used to calculate the GHG emissions from crude palm oil (CPO) production in Pará State,* 

**98**

*1*

**Table 2.**

*Brazil.*

**Fuel**

**Fertilizer**

**Electricity**

**Herbicide**

**Insecticide**

**Residues**

*A.I., active ingredient.*

The total GHG emissions resulting from the production of FFB, extraction and transportation of CPO were 112,825 t CO2-eq (**Figure 3**). The main source of GHG was the management of POME, followed by fertilizer application, fuel combustion, pesticide application, and electricity use. The high CH4 emissions in the anaerobic ponds, when converted into CO2-eq represented 66.5% of the total emissions. The use of fertilizers and fuels contributed to 17.9 and 15.1% of the total emissions, respectively. The application and electricity use represented less than 1% of the total GHG emissions (**Figure 4**).

The highest GHG amount emitted from POME is related to CH4 emissions in the anaerobic ponds. The anaerobic ponds located in Agropalma farm are over 2 m deep and the POME has a large amount of C available and, consequently, high COD (chemical oxygen demand). In this study, the COD had an average of 21.65 kg m<sup>−</sup><sup>3</sup> , which is considered a high value by the standards of the Intergovernmental Panel on Climate Change [18] for effluents generated in the vegetable oil industry.

Similar results were found by Choo et al. [19] determining the GHG contribution by subsystems in the oil palm supply chain at Malaysia. The highest emissions were associated to POME without biogas capture. After POME disposal into the ponds, the CH4 content is higher in the outlet region [20]. This is explained by excess concentration of organic matter in the inlet region that would influence the methanogenic activities [21]. As a result, lower CH4 and higher CO2 are emitted from the inlet region.

The fertilizers applied in the seedlings production and oil palm plantations resulted in the second largest GHG emission source. It is important to notice that GHG emissions are released both during the industrial production of fertilizer and through the application of these fertilizers on the field. The cultivation of oil palm requires high inputs of nitrogen fertilizer, which can create high soil emissions due to a conversion into N2O [22].

The oil palm cultivation in Agropalma farm uses small amount of pesticides, resulting in low GHG emissions due to the use of these products (**Figure 3**). In 2009, glyphosate (herbicide) and acephate (insecticide) were used, so that GHG emissions were lower than other results previously reported in Malaysia [13, 19] and in Brazil [12].

The measured fuel combustion was related to agricultural operations, FFB transportation, extraction and transportation of CPO to a refinery. According to previous studies [13, 23], GHG emissions associated to use of diesel in plantations, internal transport and machinery are in order of 180–404 kg CO2-eq ha<sup>−</sup><sup>1</sup> yr.<sup>−</sup><sup>1</sup> . If the FFB yield is set at 21.2 t ha<sup>−</sup><sup>1</sup> , the total emissions would be in order of 8.5–19.1 kg CO2-eq/t FFB. We found a total emission of 23.08 kg CO2-eq/t FFB and this value can be attributed to the highest number of mechanized operations at Agropalma farm compared with the most part of palm oil companies in Southeast Asia. Moreover, we also include the emissions from the combustion of fibers and

**Figure 3.**

*Total GHG emissions (t CO2-eq) in 2009 from crude palm oil production in the Brazilian Amazon region.*

#### **Figure 4.**

*Partition of total GHG emissions from crude palm oil production in the Brazilian Amazon region.*

shells used in the boilers, which represent 10.5% of total emissions from the use of fuels.

The electricity is derived from hydroelectric power plants, which are considered a clean energy source. So, the GHG emissions were low, in agreement with previous results reported by Souza et al. [12]. The use of biomass (shell and fiber) in the boilers also contributed to the reduced use of electricity. In Malaysia, Yee et al. [24] have reported that from the amount of energy generated from the fibers and shell, about 55–77% is being utilized in the milling processes in the form of heat (steam) and power (electricity). The combustion of coproducts in high-efficiency boilers and turbines for power production reduces life cycle GHG emissions even when the most part of the electricity consumed comes from hydroelectric power plants [12].

#### **3.2 GHG emissions in the agricultural phase**

The agricultural phase (seedling production, juvenile and mature plantations) contributed to 28% of the total GHG emissions in the palm oil production, emitting

**101**

**Figure 6.**

**Figure 5.**

*Amazon region.*

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm…*

32,131 t CO2-eq in 2009 (**Figure 5**). The use of fertilizer was the main source of GHG emissions, followed by the use of fuels and pesticides. We found that in the production of FFB, 88% of GHG emissions are related to mature crop stage, while 1 and 9% are from the nursery and juvenile stands, respectively (**Figure 6**). These results are in agreement with other studies analyzing the GHG emission sources in

*GHG emissions (t CO2-eq) from agricultural phase, CPO extraction and transportation in the Brazilian* 

emissions, corroborating with the results reported by Choo et al. [19].

In the oil palm nursery, the inputs of fertilizers and pesticides are relatively low compared to the other stages, and the activities for the seedlings cultivation are performed manually. The use of fuel is required only for the seedlings transportation and irrigation. So, this step contributed to insignificant amounts to the GHG

In the oil palm plantations (juvenile and mature stands), the fertilizer application rate is dependent on a number of factors including yield potential, age of palm plant, nutrient balance, field conditions, and soil types. In 2009, the medium amount or

*GHG emissions (t CO2-eq) in the agricultural phase of CPO production in the Brazilian Amazon region.*

the agricultural phase of oil palm production [23, 25].

*DOI: http://dx.doi.org/10.5772/intechopen.92772*

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm… DOI: http://dx.doi.org/10.5772/intechopen.92772*

#### **Figure 5.**

*CO2 Sequestration*

**100**

of fuels.

**Figure 4.**

**Figure 3.**

shells used in the boilers, which represent 10.5% of total emissions from the use

*Partition of total GHG emissions from crude palm oil production in the Brazilian Amazon region.*

*Total GHG emissions (t CO2-eq) in 2009 from crude palm oil production in the Brazilian Amazon region.*

**3.2 GHG emissions in the agricultural phase**

The electricity is derived from hydroelectric power plants, which are considered a clean energy source. So, the GHG emissions were low, in agreement with previous results reported by Souza et al. [12]. The use of biomass (shell and fiber) in the boilers also contributed to the reduced use of electricity. In Malaysia, Yee et al. [24] have reported that from the amount of energy generated from the fibers and shell, about 55–77% is being utilized in the milling processes in the form of heat (steam) and power (electricity). The combustion of coproducts in high-efficiency boilers and turbines for power production reduces life cycle GHG emissions even when the most part of the electricity consumed comes from hydroelectric power plants [12].

The agricultural phase (seedling production, juvenile and mature plantations) contributed to 28% of the total GHG emissions in the palm oil production, emitting

*GHG emissions (t CO2-eq) from agricultural phase, CPO extraction and transportation in the Brazilian Amazon region.*

32,131 t CO2-eq in 2009 (**Figure 5**). The use of fertilizer was the main source of GHG emissions, followed by the use of fuels and pesticides. We found that in the production of FFB, 88% of GHG emissions are related to mature crop stage, while 1 and 9% are from the nursery and juvenile stands, respectively (**Figure 6**). These results are in agreement with other studies analyzing the GHG emission sources in the agricultural phase of oil palm production [23, 25].

In the oil palm nursery, the inputs of fertilizers and pesticides are relatively low compared to the other stages, and the activities for the seedlings cultivation are performed manually. The use of fuel is required only for the seedlings transportation and irrigation. So, this step contributed to insignificant amounts to the GHG emissions, corroborating with the results reported by Choo et al. [19].

In the oil palm plantations (juvenile and mature stands), the fertilizer application rate is dependent on a number of factors including yield potential, age of palm plant, nutrient balance, field conditions, and soil types. In 2009, the medium amount or

**Figure 6.**

*GHG emissions (t CO2-eq) in the agricultural phase of CPO production in the Brazilian Amazon region.*

fertilizer applied for juvenile stands (1–3 years) was 36 kg N ha<sup>−</sup><sup>1</sup> , while in the mature stands (FFB production areas), it was 48 kg N ha<sup>−</sup><sup>1</sup> . We found that the use of fertilizer contributes to 63% of GHG emissions in the agricultural phase, agreeing with previous results reported by Yee et al. [24], Souza et al. [12], and Choo et al. [19].

The application of fertilizers and harvesting operations and the transportation of FFB from the field to the mill require the use of fossil fuels and biofuels. GHG emissions from the use of fossil fuels and biofuels accounted for 36% of total GHG emissions in the agricultural phase.

#### **3.3 GHG emissions in the CPO extraction**

In the palm oil milling stage, the GHG emissions were from the use of fuels, electricity, and disposal of POME. We observed that CPO extraction was the largest source of GHG emissions (71%) in 2009 (**Figure 5**).

As mentioned before, the use of fuels in the palm oil mill is represented by fossil fuels, biofuels, and residues of CPO extraction (fiber and shells). In the Agropalma farm, 80,000 t of fiber and shells were used as fuel in 2009. Normally, biomass is used for heat and/or power production through direct combustion. Yee et al. [24] have reported that palm oil mills in Malaysia are self-sufficient in terms of electricity consumption due the use of fiber and shells as source of power. The use of fossil fuels blended with biofuels, and residues of CPO extraction contributed to 3.4 and 2.3% of the total GHG emissions (**Figure 7**).

The CH4 from POME in anaerobic ponds represented 94.3% of the total GHG emissions in the palm oil mills. In Malaysia, Shirai et al. [26] and Yacob et al. [27] have reported that the CH4 composition was between 35 and 45% for the anaerobic treatment of POME, while Yacob et al. [20] recorded an average of 54.4%. After 1 year of observation at the anaerobic ponds, these authors observed that CH4 emission pattern is governed by the oil palm seasonal cropping and mill activities. In this study, we used the default value proposed by IPCC, so the continuous monitoring is necessary to obtain the seasonal fluctuations in GHG emissions.

**103**

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm…*

Determining the GHG emissions by subsystems in the oil palm supply chain, Choo et al. [19] also reported the highest emissions associated to POME production. Their results showed reduction of GHG emissions from oil palm mill when the CH4 was captured. Reijnders and Huijbregts [23] reported a reduction on GHG emissions of about 0.15 t CO2-eq/t CPO produced when 95% of control efficiency for the

The fuel combustion during the CPO transportation from the palm oil mill to the refinery represented 1% of the total GHG emissions in 2009 (**Figure 5**). As mentioned before, the transportation of CPO from oil palm mill to refinery at Agropalma farm is performed by barge where one roundtrip carries 1100 t of CPO and consumes 3500 L of diesel. Since 105 roundtrips were performed in 2009, the GHG emissions from the use of diesel at Agropalma farm during the transportation

According to Majer et al. [22], the GHG emissions from transportation process typically represent only a small share of the overall balance results in the biodiesel production. In contrast to our results, Choo et al. [19] reported higher GHG emissions from the transportation process in Malaysia due the distance of oil palm mill until the refinery. The authors point out those GHG emissions could be reduced by improving transport logistic by routing delivery of CPO, for the shortest distance

In the palm oil mill, CPO and KPO are obtained as main products among the several by-products from the extraction process (**Figure 2**). Several studies have reported the GHG emissions considering the production area or the quantity produced [12, 19, 23, 28]. We calculated the GHG emissions related to CPO production using mass allocation based on a specific agricultural year. The carbon footprint was calculated considering the GHG emissions per t of CPO produced at Agropalma farm. In 2009, the CPO and KPO production were 130,210 and 11,205 t, respectively. Considering the agricultural production of FFB, CPO extraction, and CPO transportation from the mill to the refinery, we found an emission of 0.79 t CO2 eq/t CPO produced at Agropalma farm in 2009. As we mentioned before, 66.5% of the total emissions are related to management of POME in the anaerobic ponds. The C footprint of CPO can be reduced significantly since oil palm and palm oil processing wastes are used to replace the input of fossil fuel in palm oil processing stage [29]. This can be combined with a reduction in the amount of CH4 emitted from oil palm processing waste [23]. The company could adopt the system of CH4 capture

Our study is the first to approach carbon footprint considering the different stages (agricultural, industry, and transportation) of CPO production in Brazil. We found that industry is the main source of GHG emissions (71%) due the management of POME in anaerobic ponds. Another study in Thailand [6] has reported similar results, and the GHG emissions in CPO extraction (industry) allocated by energy value were 0.55 t CO2-eq/t CPO. But contrary to what was observed in this

*DOI: http://dx.doi.org/10.5772/intechopen.92772*

**3.4 GHG emissions from the CPO transportation**

treatment of POME is assumed.

of CPO were 1104 t CO2-eq.

between the supplier and the refinery.

**3.5 Carbon footprint of CPO production and transportation**

from POME and use it as electricity or power source [19, 20].

**3.6 Comparative GHG emissions in CPO production**

study, the authors have considered the carbon stocks.

**Figure 7.** *GHG emissions (t CO2-eq) in the palm oil milling stage in the Brazilian Amazon region.*

#### *Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm… DOI: http://dx.doi.org/10.5772/intechopen.92772*

Determining the GHG emissions by subsystems in the oil palm supply chain, Choo et al. [19] also reported the highest emissions associated to POME production. Their results showed reduction of GHG emissions from oil palm mill when the CH4 was captured. Reijnders and Huijbregts [23] reported a reduction on GHG emissions of about 0.15 t CO2-eq/t CPO produced when 95% of control efficiency for the treatment of POME is assumed.

#### **3.4 GHG emissions from the CPO transportation**

*CO2 Sequestration*

fertilizer applied for juvenile stands (1–3 years) was 36 kg N ha<sup>−</sup><sup>1</sup>

izer contributes to 63% of GHG emissions in the agricultural phase, agreeing with previous results reported by Yee et al. [24], Souza et al. [12], and Choo et al. [19]. The application of fertilizers and harvesting operations and the transportation of FFB from the field to the mill require the use of fossil fuels and biofuels. GHG emissions from the use of fossil fuels and biofuels accounted for 36% of total GHG

In the palm oil milling stage, the GHG emissions were from the use of fuels, electricity, and disposal of POME. We observed that CPO extraction was the largest

As mentioned before, the use of fuels in the palm oil mill is represented by fossil fuels, biofuels, and residues of CPO extraction (fiber and shells). In the Agropalma farm, 80,000 t of fiber and shells were used as fuel in 2009. Normally, biomass is used for heat and/or power production through direct combustion. Yee et al. [24] have reported that palm oil mills in Malaysia are self-sufficient in terms of electricity consumption due the use of fiber and shells as source of power. The use of fossil fuels blended with biofuels, and residues of CPO extraction contributed to 3.4 and

The CH4 from POME in anaerobic ponds represented 94.3% of the total GHG emissions in the palm oil mills. In Malaysia, Shirai et al. [26] and Yacob et al. [27] have reported that the CH4 composition was between 35 and 45% for the anaerobic treatment of POME, while Yacob et al. [20] recorded an average of 54.4%. After 1 year of observation at the anaerobic ponds, these authors observed that CH4 emission pattern is governed by the oil palm seasonal cropping and mill activities. In this study, we used the default value proposed by IPCC, so the continuous monitoring is

stands (FFB production areas), it was 48 kg N ha<sup>−</sup><sup>1</sup>

emissions in the agricultural phase.

**3.3 GHG emissions in the CPO extraction**

2.3% of the total GHG emissions (**Figure 7**).

necessary to obtain the seasonal fluctuations in GHG emissions.

*GHG emissions (t CO2-eq) in the palm oil milling stage in the Brazilian Amazon region.*

source of GHG emissions (71%) in 2009 (**Figure 5**).

, while in the mature

. We found that the use of fertil-

**102**

**Figure 7.**

The fuel combustion during the CPO transportation from the palm oil mill to the refinery represented 1% of the total GHG emissions in 2009 (**Figure 5**). As mentioned before, the transportation of CPO from oil palm mill to refinery at Agropalma farm is performed by barge where one roundtrip carries 1100 t of CPO and consumes 3500 L of diesel. Since 105 roundtrips were performed in 2009, the GHG emissions from the use of diesel at Agropalma farm during the transportation of CPO were 1104 t CO2-eq.

According to Majer et al. [22], the GHG emissions from transportation process typically represent only a small share of the overall balance results in the biodiesel production. In contrast to our results, Choo et al. [19] reported higher GHG emissions from the transportation process in Malaysia due the distance of oil palm mill until the refinery. The authors point out those GHG emissions could be reduced by improving transport logistic by routing delivery of CPO, for the shortest distance between the supplier and the refinery.

#### **3.5 Carbon footprint of CPO production and transportation**

In the palm oil mill, CPO and KPO are obtained as main products among the several by-products from the extraction process (**Figure 2**). Several studies have reported the GHG emissions considering the production area or the quantity produced [12, 19, 23, 28]. We calculated the GHG emissions related to CPO production using mass allocation based on a specific agricultural year. The carbon footprint was calculated considering the GHG emissions per t of CPO produced at Agropalma farm. In 2009, the CPO and KPO production were 130,210 and 11,205 t, respectively.

Considering the agricultural production of FFB, CPO extraction, and CPO transportation from the mill to the refinery, we found an emission of 0.79 t CO2 eq/t CPO produced at Agropalma farm in 2009. As we mentioned before, 66.5% of the total emissions are related to management of POME in the anaerobic ponds. The C footprint of CPO can be reduced significantly since oil palm and palm oil processing wastes are used to replace the input of fossil fuel in palm oil processing stage [29]. This can be combined with a reduction in the amount of CH4 emitted from oil palm processing waste [23]. The company could adopt the system of CH4 capture from POME and use it as electricity or power source [19, 20].

#### **3.6 Comparative GHG emissions in CPO production**

Our study is the first to approach carbon footprint considering the different stages (agricultural, industry, and transportation) of CPO production in Brazil. We found that industry is the main source of GHG emissions (71%) due the management of POME in anaerobic ponds. Another study in Thailand [6] has reported similar results, and the GHG emissions in CPO extraction (industry) allocated by energy value were 0.55 t CO2-eq/t CPO. But contrary to what was observed in this study, the authors have considered the carbon stocks.

Determining the GHG contributions by subsystems in the oil palm supply chain using the LCA approach in Malaysia, Choo et al. [19] have reported that the production of 1 t of CPO in a mill without and with biogas capture emitted 0.97 and 0.51 t CO2-eq, respectively. As we found is this study, the contribution of nursery subsystem was found to be minimal, and in the plantation subsystem the major sources of GHG were from nitrogen fertilizers.

Regarding the soil GHG emissions in Indonesian oil palm plantations, Rahman et al. [5] have reported that the use of inorganic fertilizers led to significantly higher N2O emissions. Therefore, as we found is this study that the use of fertilizers accounted for 63% of GHG emissions in the agricultural phase, the use of organic amendments (empty fruit bunches, enriched mulch, and pruned oil palm fronds) can be an option for reducing GHG emissions.

#### **3.7 Mitigation of GHG emissions and opportunities do achieve CO2 sequestration**

The GHG emissions have been reported along the palm oil production chain from the roundtable on sustainable palm oil (RSPO) [30]. Methane (CH4) emissions from wastewater in open ponds at the milling phase and nitrous oxide (N2O) emissions from nitrogen fertilizer application in the cultivation phase are the most related sources of GHG emissions [31, 32].

In this study, the C footprint associated to CPO production was about 0.79 kg CO2/kg CPO and the main source of GHG emissions is associated to management of POME in the anaerobic ponds. Previous study in Thailand also has reported that wastewater treatment and empty-fruit-bunch disposal in mills are a main source of CH4 emissions and cause global warming, with up to 47 and 45% of total global warming impact [33]. So, the effluent treatment in the anaerobic ponds and the combustion of CH4 during anaerobic decomposition [34] are cited as viable strategies to reduce the GHG emissions at the milling phase.

According to Chai et al. [35], energy content in wastewater, in the form of chemical oxygen demand (COD), is usually converted into CO2 or CH4 and biosolids through either aerobic treatment or anaerobic treatment. Therefore, decreasing the degree of aerobic treatment and maximizing energy recovery from CH4 and biosolids are crucial to lower carbon footprint. An efficient anaerobic digestion could contribute to the decrease of the degree of subsequent aerobic treatment, by removing certain amount of COD and reducing CO2 emissions, and recover energy from CH4 by anaerobic digestion.

When the POME is converted into biogas (CH4) through a gasification process and then used to fuel gas engine and generate electricity, it is possible to reduce the environmental impact of CPO production. In addition, other recent technological advances have turned POME to useful sustainable feedstock that can be used to produce valuable by-products like biohydrogen [36] and biomethane [37].

Regarding the oil palm plantations, there are four main steps that contribute to GHG emissions: soil preparation, fertilizer management, weed control, and FFB transportation. In this study, we reported that the use of fertilizer was the main source of GHG emissions, followed by the use of fuels and pesticides. The use of EFB for infield application in young and mature palm areas has been used in the management of soil nutrients and organic matter and promoting the increase of organic carbon in the soil over time [38, 39]. So, the continuous use of EFB as mulching could play a significant role in reducing CO2 emissions into the atmosphere through soil C sequestration [39].

As also mentioned before, the use of *Pueraria phaseoloides* as cover crop can also reduce the use of nitrogen fertilizers in the young and mature palm plantations.

**105**

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm…*

use of EFB and legumes in the agricultural phase can reduce the mineral fertilizer

Considering the production of seedlings and FFB, the extraction and transportation of CPO in a Brazilian commercial farm at Amazon region, it emitted 0.79 t CO2-eq/t CPO produced in 2009. Main contributing factor to GHG emissions during the cultivation step is the use of industrial fertilizers, which accounted for 17.9% of the total GHG emissions mainly due the high input of nitrogen. The management of POME from palm oil mill is the main source of GHG emissions to the atmosphere, representing 66.5% of the carbon footprint during the evaluated period. Regarding the use of fuels in all evaluated stages, they accounted for 15.1%

The POME treatment in the anaerobic ponds and the use of CH4 for steam or electricity production and the use of EFB and legumes in the agricultural phase are cited as the main strategies to reduce the GHG emissions in the palm oil produc-

Our results may be used to encourage new researches and improve the life cycle assessment and the measurements of GHG emissions associated to palm oil produc-

tion chain in Brazil and other regions of South America.

In the Brazilian Amazon region, the maintenance of native vegetation and the use of degraded areas to introduce new oil palm plantations can promote environmental benefits to commercial farms, reducing the GHG emissions. Brazilian government approved a bill to expand 4.3 million ha of previously deforested lands to oil palm plantations [41]. Pará State is intensively studied because the majority of the land deemed suitable for oil palm expansion by the government is located in this state. According to Yui and Yeh [42], the encouragement of oil palm plantations on deforested lands could drastically reduce the conversion of forest land, thus reduc-

to the system through biological nitrogen fixation [40]. So, the

Previous study has reported that the use of legumes contributes about 150 kg

*DOI: http://dx.doi.org/10.5772/intechopen.92772*

ing GHG emissions from deforestation.

demand and consequently minimize GHG emissions.

year<sup>−</sup><sup>1</sup>

nitrogen ha<sup>−</sup><sup>1</sup>

**4. Conclusions**

of the total GHG emissions.

tion system.

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm… DOI: http://dx.doi.org/10.5772/intechopen.92772*

Previous study has reported that the use of legumes contributes about 150 kg nitrogen ha<sup>−</sup><sup>1</sup> year<sup>−</sup><sup>1</sup> to the system through biological nitrogen fixation [40]. So, the use of EFB and legumes in the agricultural phase can reduce the mineral fertilizer demand and consequently minimize GHG emissions.

In the Brazilian Amazon region, the maintenance of native vegetation and the use of degraded areas to introduce new oil palm plantations can promote environmental benefits to commercial farms, reducing the GHG emissions. Brazilian government approved a bill to expand 4.3 million ha of previously deforested lands to oil palm plantations [41]. Pará State is intensively studied because the majority of the land deemed suitable for oil palm expansion by the government is located in this state. According to Yui and Yeh [42], the encouragement of oil palm plantations on deforested lands could drastically reduce the conversion of forest land, thus reducing GHG emissions from deforestation.

#### **4. Conclusions**

*CO2 Sequestration*

**sequestration**

GHG were from nitrogen fertilizers.

can be an option for reducing GHG emissions.

related sources of GHG emissions [31, 32].

from CH4 by anaerobic digestion.

sphere through soil C sequestration [39].

gies to reduce the GHG emissions at the milling phase.

Determining the GHG contributions by subsystems in the oil palm supply chain using the LCA approach in Malaysia, Choo et al. [19] have reported that the production of 1 t of CPO in a mill without and with biogas capture emitted 0.97 and 0.51 t CO2-eq, respectively. As we found is this study, the contribution of nursery subsystem was found to be minimal, and in the plantation subsystem the major sources of

Regarding the soil GHG emissions in Indonesian oil palm plantations, Rahman

The GHG emissions have been reported along the palm oil production chain from the roundtable on sustainable palm oil (RSPO) [30]. Methane (CH4) emissions from wastewater in open ponds at the milling phase and nitrous oxide (N2O) emissions from nitrogen fertilizer application in the cultivation phase are the most

In this study, the C footprint associated to CPO production was about 0.79 kg CO2/kg CPO and the main source of GHG emissions is associated to management of POME in the anaerobic ponds. Previous study in Thailand also has reported that wastewater treatment and empty-fruit-bunch disposal in mills are a main source of CH4 emissions and cause global warming, with up to 47 and 45% of total global warming impact [33]. So, the effluent treatment in the anaerobic ponds and the combustion of CH4 during anaerobic decomposition [34] are cited as viable strate-

According to Chai et al. [35], energy content in wastewater, in the form of chemical oxygen demand (COD), is usually converted into CO2 or CH4 and biosolids through either aerobic treatment or anaerobic treatment. Therefore, decreasing the degree of aerobic treatment and maximizing energy recovery from CH4 and biosolids are crucial to lower carbon footprint. An efficient anaerobic digestion could contribute to the decrease of the degree of subsequent aerobic treatment, by removing certain amount of COD and reducing CO2 emissions, and recover energy

When the POME is converted into biogas (CH4) through a gasification process and then used to fuel gas engine and generate electricity, it is possible to reduce the environmental impact of CPO production. In addition, other recent technological advances have turned POME to useful sustainable feedstock that can be used to produce valuable by-products like biohydrogen [36] and biomethane [37].

