**1. Introduction**

There were around 28,000 commercial aircraft as of 2017, and out of these, 22,337 passenger jet aircraft have operations that yielded around 859 million tonnes of CO2 [1–3]. Based on forecast of growth in air traffic, aviation emissions are also expected to grow in the long term. For example, Japan Aircraft Development Corporation [3] claimed that approximately 33,500 aircraft would be added to the global fleet over the next 20 years. The International Civil Aviation Organization [4] also claimed that a five percent growth in air traffic, compared to the projected one to two percent annual increase in aircraft fuel efficiency, would lead to the growth in emissions.

According to the International Air Transport Association [5], the air transport industry developed and has restated commitment to its aviation emission mitigation targets as follows:

i.An average improvement in fuel efficiency of 1.5% per year from 2009 to 2020


A combination of different measures (technology, operations, infrastructure, economic and additional technologies and biofuels) would help achieve the 2050 target of reducing net aviation CO2 emissions by 50%, relative to 2005 levels [6]. Thus, this study proposes a strategic measure of mitigating aviation emissions by giving priority to retiring passenger aircraft at the global fleet level when they are evaluated to have an operating cost disadvantage in comparison with other aircraft. The emission mitigation potential (EMP) of the measure is also evaluated.

The next section gives an overview of measures already proposed in different studies for mitigating aviation emissions. Section III describes the methodological approach used in the study. Subsequently, two fleet renewal strategies (*Replacement Strategy* and *Growth Strategy*) are presented before analysing the potential of using the *Replacement Strategy* over the *Growth Strategy*.

#### **2. Review of measures for mitigating aviation emissions**

The process of fleet development is majorly driven by the satisfaction of demand, subject to objective conditions. These conditions include profit maximisation or return on investment, minimising operating costs especially when faced with major maintenance events, environmental constraints effected as governmental restrictions and exogenous market dynamics like aircraft demand and supply and fuel prices [7]. Furthermore, before an airline decides to add aircraft to the fleet, an evaluation period is chosen to ensure that the aircraft introduced to the global fleet either to fill capacity gap or as replacement aircraft still gives a unit cost advantage by the end of the evaluation period. Wensveen [8] claimed a planning horizon of 10 years for a typical fleet planning model, while Clark [9] and Belobaba [10] stated possible periods between 6 and 12 and 10–15 years, respectively, for the macro-approach to fleet planning.

Extensive work has been done in proposing emission mitigation measures that can be applied at the aircraft fleet level, using various fleet development tools [11–21]. A review of these studies was done by Oguntona [22]. **Table 1** summarises the measures proposed in these studies and categorises them under the broad groups of measures for mitigating aviation emissions.

Although these studies have covered essential aspects of measures proposed by the industry, there has been no consideration of prioritising aircraft economic retirement as an emission mitigation measure.

### **3. Method**

Fleet system dynamics model (FSDM), an integrated modelling environment (IME), was developed by Randt [23] for evaluating longer-term emissions of

**147**

**Basket of measures** Technology, additional technologies and biofuels

Next-

X

X

X

X

X

X

—

X

X

Retrofits

Performance

X

X

X

—

—

X

X

—

—

Improvement

Package (PIP)

of 1% per year

for all aircraft

Alternative

X

X

—

—

—

—

—

X

—

fuels

Infrastructure

ATM

X

X

—

—

—

X

X

X

—

improvements

Early aircraft

—

—

X

—

—

X

—

—

—

retirement

Increased

X

—

—

—

—

X

—

—

—

Load factor/

reduced

frequency

Others♐

X

—

—

—

—

—

—

—

—

measure

Operations

measure

X

—

—

—

—

—

—

—

—

generation aircraft with improved technology‡

**Scenario measures studied**

**Dray et al. [11, 12]**

**Owen et al. [13]**

**Hassan et al. [14, 15]**

**Schilling et al. [16] Ogunsina et al. [17]**

**EASA [18]**

**Winchester et al. [19]**

**ICAO [20]**

**Randt et al. [21]**

*Increasing the Emission Mitigation Potential by Employing an Economically Optimised…*

*DOI: http://dx.doi.org/10.5772/intechopen.88219*

#### *Increasing the Emission Mitigation Potential by Employing an Economically Optimised… DOI: http://dx.doi.org/10.5772/intechopen.88219*


*Environmental Impact of Aviation and Sustainable Solutions*

the *Replacement Strategy* over the *Growth Strategy*.

macro-approach to fleet planning.

groups of measures for mitigating aviation emissions.

retirement as an emission mitigation measure.

