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Review

Evaluating Methods That Calculate Aircraft Emission Impacts on Air Quality: A Systematic Literature Review

by
Manori Dissanayaka
1,*,
Tim Ryley
1,2,
Bojana Spasojevic
1,3 and
Savindi Caldera
2,4
1
Griffith Aviation, School of Engineering & Built Environment, Griffith University, Brisbane, QLD 4111, Australia
2
Cities Research Institute, Griffith University, Brisbane, QLD 4111, Australia
3
Griffith Institute for Tourism (GIFT), Griffith University, Brisbane, QLD 4111, Australia
4
School of Science, Technology and Engineering, University of the Sunshine Coast, Petrie, QLD 4502, