1. Introduction

Energy demand has gradually become a critical factor for the international industrial sector. For this reason, technologies based on renewable-energy sources, such as biomass residues, have been developed and promoted. Biomass has the potential to become one of the main sources of energy worldwide; it is estimated that by 2050, its contribution to the global energy model could be between 100 and 400 EJ/year [1].

In this chapter, the kinetic characterization of different lignocellulosic waste gasification processes by thermogravimetric techniques using the Coats-Redfern method is presented [8]. The experimental data were fitted with several models, and each one was evaluated with different statistical parameters. Using the model with the best fit, the activation energy and preexponential factor were calculated, and their variation with the heating rate was evaluated [9]. On the other hand and in order to extend and improve the basic knowledge on composition and properties and to apply this knowledge for the most advanced and environmentally safe utilization, an exergy analysis of a gasification process is presented, taking into account

Coats and Redfern [8] method has been widely applied to study the thermal decomposition

where k(T) is the rate constant, dα/dt is the process rate, T is the absolute temperature, t is the time, f(α) represents function commonly used for description of biomass thermal decomposition, and α is the degree of transformation; α can be calculated from the corresponding TG

where m is the mass of the sample at a given time t and m0 and mf refer to values at the initial and final mass of samples. For non-isothermal conditions, when the temperature varies with

where A is the pre-exponential factor, E is the activation energy, and R is the universal gas

After a combination of Eqs. (1) and (4) and integrating, the following expression is obtained:

<sup>d</sup>α=fð Þ¼ <sup>α</sup> <sup>A</sup>=<sup>β</sup> � � <sup>ð</sup><sup>T</sup>

Eq. (5) can be integrated when the right hand side is expanded into an asymptotic series and

0

dα=dt ¼ k Tð Þ fð Þ α (1)

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification

http://dx.doi.org/10.5772/intechopen.73288

59

α ¼ ð Þ m0 � m =ð Þ m0 � mf (2)

β ¼ dT=dt (3)

k ¼ A expð Þ �E=RT (4)

eð Þ �E=RT dT (5)

different byproducts' production.

curve by the following equation:

time with a constant heating rate defined by

gð Þ¼ α

ðα 0

According to Arrhenius expression:

higher order terms are ignored:

constant.

kinetics of biomass. The reaction kinetic equation is

2. Kinetic analysis

The biomass waste utilization, as a substitute for fossil biofuels, has the advantage to produce environmentally beneficial fuel, due to the energy production, and its sustainable use allows the emitted CO2 to be absorbed during the biomass growth. In short time periods, this cycle was fulfilled, which allows confirming that the energetic biomass uses under these conditions in neutral with respect to the CO2 emissions [2]. One of the main disadvantages for the biomass waste utilization is its low production per unit area, causing high costs related with the collection and the transport from the origin to the consumption place [3]. Due to this reason, the systems using biomass must have a high efficiency.

Recently, to develop the energy obtaining from waste biomass, several works have been carried out; particularly about pyrolysis and gasification because these thermal processes are effective and attractive methods [4, 5]. Considering the gasification, it converts biomass wastes into low heating value gas generally called syngas. This product is more suitably used to produce electricity through internal combustion engines or gas turbines [6].

Different operating variables have a high influence on the gasification behavior: biomass feedstocks, temperature (T), equivalence ratio (ER, supply air/stoichiometric air), and supply steam/biomass ratio (SBR) [7]. In order to evaluate the gasification performance, the exergy analysis can be employed (based on the second law of thermodynamic).

On the other hand, considering the kinetic behavior, the biomass waste gasification occurs in three stages: drying (evaporation of moisture contained in the solid), pyrolysis (thermal decomposition in the oxygen absence), and the last step associated with the reaction of the char by CO2 to produce CO. When the solid fuel is heated to temperatures between 473 and 648 K in the absence of an oxidant agent, it is pyrolyzed. The process products are a solid (char), condensable hydrocarbons (tar), and gases. Then, at higher temperatures, the condensable fraction and the gases form part of the volatile phase of the pyrolysis. The additional permanence of the solid and volatile phases in the reaction zone allows their conversion to a fraction of gases (gasification) [8].

The tar presence in the gas mixture is the main problem in the technological development of the gasification systems of biomass. The generated char during the pyrolysis stage can react with water vapor, CO2, and oxygen. These reactions occur slower than that corresponding to the volatile phase; however, these contribute significantly to increase the amount and calorific value of the syngas.

Considering the gasification process description above, the involved reaction number, and their unknown mechanisms, simple kinetic models cannot describe the global reactions.

In this chapter, the kinetic characterization of different lignocellulosic waste gasification processes by thermogravimetric techniques using the Coats-Redfern method is presented [8]. The experimental data were fitted with several models, and each one was evaluated with different statistical parameters. Using the model with the best fit, the activation energy and preexponential factor were calculated, and their variation with the heating rate was evaluated [9]. On the other hand and in order to extend and improve the basic knowledge on composition and properties and to apply this knowledge for the most advanced and environmentally safe utilization, an exergy analysis of a gasification process is presented, taking into account different byproducts' production.

## 2. Kinetic analysis

1. Introduction

58 Gasification for Low-grade Feedstock

model could be between 100 and 400 EJ/year [1].

fraction of gases (gasification) [8].

value of the syngas.

reason, the systems using biomass must have a high efficiency.

produce electricity through internal combustion engines or gas turbines [6].

analysis can be employed (based on the second law of thermodynamic).

Energy demand has gradually become a critical factor for the international industrial sector. For this reason, technologies based on renewable-energy sources, such as biomass residues, have been developed and promoted. Biomass has the potential to become one of the main sources of energy worldwide; it is estimated that by 2050, its contribution to the global energy

The biomass waste utilization, as a substitute for fossil biofuels, has the advantage to produce environmentally beneficial fuel, due to the energy production, and its sustainable use allows the emitted CO2 to be absorbed during the biomass growth. In short time periods, this cycle was fulfilled, which allows confirming that the energetic biomass uses under these conditions in neutral with respect to the CO2 emissions [2]. One of the main disadvantages for the biomass waste utilization is its low production per unit area, causing high costs related with the collection and the transport from the origin to the consumption place [3]. Due to this

Recently, to develop the energy obtaining from waste biomass, several works have been carried out; particularly about pyrolysis and gasification because these thermal processes are effective and attractive methods [4, 5]. Considering the gasification, it converts biomass wastes into low heating value gas generally called syngas. This product is more suitably used to

Different operating variables have a high influence on the gasification behavior: biomass feedstocks, temperature (T), equivalence ratio (ER, supply air/stoichiometric air), and supply steam/biomass ratio (SBR) [7]. In order to evaluate the gasification performance, the exergy

On the other hand, considering the kinetic behavior, the biomass waste gasification occurs in three stages: drying (evaporation of moisture contained in the solid), pyrolysis (thermal decomposition in the oxygen absence), and the last step associated with the reaction of the char by CO2 to produce CO. When the solid fuel is heated to temperatures between 473 and 648 K in the absence of an oxidant agent, it is pyrolyzed. The process products are a solid (char), condensable hydrocarbons (tar), and gases. Then, at higher temperatures, the condensable fraction and the gases form part of the volatile phase of the pyrolysis. The additional permanence of the solid and volatile phases in the reaction zone allows their conversion to a

The tar presence in the gas mixture is the main problem in the technological development of the gasification systems of biomass. The generated char during the pyrolysis stage can react with water vapor, CO2, and oxygen. These reactions occur slower than that corresponding to the volatile phase; however, these contribute significantly to increase the amount and calorific

Considering the gasification process description above, the involved reaction number, and their unknown mechanisms, simple kinetic models cannot describe the global reactions.