**2. Review of measures for mitigating aviation emissions**

tion targets as follows:

levels

According to the International Air Transport Association [5], the air transport industry developed and has restated commitment to its aviation emission mitiga-

i.An average improvement in fuel efficiency of 1.5% per year from 2009 to 2020

iii.A reduction in net aviation CO2 emissions of 50% by 2050, relative to 2005

ii.A cap on net aviation CO2 emissions from 2020 (carbon-neutral growth)

A combination of different measures (technology, operations, infrastructure, economic and additional technologies and biofuels) would help achieve the 2050 target of reducing net aviation CO2 emissions by 50%, relative to 2005 levels [6]. Thus, this study proposes a strategic measure of mitigating aviation emissions by giving priority to retiring passenger aircraft at the global fleet level when they are evaluated to have an operating cost disadvantage in comparison with other aircraft.

The next section gives an overview of measures already proposed in different studies for mitigating aviation emissions. Section III describes the methodological approach used in the study. Subsequently, two fleet renewal strategies (*Replacement Strategy* and *Growth Strategy*) are presented before analysing the potential of using

The process of fleet development is majorly driven by the satisfaction of demand, subject to objective conditions. These conditions include profit maximisation or return on investment, minimising operating costs especially when faced with major maintenance events, environmental constraints effected as governmental restrictions and exogenous market dynamics like aircraft demand and supply and fuel prices [7]. Furthermore, before an airline decides to add aircraft to the fleet, an evaluation period is chosen to ensure that the aircraft introduced to the global fleet either to fill capacity gap or as replacement aircraft still gives a unit cost advantage by the end of the evaluation period. Wensveen [8] claimed a planning horizon of 10 years for a typical fleet planning model, while Clark [9] and Belobaba [10] stated possible periods between 6 and 12 and 10–15 years, respectively, for the

Extensive work has been done in proposing emission mitigation measures that

Although these studies have covered essential aspects of measures proposed by the industry, there has been no consideration of prioritising aircraft economic

Fleet system dynamics model (FSDM), an integrated modelling environment (IME), was developed by Randt [23] for evaluating longer-term emissions of

can be applied at the aircraft fleet level, using various fleet development tools [11–21]. A review of these studies was done by Oguntona [22]. **Table 1** summarises the measures proposed in these studies and categorises them under the broad

The emission mitigation potential (EMP) of the measure is also evaluated.

**146**

**3. Method**


**Table 1.**

**149**

**Table 2.**

*Increasing the Emission Mitigation Potential by Employing an Economically Optimised…*

aircraft at the global fleet level. FSDM initially used aircraft-specific fuel consumption as the performance criterion for aircraft addition to the fleet, while aircraft were retired from the fleet using functions dependent on aircraft calendar age. This aircraft retirement method was also used in some studies previously mentioned in Section 2, without inclusion of the objective functions mentioned in Section 2. FSDM was later adapted by Oguntona et al. [24] who evaluated aircraft direct operating cost (DOC) performance in analysing the development of the global passenger aircraft fleet under a specified forecast fuel price development. The model adaptation excluded the aircraft economic retirement consideration. However, in this study, the DOC calculation method is revised while using this approach also for

The network simplification approach used by Oguntona et al. [24] was retained,

in which average distances (hereafter referred to as route groups) between and

Furthermore, the method of classifying the aircraft fleet available in year 2008 that was adopted by Randt [23] was retained while excluding aircraft types that are unlikely to be produced as well as freighter aircraft. Two generations of aircraft types were used in the model. The initial fleet aircraft clusters referred to aircraft types available in year 2008 (see **Table 2**), while next-generation aircraft (next-gen aircraft) referred to aircraft types produced afterwards (see **Table 3**). Cost improvements in the FSDM aircraft are shown in the Appendix

The FSDM was built in an integrated modelling environment [23]. It receives mission fuel burn values from a global fleet mission calculator (GFMC) that is based on the Base of Aircraft Data (BADA) tool [23]. The fuel performance data is then used alongside other input data in the Aircraft Lifetime Cost (ALiTiCo) module. ALiTiCo produces lifetime direct operating cost (DOC) estimates for the different entry into service (EIS) years of the FSDM aircraft. Input for ALiTiCo includes aircraft and engine characteristics as well as other parameters that vary over time and are unique to the considered FSDM flight distances. These are