Regarding the oil palm plantations, there are four main steps that contribute to GHG emissions: soil preparation, fertilizer management, weed control, and FFB transportation. In this study, we reported that the use of fertilizer was the main source of GHG emissions, followed by the use of fuels and pesticides. The use of EFB for infield application in young and mature palm areas has been used in the management of soil nutrients and organic matter and promoting the increase of organic carbon in the soil over time [38, 39]. So, the continuous use of EFB as mulching could play a significant role in reducing CO2 emissions into the atmo-

As also mentioned before, the use of *Pueraria phaseoloides* as cover crop can also reduce the use of nitrogen fertilizers in the young and mature palm plantations.

et al. [5] have reported that the use of inorganic fertilizers led to significantly higher N2O emissions. Therefore, as we found is this study that the use of fertilizers accounted for 63% of GHG emissions in the agricultural phase, the use of organic amendments (empty fruit bunches, enriched mulch, and pruned oil palm fronds)

**3.7 Mitigation of GHG emissions and opportunities do achieve CO2**

**104**

Considering the production of seedlings and FFB, the extraction and transportation of CPO in a Brazilian commercial farm at Amazon region, it emitted 0.79 t CO2-eq/t CPO produced in 2009. Main contributing factor to GHG emissions during the cultivation step is the use of industrial fertilizers, which accounted for 17.9% of the total GHG emissions mainly due the high input of nitrogen. The management of POME from palm oil mill is the main source of GHG emissions to the atmosphere, representing 66.5% of the carbon footprint during the evaluated period. Regarding the use of fuels in all evaluated stages, they accounted for 15.1% of the total GHG emissions.

The POME treatment in the anaerobic ponds and the use of CH4 for steam or electricity production and the use of EFB and legumes in the agricultural phase are cited as the main strategies to reduce the GHG emissions in the palm oil production system.

Our results may be used to encourage new researches and improve the life cycle assessment and the measurements of GHG emissions associated to palm oil production chain in Brazil and other regions of South America.

### **Author details**

Leidivan Almeida Frazão1 \*, Guilherme Silva Raucci<sup>2</sup> , João Luis Nunes Carvalho3 , Marcelo Valadares Galdos4 , Cindy Silva Moreira<sup>5</sup> , Carlos Eduardo Pellegrino Cerri6 and Carlos Clemente Cerri6


\*Address all correspondence to: lafrazao@ufmg.br

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**107**

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm…*

Solos; 2013

Classificação de Solos. 2nd ed. Rio de Janeiro: Centro Nacional de Pesquisa de

[9] United States Department of Agriculture. Soil Taxonomy: A Basic System of Soil Classification for Making and Interpreting Soil Surveys. 3rd ed. Washington: Soil Survey Staff; 1999

[10] Teoh CH. The Palm Oil Industry in Malaysia: From Seed to Frying Pan.

[11] Arnold MG, Teoh KT, Carlin G. Steam (physical) refining deodorizer for Malaysian palm oil. Journal of the American Oil Chemists Society.

[12] Souza SP, Pacca S, Ávilla MT, Borges JL. Greenhouse gas emissions and energy balance of palm oil biofuel. Renewable Energy. 2010;**35**:2552-2561

[13] Wicke B, Dornburg V, Junginge RM, Faaij M. Different palm oil production systems for energy purposes and their greenhouse gas implications. Biomass and Bioenergy. 2008;**32**:1322-1337

[14] Centre E. Ecoinvent Data. v2.2. Dübendorf: Swiss Centre for Life Cycle

[15] Macedo IC, Seabra JEA, Silva JEAR. Greenhouse gases emissions in the production and use of ethanol from sugarcane in Brazil: The 2005/2006 averages and a prediction for 2020. Biomass and Bioenergy. 2008;**32**:582-595

[16] West T, Marland GA. Synthesis of carbon sequestration, carbon emissions, and net carbon flux in agriculture: Comparing tillage practices in the United States. Agriculture, Ecosystems & Environment. 2002;**91**:217-232

[17] Ministério da Ciência e Tecnologia— MCT. Fatores de Emissão de CO2 para

Malaysia: WWF; 2002

1997;**54**:312-316

Inventories; 2010

*DOI: http://dx.doi.org/10.5772/intechopen.92772*

[2] Ministério da Agricultura, Pecuária e Abastecimento. Diagnóstico da produção sustentável do óleo de palma.

[1] Barcelos E, Almeida Rios S, Cunha RNV, Lopes R, Motoike SY, Babiychuk E, et al. Oil palm natural diversity and the potential for yield improvement. Frontiers in Plant

Science. 2015;**6**:190

**References**

Brasília: MAPA/ACE; 2018

Abastecimiento; 2010

2019;**11**:1056-1074

2017;**22**:1802-1814

[6] Bunchai A, Suttinun O,

[3] Empresa Brasileira de Pesquisa Agropecuária. Dendê. Brasil:

[4] Glass V. Expansão do dendê na Amazônia brasileira: Elementos para uma análise dos impactos sobre a

Ministério da Agricultura, Pecuária e

agricultura familiar no nordeste do Pará. Brasil: Centro de Monitoramento de Agrocombustíveis. ONG Repórter; 2013

[5] Rahman N, Bruun TB, Giller KE, Magid J, Ven GWJ, de Neergaard A. Soil greenhouse gas emissions from inorganic fertilizers and recycled oil palm waste products from Indonesian oil palm plantations. GCB Bioenergy.

H-Kittikun A, Musikavong C. Life cycle greenhouse gas emissions of palm oil production by wet and dry extraction processes in Thailand. International Journal of Life Cycle Assessment.

[7] Menichetti E, Otto M. Energy balance & greenhouse gas emissions of biofuels from a life cycle perspective. In: Howarth RH, Bringezu S, editors. Proceedings of the Scientific Committee

on Problems of the Environment (SCOPE) International Biofuels Project Rapid Assessment. Gummersbach; 2009

[8] Empresa Brasileira de Pesquisa Agropecuária. Sistema Brasileiro de *Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm… DOI: http://dx.doi.org/10.5772/intechopen.92772*

#### **References**

*CO2 Sequestration*

**Author details**

Leidivan Almeida Frazão1

Marcelo Valadares Galdos4

and Carlos Clemente Cerri6

2 Agrosmart, Campinas, SP, Brazil

4 University of Leeds, Leeds, UK

6 University of São Paulo, Piracicaba, SP, Brazil

provided the original work is properly cited.

\*Address all correspondence to: lafrazao@ufmg.br

5 Abiove, São Paulo, SP, Brazil

\*, Guilherme Silva Raucci<sup>2</sup>

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

, Cindy Silva Moreira<sup>5</sup>

1 Federal University of Minas Gerais, Montes Claros, MG, Brazil

3 Brazilian Biorenewables National Laboratory, Campinas, SP, Brazil

, João Luis Nunes Carvalho3

, Carlos Eduardo Pellegrino Cerri6

,

**106**

[1] Barcelos E, Almeida Rios S, Cunha RNV, Lopes R, Motoike SY, Babiychuk E, et al. Oil palm natural diversity and the potential for yield improvement. Frontiers in Plant Science. 2015;**6**:190

[2] Ministério da Agricultura, Pecuária e Abastecimento. Diagnóstico da produção sustentável do óleo de palma. Brasília: MAPA/ACE; 2018

[3] Empresa Brasileira de Pesquisa Agropecuária. Dendê. Brasil: Ministério da Agricultura, Pecuária e Abastecimiento; 2010

[4] Glass V. Expansão do dendê na Amazônia brasileira: Elementos para uma análise dos impactos sobre a agricultura familiar no nordeste do Pará. Brasil: Centro de Monitoramento de Agrocombustíveis. ONG Repórter; 2013

[5] Rahman N, Bruun TB, Giller KE, Magid J, Ven GWJ, de Neergaard A. Soil greenhouse gas emissions from inorganic fertilizers and recycled oil palm waste products from Indonesian oil palm plantations. GCB Bioenergy. 2019;**11**:1056-1074

[6] Bunchai A, Suttinun O, H-Kittikun A, Musikavong C. Life cycle greenhouse gas emissions of palm oil production by wet and dry extraction processes in Thailand. International Journal of Life Cycle Assessment. 2017;**22**:1802-1814

[7] Menichetti E, Otto M. Energy balance & greenhouse gas emissions of biofuels from a life cycle perspective. In: Howarth RH, Bringezu S, editors. Proceedings of the Scientific Committee on Problems of the Environment (SCOPE) International Biofuels Project Rapid Assessment. Gummersbach; 2009

[8] Empresa Brasileira de Pesquisa Agropecuária. Sistema Brasileiro de Classificação de Solos. 2nd ed. Rio de Janeiro: Centro Nacional de Pesquisa de Solos; 2013

[9] United States Department of Agriculture. Soil Taxonomy: A Basic System of Soil Classification for Making and Interpreting Soil Surveys. 3rd ed. Washington: Soil Survey Staff; 1999

[10] Teoh CH. The Palm Oil Industry in Malaysia: From Seed to Frying Pan. Malaysia: WWF; 2002

[11] Arnold MG, Teoh KT, Carlin G. Steam (physical) refining deodorizer for Malaysian palm oil. Journal of the American Oil Chemists Society. 1997;**54**:312-316

[12] Souza SP, Pacca S, Ávilla MT, Borges JL. Greenhouse gas emissions and energy balance of palm oil biofuel. Renewable Energy. 2010;**35**:2552-2561

[13] Wicke B, Dornburg V, Junginge RM, Faaij M. Different palm oil production systems for energy purposes and their greenhouse gas implications. Biomass and Bioenergy. 2008;**32**:1322-1337

[14] Centre E. Ecoinvent Data. v2.2. Dübendorf: Swiss Centre for Life Cycle Inventories; 2010

[15] Macedo IC, Seabra JEA, Silva JEAR. Greenhouse gases emissions in the production and use of ethanol from sugarcane in Brazil: The 2005/2006 averages and a prediction for 2020. Biomass and Bioenergy. 2008;**32**:582-595

[16] West T, Marland GA. Synthesis of carbon sequestration, carbon emissions, and net carbon flux in agriculture: Comparing tillage practices in the United States. Agriculture, Ecosystems & Environment. 2002;**91**:217-232

[17] Ministério da Ciência e Tecnologia— MCT. Fatores de Emissão de CO2 para

utilizações que necessitam do fator médio de emissão do Sistema Interligado Nacional do Brasil, como, por exemplo, inventários corporativos. Brasília: MCT; 2010

[18] Intergovernmental Panel on Climate Change. Guidelines for National Greenhouse Gas Inventories: Agriculture, Forestry and Other Land Use. Vol. 4. Hayama: National Greenhouse Gas Inventories Programme; 2006

[19] Choo YM, Muhamad H, Hashim Z, Subramaniam V, Puah CW, Tan YA. Determination of GHG contributions by subsystems in the oil palm supply chain using the LCA approach. International Journal of Life Cycle Assessment. 2011;**16**:669-681

[20] Yacob S, Hassan MA, Shirai Y, Wakisava M, Subash S. Baseline study of methane emission from anaerobic ponds of palm oil mill effluent treatment. Science of the Total Environment. 2006;**366**:187-196

[21] Masse L, Massé DI. Effect of soluble organic, particulate organic, and hydraulic shock loads on anaerobic sequencing batch reactors treating slaughterhouse wastewater at 20 C. Process Biochemistry. 2005;**40**:1225-1232

[22] Majer S, Mueller-Langer F, Zeller V, Kaltschmitt M. Implications of biodiesel production and utilization on global climate – A literature review. European Journal of Lipid Science and Technology. 2009;**11**:747-762

[23] Reijnders L, Huijbregts MAJ. Palm oil and the emission of carbon-based greenhouse gases. Journal of Cleaner Production. 2008;**16**:477-482

[24] Yee KF, Tan KT, Abdullah AZ, Lee KT. Life cycle assessment of palm biodiesel: Revealing facts and benefits for sustainability. Applied Energy. 2009;**86**:189-196

[25] Hardter R, Chow WY, Hock OS. Intensive plantation cropping: A source of sustainable food and energy production in the tropical rainforest areas in Southeast Asia. Forest Ecology and Management. 1997;**93**:95-102

[26] Shirai Y, Wakisaka M, Yacob S, Hassan MA, Suzuki S. Reduction of methane released from palm oil mill lagoon in Malaysia and its countermeasures. Mitigation and Adaptation Strategies for Global Change. 2003;**8**:237-252

[27] Yacob S, Hassan MA, Shirai Y, Wakisava M, Subash S. Baseline study of methane emission from open digesting tanks of palm oil mill effluent treatment. Chemosphere. 2005;**59**:1575-1581

[28] Stichnothe H, Schuchardt F. Life cycle assessment of two palm oil production systems. Biomass and Bioenergy. 2011;**35**:3976-3984

[29] Yusoff S. Renewable energy from palm oil e an innovation on effective utilization of waste. Journal of Cleaner Production. 2006;**14**:87-93

[30] Bessou C, Chase LC, Henson IE, Abdul-Manan AFN, Milà I, Canals L, et al. Pilot application of palm GHG, the roundtable on sustainable palm oil greenhouse gas calculator for oil palm products. Journal of Cleaner Production. 2014;**73**:136-145

[31] Silalertruksa T, Gheewala SH. Sustainability assessment of palm biodiesel production in Thailand. Journal of Energy. 2012;**43**:306-314

[32] Kaewmai R, H-Kittikun A, Musikavong C. Greenhouse gas emissions of palm oil mills in Thailand. International Journal of Greenhouse Gas Control. 2012;**11**:141-151

[33] Saswattecha K, Kroeze C, Jawjit W, Hein L. Assessing the environmental

**109**

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm…*

http://www.ipsnews.net/2010/12/ brazil-oil-palm-plantations-expand-on-

[42] Yui S, Yeh S. Land use change emissions from oil palm expansion in Pará, Brazil depend on proper policy enforcement on deforested lands. Environmental Research Letters.

degraded-land-in-amazon/

2013;**8**:1-9

*DOI: http://dx.doi.org/10.5772/intechopen.92772*

[34] Rana S, Lakhveer Singh L, Wahid Z, Liu H. A recent overview of palm oil mill effluent management via bioreactor configurations. Current Pollution

[35] Chai C, Zhang D, Yu Y, Feng Y, Wong MS. Carbon footprint analyses of mainstream wastewater treatment technologies under different sludge treatment scenarios in China. Water.

[36] Sivasangar S, Zainal Z, Salmiaton A, Taufiq-Yap YH. Supercritical water gasification of empty fruit bunches from oil palm for hydrogen production.

[37] Montafia P, Gnansounou E. Life cycle assessment of thermochemical conversion of empty fruit bunch of oil palm to biomethane. In: Edgard Gnansounou E, Pandey A, editors. Life-Cycle Assessment of Biorefineries.

[38] Zaharah AR, Lim KC. Oil palm empty fruit bunch as a source of

[39] Moradi A, Sung CTB, Joo GK, Hanif AHN, Ishak CF. Soil organic C sequestration due to different oil palm residue mulches. Advances in Tropical

[40] Agamuthu P, Broughton WJ. Nutrient cycling within the developing

oil palm-legume ecosystem. Agriculture, Ecosystems and Environment. 1985;**13**:111-123

[41] Osava M. Brazil: Oil Palm

Plantations Expand on Degraded Lands in Amazon. Rome: Inter Press Service News Agency; 2010. Available from:

nutrients and soil ameliorant in oil palm plantation. Malaysian Journal of Soil

impact of palm oil produced in Thailand. Journal of Cleaner Production. 2015;**100**:150-169

Reports. 2017;**3**:254-267

2015;**7**:918-938

Fuel. 2015;**143**:563-569

Amsterdam: Elsevier; 2017

Science. 2000;**4**:51-66

Soil Science. 2013:169-186

*Greenhouse Gas Assessment and Strategies to Achieve CO2 Sequestration in the Brazilian Palm… DOI: http://dx.doi.org/10.5772/intechopen.92772*

impact of palm oil produced in Thailand. Journal of Cleaner Production. 2015;**100**:150-169

*CO2 Sequestration*

Programme; 2006

2006;**366**:187-196

2005;**40**:1225-1232

[19] Choo YM, Muhamad H,

Hashim Z, Subramaniam V, Puah CW, Tan YA. Determination of GHG contributions by subsystems in the oil palm supply chain using the LCA approach. International Journal of Life Cycle Assessment. 2011;**16**:669-681

[20] Yacob S, Hassan MA, Shirai Y, Wakisava M, Subash S. Baseline study of methane emission from anaerobic ponds of palm oil mill effluent treatment. Science of the Total Environment.

[21] Masse L, Massé DI. Effect of soluble organic, particulate organic, and hydraulic shock loads on anaerobic sequencing batch reactors treating slaughterhouse wastewater at 20 C. Process Biochemistry.

[22] Majer S, Mueller-Langer F, Zeller V, Kaltschmitt M. Implications of biodiesel production and utilization on global climate – A literature review. European Journal of Lipid Science and

Technology. 2009;**11**:747-762

Production. 2008;**16**:477-482

[24] Yee KF, Tan KT, Abdullah AZ, Lee KT. Life cycle assessment of palm biodiesel: Revealing facts and benefits for sustainability. Applied Energy.

[23] Reijnders L, Huijbregts MAJ. Palm oil and the emission of carbon-based greenhouse gases. Journal of Cleaner

2010

utilizações que necessitam do fator médio de emissão do Sistema Interligado Nacional do Brasil, como, por exemplo, inventários corporativos. Brasília: MCT;

[25] Hardter R, Chow WY, Hock OS. Intensive plantation cropping: A source

[26] Shirai Y, Wakisaka M, Yacob S, Hassan MA, Suzuki S. Reduction of methane released from palm oil mill lagoon in Malaysia and its countermeasures. Mitigation and Adaptation Strategies for Global

[27] Yacob S, Hassan MA, Shirai Y, Wakisava M, Subash S. Baseline study of methane emission from open digesting tanks of palm oil mill effluent treatment. Chemosphere.

[28] Stichnothe H, Schuchardt F. Life cycle assessment of two palm oil production systems. Biomass and Bioenergy. 2011;**35**:3976-3984

[29] Yusoff S. Renewable energy from palm oil e an innovation on effective utilization of waste. Journal of Cleaner

[30] Bessou C, Chase LC, Henson IE, Abdul-Manan AFN, Milà I, Canals L, et al. Pilot application of palm GHG, the roundtable on sustainable palm oil greenhouse gas calculator for oil palm products. Journal of Cleaner Production. 2014;**73**:136-145

[31] Silalertruksa T, Gheewala SH. Sustainability assessment of palm biodiesel production in Thailand. Journal of Energy. 2012;**43**:306-314

[32] Kaewmai R, H-Kittikun A, Musikavong C. Greenhouse gas

Gas Control. 2012;**11**:141-151

emissions of palm oil mills in Thailand. International Journal of Greenhouse

[33] Saswattecha K, Kroeze C, Jawjit W, Hein L. Assessing the environmental

Production. 2006;**14**:87-93

Change. 2003;**8**:237-252

2005;**59**:1575-1581

of sustainable food and energy production in the tropical rainforest areas in Southeast Asia. Forest Ecology and Management. 1997;**93**:95-102

[18] Intergovernmental Panel on Climate Change. Guidelines for National Greenhouse Gas Inventories: Agriculture, Forestry and Other Land Use. Vol. 4. Hayama: National Greenhouse Gas Inventories

**108**

2009;**86**:189-196

[34] Rana S, Lakhveer Singh L, Wahid Z, Liu H. A recent overview of palm oil mill effluent management via bioreactor configurations. Current Pollution Reports. 2017;**3**:254-267

[35] Chai C, Zhang D, Yu Y, Feng Y, Wong MS. Carbon footprint analyses of mainstream wastewater treatment technologies under different sludge treatment scenarios in China. Water. 2015;**7**:918-938

[36] Sivasangar S, Zainal Z, Salmiaton A, Taufiq-Yap YH. Supercritical water gasification of empty fruit bunches from oil palm for hydrogen production. Fuel. 2015;**143**:563-569

[37] Montafia P, Gnansounou E. Life cycle assessment of thermochemical conversion of empty fruit bunch of oil palm to biomethane. In: Edgard Gnansounou E, Pandey A, editors. Life-Cycle Assessment of Biorefineries. Amsterdam: Elsevier; 2017

[38] Zaharah AR, Lim KC. Oil palm empty fruit bunch as a source of nutrients and soil ameliorant in oil palm plantation. Malaysian Journal of Soil Science. 2000;**4**:51-66

[39] Moradi A, Sung CTB, Joo GK, Hanif AHN, Ishak CF. Soil organic C sequestration due to different oil palm residue mulches. Advances in Tropical Soil Science. 2013:169-186

[40] Agamuthu P, Broughton WJ. Nutrient cycling within the developing oil palm-legume ecosystem. Agriculture, Ecosystems and Environment. 1985;**13**:111-123

[41] Osava M. Brazil: Oil Palm Plantations Expand on Degraded Lands in Amazon. Rome: Inter Press Service News Agency; 2010. Available from:

http://www.ipsnews.net/2010/12/ brazil-oil-palm-plantations-expand-ondegraded-land-in-amazon/

[42] Yui S, Yeh S. Land use change emissions from oil palm expansion in Pará, Brazil depend on proper policy enforcement on deforested lands. Environmental Research Letters. 2013;**8**:1-9

**Chapter 7**

**Abstract**

Capture

model and determination coefficient (r2

production in future studies.

**1. Introduction**

per year [2].

**111**

Experimental Study of Adsorption

The adsorption of carbon dioxide (CO2) on activated carbon (AC) prepared from olive trees has been investigated by using a fixed bed adsorption apparatus. The adsorption equilibrium and breakthrough curves were determined at different temperatures 30, 50, 70, and 90°C in order to investigate both kinetic and thermodynamic parameters. Maximum CO2 sorption capacity on AC ranged from 109.5 to 35.46 and from 129.65 to 35.55 mg CO2/g of AC for initial concentrations 10 and 13.725% vol., respectively. Different isotherm models are applied to mathematically model the CO2 adsorption, and on the basis of the estimated adsorption capacity by

to the experimental data owing to closeness of the r2 to unity. From the correlation coefficient, it is found that the pseudo-second-order model is well-fitted with the experimental data. In addition, it indicates that CO2 adsorption is a physical adsorption process and demonstrates a behavior of an exothermic reaction, which is consistent with the thermodynamic analysis. The results obtained in this study conclude that AC prepared from olive trees can be considered as adequate for designing a fixed bed cycle to separate carbon dioxide from flue gases and serve as a benchmark while searching for inexpensive and superior activated carbon

**Keywords:** adsorption, breakthrough, equilibrium, kinetic, thermodynamic

in the concentration of this gas in the atmosphere [1]. The amount of carbon dioxide in the atmosphere is currently increasing globally by around 6 billion tons

The emissions of CO2 from burn fossil fuels are the major reason for the increase

A feasible technique method used industrially in reduction of CO2 emissions is capture and storage. CO2 capture means separating the CO2 from other gases in flue. The advanced technologies being used worldwide for CO2 capture in different arrangements are post-combustion, pre-combustion, and oxy-fuel processes [1]. Numerous investigations have been done for CO2 capture field by using adsorption, which are indicating to the effective usage of a post-combustion treatment of gas emissions of flue. The proposed schemes in a cycle process of capture by adsorption include pressure swing adsorption (PSA) and temperature swing

), the Langmuir model provides a perfect fit

on Activated Carbon for CO2

*Hesham G. Ibrahim and Mohamed A. Al-Meshragi*

#### **Chapter 7**

## Experimental Study of Adsorption on Activated Carbon for CO2 Capture

*Hesham G. Ibrahim and Mohamed A. Al-Meshragi*

#### **Abstract**

The adsorption of carbon dioxide (CO2) on activated carbon (AC) prepared from olive trees has been investigated by using a fixed bed adsorption apparatus. The adsorption equilibrium and breakthrough curves were determined at different temperatures 30, 50, 70, and 90°C in order to investigate both kinetic and thermodynamic parameters. Maximum CO2 sorption capacity on AC ranged from 109.5 to 35.46 and from 129.65 to 35.55 mg CO2/g of AC for initial concentrations 10 and 13.725% vol., respectively. Different isotherm models are applied to mathematically model the CO2 adsorption, and on the basis of the estimated adsorption capacity by model and determination coefficient (r2 ), the Langmuir model provides a perfect fit to the experimental data owing to closeness of the r2 to unity. From the correlation coefficient, it is found that the pseudo-second-order model is well-fitted with the experimental data. In addition, it indicates that CO2 adsorption is a physical adsorption process and demonstrates a behavior of an exothermic reaction, which is consistent with the thermodynamic analysis. The results obtained in this study conclude that AC prepared from olive trees can be considered as adequate for designing a fixed bed cycle to separate carbon dioxide from flue gases and serve as a benchmark while searching for inexpensive and superior activated carbon production in future studies.

**Keywords:** adsorption, breakthrough, equilibrium, kinetic, thermodynamic

#### **1. Introduction**

The emissions of CO2 from burn fossil fuels are the major reason for the increase in the concentration of this gas in the atmosphere [1]. The amount of carbon dioxide in the atmosphere is currently increasing globally by around 6 billion tons per year [2].

A feasible technique method used industrially in reduction of CO2 emissions is capture and storage. CO2 capture means separating the CO2 from other gases in flue. The advanced technologies being used worldwide for CO2 capture in different arrangements are post-combustion, pre-combustion, and oxy-fuel processes [1].

Numerous investigations have been done for CO2 capture field by using adsorption, which are indicating to the effective usage of a post-combustion treatment of gas emissions of flue. The proposed schemes in a cycle process of capture by adsorption include pressure swing adsorption (PSA) and temperature swing

adsorption (TSA) [1, 3–5]. The capture of carbon dioxide by adsorptive process is mainly based on preferential adsorption of this gas on a porous adsorbent. Thus, the first and most important step is to find a suitable adsorbent [1]. Carbon materials are relatively insensitive to moisture and are suitable candidates for CO2 capture due to their pore structure and surface chemistry properties [6].

In recent years, considerable attention has been focused on removal of pollutants by using adsorbents derived from low-cost agro-wastes. Olive trees (*Olea europaea*) are abundantly found and easily available in the Mediterranean countries generally and especially Libya. Thus, the aim of the present study is to describe the dynamics and equilibrium of CO2-N2 mixture adsorption on local activated carbon (AC) prepared from olive trees using the breakthrough curve method. Experimental breakthrough curves are used to obtain equilibrium data, and then Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich equilibrium adsorption models were applied. Kinetic models examined herein are simple first-order, pseudo-first-order, pseudo-second-order, and intra-particle diffusion. Model validity with experimental data is assessed by using the coefficient of determination (r<sup>2</sup> ); the closer the value to unity means that the model will be better. Thermodynamic analysis of adsorption of CO2 on AC estimates the values of enthalpy, free energy, and entropy. Also, effects of the interaction between CO2 and NO are studied.