Coats and Redfern [8] method has been widely applied to study the thermal decomposition kinetics of biomass. The reaction kinetic equation is

$$\mathbf{d}\alpha/\mathbf{dt} = \mathbf{k}(\mathbf{T})\,\mathbf{f}(\alpha) \tag{1}$$

where k(T) is the rate constant, dα/dt is the process rate, T is the absolute temperature, t is the time, f(α) represents function commonly used for description of biomass thermal decomposition, and α is the degree of transformation; α can be calculated from the corresponding TG curve by the following equation:

$$\mathbf{a} = (\mathbf{m}\_0 - \mathbf{m})/(\mathbf{m}\_0 - \mathbf{m}\_\ell) \tag{2}$$

$$
\beta = \text{dT/dt} \tag{3}
$$

where m is the mass of the sample at a given time t and m0 and mf refer to values at the initial and final mass of samples. For non-isothermal conditions, when the temperature varies with time with a constant heating rate defined by

$$\mathbf{k} = \mathbf{A} \exp(-\mathbf{E}/\mathbf{R}\mathbf{T})\tag{4}$$

According to Arrhenius expression:

where A is the pre-exponential factor, E is the activation energy, and R is the universal gas constant.

After a combination of Eqs. (1) and (4) and integrating, the following expression is obtained:

$$\mathbf{g}(\boldsymbol{\alpha}) = \int\_0^{\alpha} \mathbf{d}\alpha / \mathbf{f}(\boldsymbol{\alpha}) = \left(\mathbf{A} / \boldsymbol{\beta}\right) \int\_0^{\mathbf{T}} \mathbf{e}^{\left(-\mathbf{E} / \mathbf{R} \mathbf{T}\right)} \, \mathbf{d}\mathbf{T} \tag{5}$$

Eq. (5) can be integrated when the right hand side is expanded into an asymptotic series and higher order terms are ignored:

$$\text{g(a)}/\text{T}^2 = \left(\text{AR}/\text{E}\beta\right)\left[\left(\text{AE}/\text{E}\beta\right) - \left(1 - 2\text{RT}/\text{E}\right)\right] - \left(\text{E}/\text{RT}\right) \tag{6}$$

products are CO, H2, CO2, CH4, H2O, and N2. The quantities of other produced hydrocar-

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification

http://dx.doi.org/10.5772/intechopen.73288

• The ash contents in the studied biomass are considered inert during all the process reactions. • All gaseous products behave as ideal gases. This assumption error is not significant for the

• The S, Cl, and N contents in the biomass are negligible because they are very low com-

The biomass is represented by the general formula CHaOb obtained from elemental analysis. The gasification process of the regional wastes can be characterized by the following global reaction:

CHaOb þ wH2O þ m Oð <sup>2</sup> þ 3:76N2Þ ! x1CO þ x2H2 þ x3CO2

where w is the water mol/biomass mol; m is the air mol/biomass mol; x1, x2, x3, x4, and x5 are unknown moles of exit gas composition; and x6 and xtar are char and tar exit moles, respectively. Zainal et al. [12] presented a representative tar composition; this composition was used in this work. w and m are determined as function of the steam/biomass ratio (SBR, kg/kg) and ER

w ¼ ð Þ� SBR þ ww

m ¼ ER � 1 þ

where ww is the mass faction of moisture content in the biomass and Mbm is reactant biomass

Mbm <sup>¼</sup> <sup>12</sup> <sup>þ</sup> <sup>a</sup> <sup>þ</sup> 16b 1 � ww

þx4H2O þ x5CH4 þ x6C þ m3:76N2 þ xtarCH1:003O0:<sup>33</sup>

Mbm

a 4 � b 2

<sup>18</sup> (7)

(8)

x<sup>1</sup> þ x<sup>3</sup> þ x<sup>5</sup> þ x<sup>6</sup> þ xtar ¼ 1 (10)

CO2 þ H2 (b)

a þ 2w ¼ 2x2 þ 2x4 þ 4x5 þ 1:003xtar (11)

b þ w þ 2m ¼ x1 þ 2x3 þ x4 þ 0:33xtar (12)

(a)

61

(9)

bons are considered negligible. The tar production is considered in this model.

gasifiers operating at low pressure and high temperature.

(oxygen/biomass ratio, kmol/kmol). So, w and m expressions are

Taking into account global reaction (a), the balances for C, H, and O are

CO <sup>þ</sup> H2O\$

Kwgs

pared with the C, H, and O contents.

quantity expressed as kmol of dry biomass/h:

Zainal et al. [12] considered the following reactions:

Water-gas-shift reaction:

Methane reaction:

The term 2RT/E can be neglected since it is much less than unity for the thermal decomposition of lignocellulosic materials. Plotting the left hand side of Eq. (6), which includes g(α)/T2 versus T, for the proposed models (Table 1), gives the E and A parameters. The least squares nonlinear regression was used by means of the Marquardt [10] and Levenvrg [11] algorithm using MATLAB software.

Table 1 lists several reaction models (g(α)) used in this work to describe biomass thermal decomposition.


Table 1. Expressions for the most common reaction mechanisms in solid-state reactions.

#### 3. Thermodynamic model

The proposed model in this work is derived from the thermodynamic equilibrium applying the following assumptions:


products are CO, H2, CO2, CH4, H2O, and N2. The quantities of other produced hydrocarbons are considered negligible. The tar production is considered in this model.


The biomass is represented by the general formula CHaOb obtained from elemental analysis. The gasification process of the regional wastes can be characterized by the following global reaction:

$$\begin{aligned} \text{CH}\_4\text{O}\_6 + \text{wH}\_2\text{O} + \text{m}(\text{O}\_2 + 3.76\text{N}\_2) &\rightarrow \text{x}\_1\text{CO} + \text{x}\_2\text{H}\_2 + \text{x}\_3\text{CO}\_2\\ &+ \text{x}\_4\text{H}\_2\text{O} + \text{x}\_5\text{CH}\_4 + \text{x}\_6\text{C} + \text{m}3.76\text{N}\_2 + \text{x}\_{\text{tar}}\text{CH}\_{1.003}\text{O}\_{0.33} \end{aligned} \tag{a)}$$

where w is the water mol/biomass mol; m is the air mol/biomass mol; x1, x2, x3, x4, and x5 are unknown moles of exit gas composition; and x6 and xtar are char and tar exit moles, respectively.

Zainal et al. [12] presented a representative tar composition; this composition was used in this work. w and m are determined as function of the steam/biomass ratio (SBR, kg/kg) and ER (oxygen/biomass ratio, kmol/kmol). So, w and m expressions are

$$\mathbf{w} = (\text{SBR} + \mathbf{w}\_{\text{w}}) \cdot \frac{\mathbf{M}\_{\text{bm}}}{18} \tag{7}$$

$$\mathbf{m} = \mathbf{ER} \cdot \left( \mathbf{1} + \frac{\mathbf{a}}{4} - \frac{\mathbf{b}}{2} \right) \tag{8}$$

where ww is the mass faction of moisture content in the biomass and Mbm is reactant biomass quantity expressed as kmol of dry biomass/h:

$$\mathbf{M}\_{\rm bm} = \frac{12 + \mathbf{a} + 16\mathbf{b}}{1 - \mathbf{w}\_{\rm w}} \tag{9}$$

Taking into account global reaction (a), the balances for C, H, and O are

$$\mathbf{x}\_1 + \mathbf{x}\_3 + \mathbf{x}\_5 + \mathbf{x}\_6 + \mathbf{x}\_{\text{tar}} = 1 \tag{10}$$

$$\mathbf{a} + \mathbf{2w} = \mathbf{2x}\_2 + \mathbf{2x}\_4 + \mathbf{4x}\_5 + 1.003\mathbf{x}\_{\text{tar}}\tag{11}$$

$$\mathbf{b} + \mathbf{w} + 2\mathbf{m} = \mathbf{x}\_1 + 2\mathbf{x}\_3 + \mathbf{x}\_4 + 0.33\mathbf{x}\_{\text{tar}} \tag{12}$$

Zainal et al. [12] considered the following reactions:

Water-gas-shift reaction:

$$\text{CO} + \text{H}\_2\text{O} \overset{\text{K}\_{\text{avg}^\*}}{\longleftrightarrow} \text{CO}\_2 + \text{H}\_2\tag{b}$$

Methane reaction:

<sup>g</sup>ð Þ <sup>α</sup> <sup>=</sup>T<sup>2</sup> <sup>¼</sup> AR=E<sup>β</sup> AE=E<sup>β</sup> � ð Þ <sup>1</sup> � 2RT=<sup>E</sup> � ð Þ <sup>E</sup>=RT (6)

n = 3/2, 1, ½, 1/3, 1/4

The term 2RT/E can be neglected since it is much less than unity for the thermal decomposition of lignocellulosic materials. Plotting the left hand side of Eq. (6), which includes g(α)/T2 versus T, for the proposed models (Table 1), gives the E and A parameters. The least squares nonlinear regression was used by means of the Marquardt [10] and Levenvrg [11] algorithm

Table 1 lists several reaction models (g(α)) used in this work to describe biomass thermal

Reaction model g(α)

Zero order α

One-dimensional diffusion α2

Power law αn

Exponential law α

Table 1. Expressions for the most common reaction mechanisms in solid-state reactions.