**Cluster name Cluster acronym Representative aircraft type**

Long-range combi LRC Boeing MD 11 Long range heavy LRH Boeing 747-400 Mid-range freighter MRF Boeing 767-300F Jet commuter JC Embraer 190 Long-range freighter LRF Boeing 747-400F Turboprop commuter TP ATR 72-500 Mid range MR Boeing 767-300 Long range LR Boeing 777-200 Narrow body NB Airbus A320-200

*Representative aircraft of the initial fleet aircraft clusters using FSDM [21].*

*DOI: http://dx.doi.org/10.5772/intechopen.88219*

aircraft economic retirement considerations.

within regions were adopted.

**3.2 Integrated model overview**

(see **Table A-1**).

shown in **Table 4**.

**3.1 Air transportation system simplification approach**

*Emission mitigation measures studied in fleet models reviewed [22].*

*Increasing the Emission Mitigation Potential by Employing an Economically Optimised… DOI: http://dx.doi.org/10.5772/intechopen.88219*

aircraft at the global fleet level. FSDM initially used aircraft-specific fuel consumption as the performance criterion for aircraft addition to the fleet, while aircraft were retired from the fleet using functions dependent on aircraft calendar age. This aircraft retirement method was also used in some studies previously mentioned in Section 2, without inclusion of the objective functions mentioned in Section 2.

FSDM was later adapted by Oguntona et al. [24] who evaluated aircraft direct operating cost (DOC) performance in analysing the development of the global passenger aircraft fleet under a specified forecast fuel price development. The model adaptation excluded the aircraft economic retirement consideration. However, in this study, the DOC calculation method is revised while using this approach also for aircraft economic retirement considerations.

#### **3.1 Air transportation system simplification approach**

The network simplification approach used by Oguntona et al. [24] was retained, in which average distances (hereafter referred to as route groups) between and within regions were adopted.

Furthermore, the method of classifying the aircraft fleet available in year 2008 that was adopted by Randt [23] was retained while excluding aircraft types that are unlikely to be produced as well as freighter aircraft. Two generations of aircraft types were used in the model. The initial fleet aircraft clusters referred to aircraft types available in year 2008 (see **Table 2**), while next-generation aircraft (next-gen aircraft) referred to aircraft types produced afterwards (see **Table 3**). Cost improvements in the FSDM aircraft are shown in the Appendix (see **Table A-1**).

#### **3.2 Integrated model overview**

*Environmental Impact of Aviation and Sustainable Solutions*

**148**

**Basket of** 

**Scenario** 

**Dray** 

**Owen** 

**Hassan** 

**Schilling** 

**Ogunsina** 

**EASA [18]**

**Winchester** 

**ICAO [20]**

**Randt et al. [21]**

**et al. [19]**

**et al. [17]**

**et al.** 

**et al.** 

**et al.** 

**et al.** 

**[11,** 

**[13]**

**[14, 15]**

**[16]** 

**12]**

**measures** 

**studied**

**measures**

Regulatory

Emission

X

—

X

—

—

X

X

—

—

and economic

trading

Set emission

—

X

—

—

—

X

X

—

—

limit

Fuel tax,

X

—

—

—

—

X

—

—

—

route and

airport charge

*aerodynamic maintenance, engine wash, increased turboprop use.*

**Table 1.**

*Emission mitigation measures studied in fleet models reviewed [22].*

*‡Electric, hybrid, distributed propulsion, blended-wing body, optimised counterrotating propeller, advanced turboprop, etc.*

♐*Surface congestion management, single-engine taxi, optimised departures, reduced cruise inefficiency, optimised approach, reduced fuel reserves, reduced tankering, increased engine maintenance, increased* 

measures

The FSDM was built in an integrated modelling environment [23]. It receives mission fuel burn values from a global fleet mission calculator (GFMC) that is based on the Base of Aircraft Data (BADA) tool [23]. The fuel performance data is then used alongside other input data in the Aircraft Lifetime Cost (ALiTiCo) module. ALiTiCo produces lifetime direct operating cost (DOC) estimates for the different entry into service (EIS) years of the FSDM aircraft. Input for ALiTiCo includes aircraft and engine characteristics as well as other parameters that vary over time and are unique to the considered FSDM flight distances. These are shown in **Table 4**.