N2 and CO2 were supplied by pressurized cylinders. The purity for CO2, NO, and N2 cylinders was 99.9, 99, and 99.99% (vol.%), respectively. The used concentrations of CO2 were 10 and 13.725% (vol.%). Delivery of the feed gas was controlled by mass flow meter. After mixing in a mixing chamber (2.45 cm diameter and 15 cm length), simulated gas was fed into the inlet of the adsorber. Prior to all measurements, an initial degassing of the sample was performed at a given temperature (30, 50, 70, and 90°C) by the flow of nitrogen until reaching steady state. Then mixed gas was passed through the fixed bed column at constant temperature. The inlet and outlet concentrations were analyzed by a Testo 350XL flue gas, which has a resolution for N2, NO, and CO2 of 0.1 ppm, 0.1 ppm, and 0.1% vol., respectively. The total flow was kept constant for 12 l/min; whereas the N2 and CO2 were controlled precisely according to the required balance gas N2 during binary experiments. The dynamic adsorption capacity of CO2 onto AC column was calculated using Eqs. (1) and (2) [10]:

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture*

*DOI: http://dx.doi.org/10.5772/intechopen.85834*

*t* ¼ ð*t*

*qi* <sup>¼</sup> *<sup>Q</sup> <sup>v</sup>:yi*

weight of the adsorbent (g).

**2.3 Adsorption isotherm studies**

three times for accuracy.

**113**

**Figure 1.**

*Schematic of the experimental set-up.*

0

<sup>1</sup> � *<sup>c</sup> co*

*:t:ρ<sup>i</sup>*

where *t* is the time of adsorption (min.), *C* is the outlet concentration of CO2 gas (mg/l), *Co* is the inlet concentration of CO2 gas (mg/l), *qi* is the amount of adsorbed gases (mg gas/g adsorbent), *Qv* is the volumetric flow rate of CO2 gas (l/min.), *yi* is the mole fraction of inlet CO2, *ρ<sup>i</sup>* is the density of inlet gas (mg/l), and *m* is the

The interval times for measurements were 5, 10, 15, 20, 25, 30, 35, 40, 50, 60, 70, and 80 min. The experimental procedures and measurements are replicated

In order to optimize the design of a sorption system to capture CO2 on AC, the suitable isotherm model for equilibrium curves must be established. Equilibrium models that have been examined herein are Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich. The conformity between the predicted values of models and experimental data is expressed by comparing the experimental adsorption

� �*dt* (1)

*<sup>m</sup>* <sup>∗</sup> <sup>1000</sup> (2)

#### **2. Materials and methods**

#### **2.1 Preparation of activated carbon**

The prepared activated carbon based on charcoal was prepared from olive trees for low cost and was abundantly available. The used activated carbon was obtained from the local area. The raw material of charcoal as received was crushed, ground, and sieved, and only the fraction of particle size 5 mm was chosen as the mean particle diameter. Then it is heated in an oven for 48 h up to 115°C to dry and activate (to remove the absorbed gases and moisture it contains) [7, 8]. The produced activated carbon is then stored in a tightly closed container to be used as required. The total pore volume and surface area of AC were determined using Gemini VII 2390a analyzer. The particle size is obtained by using standard mesh sieves (standard sieve AS 200), and average value of bed porosity is calculated in terms of the average diameter of particles [9].

#### **2.2 Dynamic adsorption capacity of carbon dioxide**

A laboratory system used for measuring breakthrough curve was set up and shown in **Figure 1**. The adsorber which is made of carbon steel tube, consists of three zones:


*Experimental Study of Adsorption on Activated Carbon for CO2 Capture DOI: http://dx.doi.org/10.5772/intechopen.85834*

**Figure 1.** *Schematic of the experimental set-up.*

adsorption (TSA) [1, 3–5]. The capture of carbon dioxide by adsorptive process is mainly based on preferential adsorption of this gas on a porous adsorbent. Thus, the first and most important step is to find a suitable adsorbent [1]. Carbon materials are relatively insensitive to moisture and are suitable candidates for CO2 capture

In recent years, considerable attention has been focused on removal of pollutants by using adsorbents derived from low-cost agro-wastes. Olive trees (*Olea europaea*) are abundantly found and easily available in the Mediterranean countries generally and especially Libya. Thus, the aim of the present study is to describe the dynamics and equilibrium of CO2-N2 mixture adsorption on local activated carbon (AC) prepared from olive trees using the breakthrough curve method. Experimental breakthrough curves are used to obtain equilibrium data, and then Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich equilibrium adsorption models were applied. Kinetic models examined herein are simple first-order, pseudo-first-order, pseudo-second-order, and intra-particle diffusion. Model

due to their pore structure and surface chemistry properties [6].

validity with experimental data is assessed by using the coefficient of

Thermodynamic analysis of adsorption of CO2 on AC estimates the values of enthalpy, free energy, and entropy. Also, effects of the interaction between CO2

The prepared activated carbon based on charcoal was prepared from olive trees for low cost and was abundantly available. The used activated carbon was obtained from the local area. The raw material of charcoal as received was crushed, ground, and sieved, and only the fraction of particle size 5 mm was chosen as the mean particle diameter. Then it is heated in an oven for 48 h up to 115°C to dry and activate (to remove the absorbed gases and moisture it contains) [7, 8]. The produced activated carbon is then stored in a tightly closed container to be used as required. The total pore volume and surface area of AC were determined using Gemini VII 2390a analyzer. The particle size is obtained by using standard mesh sieves (standard sieve AS 200), and average value of bed porosity is calculated in

A laboratory system used for measuring breakthrough curve was set up and shown in **Figure 1**. The adsorber which is made of carbon steel tube, consists of

• Calming zone with 6.5 cm diameter and 8 cm length containing spherical

• Active zone with 8.44 cm diameter and 39 cm length containing the activated carbon particles, and it was surrounded by a shell containing a heating medium.

• Ending zone with 6.5 cm diameter and 8 cm length containing spherical

); the closer the value to unity means that the model will be better.

determination (r<sup>2</sup>

*CO2 Sequestration*

and NO are studied.

three zones:

**112**

**2. Materials and methods**

**2.1 Preparation of activated carbon**

terms of the average diameter of particles [9].

particles of carbon steel.

particles of carbon steel.

**2.2 Dynamic adsorption capacity of carbon dioxide**

N2 and CO2 were supplied by pressurized cylinders. The purity for CO2, NO, and N2 cylinders was 99.9, 99, and 99.99% (vol.%), respectively. The used concentrations of CO2 were 10 and 13.725% (vol.%). Delivery of the feed gas was controlled by mass flow meter. After mixing in a mixing chamber (2.45 cm diameter and 15 cm length), simulated gas was fed into the inlet of the adsorber. Prior to all measurements, an initial degassing of the sample was performed at a given temperature (30, 50, 70, and 90°C) by the flow of nitrogen until reaching steady state. Then mixed gas was passed through the fixed bed column at constant temperature. The inlet and outlet concentrations were analyzed by a Testo 350XL flue gas, which has a resolution for N2, NO, and CO2 of 0.1 ppm, 0.1 ppm, and 0.1% vol., respectively. The total flow was kept constant for 12 l/min; whereas the N2 and CO2 were controlled precisely according to the required balance gas N2 during binary experiments. The dynamic adsorption capacity of CO2 onto AC column was calculated using Eqs. (1) and (2) [10]:

$$t = \int\_0^t \left(1 - \frac{c}{c\_o}\right) dt\tag{1}$$

$$q\_i = \frac{Q\_{\nu\nu} y\_i.t.\rho\_i}{m} \ast 1000\tag{2}$$

where *t* is the time of adsorption (min.), *C* is the outlet concentration of CO2 gas (mg/l), *Co* is the inlet concentration of CO2 gas (mg/l), *qi* is the amount of adsorbed gases (mg gas/g adsorbent), *Qv* is the volumetric flow rate of CO2 gas (l/min.), *yi* is the mole fraction of inlet CO2, *ρ<sup>i</sup>* is the density of inlet gas (mg/l), and *m* is the weight of the adsorbent (g).

The interval times for measurements were 5, 10, 15, 20, 25, 30, 35, 40, 50, 60, 70, and 80 min. The experimental procedures and measurements are replicated three times for accuracy.

#### **2.3 Adsorption isotherm studies**

In order to optimize the design of a sorption system to capture CO2 on AC, the suitable isotherm model for equilibrium curves must be established. Equilibrium models that have been examined herein are Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich. The conformity between the predicted values of models and experimental data is expressed by comparing the experimental adsorption

capacity with the adsorption capacity estimated by these models, by means of the determination coefficient (r2 , values close or equal to 1) [11, 12].

#### *2.3.1 The Langmuir isotherm*

The widely used Langmuir isotherm found as a successful application in many real sorption processes [12] is expressed as

$$q\_{\epsilon} = \frac{K\_L C\_{\epsilon}}{1 + a\_L C\_{\epsilon}} \tag{3}$$

*2.3.4 Dubinin-Radushkevich isotherm*

*DOI: http://dx.doi.org/10.5772/intechopen.85834*

**2.4 Kinetic models of adsorption**

[17–19]. The determination coefficient (r2

nation coefficient (r2

**115**

*2.4.1 Simple first-order model*

The Dubinin-Radushkevich equation in Eq*.* (9) is as follows [15]:

*<sup>ε</sup>* <sup>¼</sup> *RT M*

bulk to the surface of AC which is calculated by using Eq. (12) [14, 16]:

A linear form of Dubinin-Radushkevich isotherm is

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture*

and it's related with equilibrium concentration as follows:

Dubinin-Radushkevich isotherm constant (mol<sup>2</sup>

*qe* ¼ *qm e*

where *qm* is the Dubinin-Radushkevich monolayer capacity (mg/g), *β* is the

ln 1 þ

where *R* is the universal constant of gases (8.314 J/mol.K),*T* is the experiment temperature (K), and *M* is the molecular weight of CO2. The constant *β* gives the mean free energy of adsorption (*E*) for CO2 molecules transported from the gas

> *<sup>E</sup>* <sup>¼</sup> <sup>1</sup> ffiffiffiffiffi

To determine an appropriate kinetic model is necessary to analyze the experimental data to investigate the mechanism of adsorption process that may include mass transfer or chemical reaction. Also, other extensive models applied to many models such as homogenous surface diffusion model and heterogeneous diffusion model (also known as pore and diffusion models, respectively) have been extensively applied to expound the adsorbate transfer onto the particles of adsorbent

the predicted values of models with experimental data (determination coefficient value close or equal to 1). The validity of these models is evaluated by the determi-

The sorption kinetic may be described by a simple order equation [21, 22]. The following simple first-order equation describes the change in bulk concentration:

implies the best fitting toward the particular kinetic model [20].

log Ct <sup>¼</sup> k1

2*:*303

where *Ct* and *Co* are the concentration of adsorbate at time t and initially (mg/l),

that can be rearranged to obtain a linear form

respectively, and k1 is the first-order rate constant, (1/min).

�*βε*<sup>2</sup>

/kJ<sup>2</sup>

1 *Ce*

ln *qe* <sup>¼</sup> ln *qm* � *βε*<sup>2</sup> (10)

), and *ε* is the Polanyi potential,

� � (11)

<sup>2</sup>*<sup>β</sup>* <sup>p</sup> (12)

) is used to examine the confirmation of

Ct <sup>¼</sup> Coek1t (13)

t þ log Co (14)

), which is within the range of 0–1, in which r<sup>2</sup> closer to unity

(9)

A linear form of this expression is

$$\frac{C\_{\epsilon}}{q\_{\epsilon}} = \frac{1}{K\_{L}} + \frac{a\_{L}}{K\_{L}} C\_{\epsilon} \tag{4}$$

where *qe* is the amount of adsorbed CO2 per unit weight of AC at equilibrium (mg/g) and *Ce* is the unadsorbed CO2 concentration in effluent at equilibrium (mg/l). *KL* is the Langmuir equilibrium constant, and *KL/aL* value is used to estimate the theoretical monolayer capacity of AC, *Qo* (mg/g). Therefore, the plot of *Ce/qe* versus *Ce* enables one to determine the constants *aL* and *KL*.

#### *2.3.2 The Freundlich isotherm*

The well-known Freundlich isotherm is often used for heterogeneous surface energy systems [12]. The Freundlich equation is given as

$$q\_e = K\_F C\_e^{\natural\_n} \tag{5}$$

A linear form of this expression is

$$\log q\_{\epsilon} = \log K\_F + \frac{1}{n} \text{ log C}\_{\epsilon} \tag{6}$$

where *KF* is the Freundlich constant (mg/g) and *n* is the Freundlich exponent. *KF* and *n* can be determined from the linear plot of log *qe* versus log *Ce*.

#### *2.3.3 Temkin isotherm*

The Temkin isotherm [13, 14] has been used in the following form:

$$q\_{\epsilon} = \frac{RT}{b} \ln \left( A C\_{\epsilon} \right) \tag{7}$$

A linear form of the Temkin isotherm can be expressed as

$$q\_{\epsilon} = \frac{RT}{b} \ln A + \frac{RT}{b} \ln C\_{\epsilon} \tag{8}$$

where *A* is the Temkin isotherm equilibrium binding constant (l/g), *b* is the Temkin isotherm constant, *R* is the universal gas constant (8.314 J/mol.K), T is the temperature, and *B* (=*RT/b*) is the constant related to heat of adsorption (J/mol).

The sorption data can be analyzed according to Eq. (8). Therefore, the plot of *qe* versus ln(*Ce*) enables one to determine the constants *A* and *B*.

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture DOI: http://dx.doi.org/10.5772/intechopen.85834*

#### *2.3.4 Dubinin-Radushkevich isotherm*

capacity with the adsorption capacity estimated by these models, by means of the

The widely used Langmuir isotherm found as a successful application in many

*qe* <sup>¼</sup> *KLCe* 1 þ *aLCe*

where *qe* is the amount of adsorbed CO2 per unit weight of AC at equilibrium (mg/g) and *Ce* is the unadsorbed CO2 concentration in effluent at equilibrium (mg/l). *KL* is the Langmuir equilibrium constant, and *KL/aL* value is used to estimate the theoretical monolayer capacity of AC, *Qo* (mg/g). Therefore, the plot of *Ce/qe*

The well-known Freundlich isotherm is often used for heterogeneous surface

*qe* <sup>¼</sup> *KFC*<sup>1</sup>*=<sup>n</sup>*

where *KF* is the Freundlich constant (mg/g) and *n* is the Freundlich exponent. *KF*

*1*

log *qe* ¼ log *KF* þ

The Temkin isotherm [13, 14] has been used in the following form:

*qe* <sup>¼</sup> *RT*

*<sup>b</sup>* ln *<sup>A</sup>* <sup>þ</sup>

where *A* is the Temkin isotherm equilibrium binding constant (l/g), *b* is the Temkin isotherm constant, *R* is the universal gas constant (8.314 J/mol.K), T is the temperature, and *B* (=*RT/b*) is the constant related to heat of adsorption (J/mol). The sorption data can be analyzed according to Eq. (8). Therefore, the plot of *qe*

*RT*

and *n* can be determined from the linear plot of log *qe* versus log *Ce*.

A linear form of the Temkin isotherm can be expressed as

versus ln(*Ce*) enables one to determine the constants *A* and *B*.

*qe* <sup>¼</sup> *RT*

*Ce qe* ¼ 1 *KL* þ *aL KL*

versus *Ce* enables one to determine the constants *aL* and *KL*.

energy systems [12]. The Freundlich equation is given as

, values close or equal to 1) [11, 12].

(3)

*Ce* (4)

*<sup>e</sup>* (5)

*<sup>n</sup>* log *Ce* (6)

*<sup>b</sup>* ln ð Þ *ACe* (7)

*<sup>b</sup>* ln*Ce* (8)

determination coefficient (r2

*CO2 Sequestration*

*2.3.1 The Langmuir isotherm*

*2.3.2 The Freundlich isotherm*

*2.3.3 Temkin isotherm*

**114**

A linear form of this expression is

real sorption processes [12] is expressed as

A linear form of this expression is

The Dubinin-Radushkevich equation in Eq*.* (9) is as follows [15]:

$$q\_{\epsilon} = q\_m \, e^{-\beta \epsilon^2} \tag{9}$$

A linear form of Dubinin-Radushkevich isotherm is

$$
\ln q\_{\varepsilon} = \ln q\_{m} - \beta \varepsilon^{2} \tag{10}
$$

where *qm* is the Dubinin-Radushkevich monolayer capacity (mg/g), *β* is the Dubinin-Radushkevich isotherm constant (mol<sup>2</sup> /kJ<sup>2</sup> ), and *ε* is the Polanyi potential, and it's related with equilibrium concentration as follows:

$$
\varepsilon = \frac{RT}{M} \ln\left(1 + \frac{1}{C\_{\varepsilon}}\right) \tag{11}
$$

where *R* is the universal constant of gases (8.314 J/mol.K),*T* is the experiment temperature (K), and *M* is the molecular weight of CO2. The constant *β* gives the mean free energy of adsorption (*E*) for CO2 molecules transported from the gas bulk to the surface of AC which is calculated by using Eq. (12) [14, 16]:

$$E = \frac{1}{\sqrt{2\beta}}\tag{12}$$

#### **2.4 Kinetic models of adsorption**

To determine an appropriate kinetic model is necessary to analyze the experimental data to investigate the mechanism of adsorption process that may include mass transfer or chemical reaction. Also, other extensive models applied to many models such as homogenous surface diffusion model and heterogeneous diffusion model (also known as pore and diffusion models, respectively) have been extensively applied to expound the adsorbate transfer onto the particles of adsorbent [17–19]. The determination coefficient (r2 ) is used to examine the confirmation of the predicted values of models with experimental data (determination coefficient value close or equal to 1). The validity of these models is evaluated by the determination coefficient (r2 ), which is within the range of 0–1, in which r<sup>2</sup> closer to unity implies the best fitting toward the particular kinetic model [20].

#### *2.4.1 Simple first-order model*

The sorption kinetic may be described by a simple order equation [21, 22]. The following simple first-order equation describes the change in bulk concentration:

$$\mathbf{C}\_{\mathbf{t}} = \mathbf{C}\_{\mathbf{o}} \mathbf{e}^{\mathbf{k}\_{\mathbf{t}} \mathbf{t}} \tag{13}$$

that can be rearranged to obtain a linear form

$$
\log \mathbf{C}\_{\mathbf{t}} = \frac{\mathbf{k}\_1}{2.303} \mathbf{t} + \log \mathbf{C}\_{\mathbf{o}} \tag{14}
$$

where *Ct* and *Co* are the concentration of adsorbate at time t and initially (mg/l), respectively, and k1 is the first-order rate constant, (1/min).

Furthermore, Sparks [23] and Hossain et al*.* [21] proposed that the simple kinetic models such as first- or second-order rate equations are not applicable to the adsorption system with solid surfaces.

#### *2.4.2 Pseudo-first-order model*

The sorption kinetics may be described by pseudo-first Eq. (15) [13, 21, 24–26]:

$$\frac{dq\_t}{dt} = k\_1(q\_\epsilon - q\_t) \tag{15}$$

*2.4.4 Intra-particle diffusion model*

*DOI: http://dx.doi.org/10.5772/intechopen.85834*

concentrations in the bulk [24, 34].

**2.5 Thermodynamic studies**

**3. Results and discussion**

**3.1 Adsorbent characterization**

*Characteristics of used AC depending on particle diameter.*

follows [12, 35]:

CO2 capture.

**Table 1.**

**117**

**3.2 Dynamic studies**

The intra-particle diffusion model is expressed as [31–33]

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture*

*qt* ¼ *kpt*

where *kp* is a rate factor (present CO2 adsorbed per minute). The plot of this model is multi-linear that indicates there are two or more steps occurring consecutively. The external surface/instantaneous adsorption stage occurred first in sharp portion. Then a gradual adsorption stage is in the second portion, where the controlled rate is the intra-particle diffusion. Final equilibrium stage occurs where intra-particle diffusion begins to slow down because of extremely low adsorbate

Thermodynamic parameters were estimated from Langmuir isotherms by using the Van't Hoff's equation as in Eqs. (22) and (23). The thermodynamic parameters can be estimated from Langmuir isotherms by using the Van't Hoff's equation as

*<sup>R</sup>* � *<sup>Δ</sup>H<sup>o</sup>*

ln *aL* <sup>¼</sup> *<sup>Δ</sup>S<sup>o</sup>*

(8.314 J/mol.K), and *T* is an absolute temperature of gas.

where *aL* is a Langmuir constant (l/mol), *R* is the universal constant of gases

The main characteristics of AC (particle diameter, bed porosity, weight of bed, BET surface area, and pore volume) are shown in **Table 1**. Due to a high value BET surface area for used AC, its good pore structure makes it a suitable candidate for

Two mixtures of CO2 and N2 gases have been used in experiments (initial concentrations of CO2 are 10 and 13.725% vol., respectively). **Figure 2** shows that

**Characteristic Value Unit** Particle diameter 5 mm Bed porosity 0.304 — Weight of bed 500 g BET surface area 602 m<sup>2</sup>

Pore volume 0.61 cm<sup>3</sup>

<sup>0</sup>*:*<sup>5</sup> <sup>þ</sup> *<sup>c</sup>* (21)

*<sup>Δ</sup>G<sup>o</sup>* ¼ �*RTlnaL* (22)

*RT* (23)

/g

/g

Integration of Eq. (15) and using the initial conditions *qt* = 0 at *t* = 0 and *qt* = *qt* at *t* = *t* yield

$$\log\left(\frac{q\_{\epsilon}}{q\_{\epsilon}-q\_{t}}\right) = \frac{k\_{1}}{2.303}t\tag{16}$$

By rearrangement of Eq. (16), a linear form is obtained:

$$
\log\left(q\_{\epsilon}-q\right) = \log q\_{\epsilon} - \frac{k\_1}{2.303}t \tag{17}
$$

where *qe* is the amount of CO2 adsorbed at equilibrium (mg/g), *q* is the amount of CO2 adsorbed at time *t* (mg/g), and *k1* is the pseudo-first-order constant (1/min).

The pseudo-first-order constant *k1* and equilibrium adsorption *qe* are determined by plot of log(*qe-q*) versus *t*.

#### *2.4.3 Pseudo-second-order model*

The adsorption kinetics may also be described by pseudo-second-order Eq. (17) [13, 26–30]:

$$\frac{dq\_t}{dt} = k\_2 \left(q\_\epsilon - q\_t\right)^2\tag{18}$$

Integrating Eq. (18) and applying the initial boundaries yield

$$\frac{1}{\left(q\_{\epsilon}-q\_{t}\right)} = \frac{1}{q\_{\epsilon}} + k\_{2}t \tag{19}$$

By rearrangement Eq. (19), a linear form is obtained:

$$\frac{t}{q\_t} = \frac{1}{k\_2 q\_e^{-2}} + \frac{1}{q\_e} t \tag{20}$$

where *k2* is the equilibrium rate constant of pseudo-second-order adsorption (g/mg.min).

The slopes and intercepts of plots *t/qe* versus *t* are used to calculate the pseudo-second-order rate constants *k2* and *qe*.

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture DOI: http://dx.doi.org/10.5772/intechopen.85834*

#### *2.4.4 Intra-particle diffusion model*

Furthermore, Sparks [23] and Hossain et al*.* [21] proposed that the simple kinetic models such as first- or second-order rate equations are not applicable to the

The sorption kinetics may be described by pseudo-first Eq. (15) [13, 21, 24–26]:

(15)

<sup>2</sup>*:*<sup>303</sup> *<sup>t</sup>* (16)

<sup>2</sup>*:*<sup>303</sup> *<sup>t</sup>* (17)

<sup>2</sup> (18)

þ *k*2*t* (19)

*t* (20)

*dt* <sup>¼</sup> *<sup>k</sup>*<sup>1</sup> *qe* � *qt*

log *qe* � *<sup>q</sup>* <sup>¼</sup> log *qe* � *<sup>k</sup>*<sup>1</sup>

The pseudo-first-order constant *k1* and equilibrium adsorption *qe* are determined

The adsorption kinetics may also be described by pseudo-second-order Eq. (17)

*dt* <sup>¼</sup> *<sup>k</sup>*<sup>2</sup> *qe* � *qt*

*qe*

*dqt*

Integrating Eq. (18) and applying the initial boundaries yield

By rearrangement Eq. (19), a linear form is obtained:

pseudo-second-order rate constants *k2* and *qe*.

1 *qe* � *qt* <sup>¼</sup> <sup>1</sup>

> *t qt*

<sup>¼</sup> <sup>1</sup> *k*2*qe* <sup>2</sup> þ 1 *qe*

The slopes and intercepts of plots *t/qe* versus *t* are used to calculate the

where *k2* is the equilibrium rate constant of pseudo-second-order adsorption

where *qe* is the amount of CO2 adsorbed at equilibrium (mg/g), *q* is the amount of CO2 adsorbed at time *t* (mg/g), and *k1* is the pseudo-first-order

Integration of Eq. (15) and using the initial conditions *qt* = 0 at *t* = 0 and *qt* = *qt* at

<sup>¼</sup> *<sup>k</sup>*<sup>1</sup>

*dqt*

log *qe qe* � *qt* 

By rearrangement of Eq. (16), a linear form is obtained:

adsorption system with solid surfaces.

*2.4.2 Pseudo-first-order model*

*CO2 Sequestration*

*t* = *t* yield

constant (1/min).

[13, 26–30]:

(g/mg.min).

**116**

by plot of log(*qe-q*) versus *t*.

*2.4.3 Pseudo-second-order model*

The intra-particle diffusion model is expressed as [31–33]

$$q\_t = k\_p t^{0.5} + c \tag{21}$$

where *kp* is a rate factor (present CO2 adsorbed per minute). The plot of this model is multi-linear that indicates there are two or more steps occurring consecutively. The external surface/instantaneous adsorption stage occurred first in sharp portion. Then a gradual adsorption stage is in the second portion, where the controlled rate is the intra-particle diffusion. Final equilibrium stage occurs where intra-particle diffusion begins to slow down because of extremely low adsorbate concentrations in the bulk [24, 34].