First order �ln (1 � α )

Nth order (n � 1) � 1 (1 � α)1 � n

Two-dimensional diffusion (1 � α) ln (1 � α) + α Three-dimensional diffusion (Jander) [1 � (1 � α)1/3]2 Three-dimensional diffusion (Ginstling-Brounstein) (1 � 2α/3)�(1 � α)2/3

The proposed model in this work is derived from the thermodynamic equilibrium applying

Avrami-Erofeev [�ln (1 � α)](1/n), n = 1, 2, 3, 4

Contracting area (1 � α)(1/n), n = 2 Contracting volume (1 � α)(1/n), n = 3

• The gasifier is considered as a system in stationary state, with homogeneous temperature

• The C content in the biomass is converted in gases due to the gasification and combustion processes, and it can remain in the fly and bottom ash like char. The considered gaseous

using MATLAB software.

60 Gasification for Low-grade Feedstock

3. Thermodynamic model

the following assumptions:

and pressure.

decomposition.

Reaction order

Diffusional

Nucleation

Contracting geometry

$$\text{C} + 2\text{H}\_2 \overset{\text{K}\_{\text{reaction}}}{\longleftrightarrow} \text{CH}\_4\tag{c}$$

where fwgs and fmethan are the nonequilibrium factors of the water-gas displacement and methanation reactions, respectively. Lim and Lee [14] obtained the values of these factors analyzing the T, ER, and SBR influences on them, considering several biomasses. Thereby,

fwgs is smaller than 0.5, and this reaction is close by to equilibrium. Since the CO production during the gasification decreases when ER increases, fwgs augments with this parameter in order to promote the water-gas displacement reaction. However, ER significantly affects

C is partially converted into gas under substoichiometric conditions, and it is related with O concentration in the atmosphere and the gasification temperature. C conversion fraction (fc) is defined as the ratio between the mol total number in the gas composition and the C concen-

The empirical parameters of these correlations were determined considering the experimental results obtained during the biomass gasification using air/steam mixture as gasifier agent [14].

Abuadala [15] defined the tar yield as a percentage by weight of the total gasification products:

The total weight of gasification products is obtained applying a global mass balance. The tar

where Mbm and ww are the fed biomass mass flow and moisture fraction of fed biomass (dry

xtar <sup>¼</sup> mtar PMtar

where PMtar is the tar molecular weight. In this case, the considered tar chemical formula is

fwgs <sup>¼</sup> <sup>0</sup>:<sup>0836</sup> � e2:882�ER (21)

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification

http://dx.doi.org/10.5772/intechopen.73288

63

x6 ¼ 1 � fc (23)

fc <sup>¼</sup> <sup>0</sup>:<sup>901</sup> <sup>þ</sup> <sup>0</sup>:<sup>439</sup> � <sup>1</sup> � <sup>e</sup>ð Þ �ERþ0:0003�<sup>T</sup> (24)

Tarwt,% <sup>¼</sup> <sup>35</sup>:98eð Þ �0:00298�<sup>T</sup> (25)

(27)

<sup>100</sup> ð Þ Mbm <sup>þ</sup> SBR � Mbm <sup>þ</sup> ww � Mbm <sup>þ</sup> 29 mð Þ <sup>þ</sup> <sup>3</sup>:76m (26)

fmethan ¼ 38:75 � 30:70 � ER (22)

two empirical equations of fwgs and fmethan are obtained:

fmethan varying between 20 and 33 approximately [14].

tration present in the biomass. The non-converted C will be [14]

3.2. C conversion fraction

3.3. Tar formation

mass is obtained by

mtar <sup>¼</sup> Tarwt,%

basis), respectively. The tar moles can be calculated by

In these reactions, the oxygen is not involved directly, and the steam is implicated in a limited form (water-gas-shift reaction). So, the gasifying agent's effect on the equilibrium reactions is not important. The equilibrium constants as partial pressure function are

$$\mathbf{K}\_{\text{wgs}} = \frac{\mathbf{P}\_{\text{CO}\_2}\mathbf{P}\_{\text{H}\_2}}{\mathbf{P}\_{\text{CO}} \cdot \mathbf{P}\_{\text{H}\_2\text{O}}} = \frac{\mathbf{x}\_2 \cdot \mathbf{x}\_3}{\mathbf{x}\_1 \cdot \mathbf{x}\_4} \tag{13}$$

$$\mathbf{K}\_{\text{methian}} = \frac{\mathbf{P}\_{\text{CH}\_4}}{\mathbf{P}\_{\text{H}\_2}^2} \mathbf{p}\_0 = \frac{\mathbf{x}\_5}{\mathbf{x}\_2^2} \frac{\mathbf{p}\_0}{\mathbf{P}} \mathbf{x}\_{\text{total}} \tag{14}$$

where p and p0 are the total and reference pressures, respectively. They are equal to 101.3 kPa. xtotal is the mol quantity of produced gas, excluding the inert gas.

The variation of Gibbs free energy at a determined temperature was used in order to know the Kwgs and Kmethan values, according to the following equations:

$$\ln \mathbf{K}(\mathbf{T}) = \frac{-\Delta \mathbf{G}\_{\mathbf{T}}^{0}}{\mathbf{RT}} \tag{15}$$

$$
\Delta \mathbf{G}\_{\rm T}^{0} = \sum\_{\rm i} \mathbf{v}\_{\rm i} \cdot \Delta \mathbf{G}\_{\rm f,i,T}^{0} \tag{16}
$$

where ΔG<sup>0</sup> <sup>f</sup> ,i,T is the free energy of each constituent formation at a temperature equal T, <sup>Δ</sup>G<sup>0</sup> <sup>T</sup> is the standard free energy at a temperature equal T, and ν<sup>i</sup> is the stoichiometric number of the reaction products.

The necessary thermodynamic data were obtained of Reid, Prausnitz, and Polling [13]. The equilibrium constants as temperature function can be expressed by

$$\mathbf{K}\_{\text{wgs}} = \text{EXP}\left(\frac{5872.45}{\text{T}} + 1.86 \text{lnT} - 2.69 \cdot 10^{-4} \text{T} - \frac{58200}{\text{T}^2} - 18\right) \tag{17}$$

$$\mathrm{K}\_{\mathrm{methan}} = \mathrm{EXP} \left( \frac{7082.842}{\mathrm{T}} - 6.567 \mathrm{lnT} + \frac{7.467 \cdot 10^{-3}}{2} \mathrm{T} - \frac{2.167 \cdot 10^{-6}}{6} \mathrm{T}^2 + \frac{0.701 \cdot 10^{-5}}{2\mathrm{T}^2} + 32.541 \right) \tag{18}$$

#### 3.1. Nonequilibrium factors

The assumed thermodynamic equilibrium for these reactions is not valid for real process due to the reactions that are not complete and the mass transfer resistance, too [14]. The equilibrium constant is modified to consider the nonequilibrium behavior:

$$\mathbf{K}\_{\text{wgs}}^{\*} = \mathbf{K}\_{\text{wgs}} \cdot \mathbf{f}\_{\text{wgs}} \tag{19}$$

$$\mathbf{K}\_{\text{methian}}^{\*} = \mathbf{K}\_{\text{methian}} \cdot \mathbf{f}\_{\text{methian}} \tag{20}$$

where fwgs and fmethan are the nonequilibrium factors of the water-gas displacement and methanation reactions, respectively. Lim and Lee [14] obtained the values of these factors analyzing the T, ER, and SBR influences on them, considering several biomasses. Thereby, two empirical equations of fwgs and fmethan are obtained:

$$\mathbf{f\_{wgs}} = 0.0836 \cdot \mathbf{e^{2.882 \cdot ER}} \tag{21}$$

$$\text{f}\_{\text{methhan}} = \text{38.75} - \text{30.70} \cdot \text{ER} \tag{22}$$

fwgs is smaller than 0.5, and this reaction is close by to equilibrium. Since the CO production during the gasification decreases when ER increases, fwgs augments with this parameter in order to promote the water-gas displacement reaction. However, ER significantly affects fmethan varying between 20 and 33 approximately [14].