#### **Table 2.**

*Representative aircraft of the initial fleet aircraft clusters using FSDM [21].*


#### **Table 3.**

*Next-generation aircraft EIS [21].*


**151**

**Figure 1.**

year are:

**Table 4.** *Input to ALiTiCo.*

*Source: Own depiction.*

*Increasing the Emission Mitigation Potential by Employing an Economically Optimised…*

• Annual frequency • Installed seats

**Time-dependent input Time-independent input**

• Belly-freight capacity • Block fuel • Block time

An overview of the interlinked submodules of the updated integrated modelling

The integrated model depends on input data extracted from various data sources and processed in calculators to give various outputs. The final output of interest is obtained from the FSDM. The data flow in and out of the calculators is shown in **Figure 2**.

The main steps of fleet renewal/development FSDM performs every calculation

i.Retirement of aircraft that have reached their design life limit, evaluated in terms of their structural retirement age [years] depending on their assumed

ii.Evaluation of aircraft before addition to fleet to fill route capacity gap.

iii.Comparison of existing aircraft with new available aircraft in terms of operating cost performance, retiring those having a cost disadvantage and replacing them with more cost-efficient ones. This is also referred to as

Direct operating costs (DOC) were estimated to comprise of cost of ownership (COO), cash operating costs (COC) and additional direct operating costs (ADOC)

The main steps of the integrated model are shown in **Figure 3**.

*DOI: http://dx.doi.org/10.5772/intechopen.88219*

approach used in this study is shown in **Figure 1**.

annual utilisation rates.

**3.3 Cost modelling approach**

economic retirement of aircraft.

according to the approach of Ploetner et al. [25].

*Interlinked submodules of integrated model environment.*

*Increasing the Emission Mitigation Potential by Employing an Economically Optimised… DOI: http://dx.doi.org/10.5772/intechopen.88219*


#### **Table 4.**

*Environmental Impact of Aviation and Sustainable Solutions*

JC Bombardier CS100/

*Next-generation aircraft EIS [21].*

**Route-independent input**

Aircraft type dependent

Environmental, macroeconomic and flight-related

**Route-dependent input**

**Representative nextgeneration aircraft type**

Embraer E190-E2

• EIS year

• Fuel price

factors • Seat load factor • Freight load factor

• Inflation adjustment

• Normalised improvements in fuel costs • Normalised improvements in non-fuel COC • Normalised improvements in ADOC

LRH Boeing 747-800 Next-gen long range heavy

**Next-gen aircraft cluster name** 

Next-gen jet commuter (NGJC) 2016

**EIS year**

2012

• Number of engines • Engine SFC • Number of shafts • Engine take-off power • Number of propeller

• Propeller diameter

• Number of compressor

• Maximum thrust • Emitted pollutant NOx per LTO cycle

• Threshold approach

• Threshold flyover noise • ETS allowance per ton

• Calculation age limit • Depreciation period

noise

CO2

• Flight distance • Flight type

blades

• BPR • OPR

stages

**(acronym)**

(NGLRH)

• Limit of validity • MTOW • Range at LRC • Mach number • Cabin length • Cabin height • Cabin width at floor • Cabin width maximum • Take-off field length • Operating weight empty

• Approach noise level • Flyover noise level • Engine dry weight

• Aircraft price scenario: minimum, mean or maximum • Exchange rate • Interest and insurance rates per year • Labour rate • Escalation factors • Navigation unit rate

MR Boeing 787-8 Next-gen mid range (NGMR) 2011

LR Airbus A350XWB Next-gen long range (NGLR) 2015 NB Airbus A320neo Next-gen narrow body (NGNB) 2016

**Time-dependent input Time-independent input**

**Initial fleet aircraft**

**Table 3.**

**150**

*Input to ALiTiCo.*

An overview of the interlinked submodules of the updated integrated modelling approach used in this study is shown in **Figure 1**.

The integrated model depends on input data extracted from various data sources and processed in calculators to give various outputs. The final output of interest is obtained from the FSDM. The data flow in and out of the calculators is shown in **Figure 2**.

The main steps of the integrated model are shown in **Figure 3**.

The main steps of fleet renewal/development FSDM performs every calculation year are:


#### **3.3 Cost modelling approach**

Direct operating costs (DOC) were estimated to comprise of cost of ownership (COO), cash operating costs (COC) and additional direct operating costs (ADOC) according to the approach of Ploetner et al. [25].

**Figure 1.** *Interlinked submodules of integrated model environment.*

**Figure 2.** *Data flow in and out of GFMC, ALiTiCo and FSDM.*