#### **2.5 Thermodynamic studies**

Thermodynamic parameters were estimated from Langmuir isotherms by using the Van't Hoff's equation as in Eqs. (22) and (23). The thermodynamic parameters can be estimated from Langmuir isotherms by using the Van't Hoff's equation as follows [12, 35]:

$$
\Delta G^{\circ} = -RTl n a\_L \tag{22}
$$

$$
\ln a\_L = \frac{\Delta S^\circ}{R} - \frac{\Delta H^\circ}{RT} \tag{23}
$$

where *aL* is a Langmuir constant (l/mol), *R* is the universal constant of gases (8.314 J/mol.K), and *T* is an absolute temperature of gas.

#### **3. Results and discussion**

#### **3.1 Adsorbent characterization**

The main characteristics of AC (particle diameter, bed porosity, weight of bed, BET surface area, and pore volume) are shown in **Table 1**. Due to a high value BET surface area for used AC, its good pore structure makes it a suitable candidate for CO2 capture.

#### **3.2 Dynamic studies**

Two mixtures of CO2 and N2 gases have been used in experiments (initial concentrations of CO2 are 10 and 13.725% vol., respectively). **Figure 2** shows that


**Table 1.**

*Characteristics of used AC depending on particle diameter.*

the rate of CO2 adsorption gradually decreased with time, until equilibrium condition was achieved. This behavior is observed for each line in **Figures 2** and **3** throughout a gradual increase of the concentration ratio of (outlet/initial) concentrations of CO2 (C/Co).

In post-combustion process, the flue gas temperature is typically within the range of 50–120°C [36, 37]. Thus, an adsorption study was conducted at 30–90°C to investigate the CO2 adsorptive properties at elevated temperatures. **Figures 4** and **5** show that the CO2 adsorption capacity of solid adsorbent decreases with temperature, and it implies the existence of physical adsorption (physisorption) between the CO2 molecules and carbonaceous adsorbent. Adsorption capacity decreased with increasing temperature because of exothermic adsorption process as shown in **Figures 4** and **5**. This behavior is also identical with the results of previous studies [3, 38]. The adsorption capacities recorded in **Figure 4** are 109.529, 74.57, 50.61, and 35.46 mg(CO2)/gAC, whereas they recorded in **Figure 5** as 129.651, 89.2, 53.079, and 35.546 mg(CO2)/gAC at temperatures 30, 50, 70, and 90°C, respectively. Thus, the optimum temperature for the removal process is 30°C. It also notices that the adsorption process occurs in the beginning quickly and be a decline in the curves and clear because of the abundance of the active sites and the presence of small surface resistance on the surface of adsorbents, then more smoothness gradually less steep and alignment over time because of the fullness of all the active sites on the surface of adsorbents and that the process has become controlled by internal diffusion within the adsorbents in accordance with what has been presented previously [39]. Also the results of comparison for both **Figures 4** and **5** together note

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture*

*DOI: http://dx.doi.org/10.5772/intechopen.85834*

*Adsorption capacity of CO2 onto AC (initial concn. = 10%vol., avg. particle diameter = 5 mm, and volumetric*

*Adsorption capacity of CO2 onto AC (initial conc. = 13.725%vol., avg. particle diameter = 5 mm, and*

**Figure 4.**

**Figure 5.**

**119**

*volumetric rate = 12 l/min.).*

*rate = 12 l/min.).*

The CO2 adsorption was most intensive during 50 min. and thereafter remains unchanged until saturation was attained. Adsorption process to carbon dioxide for different temperatures (30, 50, 70, and 90°C) on AC reaches equilibrium for increased temperature. The same behavior is shown in **Figure 3** when using a high concentration of carbon dioxide but fast (30 min. to reach the equilibrium), due to high CO2 concentration, and this behavior is compatible with previous results when using AC prepared from coconut residue to remove carbon dioxide [36]. It is noted that breakthrough curves become shorter and steeper for high temperatures; this indicates the adsorption process here is exothermic and that's compatible with previous results for some of the previous adsorption of carbon dioxide on the zeolite [1]. The adsorption of carbon dioxide carbon process was not affected by the presence of nitrogen gas, and this is due to the strength of the links formed by carbon dioxide with AC particles [36].

**Figure 2.**

*Breakthrough curve for CO2 adsorption onto AC (initial conc. = 10%vol., avg. particle diameter = 5 mm, and volumetric rate = 12 l/min).*

#### **Figure 3.**

*Breakthrough curve for CO2 adsorption onto AC (initial conc. = 13.725%vol., avg. particle diameter = 5 mm, and volumetric rate = 12 l/min).*

#### *Experimental Study of Adsorption on Activated Carbon for CO2 Capture DOI: http://dx.doi.org/10.5772/intechopen.85834*

In post-combustion process, the flue gas temperature is typically within the range of 50–120°C [36, 37]. Thus, an adsorption study was conducted at 30–90°C to investigate the CO2 adsorptive properties at elevated temperatures. **Figures 4** and **5** show that the CO2 adsorption capacity of solid adsorbent decreases with temperature, and it implies the existence of physical adsorption (physisorption) between the CO2 molecules and carbonaceous adsorbent. Adsorption capacity decreased with increasing temperature because of exothermic adsorption process as shown in **Figures 4** and **5**. This behavior is also identical with the results of previous studies [3, 38]. The adsorption capacities recorded in **Figure 4** are 109.529, 74.57, 50.61, and 35.46 mg(CO2)/gAC, whereas they recorded in **Figure 5** as 129.651, 89.2, 53.079, and 35.546 mg(CO2)/gAC at temperatures 30, 50, 70, and 90°C, respectively. Thus, the optimum temperature for the removal process is 30°C. It also notices that the adsorption process occurs in the beginning quickly and be a decline in the curves and clear because of the abundance of the active sites and the presence of small surface resistance on the surface of adsorbents, then more smoothness gradually less steep and alignment over time because of the fullness of all the active sites on the surface of adsorbents and that the process has become controlled by internal diffusion within the adsorbents in accordance with what has been presented previously [39]. Also the results of comparison for both **Figures 4** and **5** together note

#### **Figure 4.**

the rate of CO2 adsorption gradually decreased with time, until equilibrium condition was achieved. This behavior is observed for each line in **Figures 2** and **3** throughout a gradual increase of the concentration ratio of (outlet/initial) concen-

The CO2 adsorption was most intensive during 50 min. and thereafter remains unchanged until saturation was attained. Adsorption process to carbon dioxide for different temperatures (30, 50, 70, and 90°C) on AC reaches equilibrium for increased temperature. The same behavior is shown in **Figure 3** when using a high concentration of carbon dioxide but fast (30 min. to reach the equilibrium), due to high CO2 concentration, and this behavior is compatible with previous results when using AC prepared from coconut residue to remove carbon dioxide [36]. It is noted that breakthrough curves become shorter and steeper for high temperatures; this indicates the adsorption process here is exothermic and that's compatible with previous results for some of the previous adsorption of carbon dioxide on the zeolite [1]. The adsorption of carbon dioxide carbon process was not affected by the presence of nitrogen gas, and this is due to the strength of the links formed by

*Breakthrough curve for CO2 adsorption onto AC (initial conc. = 10%vol., avg. particle diameter = 5 mm, and*

*Breakthrough curve for CO2 adsorption onto AC (initial conc. = 13.725%vol., avg. particle diameter = 5 mm,*

trations of CO2 (C/Co).

*CO2 Sequestration*

**Figure 2.**

**Figure 3.**

**118**

*and volumetric rate = 12 l/min).*

*volumetric rate = 12 l/min).*

carbon dioxide with AC particles [36].

*Adsorption capacity of CO2 onto AC (initial concn. = 10%vol., avg. particle diameter = 5 mm, and volumetric rate = 12 l/min.).*

#### **Figure 5.**

*Adsorption capacity of CO2 onto AC (initial conc. = 13.725%vol., avg. particle diameter = 5 mm, and volumetric rate = 12 l/min.).*

that the amount of the CO2 adsorbed onto AC increases due to increase of the concentration difference of CO2 between bulk and surface of AC leading to an increase of mass transfer [9, 40].

In addition, the Dubinin-Radushkevich isotherm will provide a useful information related to the energy parameters, in terms of *E* (mean free energy of adsorption). The calculated *E* values which are within the range of 1.213–8 and 0.626–2.193 kJ/mol for both initial concentrations 10 and 13.725% vol., respectively, suggest that the CO2 adsorption is physical in nature, as the magnitude of *E* is below 8 kJ/mol, whereas the value of 8 < *E* < 16 is an indicator of the chemical adsorption [41]. Also, *B* (value of heat adsorption) in Temkin isotherm ranged between 15.47

On the basis of corresponding r2 values and adsorption capacity estimated by each model shown in **Table 2**, the Langmuir model gives the best fit toward the experimental data over the entire temperature range. Therefore, it implies that the surface of the activated carbon is heterogeneous and a restricted monolayer CO2 adsorption occurs, as results of adsorption CO2 onto activated carbon prepared

An analysis of kinetic adsorption process is a useful tool to estimate the time of residence for the adsorption process to complete and to determine the dynamics of adsorption and its performance in industrial scale of fixed bed or in flow-through systems. Thus, simple first-order, pseudo-first-order, pseudo-second-order, and intra-particle diffusion models were performed in this study. Kinetic parameters of

**Table 3** shows the simple first-order kinetic model for activated carbon did not fit well with the experimental data, with r2 value found to be within the range of 0.4344–0.7873 and 0.319–0.734 for both initial concentrations 10 and 13.725% vol., respectively. Also, **Table 3** shows the pseudo-first-order kinetic model for activated carbon did not fit well with the experimental data, with r<sup>2</sup> value found to be within the range of 0.9521–0.967 also from 0.9175 to 0.9487 for both initial concentrations

Comparing the values of determination coefficients as stated in **Table 3**, pseudo-second-order model gives better fit than the pseudo-first-order and intra-particle diffusion models with experimental data, with r<sup>2</sup> value within the range of 0.963–0.996 and 0.955–0.998 for both initial concentrations 10 and 13.725% vol., respectively. Also, the values of adsorption capacity of equilibrium

In similarity to pseudo-first-order and pseudo-second-order models, the intraparticle diffusion model provides insight of the mechanism in adsorption process. Adsorption contains of few steps involved in the transfer of adsorbate (CO2) from the phase of bulk to the solid surface of AC and is followed by the molecule diffusion into the interior of the pores of AC. Intra-particle diffusion is typically described as a slow process and is a limiting step in many adsorption processes. Theoretically, if the adsorption process obeys the intra-particle diffusion model, a straight linear plot that passes through the origin is expected. However, results of the variation of gradient with respect to time show that the intra-particle diffusion is not the sole rate-limiting step in this adsorption process. Note that the first

(*qe*) were observed to decrease with respect to temperature. The kinetic energy of CO2 adsorbed at elevated temperatures is high, and it leads to its increasing tendency to escape from the AC surface. Maroto-Valer et al*.* [42] reported that physisorption process involves high surface adsorption energy and molecule diffusion at elevated temperatures, which result in instability of the adsorbed gas on the surface of activated carbon, and consequently desorption

and 35.826 J/mol indicating a physisorption process occurs.

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture*

*DOI: http://dx.doi.org/10.5772/intechopen.85834*

from coconut fiber studied by Hauchhum and Mahanta [3].

**3.4 Kinetic studies**

these models are shown in **Table 3**.

10 and 13.725% vol., respectively.

process will occur.

**121**

#### **3.3 Equilibrium isotherm studies**

The equilibrium data can be approximated using common and practical adsorption isotherms, which provide the basis for the design of adsorption systems. The amount of adsorbed CO2 onto adsorbent (AC) as a function of its concentration at constant temperature can be described by different adsorption isotherm models (Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich). The predicted isotherm constants for the CO2 adsorption and the determination coefficient r<sup>2</sup> value from the linear regression method are shown in **Table 2**.

Based on tabulated data, the maximum capacity (*Qo*) of AC and *aL* values (Langmuir parameters) for CO2 adsorption decreased with increasing temperature; this reveals a physisorption process occurred. The decline in values of maximum adsorption capacity with increased in the adsorption temperature is due to the exothermic nature of the CO2 adsorption on AC. It is confirmed by *n* values higher than 1 in the Freundlich isotherm model that the adsorption is favorable for AC.


**Table 2.**

*Parameters of isotherm models at different temperatures via linearized technique for adsorption of CO2 onto AC.*

#### *Experimental Study of Adsorption on Activated Carbon for CO2 Capture DOI: http://dx.doi.org/10.5772/intechopen.85834*

In addition, the Dubinin-Radushkevich isotherm will provide a useful information related to the energy parameters, in terms of *E* (mean free energy of adsorption). The calculated *E* values which are within the range of 1.213–8 and 0.626–2.193 kJ/mol for both initial concentrations 10 and 13.725% vol., respectively, suggest that the CO2 adsorption is physical in nature, as the magnitude of *E* is below 8 kJ/mol, whereas the value of 8 < *E* < 16 is an indicator of the chemical adsorption [41]. Also, *B* (value of heat adsorption) in Temkin isotherm ranged between 15.47 and 35.826 J/mol indicating a physisorption process occurs.

On the basis of corresponding r2 values and adsorption capacity estimated by each model shown in **Table 2**, the Langmuir model gives the best fit toward the experimental data over the entire temperature range. Therefore, it implies that the surface of the activated carbon is heterogeneous and a restricted monolayer CO2 adsorption occurs, as results of adsorption CO2 onto activated carbon prepared from coconut fiber studied by Hauchhum and Mahanta [3].

#### **3.4 Kinetic studies**

that the amount of the CO2 adsorbed onto AC increases due to increase of the concentration difference of CO2 between bulk and surface of AC leading to an

The equilibrium data can be approximated using common and practical adsorption isotherms, which provide the basis for the design of adsorption systems. The amount of adsorbed CO2 onto adsorbent (AC) as a function of its concentration at constant temperature can be described by different adsorption isotherm models (Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich). The predicted isotherm constants for the CO2 adsorption and the determination coefficient r<sup>2</sup> value

Based on tabulated data, the maximum capacity (*Qo*) of AC and *aL* values (Langmuir parameters) for CO2 adsorption decreased with increasing temperature; this reveals a physisorption process occurred. The decline in values of maximum adsorption capacity with increased in the adsorption temperature is due to the exothermic nature of the CO2 adsorption on AC. It is confirmed by *n* values higher than 1 in the Freundlich isotherm model that the adsorption is favorable for AC.

10 30 0.0492 120.482 0.00081 0.3865 109.53 108.03 0.997 522.49 0.955 50 0.01835 99.009 0.04223 0.527 74.57 90.633 0.9976 685.26 0.954 70 0.01076 81.301 0.2138 0.5998 50.61 50.92 0.9865 966.67 0.964 90 0.00778 66.667 0.5181 0.6342 35.46 49.835 0.9829 1358.19 0.972 13.725 30 0.01171 161.29 0.002202 0.5324 129.65 129.693 0.9976 649.62 0.936 50 0.0921 133.333 0.0933 0.5821 89.2 89.92 0.9919 1024.09 0.959 70 0.0782 85.47 0.1711 0.5596 53.08 53.2934 0.9964 2453.47 0.982 90 0.0466 67.11 0.6192 0.5996 35.55 35.78 0.9872 6014.59 0.984

**D-R constants Qexp QT r**

**ε (kJ/ mol)**

10 30 22.305 0.746 0.0078 93.841 8.006 109.53 108.84 0.998 93.76 0.806 50 22.582 0.167 0.0881 70.316 2.382 74.57 75.009 0.997 69.48 0.909 70 19.114 0.092 0.221 51.07 1.506 50.61 50.965 0.994 49.16 0.955 90 15.473 0.067 0.339 37.68 1.123 35.46 35.58 0.996 35.02 0.982

13.725 30 35.826 0.164 0.104 117.47 2193 129.65 131.45 0.989 116.78 0.86

*Parameters of isotherm models at different temperatures via linearized technique for adsorption of CO2 onto*

50 30.949 0.0813 0.308 86.59 1.27 89.2 89.93 0.996 84.62 0.923 70 20.395 0.0642 0.519 54.806 0.981 53.08 53.24 0.998 52.21 0.968 90 16.048 0.0378 1.276 39.186 0.626 35.55 35.63 0.9947 35.43 0.996

**<sup>2</sup> QD-R r**

**(mg/g) (mg/g) — (mg/g) —**

**2**

*Freundlich constants Qexp QL r<sup>2</sup> QF r<sup>2</sup>*

**KF (mg/g) n () (mg/g) (mg/g) — (mg/g) —**

increase of mass transfer [9, 40].

*CO2 Sequestration*

**3.3 Equilibrium isotherm studies**

*Co T Langmuir*

**Co T Temkin**

**o C B (J/mol)**

**constants**

**A (l/g) ß**

**(mol2 / kJ2 )**

**qm (mg/g)**

**o C** *aL* **(l/mg)**

**Vol. %**

**Vol. %**

**Table 2.**

*AC.*

**120**

*constants*

**Qo (mg/g)**

from the linear regression method are shown in **Table 2**.

An analysis of kinetic adsorption process is a useful tool to estimate the time of residence for the adsorption process to complete and to determine the dynamics of adsorption and its performance in industrial scale of fixed bed or in flow-through systems. Thus, simple first-order, pseudo-first-order, pseudo-second-order, and intra-particle diffusion models were performed in this study. Kinetic parameters of these models are shown in **Table 3**.

**Table 3** shows the simple first-order kinetic model for activated carbon did not fit well with the experimental data, with r2 value found to be within the range of 0.4344–0.7873 and 0.319–0.734 for both initial concentrations 10 and 13.725% vol., respectively. Also, **Table 3** shows the pseudo-first-order kinetic model for activated carbon did not fit well with the experimental data, with r<sup>2</sup> value found to be within the range of 0.9521–0.967 also from 0.9175 to 0.9487 for both initial concentrations 10 and 13.725% vol., respectively.

Comparing the values of determination coefficients as stated in **Table 3**, pseudo-second-order model gives better fit than the pseudo-first-order and intra-particle diffusion models with experimental data, with r<sup>2</sup> value within the range of 0.963–0.996 and 0.955–0.998 for both initial concentrations 10 and 13.725% vol., respectively. Also, the values of adsorption capacity of equilibrium (*qe*) were observed to decrease with respect to temperature. The kinetic energy of CO2 adsorbed at elevated temperatures is high, and it leads to its increasing tendency to escape from the AC surface. Maroto-Valer et al*.* [42] reported that physisorption process involves high surface adsorption energy and molecule diffusion at elevated temperatures, which result in instability of the adsorbed gas on the surface of activated carbon, and consequently desorption process will occur.

In similarity to pseudo-first-order and pseudo-second-order models, the intraparticle diffusion model provides insight of the mechanism in adsorption process. Adsorption contains of few steps involved in the transfer of adsorbate (CO2) from the phase of bulk to the solid surface of AC and is followed by the molecule diffusion into the interior of the pores of AC. Intra-particle diffusion is typically described as a slow process and is a limiting step in many adsorption processes. Theoretically, if the adsorption process obeys the intra-particle diffusion model, a straight linear plot that passes through the origin is expected. However, results of the variation of gradient with respect to time show that the intra-particle diffusion is not the sole rate-limiting step in this adsorption process. Note that the first


#### **Table 3.**

*Kinetic parameters of CO2 onto AC.*

steeper region (2–4 min.1/2) could be due to surface sorption, while the second region (4–9 min.1/2) may be attributed by the intra-particle diffusion rate controlled.

According to findings of the experimental data, the negative sign of *ΔH<sup>o</sup>* value indicates an exothermic nature of the CO2 adsorption process onto AC, and the negative value of *ΔSo* suggests high orderliness of the adsorbate molecules (CO2) upon adsorption. Zhao et al*.* [45] mentioned that the negative value of *ΔS<sup>o</sup>* can be interpreted by the behavior of the CO2 molecules upon the adsorption process, which is from randomized to an ordered form on the surface of the adsorbent. The decline in the entropy value upon the adsorption process is due to a lesser degree of freedom of the CO2 molecules, due to minimum free space on the surface of AC. Moreover, the value of *ΔHo* indicates the type of CO2 adsorption process, whether it belongs to the physisorption or chemisorption. It has been reported that the value of *ΔH<sup>o</sup>* for the physisorption process is <20 kJ/mol, while for the chemisorption process, the value is within 80–200 kJ/mol [45, 46]. Therefore, the calculated values of *ΔH<sup>o</sup>* approximately ranging between 18 and 28 kJ/mol suggest that the CO2 adsorption can be attributed to a physi-intra-particle diffusion adsorption process rather than a pure physisorption or chemisorption process. Also, this supports the isotherm study results that reveal the adsorption mechanism is physisorption and

**Conc. Temp.** *aL ΔG<sup>o</sup> ΔH<sup>o</sup> ΔSo* **(vol.%) (K) (mol/l) (J/mol) (J/mol) (J/mol.K)** 10 303 2164.79 19347.21 28038.965 29.7716

13.725 303 753.38 16688.24 18630.843 6.748

323 807.71 17976.75 343 473.45 17566.61 363 342.50 17613.77

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture*

*DOI: http://dx.doi.org/10.5772/intechopen.85834*

323 405.31 16124.99 343 344.14 16065.94 363 204.91 16063.38

obeys Langmuir isotherm model.

**Figure 6.**

**Table 4.**

**123**

*Van't Hoff plot for adsorption of CO2/AC system.*

*Thermodynamic parameters of CO2 adsorption onto AC.*

#### **3.5 Thermodynamic studies**

The values of thermodynamic parameters of CO2 adsorption process on AC based on Van't Hoff plot for Eqs. (22) and (23) are shown in **Figure 6**.

The estimated values of the thermodynamic parameters are tabulated in **Table 4**. For significant adsorption to occur, the Gibbs free energy change of adsorption (*ΔG<sup>o</sup>* ) must be negative [43]. **Table 4** shows that the (*ΔG<sup>o</sup>* ) was negative values for all five temperatures studied, which indicates the feasibility and spontaneity of the adsorption process. In addition, decreased negative *ΔG<sup>o</sup>* value with increasing temperature implies that the CO2 adsorption process is more favorable at 30°C rather than at 90°C; this behavior is also noticed by Rashidi et al*.* [44] and Hauchhum and Mahanta [3].

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture DOI: http://dx.doi.org/10.5772/intechopen.85834*

#### **Figure 6.**

*Van't Hoff plot for adsorption of CO2/AC system.*


#### **Table 4.**

steeper region (2–4 min.1/2) could be due to surface sorption, while the second region (4–9 min.1/2) may be attributed by the intra-particle diffusion rate

The values of thermodynamic parameters of CO2 adsorption process on AC

) must be negative [43]. **Table 4** shows that the (*ΔG<sup>o</sup>*

values for all five temperatures studied, which indicates the feasibility and spontaneity of the adsorption process. In addition, decreased negative *ΔG<sup>o</sup>* value with increasing temperature implies that the CO2 adsorption process is more favorable at 30°C rather than at 90°C; this behavior is also noticed by Rashidi et al*.* [44] and

) was negative

The estimated values of the thermodynamic parameters are tabulated in **Table 4**. For significant adsorption to occur, the Gibbs free energy change of

based on Van't Hoff plot for Eqs. (22) and (23) are shown in **Figure 6**.

controlled.

**Table 3.**

Intra-particle diffusion

adsorption (*ΔG<sup>o</sup>*

**122**

**3.5 Thermodynamic studies**

*Kinetic parameters of CO2 onto AC.*

**Kinetic model** *Co*

*CO2 Sequestration*

**(vol.%)**

**Parameter Temperature (°C)**

13.725 *k1* 3.293 2.404 1.457 1.091

13.725 *k1* 0.1508 0.182 0.2116 0.282

13.725 *k2* 2.88 105 1.29 <sup>10</sup><sup>5</sup> 5.76 <sup>10</sup><sup>4</sup> 3.23 104

10 *kp* 13.974 8.755 5.436 3.489

13.725 *kp* 15.976 10.169 5.219 3.151

Simple first-order 10 *k1* 2.633 1.974 1.394 0.955

Pseudo-first-order 10 *k1* 0.0972 0.1521 0.1864 0.2367

Pseudo-second-order 10 *k2* 1.6 105 6.59 <sup>10</sup><sup>4</sup> 3.14 104 1.69 <sup>10</sup><sup>4</sup>

r

r

r

r

r

r

r

r

**30 50 70 90**

*Co* 4.1 105 1.75 1021 1.67 <sup>10</sup><sup>33</sup> 6.73 1040

<sup>2</sup> 0.787 0.667 0.539 0.434

*Co* 3.04 <sup>10</sup><sup>17</sup> 8.414 1036 6.52 1056 1.023 <sup>10</sup><sup>80</sup>

<sup>2</sup> 0.734 0.624 0.427 0.319

*qe* 159.48 143.481 84.94 62.22

<sup>2</sup> 0.967 0.96 0.915 0.952

*qe* 292.89 195.45 78.25 49.47

<sup>2</sup> 0.918 0.927 0.944 0.949

*qe* 144.93 87.719 55.56 37.45

<sup>2</sup> 0.968 0.976 0.989 0.995

*qe* 161.29 102.04 56.179 36.496

<sup>2</sup> 0.96 0.982 0.955 0.998

*c* 7.686 12.25 13.025 11.775

<sup>2</sup> 0.874 0.8123 0.7417 0.6811

*c* 14.137 17.633 17.693 14.578

<sup>2</sup> 0.841 0.788 0.677 0.601

Hauchhum and Mahanta [3].

*Thermodynamic parameters of CO2 adsorption onto AC.*

According to findings of the experimental data, the negative sign of *ΔH<sup>o</sup>* value indicates an exothermic nature of the CO2 adsorption process onto AC, and the negative value of *ΔSo* suggests high orderliness of the adsorbate molecules (CO2) upon adsorption. Zhao et al*.* [45] mentioned that the negative value of *ΔS<sup>o</sup>* can be interpreted by the behavior of the CO2 molecules upon the adsorption process, which is from randomized to an ordered form on the surface of the adsorbent. The decline in the entropy value upon the adsorption process is due to a lesser degree of freedom of the CO2 molecules, due to minimum free space on the surface of AC. Moreover, the value of *ΔHo* indicates the type of CO2 adsorption process, whether it belongs to the physisorption or chemisorption. It has been reported that the value of *ΔH<sup>o</sup>* for the physisorption process is <20 kJ/mol, while for the chemisorption process, the value is within 80–200 kJ/mol [45, 46]. Therefore, the calculated values of *ΔH<sup>o</sup>* approximately ranging between 18 and 28 kJ/mol suggest that the CO2 adsorption can be attributed to a physi-intra-particle diffusion adsorption process rather than a pure physisorption or chemisorption process. Also, this supports the isotherm study results that reveal the adsorption mechanism is physisorption and obeys Langmuir isotherm model.