#### 3.2. C conversion fraction

<sup>C</sup> <sup>þ</sup> 2H2 \$

not important. The equilibrium constants as partial pressure function are

xtotal is the mol quantity of produced gas, excluding the inert gas.

Kwgs and Kmethan values, according to the following equations:

equilibrium constants as temperature function can be expressed by

Kwgs <sup>¼</sup> EXP <sup>5872</sup>:<sup>45</sup>

<sup>T</sup> � <sup>6</sup>:567lnT <sup>þ</sup>

constant is modified to consider the nonequilibrium behavior:

where ΔG<sup>0</sup>

reaction products.

62 Gasification for Low-grade Feedstock

Kmethan <sup>¼</sup> EXP <sup>7082</sup>:<sup>842</sup>

3.1. Nonequilibrium factors

Kwgs <sup>¼</sup> pCO2�

Kmethan <sup>¼</sup> pCH4

ΔG<sup>0</sup>

p2 H2

where p and p0 are the total and reference pressures, respectively. They are equal to 101.3 kPa.

The variation of Gibbs free energy at a determined temperature was used in order to know the

lnK Tð Þ¼ �ΔG<sup>0</sup>

the standard free energy at a temperature equal T, and ν<sup>i</sup> is the stoichiometric number of the

The necessary thermodynamic data were obtained of Reid, Prausnitz, and Polling [13]. The

<sup>T</sup> <sup>þ</sup> <sup>1</sup>:86lnT � <sup>2</sup>:<sup>69</sup> � <sup>10</sup>�<sup>4</sup>

The assumed thermodynamic equilibrium for these reactions is not valid for real process due to the reactions that are not complete and the mass transfer resistance, too [14]. The equilibrium

K∗

K∗

<sup>7</sup>:<sup>467</sup> � <sup>10</sup>�<sup>3</sup>

� �

<sup>2</sup> <sup>T</sup> � <sup>2</sup>:<sup>167</sup> � <sup>10</sup>�<sup>6</sup>

� �

<sup>T</sup> <sup>¼</sup> <sup>X</sup> i

T

<sup>ν</sup><sup>i</sup> � <sup>Δ</sup>G<sup>0</sup>

<sup>f</sup> ,i,T is the free energy of each constituent formation at a temperature equal T, <sup>Δ</sup>G<sup>0</sup>

Kmethan

In these reactions, the oxygen is not involved directly, and the steam is implicated in a limited form (water-gas-shift reaction). So, the gasifying agent's effect on the equilibrium reactions is

> pH2 pCO � pH2O

> > p0 <sup>¼</sup> x5 x2 2 p0 p

<sup>¼</sup> x2 � x3 x1 � x4

CH4 (c)

xtotal (14)

RT (15)

<sup>T</sup> � <sup>58200</sup>

<sup>6</sup> T2 <sup>þ</sup>

wgs ¼ Kwgs � fwgs (19)

methan ¼ Kmethan � fmethan (20)

<sup>T</sup><sup>2</sup> � <sup>18</sup>

<sup>0</sup>:<sup>701</sup> � <sup>10</sup>�<sup>5</sup>

2T<sup>2</sup> <sup>þ</sup> <sup>32</sup>:<sup>541</sup>

<sup>f</sup>,i,<sup>T</sup> (16)

(13)

<sup>T</sup> is

(17)

(18)

C is partially converted into gas under substoichiometric conditions, and it is related with O concentration in the atmosphere and the gasification temperature. C conversion fraction (fc) is defined as the ratio between the mol total number in the gas composition and the C concentration present in the biomass. The non-converted C will be [14]

$$\mathbf{x}\_6 = \mathbf{1} - \mathbf{f}\_6 \tag{23}$$

$$\mathbf{f\_c} = 0.901 + 0.439 \cdot \left(1 - \mathbf{e^{\left(-\text{ER} + 0.0003 \cdot \text{T}\right)}}\right) \tag{24}$$

The empirical parameters of these correlations were determined considering the experimental results obtained during the biomass gasification using air/steam mixture as gasifier agent [14].

#### 3.3. Tar formation

Abuadala [15] defined the tar yield as a percentage by weight of the total gasification products:

$$\mathbf{T} \mathbf{a}\_{\mathbf{w}, \%} = \mathbf{35}.98 \mathbf{e}^{(-0.00298 \cdot \text{T})} \tag{25}$$

The total weight of gasification products is obtained applying a global mass balance. The tar mass is obtained by

$$\mathbf{m}\_{\text{tar}} = \frac{\mathbf{T} \mathbf{a}\_{\text{wt},\%}}{100} (\mathbf{M}\_{\text{bm}} + \mathbf{SBR} \cdot \mathbf{M}\_{\text{bm}} + \mathbf{w}\_{\text{w}} \cdot \mathbf{M}\_{\text{bm}} + 29(\mathbf{m} + 3.76 \mathbf{m})) \tag{26}$$

where Mbm and ww are the fed biomass mass flow and moisture fraction of fed biomass (dry basis), respectively. The tar moles can be calculated by

$$\chi\_{\text{tar}} = \frac{\mathbf{m}\_{\text{tar}}}{\mathbf{PM}\_{\text{tar}}} \tag{27}$$

where PMtar is the tar molecular weight. In this case, the considered tar chemical formula is

CH1.003O0.33 proposed by Allesina et al. [16]. Considering Eqs. (5)–(7), (13)–(15), (17), and (21), the syngas composition can be obtained as operative variable function, T, ER, and SBR.

#### 3.4. Process performance condition

The performance condition used in this work is the exergetic efficiency (ηex). It is defined as the ratio between the profitable exergy outputs flow from the gasifier and the necessary exergy input flow to the gasifier [18]:

$$\eta\_{\rm ex} = \frac{\varepsilon \mathbf{x}\_{\rm gas} + \varepsilon \mathbf{x}\_{\rm loss} + \varepsilon \mathbf{x}\_{\rm tar} + \varepsilon \mathbf{x}\_{\rm char}}{\varepsilon \mathbf{x}\_{\rm biomass} + \varepsilon \mathbf{x}\_{\rm steam}} \tag{28}$$

enthalpy values are necessary. The specific heat capacity of tar (kJ/kgtar�K) from biomass

tar þ ðT T

The tar enthalpy and the entropy are calculated with the following expression [21]:

Htar <sup>¼</sup> <sup>H</sup>�

tar ¼ �30:<sup>980</sup> <sup>þ</sup> xCO2 � <sup>H</sup>�

Star ¼ S � tar þ ðT T � Cp

tar <sup>¼</sup> <sup>37</sup>:<sup>1636</sup> þ �ð Þ <sup>31</sup>:<sup>4767</sup> exp �0:<sup>564682</sup> <sup>H</sup>

Cp <sup>¼</sup> <sup>17</sup>:<sup>166</sup> <sup>þ</sup> <sup>4</sup>:<sup>271</sup> <sup>T</sup>

C þ N � �

<sup>þ</sup>20:<sup>1145</sup> <sup>O</sup>

char is pure carbon. Its specific heat capacity (kJ/kmol�K) is

β factor is calculated by the following Eq. (24):

H�

Cp ¼ 0:00422 � T (34)

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification

CO2 <sup>þ</sup> xH2O � <sup>H</sup>�

<sup>C</sup> <sup>þ</sup> <sup>N</sup>

<sup>þ</sup> <sup>44</sup>:<sup>6712</sup> <sup>S</sup>

C þ N

<sup>T</sup><sup>2</sup> (39)

� � (38)

� � � �

C þ N � �

<sup>1000</sup> � <sup>8</sup>:<sup>79</sup> � <sup>105</sup>

εch,biomass ¼ mbiomass � β � LHVbiomass (40)

<sup>i</sup> are the molar fraction and the standard formation enthalpy of i species,

tar is the tar standard entropy (kJ/kmol�K), and it is calculated using the following

<sup>þ</sup> <sup>54</sup>:<sup>3111</sup> <sup>N</sup>

where C, H, N, O, and S are the weight fraction of carbon, hydrogen, nitrogen, oxygen, and sulfur present in the biomass, respectively. Usually, the gasifier losses at the environment are negligible comparing with the incoming and leaving energy of the gasifier. Several researchers consider that these losses are between 1 and 2% [22]. On the other hand, it is assumed that the

The char chemical exergy is equal to 410 kJ/kmol, according to Moran and Shapiro [19]. Cengel [23] listed the values of standard enthalpy, entropy, and chemical exergy for the gaseous components. The biomass wastes are fed at environment temperature; its physical exergy is negligible. Ptasinski [24] calculated the biomass chemical exergy according to the expression

� Cp � dT (35)

http://dx.doi.org/10.5772/intechopen.73288

65

<sup>T</sup> � dT (37)

H2O (36)

gasification process is [20]

where xi and H�

where S �

present:

expression:

respectively. The tar entropy is

S �

where εxloss, is the loss exergy flow and, εxgas, εxtar, εxchar, εxbiomass, and εxsteam are the loss exergy flow and exergy flows of gas, tar, char, biomass, and steam, respectively. There is a loss due to the entropy production, heat and mass transfers, and chemical reaction irreversibility [18]. Considering the gasification process, it must satisfy the first and second thermodynamic laws. The second law leads to the following expression:

$$
\sum\_{\mathbf{R}} \varepsilon \mathbf{x} - \sum\_{\mathbf{P}} \varepsilon \mathbf{x} = \mathbf{I} \tag{29}
$$

where εx is the exergy and I is the irreversibility, and it represents the lost internal exergy as the material quality loss and energy due to dissipation. It is calculated basing to the generated entropy during the gasification process:

$$\mathbf{I} = \mathbf{T}^{\top} \cdot \mathbf{S} \mathbf{S} \mathbf{n} \tag{30}$$

The exergy depends on the biomass composition (chemical exergy), temperature, and pression (physical exergy). The chemical exergy (εxchÞ can be calculated by

$$\varepsilon \mathbf{x}\_{\rm ch} = \sum\_{\rm i} \mathbf{x}\_{\rm i} \cdot \varepsilon \mathbf{x}\_{\rm ch, i}^{\circ} + \text{RT}^{\circ} \sum\_{\rm i} \mathbf{x}\_{\rm i} \cdot \ln \mathbf{x}\_{\rm i} \tag{31}$$

where xi and εx� ch,<sup>i</sup> are the molar fraction and standard exergy of i species [19]. The produced gaseous and tar physical exergies (εxph) can be calculated by

$$
\varepsilon \text{x}\_{\text{ph}} = \left(\text{H} - \text{H}^{\circ}\right) - \text{T}^{\circ}\left(\text{S} - \text{S}^{\circ}\right) \tag{32}
$$

where H and S are the enthalpy and entropy of a species when the gasifier operates at determined T and pression and H� and S� are the enthalpy and entropy when the reactor works under standard conditions (T� = 298 K and p� = 1 atm). The total exergy is

$$
\varepsilon \mathbf{x} = \varepsilon \mathbf{x}\_{\text{ch}} + \varepsilon \mathbf{x}\_{\text{ph}} \tag{33}
$$

In order to carry out the analysis of the first and second thermodynamic laws, the entropy and

enthalpy values are necessary. The specific heat capacity of tar (kJ/kgtar�K) from biomass gasification process is [20]

$$\mathbf{Cp} = 0.00422 \cdot \mathbf{T} \tag{34}$$

The tar enthalpy and the entropy are calculated with the following expression [21]:

CH1.003O0.33 proposed by Allesina et al. [16]. Considering Eqs. (5)–(7), (13)–(15), (17), and (21), the syngas composition can be obtained as operative variable function, T, ER, and SBR.

The performance condition used in this work is the exergetic efficiency (ηex). It is defined as the ratio between the profitable exergy outputs flow from the gasifier and the necessary exergy

> <sup>η</sup>ex <sup>¼</sup> <sup>ε</sup>xgas <sup>þ</sup> <sup>ε</sup>xloss <sup>þ</sup> <sup>ε</sup>xtar <sup>þ</sup> <sup>ε</sup>xchar εxbiomass þ εxsteam

where εxloss, is the loss exergy flow and, εxgas, εxtar, εxchar, εxbiomass, and εxsteam are the loss exergy flow and exergy flows of gas, tar, char, biomass, and steam, respectively. There is a loss due to the entropy production, heat and mass transfers, and chemical reaction irreversibility [18]. Considering the gasification process, it must satisfy the first and second thermodynamic

> <sup>ε</sup><sup>x</sup> �<sup>X</sup> P

where εx is the exergy and I is the irreversibility, and it represents the lost internal exergy as the material quality loss and energy due to dissipation. It is calculated basing to the generated

The exergy depends on the biomass composition (chemical exergy), temperature, and pression

ch,<sup>i</sup> <sup>þ</sup> RT� <sup>X</sup>

� T � <sup>S</sup> � <sup>S</sup> � ��

where H and S are the enthalpy and entropy of a species when the gasifier operates at determined T and pression and H� and S� are the enthalpy and entropy when the reactor

In order to carry out the analysis of the first and second thermodynamic laws, the entropy and

i

ch,<sup>i</sup> are the molar fraction and standard exergy of i species [19]. The produced

I ¼ T �

xi � εx�

<sup>ε</sup>xph <sup>¼</sup> <sup>H</sup> � <sup>H</sup> � ��

works under standard conditions (T� = 298 K and p� = 1 atm). The total exergy is

X R

(28)

(32)

εx ¼ I (29)

� Sgen (30)

εx ¼ εxch þ εxph (33)

xi � lnxi (31)

3.4. Process performance condition

laws. The second law leads to the following expression:

(physical exergy). The chemical exergy (εxchÞ can be calculated by

<sup>ε</sup>xch <sup>¼</sup> <sup>X</sup> i

gaseous and tar physical exergies (εxph) can be calculated by

entropy during the gasification process:

where xi and εx�

input flow to the gasifier [18]:

64 Gasification for Low-grade Feedstock

$$\mathbf{H}\_{\text{tar}} = \mathbf{H}\_{\text{tar}}^{\circ} + \int\_{\mathbf{T}^{\circ}}^{\text{T}} \mathbf{C} \mathbf{p} \cdot \mathbf{d} \mathbf{T} \tag{35}$$

$$\text{H}\_{\text{tar}}^{\circ} = -30.980 + \text{x}\_{\text{CO}\_2} \cdot \text{H}\_{\text{CO}\_2}^{\circ} + \text{x}\_{\text{H}\text{O}} \cdot \text{H}\_{\text{H}\text{O}}^{\circ} \tag{36}$$

where xi and H� <sup>i</sup> are the molar fraction and the standard formation enthalpy of i species, respectively. The tar entropy is

$$\mathbf{S}\_{\rm tar} = \mathbf{S}\_{\rm tar}^{\circ} + \int\_{\rm T}^{\rm T} \frac{\mathbf{C} \mathbf{p}}{\mathbf{T}} \cdot \mathbf{d} \mathbf{T} \tag{37}$$

where S � tar is the tar standard entropy (kJ/kmol�K), and it is calculated using the following expression:

$$\begin{split} \mathbf{S}\_{\text{tar}}^{\circ} &= & 37.1636 + (-31.4767) \exp\left[ -0.564682 \left( \frac{\text{H}}{\text{C}} + \text{N} \right) \right] \\ &+ 20.1145 \left( \frac{\text{O}}{\text{C} + \text{N}} \right) + 54.3111 \left( \frac{\text{N}}{\text{C} + \text{N}} \right) + 44.6712 \left( \frac{\text{S}}{\text{C} + \text{N}} \right) \end{split} \tag{38}$$

where C, H, N, O, and S are the weight fraction of carbon, hydrogen, nitrogen, oxygen, and sulfur present in the biomass, respectively. Usually, the gasifier losses at the environment are negligible comparing with the incoming and leaving energy of the gasifier. Several researchers consider that these losses are between 1 and 2% [22]. On the other hand, it is assumed that the char is pure carbon. Its specific heat capacity (kJ/kmol�K) is

$$\text{Cp} = 17.166 + 4.271 \frac{\text{T}}{1000} - \frac{8.79 \cdot 10^5}{\text{T}^2} \tag{39}$$