#### **3.6 Effects of interaction between gases in mixture**

The adsorption amount for each component in a complex mixture of (CO2, NO, and N2) was compared with that under the single-component conditions, with the results shown in **Figure 7**. In the single-component condition, the adsorption amount was 109.24 mgCO2/gAC and 0.245 mgNO/gAC in 50 and 40 min for each one, respectively. When all of the components were present in a mixture of CO2, NO, and N2, the CO2 adsorption amount decreased by 6%, and the NO adsorption amount also decreased by 7.6%. The adsorption capacity of CO2 in complex mixture is not changed compared with that under the single-component conditions but is favorable due to decreased equilibrium time required. The adsorption capacities of complex mixture were 103.2 mgCO2/gAC in 40 min and 0.229 mgNO/gAC in 30 min. This decrease in adsorption capacity is due to the competition between both gases on the active sites, whereas the CO2 adsorption capacity is higher than NO gas because of the presence of CO2 gas at high concentrations. NO and CO2 display fast breakthrough, and high adsorption amounts were observed in the pure component adsorption experiments. When the interaction effect of CO2 and NO was considered, a very interesting phenomenon appeared. After the initial breakthrough, the CO2 concentration descends to a minimum and then gradually ascends with the breakthrough ending point of NO. This is observed from the arrival time of the

equilibrium state which was 30 min for the NO gas and 40 min for the CO2 gas; the same behavior is shown for the single-component conditions; the difference between them was reached in the equilibrium stage fast approximately 10 min. In **Figure 8** the adsorption capacities of complex mixture were 124.4 mgCO2/gAC in 40 min and 0.22 mgNO/gAC in 30 min by using different initial concentrations of gases. This is confirmed by the fact that free Gibbs energy values of both gases are very different, as they have NO gas higher in value, while in the case of CO2, they are much lower. This behavior is shown in previous study for adsorption on

In this study, the fixed bed adsorption of carbon dioxide from CO2/N2 mixtures

) closeness

on activated carbon was studied. The adsorption dynamics was investigated at different operating temperatures (30–90°C). The results show that the low-cost activated carbon can be prepared from olive trees as potential carbonaceous material serving as porous media for CO2 capture. Based on the experimental results, it is concluded that the CO2 adsorption onto the olive tree activated carbon follows the physisorption behavior, whereby the CO2 adsorption capacity decreases with respect to increasing temperature. Based on the equilibrium models of isotherm used herein to fit the experimental data of adsorption, the Langmuir model was the best fit with experimental data over the whole temperature range, due to the highest estimated adsorption capacity and determination coefficient (r2

to unity, thus implying a perfect fit to the experimental data. Besides, thermodynamic analysis proves that the CO2 adsorption is a spontaneous process at low temperature, physisorption, and intra-particle diffusion and exothermic in nature. Also, the negative values of the entropy of the adsorption manifest the restricted randomness of the adsorbate molecules on the surfaces of adsorbent. CO2 adsorption capacity has been reduced slightly when NO appears, but the process of adsorption has been faster as a result of competition on carbon-active sites.

Olive trees are dominant and easily available in the Mediterranean countries generally and especially Libya, and because charcoal is prepared from olive trees, it is cheap in Libya. According to the obtained result, this study concludes that AC prepared from olive trees can be considered as adequate for designing a fixed bed cycle to separate carbon dioxide from flue gases and serve as a benchmark while searching for inexpensive and superior activated carbon production in future studies that concerned of capturing CO2 from flue gases of the industrial sectors (such as

cement plants and power stations) that are prevailing in Libya.

activated carbon prepared from coconut husk residues [47].

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture*

*DOI: http://dx.doi.org/10.5772/intechopen.85834*

**4. Conclusion**

**125**

#### **Figure 7.**

*Breakthrough curves for mixture gas (CO2, NO, and N2) (initial conc. = 10% vol. of CO2, and 550 ppm of NO, avg. particle diameter = 5 mm, temperature = 30°C, and volumetric rate = 12 l/min.)*

#### **Figure 8.**

*Breakthrough curves for mixture gas (CO2, NO, and N2) (initial conc. = 13.725%vol. of CO2, and 550 ppm of NO, avg. particle diameter = 5 mm, temperature = 30°C, and volumetric rate = 12 l/min.)*

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture DOI: http://dx.doi.org/10.5772/intechopen.85834*

equilibrium state which was 30 min for the NO gas and 40 min for the CO2 gas; the same behavior is shown for the single-component conditions; the difference between them was reached in the equilibrium stage fast approximately 10 min. In **Figure 8** the adsorption capacities of complex mixture were 124.4 mgCO2/gAC in 40 min and 0.22 mgNO/gAC in 30 min by using different initial concentrations of gases. This is confirmed by the fact that free Gibbs energy values of both gases are very different, as they have NO gas higher in value, while in the case of CO2, they are much lower. This behavior is shown in previous study for adsorption on activated carbon prepared from coconut husk residues [47].

#### **4. Conclusion**

**3.6 Effects of interaction between gases in mixture**

*CO2 Sequestration*

**Figure 7.**

**Figure 8.**

**124**

The adsorption amount for each component in a complex mixture of (CO2, NO, and N2) was compared with that under the single-component conditions, with the results shown in **Figure 7**. In the single-component condition, the adsorption amount was 109.24 mgCO2/gAC and 0.245 mgNO/gAC in 50 and 40 min for each one, respectively. When all of the components were present in a mixture of CO2, NO, and N2, the CO2 adsorption amount decreased by 6%, and the NO adsorption amount also decreased by 7.6%. The adsorption capacity of CO2 in complex mixture is not changed compared with that under the single-component conditions but is favorable due to decreased equilibrium time required. The adsorption capacities of complex mixture were 103.2 mgCO2/gAC in 40 min and 0.229 mgNO/gAC in 30 min. This decrease in adsorption capacity is due to the competition between both gases on the active sites, whereas the CO2 adsorption capacity is higher than NO gas because of the presence of CO2 gas at high concentrations. NO and CO2 display fast breakthrough, and high adsorption amounts were observed in the pure component adsorption experiments. When the interaction effect of CO2 and NO was considered, a very interesting phenomenon appeared. After the initial breakthrough, the CO2 concentration descends to a minimum and then gradually ascends with the breakthrough ending point of NO. This is observed from the arrival time of the

*Breakthrough curves for mixture gas (CO2, NO, and N2) (initial conc. = 10% vol. of CO2, and 550 ppm of*

*Breakthrough curves for mixture gas (CO2, NO, and N2) (initial conc. = 13.725%vol. of CO2, and 550 ppm of*

*NO, avg. particle diameter = 5 mm, temperature = 30°C, and volumetric rate = 12 l/min.)*

*NO, avg. particle diameter = 5 mm, temperature = 30°C, and volumetric rate = 12 l/min.)*

In this study, the fixed bed adsorption of carbon dioxide from CO2/N2 mixtures on activated carbon was studied. The adsorption dynamics was investigated at different operating temperatures (30–90°C). The results show that the low-cost activated carbon can be prepared from olive trees as potential carbonaceous material serving as porous media for CO2 capture. Based on the experimental results, it is concluded that the CO2 adsorption onto the olive tree activated carbon follows the physisorption behavior, whereby the CO2 adsorption capacity decreases with respect to increasing temperature. Based on the equilibrium models of isotherm used herein to fit the experimental data of adsorption, the Langmuir model was the best fit with experimental data over the whole temperature range, due to the highest estimated adsorption capacity and determination coefficient (r2 ) closeness to unity, thus implying a perfect fit to the experimental data. Besides, thermodynamic analysis proves that the CO2 adsorption is a spontaneous process at low temperature, physisorption, and intra-particle diffusion and exothermic in nature. Also, the negative values of the entropy of the adsorption manifest the restricted randomness of the adsorbate molecules on the surfaces of adsorbent. CO2 adsorption capacity has been reduced slightly when NO appears, but the process of adsorption has been faster as a result of competition on carbon-active sites.

Olive trees are dominant and easily available in the Mediterranean countries generally and especially Libya, and because charcoal is prepared from olive trees, it is cheap in Libya. According to the obtained result, this study concludes that AC prepared from olive trees can be considered as adequate for designing a fixed bed cycle to separate carbon dioxide from flue gases and serve as a benchmark while searching for inexpensive and superior activated carbon production in future studies that concerned of capturing CO2 from flue gases of the industrial sectors (such as cement plants and power stations) that are prevailing in Libya.

*CO2 Sequestration*

### **Author details**

Hesham G. Ibrahim<sup>1</sup> \* and Mohamed A. Al-Meshragi<sup>2</sup>

1 Mechanical Engineering Department, Faculty of Marine Resources, Al-Asmarya Islamic University, Zliten, Libya

**References**

[1] Dantas TLP, Luna FMT, Silva Jr IJ,

*DOI: http://dx.doi.org/10.5772/intechopen.85834*

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture*

activated carbon: Isotherm and breakthrough curve measurements. Middle-East Journal of Scientific Research. 2010;**5**(4):191-198. DOI: 10.1080/00986445.2011.584354

[8] Alshuiref AA, Ibrahim HG, Ben Mahmoud MM, Maraie AA. Treatment of wastewater contaminated with Cu(II) by adsorption onto acacia activated carbon. Journal of Marine Sciences and Environmental Technologies (JMSET). 2017;**3**(2):25-36 Available from: http:// www.asmarya.edu.ly/journal2/wpcontent/uploads/2018/04/JMSET03-3-

[9] Kuboňová L, Obalová L, Vlach O, Troppová I, Kalousek J. Modeling of NO adsorption in fixed bed on activated carbon. Chemical and Process

Engineering. 2011;**32**(4):367-377. DOI:

[10] McCabe W, Smith J, Harriott P. Unit Operations of Chemical

Engineering. 7th ed. NY, USA: McGraw Hill Chemical Engineering Series; 2004.

[11] Khalili S, Ghoreyshi A, Jahanshai M. Carbon dioxide captured by multiwalled carbon nanotube and activated charcoal: A comparative study. Chemical Industry & Chemical Engineering. 2013;**19**(1):153-164. DOI:

[12] Ibrahim HG. Removal and Recovery of Chromium from Aqueous Solutions. Saarbrucken, Germany: LAP Lambert Academic Publishing GmbH and Co. KG;

[13] Özacar M. Adsorption of phosphate from aqueous solution onto alunite. Chemosphere. 2003;**51**(4):321-327. DOI: 10.1016/s0045-6535(02)00847-0

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10.2478/v10176-011-0029-z

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10.2298/ciceq120217050k

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International Journal of Greenhouse Gas

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3893-3906. DOI: 10.1016/j.ces.2006.01.

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357d.pdf

00116-8

023

**127**

Control. 2007;**1**(3):355-357. DOI: 10.1016/s1750-5836(07)00072-2

2 Chemical Engineering Department, University of Tripoli, Tripoli, Libya

\*Address all correspondence to: h.ibrahim@asmarya.edu.ly

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Experimental Study of Adsorption on Activated Carbon for CO2 Capture DOI: http://dx.doi.org/10.5772/intechopen.85834*

#### **References**

[1] Dantas TLP, Luna FMT, Silva Jr IJ, Torres AEB, de Azevedo DCS, Rodrigues AE, et al. Modeling of the fixed-bed adsorption of carbon dioxide and a carbon dioxide-nitrogen mixture on zeolite 13x. Brazilian Journal of Chemical Engineering. 2011;**28**(3): 533-544. DOI: 10.1590/ S0104-66322011000300018

[2] Zhao Z, Cui X, Ma J, Li R. Adsorption of carbon dioxide on alkaline-modified zeolite 13X adsorbents. The International Journal of Greenhouse Gas Control. 2007;**1**(3):355-357. DOI: 10.1016/s1750-5836(07)00072-2

[3] Hauchhum L, Mahanta P. Kinetic, thermodynamic and regeneration studies for CO2 adsorption onto activated carbon. International Journal of Advanced Mechanical Engineering. 2004;**4**(1):27-32. Available from: https://pdfs.semanticscholar.org/eacc/ 3f82336a3276744eda9a898c4621da7d 357d.pdf

[4] Grande CA, Rodrigous AE. Electric swing adsorption for CO2 removal from flue gases. International Journal of Greenhouse Gas Control. 2008;**2**: 194-202. DOI: 10.1016/s1750-5836(07) 00116-8

[5] Cavenati S, Grande CA, Rodrigues AE. Separation CH4/CO2/N2 mixtures by layered pressure swing adsorption for upgrade of natural gases. Chemical Engineering Science. 2006;**61**: 3893-3906. DOI: 10.1016/j.ces.2006.01. 023

[6] Chen LC, Peng PY, Lin LF, Yang TCK, Huang CM. Facile preparation of nitrogen-doped activated carbon for carbon dioxide adsorption. Aerosol and Air Quality Research. 2014;**14**:916-927. DOI: 10.4209/aaqr.2013.03. 0089

[7] Zeinali F, Ghoreyshi AA, Najafpour GD. Adsorption of dichloromethane from aqueous phase using granular

activated carbon: Isotherm and breakthrough curve measurements. Middle-East Journal of Scientific Research. 2010;**5**(4):191-198. DOI: 10.1080/00986445.2011.584354

[8] Alshuiref AA, Ibrahim HG, Ben Mahmoud MM, Maraie AA. Treatment of wastewater contaminated with Cu(II) by adsorption onto acacia activated carbon. Journal of Marine Sciences and Environmental Technologies (JMSET). 2017;**3**(2):25-36 Available from: http:// www.asmarya.edu.ly/journal2/wpcontent/uploads/2018/04/JMSET03-3- 2-2017.pdf

[9] Kuboňová L, Obalová L, Vlach O, Troppová I, Kalousek J. Modeling of NO adsorption in fixed bed on activated carbon. Chemical and Process Engineering. 2011;**32**(4):367-377. DOI: 10.2478/v10176-011-0029-z

[10] McCabe W, Smith J, Harriott P. Unit Operations of Chemical Engineering. 7th ed. NY, USA: McGraw Hill Chemical Engineering Series; 2004. ISBN-10: 0072848235

[11] Khalili S, Ghoreyshi A, Jahanshai M. Carbon dioxide captured by multiwalled carbon nanotube and activated charcoal: A comparative study. Chemical Industry & Chemical Engineering. 2013;**19**(1):153-164. DOI: 10.2298/ciceq120217050k

[12] Ibrahim HG. Removal and Recovery of Chromium from Aqueous Solutions. Saarbrucken, Germany: LAP Lambert Academic Publishing GmbH and Co. KG; 2010; ISBN-10: 3838339037

[13] Özacar M. Adsorption of phosphate from aqueous solution onto alunite. Chemosphere. 2003;**51**(4):321-327. DOI: 10.1016/s0045-6535(02)00847-0

[14] Choy KK, McKay G, Porter JF. Sorption of acid dyes from effluents using activated carbon. Resources,

**Author details**

*CO2 Sequestration*

**126**

Hesham G. Ibrahim<sup>1</sup>

Islamic University, Zliten, Libya

provided the original work is properly cited.

\* and Mohamed A. Al-Meshragi<sup>2</sup>

2 Chemical Engineering Department, University of Tripoli, Tripoli, Libya

\*Address all correspondence to: h.ibrahim@asmarya.edu.ly

1 Mechanical Engineering Department, Faculty of Marine Resources, Al-Asmarya

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

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[16] Lin SH, Juang RS. Heavy metal removal from water by sorption using surfactant-modified montmorillonite. Journal of Hazardous Materials. 2002; **92**(3):315-326. DOI: 10.1016/ s0304-3894(02)00026-2

[17] Fadali OA, Magdy YH, Daifullah AAM, Ebrahiem EE, Nassar MM. Removal of chromium from tannery effluents by adsorption. Journal of Environmental Science and Health. 2004;**39**(2):465-472. DOI: 10.1081/ese-120027537

[18] Yang H, Xu Z, Fan M, Gupta R, Slimane RB, Bland AE, et al. Progress in carbon dioxide separation and capture: A review. Journal of Environmental Sciences. 2008;**20**:14-27. DOI: 10.1016/ S1001-0742(08)60002-9

[19] Raven KP, Jain A, Loeppert RH. Arsenite and arsenate adsorption on ferrihydrite: Kinetics, equilibrium, and adsorption envelopes. Environmental Science & Technology. 1998;**32**(3): 344-349. DOI: 10.1021/es970421p

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[21] Hossain MA, Kumita M, Michigami Y, Mori S. Optimization of parameters for Cr (VI) adsorption on used black tea leaves. Adsorption. 2005;**11**(5–6):561-568. DOI: 10.1007/s10450-005-5613-4

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Sustainability. 2017;**9**(9):1-13. DOI:

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*Experimental Study of Adsorption on Activated Carbon for CO2 Capture DOI: http://dx.doi.org/10.5772/intechopen.85834*

Process Biochemistry. 1999;**34**(5): 451-465. DOI: 10.1016/s0032-9592(98) 00112-5

Conservation and Recycling. 1999;**27**(1– 2):57-71. DOI: 10.1016/s0921-3449(98)

[22] Eligwe CA, Okolue NB. Adsorption of iron (II) by a Nigerian brown coal. Fuel. 1994;**73**(4):569-572. DOI: 10.1016/

[23] Sparks DL. Kinetics of Soil Chemical Processes. 1st ed. Massachusetts, USA: Academic Press; 1989. DOI: 10.1016/

[24] Annadurai G, Juang RS, Lee DJ. Use of cellulose-based wastes for adsorption of dyes from aqueous solutions. Journal of Hazardous Materials. 2002;**92**(3): 263-274. DOI: 10.1016/s0304-3894(02)

[25] Özacar M, Şengil IA. Adsorption of reactive dyes on calcined alunite from aqueous solutions. Journal of Hazardous Materials. 2003;**98**(1–3):211-224. DOI: 10.1016/s0304-3894(02)00358-8

[26] Ho YS, Chiang CC. Sorption studies

[27] Chiou MS, Li HY. Equilibrium and kinetic modeling of adsorption of reactive dye on cross-linked chitosan beads. Journal of Hazardous Materials. 2002;**93**(2):233-248. DOI: 10.1016/

[28] Wu FC, Tseng RL, Juang RS. Kinetic modeling of liquid-phase adsorption of

of acid dye by mixed sorbents. Adsorption. 2001;**7**(2):139-147. DOI:

10.1023/A:1011652224816

s0304-3894(02)00030-4

00307-9

reactive dyes and metal ions on chitosan. Water Research. 2001;**35**(3): 613-618. DOI: 10.1016/s0043-1354(00)

[29] Wu FC, Tseng RL, Juang RS. Kinetics of color removal by adsorption from water using activated clay.

721-729. DOI: 10.1080/ 09593332208618235

Environmental Technology. 2001;**22**(6):

[30] Ho YS, McKay G. Pseudo-second order model for sorption processes.

0016-2361(94)90042-6

b978-012656446-4/50007-4

00017-1

[15] Carrasco-Marin F, Lopez-Ramon MV, Moreno-Castilla C. Applicability of the Dubinin-Radushkevich equation to carbon dioxide adsorption on activated

2758-2760. DOI: 10.1021/-la00035a002

[16] Lin SH, Juang RS. Heavy metal removal from water by sorption using surfactant-modified montmorillonite. Journal of Hazardous Materials. 2002;

[17] Fadali OA, Magdy YH, Daifullah AAM, Ebrahiem EE, Nassar MM. Removal of chromium from tannery effluents by adsorption. Journal of Environmental Science and Health. 2004;**39**(2):465-472. DOI: 10.1081/ese-

[18] Yang H, Xu Z, Fan M, Gupta R, Slimane RB, Bland AE, et al. Progress in carbon dioxide separation and capture: A review. Journal of Environmental Sciences. 2008;**20**:14-27. DOI: 10.1016/

[19] Raven KP, Jain A, Loeppert RH. Arsenite and arsenate adsorption on ferrihydrite: Kinetics, equilibrium, and adsorption envelopes. Environmental Science & Technology. 1998;**32**(3): 344-349. DOI: 10.1021/es970421p

[20] Al-Meshragi M, Ibrahim HG, Okasha AY. Removal of trivalent chromium from aquatic environment by cement kiln dust: Batch studies. AIP Conf. Proc. 2009;**1127**(1):74-85. DOI:

[21] Hossain MA, Kumita M, Michigami Y, Mori S. Optimization of parameters for Cr (VI) adsorption on used black tea leaves. Adsorption. 2005;**11**(5–6):561-568. DOI:

10.1063/1. 3146200

**128**

10.1007/s10450-005-5613-4

S1001-0742(08)60002-9

carbons. Langmuir. 1993;**9**(11):

**92**(3):315-326. DOI: 10.1016/ s0304-3894(02)00026-2

00085-8

*CO2 Sequestration*

120027537

[31] Srivastava SK, Tyagi R, Pant N. Adsorption of heavy metal ions on carbonaceous material developed from the waste slurry generated in local fertilizer plants. Water Research. 1980; **23**(9):1161-1165. DOI: 10.1016/ 0043-1354(89)90160-7

[32] Shiue A, Hu SC, Chang SM, Ko TY, Hsieh A, Chan A. Adsorption kinetics and breakthrough of carbon dioxide for the chemical modified activated carbon filter used in the building. Sustainability. 2017;**9**(9):1-13. DOI: 10.3390/su9091533

[33] Demirbaş E, Kobya M, Öncel S, Şencan S. Removal of Ni(II) from aqueous solution by adsorption onto hazelnut shell activated carbon: Equilibrium studies. Bioresource Technology. 2002;**84**(3):291-293. DOI: 10.1016/s0960-8524(02)00052-4

[34] Sahmoune MN, Louhab K, Boukhiar A, Addad J, Barr S. Kinetic and equilibrium models for the biosorption of Cr(III) on Streptomyces rimosus. Toxicological and Environmental Chemistry. 2009;**91**(7):1291-1303. DOI: 10.1080/02772240802613731

[35] Wang S, Li H. Dye adsorption on unburned carbon: Kinetics and equilibrium. Journal of Hazardous Materials. 2005;**126**(1–3):71-77. DOI: 10.1016/j.jhazmat.2005.05.049

[36] Rashidi NA, Yusup S, Loong LH. Kinetic studies on carbon dioxide capture using activated carbon. Chemical Engineering Transaction, AIDIC Publications. 2013;**35**:361-366. DOI: 10.3303/CET1335060

[37] Kaithwas A, Prasad M, Kulshreshtha A, Verma S. Industrial wastes derived

solid adsorbents for CO2 capture: A mini review. Chemical Engineering Research and Design. 2012;**90**:1632-1641. DOI: 10.1016/j.cherd.2012.02.011

[38] Guo B, Chang L, Xiel K. Adsorption of carbon dioxide on activated carbon. Journal of Natural Gas Chemistry. 2006; **15**(3):223-229. DOI: 10.1016/S1003-9953 (06)60030-3

[39] Li A, Wu H, Zhang Q, Zhang G, Long C, Fei Z, et al. Thermodynamic study of adsorption of phenolic compounds from aqueous solution by a water-compatible hypercrosslinked polymeric adsorbent. Chinese Journal of Polymer Science. 2004;**22**(3):259-267

[40] Thomas WJ, Crittenden B. The Literature of Adsorption. Adsorption Technology and Design. Massachusetts, USA: Butterworth-Heinemann; 1989. DOI: 10.1016/b978-075061959-2/ 50009-4

[41] Soltani DC, Safari M, Rezaee A, Godini H. Application of a compound containing silica for removing ammonium in aqueous media. Environmental Progress & Sustainable Energy. 2014;**34**(1):105-111. DOI: 10.1002/ep.11969

[42] Maroto-Valer MM, Tang Z, Zhang Y. CO2 capture by activated and impregnated anthracites. Fuel Processing Technology. 2005;**86**: 1487-1502. DOI: 10.1016/j. fuproc.2005.01.003

[43] Saha P, Chowdhury S. Insight into adsorption thermodynamics. In: Tadashi M, editor. Thermodynamics. Rijeka: InTech; 2011. DOI: 10.5772/13474

[44] Rashidi NA, Yusup S, Borhan A. Isotherm and thermodynamic analysis of carbon dioxide on activated carbon. Procedia Engineering. 2016;**148**: 630-637. DOI: 10.1016/j. proeng.2016.06.527

[45] Zhao Y, Wang D, Xie H, Won SW, Cui L, Wu G. Adsorption of Ag (I) from aqueous solution by waste yeast: Kinetic, equilibrium and mechanism studies. Bioprocess and Biosystems Engineering. 2015;**38**(1):69-77. DOI: 10.1007/s00449-014-1244-z

[46] Liang S, Guo X, Feng N, Tian Q. Isotherms, kinetics and thermodynamic studies of adsorption of Cu2+ from aqueous solutions by Mg2+/K+ type orange peel adsorbents. Journal of Hazardous Materials. 2010;**174**(1–3): 756-762. DOI: 10.1016/j. jhazmat.2009.09.116

[47] Yi H, Wang Z, Liu H, Tang X, Ma D, Zhao S, et al. Adsorption of SO2, NO, and CO2 on activated carbons: Equilibrium and thermodynamics. Journal of Chemical & Engineering Data. 2014;**59**(5):1556-1563. DOI: 10.1021/je4011135

**131**

**Chapter 8**

of CO2

**Abstract**

**1. Introduction**

safety of technology.

Carbon Capture and Storage

(CCS): Geological Sequestration

*Nediljka Gaurina-Međimurec and Karolina Novak Mavar*

The European Union greenhouse gas emission reduction target can be achieved only by applying efficient technologies, which give reliable results in a very short time. Carbon capture and storage (CCS) into geological formations covers capturing CO2 at the large point sources, its transportation and underground deposition. The CCS technology is applicable to different industries (natural gas processing, power generation, iron and steel production, cement manufacturing, etc.). Due to huge storage capacity and existing infrastructure, depleted hydrocarbon reservoirs are one of the most favourable storage options. In order to give overall cross section through CCS technology, implementation status and other relevant issues, the chapter covers EU regulation, technology overview, large-scale and pilot CCS projects, CO2-enhanced oil recovery (EOR) projects, geological storage components, CO2 storage capacity, potential CO2 migration paths, risk assessment and CO2 injection monitoring. Permanent geological sequestration depends on both natural and technical site performance. Site selection, designing, construction and management must ensure acceptable

risk rates of less than 1% over thousands of years.