The char chemical exergy is equal to 410 kJ/kmol, according to Moran and Shapiro [19]. Cengel [23] listed the values of standard enthalpy, entropy, and chemical exergy for the gaseous components. The biomass wastes are fed at environment temperature; its physical exergy is negligible. Ptasinski [24] calculated the biomass chemical exergy according to the expression present:

$$
\varepsilon\_{\text{ch,biomass}} = \mathbf{m}\_{\text{biomass}} \cdot \beta \cdot \text{LHV}\_{\text{biomass}} \tag{40}
$$

β factor is calculated by the following Eq. (24):

$$\beta = \frac{1.0414 + 0.0177 \left(\frac{\text{H}}{\text{C}}\right) - 0.3328 \left(\frac{\text{O}}{\text{C}}\right) \left(1 + 0.0537 \left(\frac{\text{H}}{\text{C}}\right)\right)}{1 - 0.4021 \left(\frac{\text{O}}{\text{C}}\right)}\tag{41}$$

Similarly, the tar chemical exergy is calculated using the liquid combustible correlation [25]:

$$
\varepsilon\_{\rm ch,tar} = \text{LHV}\_{\rm tar} \left[ 1.0401 + 0.1728 \left( \frac{\text{H}}{\text{C}} \right) + 0.0432 \left( \frac{\text{O}}{\text{C}} \right) \right] \tag{42}
$$

To evaluate the biomass high heating value (HHV,MJ/kg), the correlations presented by Sheng and Azevedo [26] were used, Eq. (1). The biomass low heating value (MJ/kg) is calculated with the following expression:

$$\text{LHV}\_{\text{biomass}} = \text{HHV}\_{\text{biomass}} (1 - \text{w}\_{\text{w}}) - 2.447 \cdot \text{w}\_{\text{w}} \tag{43}$$

2 MJ/kg is the latent heat of water vaporization at 298 K. In order to calculate the tar HHV, the following correlation is applied [27]

$$\text{HHV}\_{\text{tar}} = 340.95 \,\text{C} + 1322.98 \,\text{H} - 119.86 \,\text{O} \tag{44}$$

each biomass was obtained. Figures 4–6 show the comparison of experimental data and the predicted values at different heating rates for the pyrolysis stage. The coefficient of correlation

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification

http://dx.doi.org/10.5772/intechopen.73288

67

The Ginstling-Brounstein model showed the better fit, and the obtained results are shown in

) for all cases is higher than 0.90, indicating a good fit.

Figure 2. Weight loss and derivative curves for plum pits at different heating rates.

Figure 1. Weight loss and derivative curves for sawdust at different heating rates.

(R2

Table 2.

According to Richard and Thunman [28], the tar mass fraction of C, H, and O fractions of the tar are 0.545, 0.065, and 0.39, respectively.

#### 4. Kinetic model application to biomass gasification

#### 4.1. Experimental weight loss

The experiments were carried out in a tubular reactor of 5 cm of internal diameter and 100 cm of height. It is heated by electrical resistance and is coupled to an analytical balance. This equipment is connected to a control system, through which it is possible to vary the heating rate and to register time, mass data, and temperature in a computer.

Experiments were carried out under air/steam atmosphere; the steam flow rate was 0.17 ml/ min, guarantying the steam/biomass ratio equal to 2.5 [7, 17]. The temperature increased from ambient temperature (approximately 300 K) to 1173 K. This final temperature ensures the highest decomposition. Three heating rates, 5, 10, and 15 K/min, were used. In order to minimize heat transfer and mass phenomena, 5 g of sample with size between 0.212 and 0.250 mm was used. Figures 1–3 show these experiments.

#### 4.2. Kinetic parameter determination

To determinate of kinetic parameters for the two stages, such as E and A, the weight loss curves have been used. Eq. (6) was applied to the experimental data, and a plot of g(α)/T2 versus T for Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification http://dx.doi.org/10.5772/intechopen.73288 67

Figure 1. Weight loss and derivative curves for sawdust at different heating rates.

<sup>β</sup> <sup>¼</sup> <sup>1</sup>:<sup>0414</sup> <sup>þ</sup> <sup>0</sup>:<sup>0177</sup> <sup>H</sup>

4. Kinetic model application to biomass gasification

rate and to register time, mass data, and temperature in a computer.

0.250 mm was used. Figures 1–3 show these experiments.

4.2. Kinetic parameter determination

the following expression:

66 Gasification for Low-grade Feedstock

following correlation is applied [27]

4.1. Experimental weight loss

tar are 0.545, 0.065, and 0.39, respectively.

C

<sup>ε</sup>ch,tar <sup>¼</sup> LHVtar <sup>1</sup>:<sup>0401</sup> <sup>þ</sup> <sup>0</sup>:<sup>1728</sup> <sup>H</sup>

� <sup>0</sup>:<sup>3328</sup> <sup>O</sup>

<sup>1</sup> � <sup>0</sup>:<sup>4021</sup> <sup>O</sup>

Similarly, the tar chemical exergy is calculated using the liquid combustible correlation [25]:

To evaluate the biomass high heating value (HHV,MJ/kg), the correlations presented by Sheng and Azevedo [26] were used, Eq. (1). The biomass low heating value (MJ/kg) is calculated with

2 MJ/kg is the latent heat of water vaporization at 298 K. In order to calculate the tar HHV, the

According to Richard and Thunman [28], the tar mass fraction of C, H, and O fractions of the

The experiments were carried out in a tubular reactor of 5 cm of internal diameter and 100 cm of height. It is heated by electrical resistance and is coupled to an analytical balance. This equipment is connected to a control system, through which it is possible to vary the heating

Experiments were carried out under air/steam atmosphere; the steam flow rate was 0.17 ml/ min, guarantying the steam/biomass ratio equal to 2.5 [7, 17]. The temperature increased from ambient temperature (approximately 300 K) to 1173 K. This final temperature ensures the highest decomposition. Three heating rates, 5, 10, and 15 K/min, were used. In order to minimize heat transfer and mass phenomena, 5 g of sample with size between 0.212 and

To determinate of kinetic parameters for the two stages, such as E and A, the weight loss curves have been used. Eq. (6) was applied to the experimental data, and a plot of g(α)/T2 versus T for

C

C 

LHVbiomass ¼ HHVbiomassð Þ� 1 � ww 2:447 � ww (43)

HHVtar ¼ 340:95 C þ 1322:98 H � 119:86 O (44)

C

<sup>1</sup> <sup>þ</sup> <sup>0</sup>:<sup>0537</sup> <sup>H</sup>

<sup>þ</sup> <sup>0</sup>:<sup>0432</sup> <sup>O</sup>

C

C

(41)

(42)

Figure 2. Weight loss and derivative curves for plum pits at different heating rates.

each biomass was obtained. Figures 4–6 show the comparison of experimental data and the predicted values at different heating rates for the pyrolysis stage. The coefficient of correlation (R2 ) for all cases is higher than 0.90, indicating a good fit.

The Ginstling-Brounstein model showed the better fit, and the obtained results are shown in Table 2.

Figure 3. Weight loss and derivative curves for olive pits at different heating rates.

Figure 4. Comparison of experimental and predicted values of g(a) for sawdust at different heating rates for pyrolysis stage.