**Keywords:** carbon capture and storage (CCS), geological sequestration, enhanced oil recovery, trapping mechanisms, risk assessment, monitoring

Global warming issue and commitments towards reducing greenhouse gas emissions of at least 40% in 2030 and up to 95% in 2050 compared to 1990 level have initiated the development of certain strategies for CO2 removal from the atmosphere, which recognised storage in underground formations as a most practical and suitable option. Although potential underground formation could be in the form of depleted oil and gas fields, deep saline formations or deep unmineable coal seams, commercial implementation is only possible if acceptable risk level is ensured. Huge practice, existing infrastructure and remaining storage capacities are the most important advantages of using depleted hydrocarbon reservoirs for those purposes. Furthermore, residual oil production, when carbon capture and storage is connected to enhanced oil recovery, is additional initiative. On the other hand, lack of research when it comes to other storage options requires different research programs to be performed in order to confirm projects feasibility and the

#### **Chapter 8**

[45] Zhao Y, Wang D, Xie H, Won SW, Cui L, Wu G. Adsorption of Ag (I) from

aqueous solution by waste yeast: Kinetic, equilibrium and mechanism studies. Bioprocess and Biosystems Engineering. 2015;**38**(1):69-77. DOI:

*CO2 Sequestration*

10.1007/s00449-014-1244-z

756-762. DOI: 10.1016/j. jhazmat.2009.09.116

10.1021/je4011135

**130**

[46] Liang S, Guo X, Feng N, Tian Q. Isotherms, kinetics and thermodynamic studies of adsorption of Cu2+ from aqueous solutions by Mg2+/K+ type orange peel adsorbents. Journal of Hazardous Materials. 2010;**174**(1–3):

[47] Yi H, Wang Z, Liu H, Tang X, Ma D, Zhao S, et al. Adsorption of SO2, NO, and CO2 on activated carbons: Equilibrium and thermodynamics. Journal of Chemical & Engineering Data. 2014;**59**(5):1556-1563. DOI:

## Carbon Capture and Storage (CCS): Geological Sequestration of CO2

*Nediljka Gaurina-Međimurec and Karolina Novak Mavar*

#### **Abstract**

The European Union greenhouse gas emission reduction target can be achieved only by applying efficient technologies, which give reliable results in a very short time. Carbon capture and storage (CCS) into geological formations covers capturing CO2 at the large point sources, its transportation and underground deposition. The CCS technology is applicable to different industries (natural gas processing, power generation, iron and steel production, cement manufacturing, etc.). Due to huge storage capacity and existing infrastructure, depleted hydrocarbon reservoirs are one of the most favourable storage options. In order to give overall cross section through CCS technology, implementation status and other relevant issues, the chapter covers EU regulation, technology overview, large-scale and pilot CCS projects, CO2-enhanced oil recovery (EOR) projects, geological storage components, CO2 storage capacity, potential CO2 migration paths, risk assessment and CO2 injection monitoring. Permanent geological sequestration depends on both natural and technical site performance. Site selection, designing, construction and management must ensure acceptable risk rates of less than 1% over thousands of years.

**Keywords:** carbon capture and storage (CCS), geological sequestration, enhanced oil recovery, trapping mechanisms, risk assessment, monitoring

#### **1. Introduction**

Global warming issue and commitments towards reducing greenhouse gas emissions of at least 40% in 2030 and up to 95% in 2050 compared to 1990 level have initiated the development of certain strategies for CO2 removal from the atmosphere, which recognised storage in underground formations as a most practical and suitable option. Although potential underground formation could be in the form of depleted oil and gas fields, deep saline formations or deep unmineable coal seams, commercial implementation is only possible if acceptable risk level is ensured. Huge practice, existing infrastructure and remaining storage capacities are the most important advantages of using depleted hydrocarbon reservoirs for those purposes. Furthermore, residual oil production, when carbon capture and storage is connected to enhanced oil recovery, is additional initiative. On the other hand, lack of research when it comes to other storage options requires different research programs to be performed in order to confirm projects feasibility and the safety of technology.

Formation storage possibility has to be defined through characterisation and assessment of potential storage complex, comprising data collection, static and dynamic modelling, sensitivity characterisation and risk assessment. Underground storage must meet relevant capacity and injectivity requirements, while storage efficiency depends on different physical and geochemical trapping mechanisms, which occur during the storage lifecycle [1]. Nevertheless, permanent storage is ensured by existing geological and equipment barriers; a certain risk of CO2 migration has to be considered, assessed and controlled [2]. Special attention must be paid to the injected fluid migration issue, which implies identification of potential migration routes, such as faults and fractures, wells (active and abandoned) and seal rocks [3, 4]. In line with legal requirements, performed risk analysis and established monitoring plan, the effectiveness of storage complex has to be constantly evaluated. Comprehensive monitoring, which covers CO2 plume tracking and surrounding environment monitoring, represents a very important part of the overall risk management strategy.

#### **2. CCS deployment legal background**

The international climate goal, set within the United Nations Framework Convention on Climate Change (UNFCCC) in Paris in 2015, seeks the limitation of the average temperature increase to below 2°C, compared to preindustrialisation reference level. That quite ambitious climate target depends on economy decarbonisation through increasing energy efficiency, enhancing the share of renewables in energy production and reducing greenhouse gas emissions. In order to achieve low carbon economy, the EU strategy targeted greenhouse gases emission reduction by 40% by 2030, and up to 95% by 2050 compared to the base year (1990) level [5, 6].

However, despite the efforts to enhance "green energy" sources, the society is still largely dependent on fossil fuels and it is evident that conventional carbon technologies cannot be removed easily from the industry processes in close future. Therefore, a systematic approach is needed.

The EU Directive 2009/31/EC on the geological storage of carbon dioxide [7] entered into force in 2009, establishing a legal framework for safe CO2 geological sequestration in Europe. The Directive attempted to prevent any significant CO2 leakage risk or damage to health and/or the environment by setting requirements for the entire storage cycle. It excludes potable water aquifers and tectonically active zones as potential sites for permanent disposal of CO2.

The EU-requested emission reductions are expected to be achieved through the main instrument—the European Emission Trading Scheme (EU ETS) (**Figure 1**). The system is based on the EU Directive 2003/87/EC, establishing a scheme for greenhouse gas emission allowance trading within the Community [8]*.* It operates on a cap and trade principle, which considers behaviour in line with installations emission permits and market trading of EU emission unit allowances. Temporarily, the third phase of the system is operational (2013–2021). The main issue at the beginning of the third trading period was the imbalance between allowances supply and demand on the market, caused mainly by lower industrial activity. In order to overcome such unsustainable situation and increase the CO2 price, which would encourage system participants to apply emission reduction measures comprising the CCS projects, a radical legislation revision was needed. It included the increase in the allowances reduction factor, auctioning the postponement of 900 million of allowances and establishment of the market stability reserve [9]*.*

Carbon capture and storage technology is often observed as a transitional solution to low-carbon economy, due to possibility of further usage of fossil fuels in power

**133**

on the oil price.

**Figure 1.**

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2*

generation while simultaneously reducing CO2 emission [10]. Since the demanding climate goals require about 4000 Mt/y of CO2 to be removed from the atmosphere by 2040 [11], a lot of further effort has to be invested. Inclusion of CCS in clean develop-

The success of the CCS project is only possible if stable, clear and efficient regulatory framework and supporting public acceptance are ensured [13]. A political decision on CCS is influenced by different factors, such as national CO2 emission level and emission reduction commitments, available storage capacity and public awareness. This means that most of the research and development activities occur in the states with the highest emissions intensity (e.g., Germany, the UK, Italy, France, Spain, the Netherlands and Norway). On the other hand, strong local public resistance (e.g., in Denmark, Germany, the UK, Poland and the Netherlands) resulted with the cancella-

Still, most of the EU Member States transposed the Directive without any restrictions and continue to support research in order to improve the technology (**Figure 2**). Since the CCS initiatives in the EU originate from climate changes mitigation intention, projects in North America are mostly connected to the EOR activities, with CO2 sales as a major incentive. Viability of such projects is strongly dependent

Due to instability of market oil prices, financial support is crucial to provide a certain level of certainty. CCS projects are supported by different policies at Federal, State and local levels. The Department of Energy (DOE) provides financial assistance and grants in line with the Energy Improvement and Extension Act (2008) and the American Recovery and Reinvestment Act (2009) [13]. In EU, additional funding may refer to the EU Energy Program for Recovery (EEPR), the NER300, FP7 or some national government funding schemes [15]. The ETS Innovation Fund is a new EU funding scheme, scheduled for 2021. Based on the

ment mechanisms (CDMs) is one step ahead in its global deployment [12].

*The European Emission Trading Scheme (EU ETS) principles.*

tion of more projects and the postponement of CO2 storage acceptance [14].

*DOI: http://dx.doi.org/10.5772/intechopen.84428*

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2 DOI: http://dx.doi.org/10.5772/intechopen.84428*

*CO2 Sequestration*

overall risk management strategy.

**2. CCS deployment legal background**

Therefore, a systematic approach is needed.

zones as potential sites for permanent disposal of CO2.

allowances and establishment of the market stability reserve [9]*.*

Formation storage possibility has to be defined through characterisation and assessment of potential storage complex, comprising data collection, static and dynamic modelling, sensitivity characterisation and risk assessment. Underground storage must meet relevant capacity and injectivity requirements, while storage efficiency depends on different physical and geochemical trapping mechanisms, which occur during the storage lifecycle [1]. Nevertheless, permanent storage is ensured by existing geological and equipment barriers; a certain risk of CO2 migration has to be considered, assessed and controlled [2]. Special attention must be paid to the injected fluid migration issue, which implies identification of potential migration routes, such as faults and fractures, wells (active and abandoned) and seal rocks [3, 4]. In line with legal requirements, performed risk analysis and established monitoring plan, the effectiveness of storage complex has to be constantly evaluated. Comprehensive monitoring, which covers CO2 plume tracking and surrounding environment monitoring, represents a very important part of the

The international climate goal, set within the United Nations Framework Convention on Climate Change (UNFCCC) in Paris in 2015, seeks the limitation of the average temperature increase to below 2°C, compared to preindustrialisation reference level. That quite ambitious climate target depends on economy decarbonisation through increasing energy efficiency, enhancing the share of renewables in energy production and reducing greenhouse gas emissions. In order to achieve low carbon economy, the EU strategy targeted greenhouse gases emission reduction by 40% by 2030, and up to 95% by 2050 compared to the base year (1990) level [5, 6]. However, despite the efforts to enhance "green energy" sources, the society is still largely dependent on fossil fuels and it is evident that conventional carbon technologies cannot be removed easily from the industry processes in close future.

The EU Directive 2009/31/EC on the geological storage of carbon dioxide [7] entered into force in 2009, establishing a legal framework for safe CO2 geological sequestration in Europe. The Directive attempted to prevent any significant CO2 leakage risk or damage to health and/or the environment by setting requirements for the entire storage cycle. It excludes potable water aquifers and tectonically active

The EU-requested emission reductions are expected to be achieved through the main instrument—the European Emission Trading Scheme (EU ETS) (**Figure 1**). The system is based on the EU Directive 2003/87/EC, establishing a scheme for greenhouse gas emission allowance trading within the Community [8]*.* It operates on a cap and trade principle, which considers behaviour in line with installations emission permits and market trading of EU emission unit allowances. Temporarily, the third phase of the system is operational (2013–2021). The main issue at the beginning of the third trading period was the imbalance between allowances supply and demand on the market, caused mainly by lower industrial activity. In order to overcome such unsustainable situation and increase the CO2 price, which would encourage system participants to apply emission reduction measures comprising the CCS projects, a radical legislation revision was needed. It included the increase in the allowances reduction factor, auctioning the postponement of 900 million of

Carbon capture and storage technology is often observed as a transitional solution to low-carbon economy, due to possibility of further usage of fossil fuels in power

**132**

**Figure 1.** *The European Emission Trading Scheme (EU ETS) principles.*

generation while simultaneously reducing CO2 emission [10]. Since the demanding climate goals require about 4000 Mt/y of CO2 to be removed from the atmosphere by 2040 [11], a lot of further effort has to be invested. Inclusion of CCS in clean development mechanisms (CDMs) is one step ahead in its global deployment [12].

The success of the CCS project is only possible if stable, clear and efficient regulatory framework and supporting public acceptance are ensured [13]. A political decision on CCS is influenced by different factors, such as national CO2 emission level and emission reduction commitments, available storage capacity and public awareness. This means that most of the research and development activities occur in the states with the highest emissions intensity (e.g., Germany, the UK, Italy, France, Spain, the Netherlands and Norway). On the other hand, strong local public resistance (e.g., in Denmark, Germany, the UK, Poland and the Netherlands) resulted with the cancellation of more projects and the postponement of CO2 storage acceptance [14].

Still, most of the EU Member States transposed the Directive without any restrictions and continue to support research in order to improve the technology (**Figure 2**).

Since the CCS initiatives in the EU originate from climate changes mitigation intention, projects in North America are mostly connected to the EOR activities, with CO2 sales as a major incentive. Viability of such projects is strongly dependent on the oil price.

Due to instability of market oil prices, financial support is crucial to provide a certain level of certainty. CCS projects are supported by different policies at Federal, State and local levels. The Department of Energy (DOE) provides financial assistance and grants in line with the Energy Improvement and Extension Act (2008) and the American Recovery and Reinvestment Act (2009) [13]. In EU, additional funding may refer to the EU Energy Program for Recovery (EEPR), the NER300, FP7 or some national government funding schemes [15]. The ETS Innovation Fund is a new EU funding scheme, scheduled for 2021. Based on the


#### **Figure 2.**

*CO2 storage permitting in European countries [14].*

NER300 platform, it is going to support innovative low-carbon technologies, including CCS demonstration projects, by monetizing 400 million of CO2 emissions unit allowances (EUA) from the New Entrants' Reserve [16].

#### **3. CCS technology overview**

Capturing CO2 from the exhaust gases generated by different energy intensive industries (e.g., power generation, oil refineries or iron, steel and cement production), its transportation and permanent sequestration are fundamental parts of the CCS processes.

Exhaust gas is a mixture, which, besides nitrogen, steam, particulate matters and some other pollutants, contains only a small share of CO2 (3–15%). That means that pure CO2 must be extracted using different capture technologies: (a) pre-combustion capture system, (b) post-combustion capture system, (c) oxyfuel combustion system and (d) industrial separation (**Figure 3**). Technology selection depends on the concentration of CO2 in the gas stream, pressure and fuel type [1, 17].

A **pre-combustion** capture processes comprise adding steam or oxygen to primary fuel, which results in synthesis gas (gas containing H2 and CO) production. Further reaction of CO and steam in the shift reactor produces a mixture of H2 and CO2 in concentration between 5 and 15% volume. After separation, CO2 is extracted by physical or chemical adsorption. In a **post-combustion** capture system, CO2 is extracted from nitrogen after combustion by different physical or chemical solvents, or it is separated by adsorbents or membranes. This common technology can be an upgrade to existing thermal power plants and different industrial facilities, etc. An **oxyfuel combustion** capture system considers oxygen addition in the process of fossil fuel combustion, resulting in more concentrated CO2 stream (more than 80% volume), which is prone to easier separation. Although this technology is simple and highly efficient in CO2 removal, wide application is still prevented by the high cost of pure oxygen production. **Industrial separation** has had the longest usage: the CO2, as unwanted compound, is separated in different industrial processes, comprising natural gas, hydrogen and ammonia production [1, 2, 17].

**135**

power sector [19].

**Figure 3.**

*Carbon capture processes [2].*

**4. CCS projects**

substantial for risk decreasing and cost reduction.

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2*

The Carbon Capture R&D program has been implemented by the US National Energy Technology Laboratory (NETL) in order to develop cost-effective technolo-

After capturing, the CO2 can be transported at solid, gaseous or liquid state or in the form of supercritical fluid. Although ships can be used, pipeline transport is

Application of CCS compared to other carbon sequestration options is preferred due to costs. The cost of geological storage of CO2 depends on several factors such as the depth of the storage formation, the number of wells needed for injection and whether the project is onshore or offshore. For instance, capture system installed at fossil fuel power plant is between 15 and 75 USD/t (CO2), where the coal-fired plants are the higher cost option. The costs are something lower in case of hydrogen, ammonia production or gas sweetening (from 5 to 55 USD/t (CO2), while application to other industries is even more expensive, with costs between 25 and 115 USD/t (CO2). Taking into consideration the costs of transportation of 5–40 Mt/y CO2 by pipeline, which are on the level of 1–8 USD/t (CO2), and geological storage and monitoring costs, which range from 0.6 to 8 USD/t (CO2), it can be concluded that capture costs make up the majority of the price. However, considering the largest emissions belong to the fossil fuel power plants, it is important that research priority is focused on developing cost-effective capture technologies for

As is the case with all new technologies, implementation of CCS is facing different obstacles, which prevent a shift from the project planning phase to construction and operation phase. Commercial scale implementation requires a certain level of experience in technical, operational and economic feasibility of projects, which is

Several decades of worldwide implementation of CCS research programs have resulted in a huge amount of experience and important knowledge on carbon capture and storage technology. The data obtained during large- and small-scale projects implementation are collected by different associations. Comprehensive

databases founded by, for example, Carbon Capture and Sequestration Technologies at the Massachusetts Institute of Technology (MIT) [15], Global CCS Institute [20], National Energy Technology Laboratory (NETL) [18], Zero

gies based on different concepts (solvent, sorbent or membrane) [18].

often preferred as the most practical and the cheapest solution.

*DOI: http://dx.doi.org/10.5772/intechopen.84428*

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2 DOI: http://dx.doi.org/10.5772/intechopen.84428*

**Figure 3.** *Carbon capture processes [2].*

*CO2 Sequestration*

NER300 platform, it is going to support innovative low-carbon technologies, including CCS demonstration projects, by monetizing 400 million of CO2 emissions

Capturing CO2 from the exhaust gases generated by different energy intensive industries (e.g., power generation, oil refineries or iron, steel and cement production), its transportation and permanent sequestration are fundamental parts of the

Exhaust gas is a mixture, which, besides nitrogen, steam, particulate matters and some other pollutants, contains only a small share of CO2 (3–15%). That means that pure CO2 must be extracted using different capture technologies: (a) pre-combustion capture system, (b) post-combustion capture system, (c) oxyfuel combustion system and (d) industrial separation (**Figure 3**). Technology selection depends on the

A **pre-combustion** capture processes comprise adding steam or oxygen to primary fuel, which results in synthesis gas (gas containing H2 and CO) production. Further reaction of CO and steam in the shift reactor produces a mixture of H2 and CO2 in concentration between 5 and 15% volume. After separation, CO2 is extracted by physical or chemical adsorption. In a **post-combustion** capture system, CO2 is extracted from nitrogen after combustion by different physical or chemical solvents, or it is separated by adsorbents or membranes. This common technology can be an upgrade to existing thermal power plants and different industrial facilities, etc. An **oxyfuel combustion** capture system considers oxygen addition in the process of fossil fuel combustion, resulting in more concentrated CO2 stream (more than 80% volume), which is prone to easier separation. Although this technology is simple and highly efficient in CO2 removal, wide application is still prevented by the high cost of pure oxygen production. **Industrial separation** has had the longest usage: the CO2, as unwanted compound, is separated in different industrial processes, comprising natural gas, hydrogen and ammonia production [1, 2, 17].

unit allowances (EUA) from the New Entrants' Reserve [16].

concentration of CO2 in the gas stream, pressure and fuel type [1, 17].

**3. CCS technology overview**

*CO2 storage permitting in European countries [14].*

CCS processes.

**Figure 2.**

**134**

The Carbon Capture R&D program has been implemented by the US National Energy Technology Laboratory (NETL) in order to develop cost-effective technologies based on different concepts (solvent, sorbent or membrane) [18].

After capturing, the CO2 can be transported at solid, gaseous or liquid state or in the form of supercritical fluid. Although ships can be used, pipeline transport is often preferred as the most practical and the cheapest solution.

Application of CCS compared to other carbon sequestration options is preferred due to costs. The cost of geological storage of CO2 depends on several factors such as the depth of the storage formation, the number of wells needed for injection and whether the project is onshore or offshore. For instance, capture system installed at fossil fuel power plant is between 15 and 75 USD/t (CO2), where the coal-fired plants are the higher cost option. The costs are something lower in case of hydrogen, ammonia production or gas sweetening (from 5 to 55 USD/t (CO2), while application to other industries is even more expensive, with costs between 25 and 115 USD/t (CO2). Taking into consideration the costs of transportation of 5–40 Mt/y CO2 by pipeline, which are on the level of 1–8 USD/t (CO2), and geological storage and monitoring costs, which range from 0.6 to 8 USD/t (CO2), it can be concluded that capture costs make up the majority of the price. However, considering the largest emissions belong to the fossil fuel power plants, it is important that research priority is focused on developing cost-effective capture technologies for power sector [19].

#### **4. CCS projects**

As is the case with all new technologies, implementation of CCS is facing different obstacles, which prevent a shift from the project planning phase to construction and operation phase. Commercial scale implementation requires a certain level of experience in technical, operational and economic feasibility of projects, which is substantial for risk decreasing and cost reduction.

Several decades of worldwide implementation of CCS research programs have resulted in a huge amount of experience and important knowledge on carbon capture and storage technology. The data obtained during large- and small-scale projects implementation are collected by different associations. Comprehensive databases founded by, for example, Carbon Capture and Sequestration Technologies at the Massachusetts Institute of Technology (MIT) [15], Global CCS Institute [20], National Energy Technology Laboratory (NETL) [18], Zero

Emissions Platform [21], British Geological Survey [22], etc., can serve as a valuable source of information in further research and design [2].

A large-scale facility captures at least 0.8 Mt of CO2 from a coal-based facility for power generation or at least 0.4 Mt of CO2 from other industry on yearly basis [20].

Due to insufficient capture capacity or absence of full integration, a number of the CCS projects cannot be declared as large scale, but since they are focused on the targeted parts of the CCS chain, they contribute to the development of technology. The small-scale projects can be used for demonstration or on a pilot scale.

The Global Carbon Capture and Storage Institute database counts 23 large-scale CCS facilities both in operation and under construction, having capture capacity of approximately 30 Mt/y. Realisation of further 5 projects, which are now in advanced planning phase, as well as another 15 projects, which are in early planning, could significantly increase capture capacity by more than 60 Mt/y.

Temporarily ongoing large-scale CCS projects are located in the USA, Canada, China, Saudi Arabia, United Arab Emirates and Europe. In Europe, the lack of national policy support and negative public opinion resulted in cancellation of some of the most promising CCS projects. However, successful operation of two Norwegian large-scale projects (Sleipner and Snøhvit) is enabled by high national carbon taxation. Future CCS activities in Europe are going to be expanded to two new offshore storage projects: Norway full chain CCS and Port of Rotterdam CCUS Backbone Initiative (Porthos).

Some of CCS projects are in the advanced planning or in the early planning phase. They are going to geologically store emissions from power generation and chemical industry. As regards CO2 capture process, high cost of oxyfuel technology is the reason that only post-combustion technology has been applied [2, 20].

According to Carbon Capture and Sequestration Technologies at MIT database, there are substantial numbers of small-scale demonstration and pilot projects worldwide applied on different industries. Most of them are performed in Asia (China, Japan and South Korea), but also and to a lesser extent in the North America and Europe [15].

#### **4.1 CO2-EOR projects**

Production from oil reservoirs is carried out in three phases: primary, secondary and tertiary. During the *primary recovery stage*, the reservoir pressure is sufficient to force the oil to the surface and recovery factor is typically 5–15%. During exploitation, reservoir pressure decreases and at one point, it becomes insufficient to force the oil to the surface. After that, *secondary recovery* methods are applied. They include water injection or natural gas reinjection to increase the reservoir pressure or gas lift (injection of gas into an active well to reduce the density of fluid in the well). The typical recovery factor from secondary operations is about 30%. Further increase of oil production is possible by the application of *tertiary oil recovery methods* or enhanced oil recovery (EOR) methods (including thermal recovery, chemical flooding and miscible gas injection), which increase the mobility of oil. Tertiary recovery provides additional production of 5–15% of oil.

CO2-EOR is one of the tertiary oil recovery methods. The petroleum industry has been injecting CO2 into partially depleted oil reservoirs for dozens of years. It is based on injection of CO2 and usually water into the oil reservoir with the aim to enhance oil recovery by maintaining pressure in the reservoir and by improving oil ability to flow in the direction of the production well (**Figure 4**).

The CO2 is produced along with the oil and then recovered and reinjected to recover more oil. When the maximum amount of oil is recovered from the reservoir, the CO2 is then "sequestered" in the underground geologic zone that formerly contained oil and the well is shut in, permanently sequestering the CO2.

**137**

600,000 t/y of CO2.

higher oil prices [1].

**Figure 4.**

increase oil recovery from fields in Texas, USA [24].

*The process of CO2 and water injection in order to improve oil recovery [23].*

the Weyburn oil field in Saskatchewan, Canada.

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2*

EOR sites offer several advantages such as (1) well-understood geology and geologic seals, (2) proven capacity to hold volumes of CO2 and (3) existing infrastructure such as surface facilities, pipelines, injection and monitoring wells. CO2-EOR can be employed onshore and offshore. It could lead to negative storage costs of 10–16 US\$/t CO2 for oil prices of 15–20 US\$ per barrel and more for

CO2-EOR was first attempted in 1972 in Scurry County, Texas. In the 1970s, Shell was one of the first companies to inject naturally occurring carbon dioxide (CO2) to

While initial CO2-EOR developments used naturally occurring carbon dioxide deposits, technologies have been developed to inject CO2 created as by-products from industrial operations. For example, Dakota Gasification Company's plant in Beulah, North Dakota, is producing CO2 and delivering it by a 204-mile pipeline to

According to the CCS institute database, within the last 2 years, four largescale projects were launched. Large-scale Emirates Steel Industries (ESI) CCS project running in Abu Dhabi represents the first application of CCS to iron and steel industry, where 0.8 Mt/y of CO2 is injected underground for the purpose of hydrocarbon recovery [2, 20]. The Illinois Industrial CCS project enabled the capture of 1.0 Mt/y of CO2 generated at the corn to ethanol facility in Decatur (Illinois, USA) and its permanent geological disposal, while the Petra New Carbon Capture project in Texas stands out for the largest power plant postcombustion CO2 capture system. Captured gas at 1.4 Mt/y capacity is transported by pipeline and injected for EOR purposes. Another recent example where CO2 is injected to improve oil recovery is the Chinese CNPC Jilin Oil Field CO2 EOR project. After 12 years of testing, commercial operation started in 2018. The CO2 source is at a natural gas processing plant. Capturing capacity is on the level of

*DOI: http://dx.doi.org/10.5772/intechopen.84428*

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2 DOI: http://dx.doi.org/10.5772/intechopen.84428*

**Figure 4.**

*CO2 Sequestration*

America and Europe [15].

**4.1 CO2-EOR projects**

Emissions Platform [21], British Geological Survey [22], etc., can serve as a valuable

The small-scale projects can be used for demonstration or on a pilot scale.

CCS facilities both in operation and under construction, having capture capacity of approximately 30 Mt/y. Realisation of further 5 projects, which are now in advanced planning phase, as well as another 15 projects, which are in early planning, could significantly increase capture capacity by more than 60 Mt/y.

Temporarily ongoing large-scale CCS projects are located in the USA, Canada, China, Saudi Arabia, United Arab Emirates and Europe. In Europe, the lack of national policy support and negative public opinion resulted in cancellation of some of the most promising CCS projects. However, successful operation of two Norwegian large-scale projects (Sleipner and Snøhvit) is enabled by high national carbon taxation. Future CCS activities in Europe are going to be expanded to two new offshore storage projects: Norway full chain CCS and Port of Rotterdam CCUS Backbone Initiative (Porthos). Some of CCS projects are in the advanced planning or in the early planning phase. They are going to geologically store emissions from power generation and chemical industry. As regards CO2 capture process, high cost of oxyfuel technology is the reason that only post-combustion technology has been applied [2, 20].

According to Carbon Capture and Sequestration Technologies at MIT database,

Production from oil reservoirs is carried out in three phases: primary, secondary and tertiary. During the *primary recovery stage*, the reservoir pressure is sufficient to force the oil to the surface and recovery factor is typically 5–15%. During exploitation, reservoir pressure decreases and at one point, it becomes insufficient to force the oil to the surface. After that, *secondary recovery* methods are applied. They include water injection or natural gas reinjection to increase the reservoir pressure or gas lift (injection of gas into an active well to reduce the density of fluid in the well). The typical recovery factor from secondary operations is about 30%. Further increase of oil production is possible by the application of *tertiary oil recovery methods* or enhanced oil recovery (EOR) methods (including thermal recovery, chemical flooding and miscible gas injection), which increase the mobility of oil. Tertiary

CO2-EOR is one of the tertiary oil recovery methods. The petroleum industry has been injecting CO2 into partially depleted oil reservoirs for dozens of years. It is based on injection of CO2 and usually water into the oil reservoir with the aim to enhance oil recovery by maintaining pressure in the reservoir and by improving oil

The CO2 is produced along with the oil and then recovered and reinjected to recover more oil. When the maximum amount of oil is recovered from the reservoir, the CO2 is then "sequestered" in the underground geologic zone that formerly contained oil and the well is shut in, permanently sequestering the CO2.

there are substantial numbers of small-scale demonstration and pilot projects worldwide applied on different industries. Most of them are performed in Asia (China, Japan and South Korea), but also and to a lesser extent in the North

recovery provides additional production of 5–15% of oil.

ability to flow in the direction of the production well (**Figure 4**).

A large-scale facility captures at least 0.8 Mt of CO2 from a coal-based facility for power generation or at least 0.4 Mt of CO2 from other industry on yearly basis [20]. Due to insufficient capture capacity or absence of full integration, a number of the CCS projects cannot be declared as large scale, but since they are focused on the targeted parts of the CCS chain, they contribute to the development of technology.

The Global Carbon Capture and Storage Institute database counts 23 large-scale

source of information in further research and design [2].

**136**

*The process of CO2 and water injection in order to improve oil recovery [23].*

EOR sites offer several advantages such as (1) well-understood geology and geologic seals, (2) proven capacity to hold volumes of CO2 and (3) existing infrastructure such as surface facilities, pipelines, injection and monitoring wells.

CO2-EOR can be employed onshore and offshore. It could lead to negative storage costs of 10–16 US\$/t CO2 for oil prices of 15–20 US\$ per barrel and more for higher oil prices [1].

CO2-EOR was first attempted in 1972 in Scurry County, Texas. In the 1970s, Shell was one of the first companies to inject naturally occurring carbon dioxide (CO2) to increase oil recovery from fields in Texas, USA [24].

While initial CO2-EOR developments used naturally occurring carbon dioxide deposits, technologies have been developed to inject CO2 created as by-products from industrial operations. For example, Dakota Gasification Company's plant in Beulah, North Dakota, is producing CO2 and delivering it by a 204-mile pipeline to the Weyburn oil field in Saskatchewan, Canada.

According to the CCS institute database, within the last 2 years, four largescale projects were launched. Large-scale Emirates Steel Industries (ESI) CCS project running in Abu Dhabi represents the first application of CCS to iron and steel industry, where 0.8 Mt/y of CO2 is injected underground for the purpose of hydrocarbon recovery [2, 20]. The Illinois Industrial CCS project enabled the capture of 1.0 Mt/y of CO2 generated at the corn to ethanol facility in Decatur (Illinois, USA) and its permanent geological disposal, while the Petra New Carbon Capture project in Texas stands out for the largest power plant postcombustion CO2 capture system. Captured gas at 1.4 Mt/y capacity is transported by pipeline and injected for EOR purposes. Another recent example where CO2 is injected to improve oil recovery is the Chinese CNPC Jilin Oil Field CO2 EOR project. After 12 years of testing, commercial operation started in 2018. The CO2 source is at a natural gas processing plant. Capturing capacity is on the level of 600,000 t/y of CO2.

In Croatia, the first application of CO2-EOR started in October 2014 by the INA—Oil Industry Ltd. oil company. The project's aim is to enhance hydrocarbon production by alternating injection of carbon dioxide and water into mature oil fields Žutica and Ivanić [25]. The *EOR* project involves dehydration, compression and transportation of 600,000 m3 /day of CO2 by 88 km long gas pipeline (20 in.) from the Gas Processing Facilities Molve to the Fractionation Facilities Ivanić Grad.

After its compression and liquefaction at the location of Fractionation Facilities Ivanić Grad, CO2 is transported by pipeline at high pressure (200 bar) to the injection wells of the Ivanić and Žutica fields, in quantities of 400,000 and 200,000 m3 /day, respectively. During the period of 25 years, which is the expected duration of the project, about 5 × 109 m3 of CO2 will be injected in the reservoirs of these fields. That will result in additional hydrocarbon production (3.4 × 106 t of oil and 599 × 106 m3 of gas). Due to geological and physical conditions, about 50% of injected CO2 will be permanently trapped in the reservoirs, while another 50% of CO2 will be produced together with associated gas. Currently, the solution regarding the further use of CO2, which will be extracted from associated gas at the location of the Compressor Station Žutica, is being developed. To implement the EOR project, it was necessary to carry out workover operations and construction modifications of existing wells. Keeping in mind corrosive features of CO2, special attention was paid to the selection of surface and underground equipment.

According to Heidug et al. [26], CO2-EOR practice can be modified to deliver significant capacity for long-term CO2 storage. EOR expansion to storage of CO2 can be achieved through at least four major activities: (1) additional site characterisation and risk assessment to evaluate the storage capability of a site, (2) additional monitoring of vented and fugitive emissions, (3) additional subsurface monitoring and (4) changes to field abandonment practices.

#### **5. Geological storage complex and surrounding area characterisation**

Potential sites for geologic storage are depleted oil and gas fields, deep saline formations and deep unmineable coal seams. According to EU Directive 2009/31/EC [7], the characterisation and assessment of the potential storage complex, including the cap rock and surrounding area, including the hydraulically connected areas, should be carried out in three steps according to best practices at the time of the assessment: (1) data collection, (2) building the three-dimensional static geological earth model and (3) characterisation of the storage dynamic behaviour, sensitivity characterisation and risk assessment (**Figure 5**).

Collecting data about the storage complex and the surrounding area is very important because it serves as a base for making their volumetric and three-dimensional (3-D) static earth model.

In the first step, for describing the storage complex, it is necessary to collect information about its characteristics. In the second step, based on the collected data and using computerised reservoir simulators, a three-dimensional static geological earth model of the candidate storage complex, including the cap rock and the hydraulically connected areas and fluids, is built. It characterises the storage complex.

In the third step, the characterisations and assessment of storage complex are based on dynamic modelling, comprising a variety of time-step simulations of CO2 injection into the storage site using the three-dimensional static geological earth model(s) constructed during the second step. The simulations are based on altering parameters in the static geological earth model(s) and changing rate functions and assumptions in the dynamic modelling exercise. Any significant sensitivity should be taken into account during risk assessment.

**139**

**Figure 6.**

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2*

*DOI: http://dx.doi.org/10.5772/intechopen.84428*

**6. Potential CO2 leakage pathways**

*The characterisation and assessment of the storage complex.*

**Figure 5.**

it is in preventing leakage.

The injected CO2 could leak or migrate from CO2 storage formation upwards (into upper rocks, aquifer or to atmosphere) if the following conditions are present: (a) CO2 gas pressure exceeds capillary pressure and passes through siltstone, (b) free CO2 leaks from siltstone into upper aquifer up the fault, (c) CO2 escapes through a "gap" in the cap rock into a higher aquifer, (d) injected CO2 migrates up the dip, increases reservoir pressure and permeability of fault, (e) CO2 escapes via poorly plugged new or old abandoned wells, (f) natural flow dissolves CO2 at CO2/water interface and transports it out of closure and (g) dissolved CO2 escapes to the atmosphere or into the ocean. **Figure 6** shows the migration paths of

injected CO2 from storage formation towards surface through a fracture in the cap rock, along fault zones and via poorly cemented active or abandoned wells.

The integrity of the cap rock is assured by an adequate fracture gradient and by sufficient cement around the casing across the cap rock and without a microannulus. The permeability and integrity of the cement will determine how effective

*Potential leakage pathways of injected CO2 and CO2 injection well design (modified after references [27, 28]).*

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2 DOI: http://dx.doi.org/10.5772/intechopen.84428*


**Figure 5.**

*CO2 Sequestration*

200,000 m3

of oil and 599 × 106

and transportation of 600,000 m3

duration of the project, about 5 × 109

m3

and (4) changes to field abandonment practices.

characterisation and risk assessment (**Figure 5**).

be taken into account during risk assessment.

sional (3-D) static earth model.

In Croatia, the first application of CO2-EOR started in October 2014 by the INA—Oil Industry Ltd. oil company. The project's aim is to enhance hydrocarbon production by alternating injection of carbon dioxide and water into mature oil fields Žutica and Ivanić [25]. The *EOR* project involves dehydration, compression

from the Gas Processing Facilities Molve to the Fractionation Facilities Ivanić Grad. After its compression and liquefaction at the location of Fractionation Facilities Ivanić Grad, CO2 is transported by pipeline at high pressure (200 bar) to the injection wells of the Ivanić and Žutica fields, in quantities of 400,000 and

m3

attention was paid to the selection of surface and underground equipment.

of these fields. That will result in additional hydrocarbon production (3.4 × 106

50% of injected CO2 will be permanently trapped in the reservoirs, while another 50% of CO2 will be produced together with associated gas. Currently, the solution regarding the further use of CO2, which will be extracted from associated gas at the location of the Compressor Station Žutica, is being developed. To implement the EOR project, it was necessary to carry out workover operations and construction modifications of existing wells. Keeping in mind corrosive features of CO2, special

According to Heidug et al. [26], CO2-EOR practice can be modified to deliver significant capacity for long-term CO2 storage. EOR expansion to storage of CO2 can be achieved through at least four major activities: (1) additional site characterisation and risk assessment to evaluate the storage capability of a site, (2) additional monitoring of vented and fugitive emissions, (3) additional subsurface monitoring

**5. Geological storage complex and surrounding area characterisation**

Collecting data about the storage complex and the surrounding area is very important because it serves as a base for making their volumetric and three-dimen-

connected areas and fluids, is built. It characterises the storage complex.

In the first step, for describing the storage complex, it is necessary to collect information about its characteristics. In the second step, based on the collected data and using computerised reservoir simulators, a three-dimensional static geological earth model of the candidate storage complex, including the cap rock and the hydraulically

In the third step, the characterisations and assessment of storage complex are based on dynamic modelling, comprising a variety of time-step simulations of CO2 injection into the storage site using the three-dimensional static geological earth model(s) constructed during the second step. The simulations are based on altering parameters in the static geological earth model(s) and changing rate functions and assumptions in the dynamic modelling exercise. Any significant sensitivity should

Potential sites for geologic storage are depleted oil and gas fields, deep saline formations and deep unmineable coal seams. According to EU Directive 2009/31/EC [7], the characterisation and assessment of the potential storage complex, including the cap rock and surrounding area, including the hydraulically connected areas, should be carried out in three steps according to best practices at the time of the assessment: (1) data collection, (2) building the three-dimensional static geological earth model and (3) characterisation of the storage dynamic behaviour, sensitivity

/day, respectively. During the period of 25 years, which is the expected

of gas). Due to geological and physical conditions, about

/day of CO2 by 88 km long gas pipeline (20 in.)

of CO2 will be injected in the reservoirs

t

**138**

*The characterisation and assessment of the storage complex.*

### **6. Potential CO2 leakage pathways**

The injected CO2 could leak or migrate from CO2 storage formation upwards (into upper rocks, aquifer or to atmosphere) if the following conditions are present: (a) CO2 gas pressure exceeds capillary pressure and passes through siltstone, (b) free CO2 leaks from siltstone into upper aquifer up the fault, (c) CO2 escapes through a "gap" in the cap rock into a higher aquifer, (d) injected CO2 migrates up the dip, increases reservoir pressure and permeability of fault, (e) CO2 escapes via poorly plugged new or old abandoned wells, (f) natural flow dissolves CO2 at CO2/water interface and transports it out of closure and (g) dissolved CO2 escapes to the atmosphere or into the ocean. **Figure 6** shows the migration paths of injected CO2 from storage formation towards surface through a fracture in the cap rock, along fault zones and via poorly cemented active or abandoned wells.

The integrity of the cap rock is assured by an adequate fracture gradient and by sufficient cement around the casing across the cap rock and without a microannulus. The permeability and integrity of the cement will determine how effective it is in preventing leakage.

#### **Figure 6.**

*Potential leakage pathways of injected CO2 and CO2 injection well design (modified after references [27, 28]).*

Potential leakage pathways along an active injection well and/or an abandoned well include leakage: through deterioration (corrosion) of the tubing, around packer, through deterioration (corrosion) of the casing, between the outside of the casing and the set cement, through the deterioration of the set cement in the annulus (cement fractures), leakage in the annular region between the set cement and the formation, through the cement plug and between the set cement and the inside of the casing [4, 29, 30].

A key concept related to the performance of an injection well, and the prevention of CO2 migration from the injection zone through an active or abandoned well, is its mechanical integrity (internal and external). Internal mechanical integrity of the well is achieved by ensuring that each of the components of the well is constructed using corrosion-resistant materials such as 316 stainless steel, fibreglass or lined (with glass reinforced epoxy, plastic or cement) carbon steel for casing and tubing. External mechanical integrity of the well is achieved by successful primary cementing operation with the use of CO2-resistant cement, resulting in a cement sheath to bond and support casing and provide zonal isolation. The permeability and integrity of the set cement will determine its effectiveness in preventing CO2 leakage.

#### **6.1 CO2 trapping mechanisms**

The possibility of potential leaks of CO2 is one of the largest barriers to largescale CCS although well-selected storage sites are likely to retain over 99% of the injected CO2 over 1000 years. Four different storage mechanisms keep the supercritical CO2 securely stored inside the CO2 storage formation: structural/ stratigraphic (or physical) trapping, (2) solubility trapping, (3) residual trapping and (4) mineral trapping [1, 31]. The most important CO2 storage mechanism during an injection process of several decades is structural/stratigraphic trapping. The other three mechanisms enable the trapping of CO2 over a long period of time [1]. The effectiveness of geological storage depends on a combination of physical and geochemical trapping mechanisms. **Figure 7** presents four injection scenarios.

#### **Figure 7.**

*The influence of a combination of physical and geochemical trapping mechanisms on CO2 security storage (modified after reference [1]).*

**141**

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2*

keep CO2 in place, leading to increased security of storage [31].

Injection scenarios A, B and C show injection into hydrodynamic traps, essentially systems open to lateral flow of fluids and gas within the injection formation. Scenario D represents injection into a physically restricted flow regime, similar to those of many producing and depleted oil and gas reservoirs. The level of security is proportional to the distance from the origin. Dashed lines are examples of million-year pathways.

As time passes and more CO2 is injected, the more secure trapping mechanisms

According to Bradshaw et al. [32], capacity calculation can be threefold, depending on the required category level: *theoretical, realistic and viable capacity*. *Theoretical capacity* considers whole reservoir pore space available for storage, or saline aquifer, which is saturated with salt water having maximum dissolved CO2. In practice, different technical and economic restrictions prevent storage quantities to reach the level of theoretical capacity. *Realistic capacity* takes into consideration reservoir quality parameters (porosity, permeability, seal, depth, pressure, stress regimes, etc.) as important indications of technical viability. *Viable capacity* includes legal and regulatory limitations and considers social and environmental aspects of the selected location while connecting the CO2 source with the nearest storage site. Storage capacity can be generally expressed as the quantity of CO2 that may be

According to the study of the Task Force for Review and Identification of Standards for CO2 Storage Capacity Estimation of Carbon Sequestration Leadership Forum (CSLF), the regional CO2 storage capacity in structural and stratigraphic traps (Eq. (1)) can be calculated using a residual water saturation [33, 34]:

VCO2t = Vtrap ∙ Φ(1 − Swirr) = A ∙ h ∙ Φ (1 − Swirr) (1)

Similar approach is used by the United States Department of Energy (DOE). It takes into account the porous space of the entire layer of saturated water and does not distinguish between CO2 storage mechanisms. It takes into account the storage efficiency coefficient, which reflects the size of the space that can be filled with CO2. The coefficient encompasses a wide variety of variables, ranging from petrophysical reservoir properties (porosity and permeability) to the sweep efficiency and effective porosity. According to the US DOE, for the regional salt water aqui-

The storage capacity of depleted hydrocarbon fields [Eqs. (2) and (3)] can be calculated from cumulative production and reserve data following the methodology

*M* = *ρ*<sup>∙</sup> CO2r (*R* ∙ <sup>f</sup> ∙ N ∙ *B*fo − *W*<sup>i</sup> + *W*p) (2)

*M* = *ρ*<sup>∙</sup> CO2r <sup>∙</sup> *R*<sup>f</sup> (1 − *F*ig) ∙ *G* ∙ *B*<sup>g</sup> (3)

where M, reservoir capacity for CO2 storage (kg); ρCO2r, CO2 density at reservoir

); Rf, recovery factor (−); N, original oil in place (m3

average trap porosity (−); Swirr, irreducible water saturation (−); A, trap area (m2

fers, the coefficient of storage efficiency is suggested to be 2% [35, 36].

); Vtrap, trap volume (m3

); Wp, water production (m3

) and Bg, gas formation volume factor (−).

); Φ,

); Bo, oil forma-

); Fig, gas

);

*DOI: http://dx.doi.org/10.5772/intechopen.84428*

injected and stored in the geological layers.

h, average trap thickness (m).

described in [37].

conditions (kg/m3

injection (m3

tion volume factor (−); Wi, water injection (m3

); G, original gas in place (m3

where VCO2t, theoretical storage volume CO2 (m3

**7. Storage capacity**

Injection scenarios A, B and C show injection into hydrodynamic traps, essentially systems open to lateral flow of fluids and gas within the injection formation. Scenario D represents injection into a physically restricted flow regime, similar to those of many producing and depleted oil and gas reservoirs. The level of security is proportional to the distance from the origin. Dashed lines are examples of million-year pathways.

As time passes and more CO2 is injected, the more secure trapping mechanisms keep CO2 in place, leading to increased security of storage [31].

#### **7. Storage capacity**

*CO2 Sequestration*

**6.1 CO2 trapping mechanisms**

**140**

**Figure 7.**

*(modified after reference [1]).*

*The influence of a combination of physical and geochemical trapping mechanisms on CO2 security storage* 

Potential leakage pathways along an active injection well and/or an abandoned well include leakage: through deterioration (corrosion) of the tubing, around packer, through deterioration (corrosion) of the casing, between the outside of the casing and the set cement, through the deterioration of the set cement in the annulus (cement fractures), leakage in the annular region between the set cement and the formation, through the cement plug and between the set cement and the inside of the casing [4, 29, 30].

A key concept related to the performance of an injection well, and the prevention of CO2 migration from the injection zone through an active or abandoned well, is its mechanical integrity (internal and external). Internal mechanical integrity of the well is achieved by ensuring that each of the components of the well is constructed using corrosion-resistant materials such as 316 stainless steel, fibreglass or lined (with glass reinforced epoxy, plastic or cement) carbon steel for casing and tubing. External mechanical integrity of the well is achieved by successful primary cementing operation with the use of CO2-resistant cement, resulting in a cement sheath to bond and support casing and provide zonal isolation. The permeability and integrity

of the set cement will determine its effectiveness in preventing CO2 leakage.

The possibility of potential leaks of CO2 is one of the largest barriers to largescale CCS although well-selected storage sites are likely to retain over 99% of the injected CO2 over 1000 years. Four different storage mechanisms keep the supercritical CO2 securely stored inside the CO2 storage formation: structural/ stratigraphic (or physical) trapping, (2) solubility trapping, (3) residual trapping and (4) mineral trapping [1, 31]. The most important CO2 storage mechanism during an injection process of several decades is structural/stratigraphic trapping. The other three mechanisms enable the trapping of CO2 over a long period of time [1]. The effectiveness of geological storage depends on a combination of physical and geochemical trapping mechanisms. **Figure 7** presents four injection scenarios.

According to Bradshaw et al. [32], capacity calculation can be threefold, depending on the required category level: *theoretical, realistic and viable capacity*. *Theoretical capacity* considers whole reservoir pore space available for storage, or saline aquifer, which is saturated with salt water having maximum dissolved CO2. In practice, different technical and economic restrictions prevent storage quantities to reach the level of theoretical capacity. *Realistic capacity* takes into consideration reservoir quality parameters (porosity, permeability, seal, depth, pressure, stress regimes, etc.) as important indications of technical viability. *Viable capacity* includes legal and regulatory limitations and considers social and environmental aspects of the selected location while connecting the CO2 source with the nearest storage site.

Storage capacity can be generally expressed as the quantity of CO2 that may be injected and stored in the geological layers.

According to the study of the Task Force for Review and Identification of Standards for CO2 Storage Capacity Estimation of Carbon Sequestration Leadership Forum (CSLF), the regional CO2 storage capacity in structural and stratigraphic traps (Eq. (1)) can be calculated using a residual water saturation [33, 34]:

$$\mathbf{V\_{CO2t}} = \mathbf{V\_{trap}} \cdot \Phi(\mathbf{1} - \mathbf{S\_{wirr}}) = \mathbf{A} \cdot \mathbf{h} \cdot \Phi\left(\mathbf{1} - \mathbf{S\_{wirr}}\right) \tag{1}$$

where VCO2t, theoretical storage volume CO2 (m3 ); Vtrap, trap volume (m3 ); Φ, average trap porosity (−); Swirr, irreducible water saturation (−); A, trap area (m2 ); h, average trap thickness (m).

Similar approach is used by the United States Department of Energy (DOE). It takes into account the porous space of the entire layer of saturated water and does not distinguish between CO2 storage mechanisms. It takes into account the storage efficiency coefficient, which reflects the size of the space that can be filled with CO2. The coefficient encompasses a wide variety of variables, ranging from petrophysical reservoir properties (porosity and permeability) to the sweep efficiency and effective porosity. According to the US DOE, for the regional salt water aquifers, the coefficient of storage efficiency is suggested to be 2% [35, 36].

The storage capacity of depleted hydrocarbon fields [Eqs. (2) and (3)] can be calculated from cumulative production and reserve data following the methodology described in [37].

$$\mathbf{M} = \rho\_{\cdot \text{CO}\_2} \left\{ \mathbf{R} \cdot \mathbf{f} \cdot \mathbf{N} \cdot \mathbf{B}\_{\text{fo}} - \mathbf{W}\_{\text{i}} \star \mathbf{W}\_{\text{p}} \right\} \tag{2}$$

$$\mathbf{M} = \rho \cdot\_{\text{CO}\_{2t}} \mathbf{R} \mathbf{f} \left(\mathbf{1} - F\_{\text{ig}}\right) \cdot \mathbf{G} \cdot \mathbf{B}\_{\text{g}} \tag{3}$$

where M, reservoir capacity for CO2 storage (kg); ρCO2r, CO2 density at reservoir conditions (kg/m3 ); Rf, recovery factor (−); N, original oil in place (m3 ); Bo, oil formation volume factor (−); Wi, water injection (m3 ); Wp, water production (m3 ); Fig, gas injection (m3 ); G, original gas in place (m3 ) and Bg, gas formation volume factor (−).

Theoretical storage capacity obtained by these equations takes into account the estimated recoverable hydrocarbon reserves as the product of original hydrocarbon in place and recovery factor. For the effective capacity, it is necessary to consider some additional factors such as the macroscopic displacement efficiency, buoyancy, reservoir heterogeneity, water saturation, reservoir drive, etc.

Although the sweep efficiency has often been ignored in the case of depleted hydrocarbons fields, instead of the total amount, only 75% replacement of original oil or gas in place can be expected [38, 39].

The very first global assessment of CO2 storage capacity was made back to the 1990s. Koide et al. [40, 41] assessed CO2 storage capacity for deep saline aquifers on the level of 320 × 109 t. According to Van der Meer [42], it was estimated to 425 × 109 tons, calculation made by Ormerod et al. [43] was on the level of 790 × 109 t CO2. Hendricks and Blok [44] reported storage capacity of 150 × 109 t, which was mainly related to depleted hydrocarbon reservoirs [25].

Preliminary estimation of CO2 storage capacity for European deep aquifers and hydrocarbon reservoirs was done within the framework of the projects GESTCO, CASTOR and GeoCapacity, financed under the 5th and 6th Framework Program for Research and Technological Development [45]. In the case of deep aquifers, a simplified methodology based on a volumetric approach was applied, calculating with average values for layer thickness, temperature, pressure and porosity for each storage location. Storage assessment of hydrocarbon reservoirs used material balancing method, assuming that extraction of hydrocarbon releases certain pore volume available for CO2 injection. The EU GeoCapacity project estimated CO2 storage capacity to be on the level of 127 Gt, covering saline formations (97 Gt), hydrocarbon fields (20 Gt) and coal seams (1 Gt). The storage capacity was evaluated in 17 countries as sufficient at national level, while in one country (Norway), it was concluded that cross-border storage is possible. However, storage capacity was defined as "insufficient" in five countries [14].