The obtained activation energy values vary between 70 and 100 kJ/mol and 24–98 kJ/mol for the pyrolysis and char gasification stages, respectively, for all studied agro-industrial wastes. The highest value of the energy activation was predicted for plum pits at heating rate of 15 K/ min for pyrolysis stage. Also, the highest value for the same parameter was predicted for sawdust at 5 K/min for char combustion stage. The calculated values of E vary slightly with the heating rate for each biomass and indicate the existence of a complex multistep mechanism that occurs in the solid state. The increasing of heating rate leads to a simultaneous increase of the heat effect. So, the maximum decomposition rate tends to increase at higher heating rates because it provides a greater thermal energy facilitating the heat transfer around and

Figure 6. Comparison of experimental and predicted values of g(a) for olive pits at different heating rates for pyrolysis

Figure 5. Comparison of experimental and predicted values of g(a) for plum pits at different heating rates for pyrolysis

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification

http://dx.doi.org/10.5772/intechopen.73288

69

stage.

stage.

Figures 7–9 show the comparison of experimental data and the predicted values at different heating rates for the char combustion stage. The Ginstling-Brounstein model showed the better fit too, and the obtained results are shown in Table 3.

This model describes the biomass waste gasification characteristics, and it assumes that the process rate is limited by the diffusion of the reaction products from the surface, the reaction surface decreases during the process, and it can be assumed that the solid phase has the form of ball-shaped grains [29].

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification http://dx.doi.org/10.5772/intechopen.73288 69

Figure 5. Comparison of experimental and predicted values of g(a) for plum pits at different heating rates for pyrolysis stage.

Figure 6. Comparison of experimental and predicted values of g(a) for olive pits at different heating rates for pyrolysis stage.

The obtained activation energy values vary between 70 and 100 kJ/mol and 24–98 kJ/mol for the pyrolysis and char gasification stages, respectively, for all studied agro-industrial wastes. The highest value of the energy activation was predicted for plum pits at heating rate of 15 K/ min for pyrolysis stage. Also, the highest value for the same parameter was predicted for sawdust at 5 K/min for char combustion stage. The calculated values of E vary slightly with the heating rate for each biomass and indicate the existence of a complex multistep mechanism that occurs in the solid state. The increasing of heating rate leads to a simultaneous increase of the heat effect. So, the maximum decomposition rate tends to increase at higher heating rates because it provides a greater thermal energy facilitating the heat transfer around and

Figures 7–9 show the comparison of experimental data and the predicted values at different heating rates for the char combustion stage. The Ginstling-Brounstein model showed the better

Figure 4. Comparison of experimental and predicted values of g(a) for sawdust at different heating rates for pyrolysis

This model describes the biomass waste gasification characteristics, and it assumes that the process rate is limited by the diffusion of the reaction products from the surface, the reaction surface decreases during the process, and it can be assumed that the solid phase has the form

fit too, and the obtained results are shown in Table 3.

Figure 3. Weight loss and derivative curves for olive pits at different heating rates.

of ball-shaped grains [29].

68 Gasification for Low-grade Feedstock

stage.


Table 2. Pre-exponential factor and activation energy obtained and the statistical parameter values for pyrolysis stage.

On the other hand, the pre-exponential factor value was obtained for each agro-industrial waste at the different heating rates. This parameter varies too with the heating rate; however, it is important to consider that it was obtained from a model-based method and it is tainted by

Figure 9. Comparison of experimental and predicted values of g(a) for olive pits at different heating rates for char

Figure 8. Comparison of experimental and predicted values of g(a) for plum pits at different heating rates for char

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification

http://dx.doi.org/10.5772/intechopen.73288

71

The syngas composition and exergetic efficiency of the gasification process were studied with the lignocellulosic waste composition, gasifier temperature, and ER and SBR variation. ER was

association with the reaction model that must be assumed to permit its calculation.

5. Exergetic analysis to biomass gasification

gasification stage.

gasification stage.

Figure 7. Comparison of experimental and predicted values of g(a) for sawdust at different heating rates for char gasification stage.

within the samples [30, 31]. The smallest value of this parameter was calculated for olive pit at 5 K/min. The found activation energy values are similar to obtained values by other authors [30, 32].

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification http://dx.doi.org/10.5772/intechopen.73288 71

Figure 8. Comparison of experimental and predicted values of g(a) for plum pits at different heating rates for char gasification stage.

Figure 9. Comparison of experimental and predicted values of g(a) for olive pits at different heating rates for char gasification stage.

On the other hand, the pre-exponential factor value was obtained for each agro-industrial waste at the different heating rates. This parameter varies too with the heating rate; however, it is important to consider that it was obtained from a model-based method and it is tainted by association with the reaction model that must be assumed to permit its calculation.

#### 5. Exergetic analysis to biomass gasification

within the samples [30, 31]. The smallest value of this parameter was calculated for olive pit at 5 K/min. The found activation energy values are similar to obtained values by other authors

Figure 7. Comparison of experimental and predicted values of g(a) for sawdust at different heating rates for char

Agro-industrial wastes Heating rate Temp range Kinetics parameters Statistical parameters

565

560

561

480

620

644

477

679

578

Table 2. Pre-exponential factor and activation energy obtained and the statistical parameter values for pyrolysis stage.

10 450

15 442

10 503

15 555

10 476

15 488

Sawdust 5 450

70 Gasification for Low-grade Feedstock

Plum pits 5 400

Olive pits 5 387

β (K/min) (K) E (KJ/mol) A (s1) R2 σ

90.96 1.34 107 0.90 7.31 <sup>10</sup><sup>8</sup>

98.62 1.91 <sup>10</sup><sup>8</sup> 0.98 3.44 <sup>10</sup><sup>8</sup>

99.80 5.10 <sup>10</sup><sup>8</sup> 0.91 6.13 <sup>10</sup><sup>8</sup>

81.42 1.94 107 0.97 4.27 <sup>10</sup><sup>8</sup>

90.66 3.92 <sup>10</sup><sup>6</sup> 0.99 1.96 <sup>10</sup><sup>8</sup>

99.88 6.26 <sup>10</sup><sup>6</sup> 0.91 8.91 <sup>10</sup><sup>8</sup>

70.23 1.59 106 0.91 7.09 <sup>10</sup><sup>8</sup>

80.45 1.22 <sup>10</sup><sup>6</sup> 0.98 3.21 <sup>10</sup><sup>8</sup>

87.46 1.07 <sup>10</sup><sup>7</sup> 0.92 8.91 <sup>10</sup><sup>8</sup>

[30, 32].

gasification stage.

The syngas composition and exergetic efficiency of the gasification process were studied with the lignocellulosic waste composition, gasifier temperature, and ER and SBR variation. ER was


exergetic efficiency increases when the gasifier temperature augments. This is consistent with Zhang results [33]; he informed that higher efficiencies can be achieved by increasing the gasification temperature. In the studied temperature range, the highest value to this parameter was calculated for olive pits (64% at a temperature equal to 950C), and the lowest value was predicted for the sawdust (41% at a temperature equal to 650C). The lower temperatures favor the exothermic reactions of CH4 and CO2 formations. The higher temperatures favor the endothermic reactions as the H2 and CO formation reactions. Therefore, in the product, moles of H2 and CO increase and consequently the exergy efficiency of the process. Therefore, the molar fraction of these gases in the syngas increases the process'

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification

http://dx.doi.org/10.5772/intechopen.73288

73

To study the ER influence on the gasification efficiency and syngas composition, the gasifier temperature was set at 850C and SBR at 1.5. Figure 11 shows that the exergetic efficiency diminishes with the increase of ER. It is because the O2 content in the gasifying agent promotes the combustion reactions. During the gasification process, these reactions are not desirable because they compete with the reactions to transform the biomass in syngas rich in H2 and CO contents. Increasing the ER value, H2, CO, and CH4 contents decrease; thus the calorific value of the produced gas and the exergetic efficiency decrease. In addition, the CO2 and H2O presences in the syngas composition diminish its calorific value and the exergetic efficiency. For the Olive pits, when ER increases, the H2 and CO contents in syngas decrease about 20%

Considering the influence of SBR in the gasification efficiency and syngas composition, this parameter was varied when ER value was equal to 0.25 and the gasifier temperature equal to 850C. Figure 12 shows the exergetic efficiency decrease with the growth of SBR. The lowest value of this parameter corresponds to SBR = 1.5; then the exergetic efficiency value increases

exergy efficiency.