#### **7.1 CO2 storage resources classification**

The Society of Petroleum Engineers (SPE) published the document entitled *CO2 Storage Resources Management System (SRMS)*, prepared by its subcommittee of the Carbon Dioxide Capture, Utilization and Storage Technical Section (CCUS), which establishes technically based capacity and resources evaluation standards [45]. This document is based on the SPE PRMS (*The Petroleum Resources Management System*), which is developed by SPE Oil and Gas Reserves Committee and used internationally within the petroleum industry for consistent and reliable definition, classification and estimation of hydrocarbon resources.

SPE CO2 SRMS provides a consistent approach to estimating storable quantities of CO2, evaluating development projects and presenting results within a comprehensive classification framework. The SRMS classification scheme is based on the accessible pore volume in a geologic formation in which CO2 could be stored. It is intended for use in geologic formation completely saturated with brine such as saline formations or saline aquifers and depleted hydrocarbon fields without hydrocarbon production.

CO2 storage resources are defined as the quantity (mass or volume) of CO2 that can be stored in a geological formation and include all quantities of naturally occurring pore volume potentially suitable for storage within underground formations *discovered* and *undiscovered* (accessible and inaccessible storage resources), as well as those quantities already used for storage (stored resources). The SPE storage resources classification system is shown in **Figure 8**.

**143**

**8. Risk assessment**

*CO2 resources classification framework [45].*

**Figure 8.**

storage (e.g., [3, 4, 28, 46–48]).

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2*

The risks associated with underground CO2 storage depend on many factors, including used infrastructure, type of reservoir dedicated to storage, geological characteristics of selected layers, cap rock and stratigraphic heterogeneity, geomechanical properties of rocks, existence of other wells, method of well abandonment experience, etc. EU CCS Directive is developed on the basis of a risk-based approach for safe storage and leakage. Therefore, it is necessary, before the application of CCS, to determine whether identified risks are acceptable. The significant

The risk assessment should comprise, among other things, hazard characterisation, exposure and effects assessment and risk characterisation. Characterisation of the hazard is carried out by characterising the potential leakage from the storage complex, as established by the dynamic modelling. It should cover the full range of

Many papers are published with the aim of assessing the risk of CO2 storage, and various methodologies are currently applied to risk assessment of geological CO2

**Figure 9** shows risk concept profiles for a large CCS project over time. The blue line represents a project with the pressure in storage formation increasing during CO2 injection and decreasing after injection stops. The red line represents potential risk profile over time. The potential risk of failure and CO2 leakage increases during the injection, and after the injection stops, it decreases. Secondary risk increases

Jewell and Senior [51] described scenarios and parameters for potential leakage from active (CO2 injection well, observation well or water extraction well) and

risk of CO2 leakage could not be permitted under the EU CCS Directive.

potential operating conditions to test the security of the storage complex.

depend on local geochemical risks of transport processes.

*DOI: http://dx.doi.org/10.5772/intechopen.84428*

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2 DOI: http://dx.doi.org/10.5772/intechopen.84428*

**Figure 8.** *CO2 resources classification framework [45].*

#### **8. Risk assessment**

*CO2 Sequestration*

Theoretical storage capacity obtained by these equations takes into account the estimated recoverable hydrocarbon reserves as the product of original hydrocarbon in place and recovery factor. For the effective capacity, it is necessary to consider some additional factors such as the macroscopic displacement efficiency, buoyancy,

Although the sweep efficiency has often been ignored in the case of depleted hydrocarbons fields, instead of the total amount, only 75% replacement of original

The very first global assessment of CO2 storage capacity was made back to the 1990s. Koide et al. [40, 41] assessed CO2 storage capacity for deep saline aquifers

tons, calculation made by Ormerod et al. [43] was on the level of

t CO2. Hendricks and Blok [44] reported storage capacity of 150 × 109

Preliminary estimation of CO2 storage capacity for European deep aquifers

The Society of Petroleum Engineers (SPE) published the document entitled *CO2 Storage Resources Management System (SRMS)*, prepared by its subcommittee of the Carbon Dioxide Capture, Utilization and Storage Technical Section (CCUS), which establishes technically based capacity and resources evaluation standards [45]. This document is based on the SPE PRMS (*The Petroleum Resources Management System*), which is developed by SPE Oil and Gas Reserves Committee and used internationally within the petroleum industry for consistent and reliable definition, classifica-

SPE CO2 SRMS provides a consistent approach to estimating storable quantities

CO2 storage resources are defined as the quantity (mass or volume) of CO2 that can be stored in a geological formation and include all quantities of naturally occurring pore volume potentially suitable for storage within underground formations *discovered* and *undiscovered* (accessible and inaccessible storage resources), as well as those quantities already used for storage (stored resources). The SPE storage

of CO2, evaluating development projects and presenting results within a comprehensive classification framework. The SRMS classification scheme is based on the accessible pore volume in a geologic formation in which CO2 could be stored. It is intended for use in geologic formation completely saturated with brine such as saline formations or saline aquifers and depleted hydrocarbon fields without

t. According to Van der Meer [42], it was estimated

t,

reservoir heterogeneity, water saturation, reservoir drive, etc.

which was mainly related to depleted hydrocarbon reservoirs [25].

and hydrocarbon reservoirs was done within the framework of the projects GESTCO, CASTOR and GeoCapacity, financed under the 5th and 6th Framework Program for Research and Technological Development [45]. In the case of deep aquifers, a simplified methodology based on a volumetric approach was applied, calculating with average values for layer thickness, temperature, pressure and porosity for each storage location. Storage assessment of hydrocarbon reservoirs used material balancing method, assuming that extraction of hydrocarbon releases certain pore volume available for CO2 injection. The EU GeoCapacity project estimated CO2 storage capacity to be on the level of 127 Gt, covering saline formations (97 Gt), hydrocarbon fields (20 Gt) and coal seams (1 Gt). The storage capacity was evaluated in 17 countries as sufficient at national level, while in one country (Norway), it was concluded that cross-border storage is possible. However, storage capacity was defined as "insufficient" in

oil or gas in place can be expected [38, 39].

on the level of 320 × 109

five countries [14].

hydrocarbon production.

**7.1 CO2 storage resources classification**

tion and estimation of hydrocarbon resources.

resources classification system is shown in **Figure 8**.

to 425 × 109

790 × 109

**142**

The risks associated with underground CO2 storage depend on many factors, including used infrastructure, type of reservoir dedicated to storage, geological characteristics of selected layers, cap rock and stratigraphic heterogeneity, geomechanical properties of rocks, existence of other wells, method of well abandonment experience, etc. EU CCS Directive is developed on the basis of a risk-based approach for safe storage and leakage. Therefore, it is necessary, before the application of CCS, to determine whether identified risks are acceptable. The significant risk of CO2 leakage could not be permitted under the EU CCS Directive.

The risk assessment should comprise, among other things, hazard characterisation, exposure and effects assessment and risk characterisation. Characterisation of the hazard is carried out by characterising the potential leakage from the storage complex, as established by the dynamic modelling. It should cover the full range of potential operating conditions to test the security of the storage complex.

Many papers are published with the aim of assessing the risk of CO2 storage, and various methodologies are currently applied to risk assessment of geological CO2 storage (e.g., [3, 4, 28, 46–48]).

**Figure 9** shows risk concept profiles for a large CCS project over time. The blue line represents a project with the pressure in storage formation increasing during CO2 injection and decreasing after injection stops. The red line represents potential risk profile over time. The potential risk of failure and CO2 leakage increases during the injection, and after the injection stops, it decreases. Secondary risk increases depend on local geochemical risks of transport processes.

Jewell and Senior [51] described scenarios and parameters for potential leakage from active (CO2 injection well, observation well or water extraction well) and

#### **Figure 9.**

*Risk concept profiles for a large CCS project over time (modified after references [3, 49]).*


#### **Table 1.**

*Scenarios and parameters for potential leakage from active and abandoned wells (modified after reference [50]).*

abandoned wells as well as via primary cap rock and fault to assist in the development of a common understanding of CO2 leakage and associated liabilities in the North Sea (**Tables 1** and **2**).

**145**

intersect and plug the leaking well.

**9. CO2 injection monitoring**

assessment analysis.

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2*

**Parameters Scenarios**

**Primary cap rock Fault**

**Low flux: vertical migration through existing faults**

1–100 years for low flux; excludes remediation

(100-year flux); no remediation

Very low (0–1.8) × 106

Negligible Not calibrated—highly site specific

Very low flux rates 1–50 50–250 1500.00

N/A 0–0.9 0.0009–0.23 0.275–1.37

**Moderate flux: vertical migration through existing faults**

1–5 years; includes remediation

(0.018–0.46) × 106 including remediation

risks in the North Sea if faults are present.

**High flux: migration through fault activated and enhanced by injection**

1–5 years; includes remediation

(0.55–2.7) × 106 including remediation

In case of leakages or significant irregularities, the operator is obliged to immediately notify the competent authority and take the necessary corrective measures, including measures related to the protection of human health. The purpose of corrective measures is to prevent or stop the escape of CO2 from the storage formation, to ensure safe geological storage and to manage the risks during the lifespan of the project and afterwards. According to the EU CCS Directive and EC Guidance Document 2, corrective measures include but are not limited to (1) limiting CO2 injection rates or stopping injection and pressure buildup, (2) reducing the reservoir pressure by extracting CO2 or water from the storage complex, close to an identified leakage area or applying peripheral extraction, (3) sealing areas of leakage such as identified fault or cap rock leakage pathways by injecting low permeability materials, creating a hydraulic barrier that stops CO2 migration in sensitive areas by increasing the pressure in the above formations, (4) well remediation for active wells (for example, repair of wellhead, damaged tubing or collapsed casing; packer replacement, squeeze cementing and so on) and (5) well control, including killing the well by injecting heavy fluids and after that cementing the well or drilling a new well to

*Scenarios and parameters for potential leakage via primary cap rock and fault (modified after reference [50]).*

Remark — Data represent the best efforts to represent leakage scenarios and

Monitoring of injection facilities, storage complex (including where possible the CO2 plume) and, where appropriate, the surrounding environment present a very important part of the overall risk management strategy for geological storage projects. It should be based on a monitoring plan established according to the risk

*DOI: http://dx.doi.org/10.5772/intechopen.84428*

**Migration through primary rock**

breakthrough

Probability of leakage

Potential CO2 leakage rates (t/day)

Potential amount of CO2 leakage (t)

% CO2 stored (200 million tonnes case)

**Table 2.**

Duration 100–1000 years to

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2 DOI: http://dx.doi.org/10.5772/intechopen.84428*


#### **Table 2.**

*CO2 Sequestration*

**144**

**Table 1.**

(**Tables 1** and **2**).

Probability of leakage

**Figure 9.**

Potential CO2 leakage rates (t/day)

Potential amount of CO2 leakage (t)

% CO2 stored (200 million tonnes case)

Duration 0.5–20 years

abandoned wells as well as via primary cap rock and fault to assist in the development of a common understanding of CO2 leakage and associated liabilities in the North Sea

*Scenarios and parameters for potential leakage from active and abandoned wells (modified after reference [50]).*

Remarks Data represent the best efforts to represent leakage scenarios and risks in the North Sea for

With 5 CO2 injection wells, 20-year injection period and 200 million tonnes of stored CO2.

**Parameters Scenarios**

*Risk concept profiles for a large CCS project over time (modified after references [3, 49]).*

**Low-level leakage: via CO2 injection well**

> (until well abandoned)

**Active CO2 injection well Abandoned well**

0.0001–0.001 0.00001–0.0001 0.0012–0.005 —

0.1–10.0 5000.00 0.60–6.00 1000.00

18–73,000.00 (0.45–0.9) × 106 220–220,000.00+ 90–180,000.00

0–0.036 0.225–0.45 0.0001–0.1+ 0.045–0.09

a storage scheme:

**Low-level leakage: via abandoned well**

3–6 months 1–100+ years 3–6 months

With 6 abandoned wells, probability of leakage over 100 years and 200 million tonnes of stored CO2.

**Worse case: complete breakdown of abandonment plugs in old well**

**Worse case: blow out on CO2 injection well after failure of initial well control activities**

*Scenarios and parameters for potential leakage via primary cap rock and fault (modified after reference [50]).*

In case of leakages or significant irregularities, the operator is obliged to immediately notify the competent authority and take the necessary corrective measures, including measures related to the protection of human health. The purpose of corrective measures is to prevent or stop the escape of CO2 from the storage formation, to ensure safe geological storage and to manage the risks during the lifespan of the project and afterwards. According to the EU CCS Directive and EC Guidance Document 2, corrective measures include but are not limited to (1) limiting CO2 injection rates or stopping injection and pressure buildup, (2) reducing the reservoir pressure by extracting CO2 or water from the storage complex, close to an identified leakage area or applying peripheral extraction, (3) sealing areas of leakage such as identified fault or cap rock leakage pathways by injecting low permeability materials, creating a hydraulic barrier that stops CO2 migration in sensitive areas by increasing the pressure in the above formations, (4) well remediation for active wells (for example, repair of wellhead, damaged tubing or collapsed casing; packer replacement, squeeze cementing and so on) and (5) well control, including killing the well by injecting heavy fluids and after that cementing the well or drilling a new well to intersect and plug the leaking well.

#### **9. CO2 injection monitoring**

Monitoring of injection facilities, storage complex (including where possible the CO2 plume) and, where appropriate, the surrounding environment present a very important part of the overall risk management strategy for geological storage projects. It should be based on a monitoring plan established according to the risk assessment analysis.


#### **Table 3.**

*Monitoring program for geologic storage of CO2 (modified after [51]).*

Benson et al. [52] provided examples of basic and enhanced programs that could be deployed for geologic storage of CO2. They include preoperational, operational and closure monitoring program and could be used over the lifetime of a geologic storage project. Their application in practice will enable the implementation of the CO2 injection project and increase security and reduce the risk of migration of injected gas, thus protecting the environment (**Table 3**).

The choice of monitoring technology should be based on best practice available at the time of the design.

The parameters to be monitored are identified so as to fulfil the purposes of monitoring. However, the monitoring plan should in any case include continuous or intermittent monitoring of (1) fugitive emissions of CO2 at the injection facility; (2) CO2 volumetric flow at injection wellheads; (3) CO2 pressure and temperature at injection wellheads (to determine mass flow); (4) chemical analysis of the injected material and (5) reservoir temperature and pressure (to determine the CO2 phase behaviour and state).

The monitoring plan should be updated if new CO2 sources, pathways and flux rates or observed significant deviations from previous assessments are identified.

Post-closure monitoring is based on the information collected and modelled during the implementation of the monitoring plan.

#### **10. Conclusions**

Increment of greenhouse gases in the atmosphere is a direct consequence of industrial development. It manifests itself in rise of the average earth temperature being responsible for a series of unfavourable climate changes. CCS can help in mitigating climate changes through a distinctive huge sequestration capacity, which

**147**

**Author details**

Zagreb, Croatia

provided the original work is properly cited.

Nediljka Gaurina-Međimurec\* and Karolina Novak Mavar

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2*

ensures global utilisation. Technology applicability and safety have been testing by

Switching CCS technology from demonstration to commercial deployment depends on CO2 market price. Although current value is not encouraging, more stringent emission reduction strategy (80–95% by 2050) will lead to commercial applications. However, besides emission reduction initiatives, there are many projects connected to EOR activities. Viability of such projects is strongly dependent on

Since geological storage permanence is enabled by natural and engineered barriers functionality, there is a certain risk of migration of CO2 from the storage formation. The potential leakage risk increases during injection phase, and with time, it decreases due to activation of different trapping mechanisms. Therefore, structural/ stratigraphic trapping represents the most important CO2 storage mechanism in the first storage period. The other mechanisms take over with storage life progressively. Mineral tapping of CO2 is the safest mechanism, as CO2 reacts with the reservoir

Well-selected, designed and managed geological storage sites pose the risks comparable to those associated with current hydrocarbon recovery activities. Such risks, determined by leakage rates of less than 1% over thousands of years, are well below levels that could endanger public safety or environment. Nevertheless, for all CCS projects, a comprehensive monitoring, including baseline, operational and

several large- and small-scale demonstration projects currently under way.

*DOI: http://dx.doi.org/10.5772/intechopen.84428*

rock minerals and remains permanently trapped.

post-closure state, is mandatory.

the oil price.

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

Faculty of Mining, Geology and Petroleum Engineering, University of Zagreb,

\*Address all correspondence to: nediljka.gaurina-medjimurec@rgn.hr

#### *Carbon Capture and Storage (CCS): Geological Sequestration of CO2 DOI: http://dx.doi.org/10.5772/intechopen.84428*

*CO2 Sequestration*

Enhanced monitoring

**Table 3.**

Benson et al. [52] provided examples of basic and enhanced programs that could be deployed for geologic storage of CO2. They include preoperational, operational and closure monitoring program and could be used over the lifetime of a geologic storage project. Their application in practice will enable the implementation of the CO2 injection project and increase security and reduce the risk of migration of

**Preoperational Operational Closure**

rates

monitoring

Seismic survey Seismic survey Seismic survey

**Additions to the basic monitoring program**

monitoring

Atmospheric-CO2 monitoring Wellhead atmospheric-CO2

— Microseismicity —

— Well logs — — — Wellhead

CO2-flux monitoring Continuous CO2-flux

Pressure and water quality above the storage formation

Injection- and production

—

—

pressure

CO2-flux monitoring

Well logs — — Wellhead pressure Wellhead pressure — Formation pressure — —

Basic monitoring **Monitoring program**

Injection- and production rate

testing

The choice of monitoring technology should be based on best practice available

The monitoring plan should be updated if new CO2 sources, pathways and flux rates or observed significant deviations from previous assessments are identified. Post-closure monitoring is based on the information collected and modelled

Increment of greenhouse gases in the atmosphere is a direct consequence of industrial development. It manifests itself in rise of the average earth temperature being responsible for a series of unfavourable climate changes. CCS can help in mitigating climate changes through a distinctive huge sequestration capacity, which

The parameters to be monitored are identified so as to fulfil the purposes of monitoring. However, the monitoring plan should in any case include continuous or intermittent monitoring of (1) fugitive emissions of CO2 at the injection facility; (2) CO2 volumetric flow at injection wellheads; (3) CO2 pressure and temperature at injection wellheads (to determine mass flow); (4) chemical analysis of the injected material and (5) reservoir temperature and pressure (to determine the CO2 phase

injected gas, thus protecting the environment (**Table 3**).

Gravity survey Electromagnetic survey

*Monitoring program for geologic storage of CO2 (modified after [51]).*

during the implementation of the monitoring plan.

at the time of the design.

behaviour and state).

**10. Conclusions**

**146**

ensures global utilisation. Technology applicability and safety have been testing by several large- and small-scale demonstration projects currently under way.

Switching CCS technology from demonstration to commercial deployment depends on CO2 market price. Although current value is not encouraging, more stringent emission reduction strategy (80–95% by 2050) will lead to commercial applications. However, besides emission reduction initiatives, there are many projects connected to EOR activities. Viability of such projects is strongly dependent on the oil price.

Since geological storage permanence is enabled by natural and engineered barriers functionality, there is a certain risk of migration of CO2 from the storage formation. The potential leakage risk increases during injection phase, and with time, it decreases due to activation of different trapping mechanisms. Therefore, structural/ stratigraphic trapping represents the most important CO2 storage mechanism in the first storage period. The other mechanisms take over with storage life progressively. Mineral tapping of CO2 is the safest mechanism, as CO2 reacts with the reservoir rock minerals and remains permanently trapped.

Well-selected, designed and managed geological storage sites pose the risks comparable to those associated with current hydrocarbon recovery activities. Such risks, determined by leakage rates of less than 1% over thousands of years, are well below levels that could endanger public safety or environment. Nevertheless, for all CCS projects, a comprehensive monitoring, including baseline, operational and post-closure state, is mandatory.

#### **Author details**

Nediljka Gaurina-Međimurec\* and Karolina Novak Mavar Faculty of Mining, Geology and Petroleum Engineering, University of Zagreb, Zagreb, Croatia

\*Address all correspondence to: nediljka.gaurina-medjimurec@rgn.hr

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **References**

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[46] Society of Petroleum Engineers (SPE). CO2 Storage Resources Management System. 2016. p. 43

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[48] White CM, Straziser BR, Granite EJ, Hoffman JS, Pennline HW. Separation and capture of CO2 from large stationary sources and sequestration in geological formations—Coalbeds and deep saline aquifers. Journal of the Air & Waste Management Association. 2003;**53**:645-715

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[51] Jewell S, Senior B. CO2 Storage Liabilities in the North Sea, an Assessment of Risks and Financial Consequences, Summary Report. UK: Department of Energy & Climate Change (DECC); 2012. p. 29

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pp. 1259-1265

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Mitigation Strategies for CCS. Presentation at WRI Workshop

Indonesia; 2009. p. 13

*Carbon Capture and Storage (CCS): Geological Sequestration of CO2 DOI: http://dx.doi.org/10.5772/intechopen.84428*

Risk-Based Approach for Well Integrity Management over Long Term in a CO2 Geological Storage Project. Paper SPE 122510 Presented at the 2009 SPE Asia Pacific Oil and Gas Conference and Exhibition; 4-6 August 2009; Jakarta, Indonesia; 2009. p. 13

*CO2 Sequestration*

2005. p. 16

2007. p. 42

Storage Capacity Measurement, CSLF-T-2005-9 15. Berlin, Germany;

[34] Carbon Sequestration Leadership Forum (CSLF). Phase II Final Report from the Task Force for Review and Identification of Standards for CO2 Storage Capacity Estimation, CSLF-T-2007-04; Melbourne, Australia; storage of carbon dioxide in depleted natural gas reservoirs and in useless aquifers. Engineering Geology.

[42] Van der Meer L. Investigations regarding the storage of carbon dioxide in aquifers in the Netherlands. Energy Conversion and Management.

[43] Ormerod WG, Webster IC, Ausdus H, Reimer PWF. An overview of large scale CO2 disposal options. Energy Conversion and Management.

[44] Hendriks CA, Blok K. Underground storage of carbon dioxide. Energy Conversion and Management.

[45] Schuppers JD, Holloway S, May F, Gerling P, Bøe R, Magnus C, et al. Storage Capacity and Quality of Hydrocarbon Structures in the North Sea and the Aegean Region. TNO-Report NITG 02-020-B; Utrecht: Netherland's Institute of Applied Geoscience; 2003. p. 54

[46] Society of Petroleum Engineers (SPE). CO2 Storage Resources Management System. 2016. p. 43

[47] Benson SM, Hepple R, Apps J, Tsang CF, Lippmann M. Lessons Learned from Natural and Industrial Analogues for Storage of Carbon Dioxide in Deep Geological Formations: Report No. LBNL-51170. Berkeley, California, USA: Lawrence Berkeley National Laboratory; 2002. p. 135

[48] White CM, Straziser BR, Granite EJ, Hoffman JS, Pennline HW. Separation

[49] Le Guen Y, Meyer V, Poupard O, Houdu E, Chammas R, Oxand SAA.

and capture of CO2 from large stationary sources and sequestration in geological formations—Coalbeds and deep saline aquifers. Journal of the Air & Waste Management Association.

2003;**53**:645-715

1993;**34**(3/4):175-179

1992;**33**(5/8):611-618

1993;**34**(9/1):833-840

1993;**34**:949-957

[35] U.S. Department of Energy (DOE). Carbon Sequestration Atlas of United States and Canada. Washington: Office

[36] U.S. Department of Energy (DOE). Methodology for Development of Geologic Storage Estimates for Carbon Dioxide. Washington: Office of Fossil

[37] Bachu S, Bonijoly D, Bradshaw J, Burrus R, Holloway S, Christensen NP, et al. CO2 storage capacity estimation methodology and gaps. Internationa Journal of Greenhouse Gas Control.

[38] Holloway S, Vincent C, Kirk K. Industrial Carbon Dioxide Emissions and Carbon Dioxide Storage Potential in the UK, DTI Cleaner Fossil Fuels Programme Report. DTI/Pub URN

[39] International Energy Agency (IEA). CO2 Storage in Depleted Gas Fields. Technical Study, Report No. 2009/01; UK: IEA Greenhouse Gas R&D

[40] Koide H, Tazaki Y, Noguchi Y, Nakayama S, Iijima M, Ito K, et al. Subterranean containment and longterm storage of carbon dioxide in unused aquifers and in depleted natural gas reservoirs. Energy Conversion and Management. 1992;**33**(5/8):619-626

[41] Koide H, Tazaki Y, Noguchi Y, Iijima M, Ito K, Shindo Y. Underground

of Fossil Energy; 2007. p. 86

Energy; 2008. p. 36

2007;**1**(4):430-443

06/2027; UK; 2006. p. 47

Programme. 2009. p. 121

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[51] Jewell S, Senior B. CO2 Storage Liabilities in the North Sea, an Assessment of Risks and Financial Consequences, Summary Report. UK: Department of Energy & Climate Change (DECC); 2012. p. 29

[52] Benson SM, Hoversten M, Gasperikova E, Haines M. Monitoring protocols and life-cycle costs for geological storage of carbon dioxide. In: Proceedings of the 7th International Conference on Greenhouse Gas Control Technologies; 5 September 2004. Vancouver, Canada: Elsevier; 2005. pp. 1259-1265

### *Edited by Leidivan Almeida Frazão, Adriana Marcela Silva-Olaya and Junio Cota Silva*

This book discusses different strategies that can be adopted by agriculture and industry to enhance CO2 sequestration and reduce the impacts of global warming and climate change. Written by researchers from different fields, chapters cover such topics as the management of agricultural systems with the implementation of agronomic practices that can reduce greenhouse gas emissions and increase soil carbon stocks, the technology of adsorption on activated carbon from low-cost raw material, and the effective methods of carbon capture and storage, among others. This volume is a useful reference for the general public, undergraduate and graduate students, and researchers who aim to deepen their knowledge of those topics.

Published in London, UK © 2020 IntechOpen © srrdvd / iStock

CO2 Sequestration

CO2 Sequestration

*Edited by Leidivan Almeida Frazão,* 

*Adriana Marcela Silva-Olaya and Junio Cota Silva*