5.2. Influence of ER

and 15%, respectively.

5.3. Influence of SBR

Figure 11. Exergetic yield vs. equivalent ratio (ER).

Table 3. Pre-exponential factor and activation energy obtained and the statistical parameter values for char gasification stage.

varied from 0.15 to 0.3, SBR from 0 (gasification with air only) to 3, and gasifier temperature in the range of 650–950C. The moisture content of wastes was set at about 6% by weight.

#### 5.1. Influence of gasifier temperature

In order to analyze the syngas composition and exergetic efficiency with the gasifier temperature variation, SBR value was set at 2, and the ER value was 0.25. Figure 10 shows that the

Figure 10. Exergetic yield vs. temperature.

exergetic efficiency increases when the gasifier temperature augments. This is consistent with Zhang results [33]; he informed that higher efficiencies can be achieved by increasing the gasification temperature. In the studied temperature range, the highest value to this parameter was calculated for olive pits (64% at a temperature equal to 950C), and the lowest value was predicted for the sawdust (41% at a temperature equal to 650C). The lower temperatures favor the exothermic reactions of CH4 and CO2 formations. The higher temperatures favor the endothermic reactions as the H2 and CO formation reactions. Therefore, in the product, moles of H2 and CO increase and consequently the exergy efficiency of the process. Therefore, the molar fraction of these gases in the syngas increases the process' exergy efficiency.

#### 5.2. Influence of ER

To study the ER influence on the gasification efficiency and syngas composition, the gasifier temperature was set at 850C and SBR at 1.5. Figure 11 shows that the exergetic efficiency diminishes with the increase of ER. It is because the O2 content in the gasifying agent promotes the combustion reactions. During the gasification process, these reactions are not desirable because they compete with the reactions to transform the biomass in syngas rich in H2 and CO contents. Increasing the ER value, H2, CO, and CH4 contents decrease; thus the calorific value of the produced gas and the exergetic efficiency decrease. In addition, the CO2 and H2O presences in the syngas composition diminish its calorific value and the exergetic efficiency. For the Olive pits, when ER increases, the H2 and CO contents in syngas decrease about 20% and 15%, respectively.

#### 5.3. Influence of SBR

varied from 0.15 to 0.3, SBR from 0 (gasification with air only) to 3, and gasifier temperature in the range of 650–950C. The moisture content of wastes was set at about 6% by weight.

Table 3. Pre-exponential factor and activation energy obtained and the statistical parameter values for char gasification stage.

Agro-industrial wastes Heating rate Temp range Kinetics parameters Statistical parameters

1073

1073

1073

1073

1073

1073

1073

1073

578

10 670

15 670

10 670

15 670

10 670

15 488

β (K/min) (K) E (KJ/mol) A (s1) R2 σ

98.19 1.20 102 0.97 2.85 <sup>10</sup><sup>9</sup>

58.17 8.33 <sup>10</sup><sup>0</sup> 0.99 4.32 <sup>10</sup><sup>9</sup>

40.11 1.03 <sup>10</sup><sup>0</sup> 0.95 6.67 <sup>10</sup><sup>9</sup>

60.25 1.00 101 0.90 8.15 <sup>10</sup><sup>9</sup>

41.50 1.03 <sup>10</sup><sup>0</sup> 0.87 1.78 <sup>10</sup><sup>8</sup>

38.64 1.11 <sup>10</sup><sup>0</sup> 0.92 1.49 <sup>10</sup><sup>8</sup>

46.40 1.01 100 0.98 6.44 <sup>10</sup><sup>9</sup>

24.10 1.01 <sup>10</sup><sup>0</sup> 0.89 1.49 <sup>10</sup><sup>8</sup>

49.34 3.50 <sup>10</sup><sup>0</sup> 0.98 6.01 <sup>10</sup><sup>9</sup>

In order to analyze the syngas composition and exergetic efficiency with the gasifier temperature variation, SBR value was set at 2, and the ER value was 0.25. Figure 10 shows that the

5.1. Influence of gasifier temperature

Figure 10. Exergetic yield vs. temperature.

Sawdust 5 670

72 Gasification for Low-grade Feedstock

Plum pits 5 670

Olive pits 5 670

Considering the influence of SBR in the gasification efficiency and syngas composition, this parameter was varied when ER value was equal to 0.25 and the gasifier temperature equal to 850C. Figure 12 shows the exergetic efficiency decrease with the growth of SBR. The lowest value of this parameter corresponds to SBR = 1.5; then the exergetic efficiency value increases

Figure 11. Exergetic yield vs. equivalent ratio (ER).

• The variation of E values with the heating rate indicates the existence of a complex

Thermodynamic and Kinetic Study of Lignocellulosic Waste Gasification

http://dx.doi.org/10.5772/intechopen.73288

75

• The results of the proposed model suggest to work at high temperatures using an airvapor mixture as gasifying agent. While the vapor increases the H2 content in the produced syngas, the exergetic efficiency decreases due to the necessary energy to convert

Rosa Ana Rodriguez\*, Germán Mazza, Marcelo Echegaray, Anabel Fernandez and

Instituto de Ingeniería Química, Facultad de Ingeniería, Universidad Nacional de San Juan,

[1] Berndes G, Hoogwijk M, van den Broek R. The contribution of biomass in the future global energy supply: A review of 17 studies. Biomass and Bioenergy. 2003;25:1-28

[2] Ma L, Wang T, Liu Q, et al. A review of thermal–chemical conversion of lignocellulosic

[3] McKendry P. Energy production from biomass (part 1): Overview of biomass. Bioresource

[4] Ellis N, Masnadi MS, Roberts DG, et al. Mineral matter interactions during co-pyrolysis of coal and biomass and their impact on intrinsic char co-gasification reactivity. Chemical

[5] Han J, Kim HJ. Pyrolysis characteristic and kinetic of sawdust-polypropylene blend. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 2009;31:

[6] Edreis EMA, Yao H. Kinetic thermal behaviour and evaluation of physical structure of sugar cane bagasse char during non-isothermal steam gasification. Journal of Materials

[7] Echegaray ME, Castro CM, Mazza GD, et al. Exergy analysis of syngas production via biomass thermal gasification. International Journal of Thermodynamics. 2016;19:

[8] AW C, JP R. Kinetic parameters from thermogravimetric data. Nature. 1964;201:68-69

biomass in China. Biotechnology Advances. 2012;30:859-873

multistep mechanism that occurs in the solid state.

\*Address all correspondence to: rrodri@unsj.edu.ar

water into steam.

Author details

Daniela Zalazar García

San Juan, Argentina

Technology. 2002;83:37-46

Engineering Journal. 2015;279:402-408

Research and Technology. 2016;5:317-326

References

364-371

178-184

Figure 12. Exergetic yield vs. steam/biomass ratio (SBR).

softly. The decrease is due to the physical exergy of the steam used as the gasifying agent. This decrease is produced because it is necessary to supply energy to the water to transform it in steam. Then, it is partially offset by the increase of H2 content in the produced syngas.

Comparing the gasification process of olive pits (SBR = 0) using air as gasifying agent and an steam–air mixture (SBR = 1), the CO content into the produced syngas decreases 38% approximately when the mixture is used; however, the H2 content increases around 31%.

For the Olive pits, exergetic efficiencies equal to 60.13% and 60.11% were obtained for air and steam/air (SBR = 3) gasification, respectively, considering that the variation is not very noticeable. Physical exergy is related to the syngas sensible heat, and this is lost when the gas cools and it influences the exergetic efficiency value. Increasing the SBR value, the water content in the produced gas flow increases, and also it contributes to the physical exergy. The exergy content of syngas is the sum of physical and chemistry exergies. The physical exergy of biomass steam gasification is higher than the exergy of air gasification due to the higher temperature of the steam, resulting in the exergetic efficiency of air gasification higher to the efficiency of steam gasification.
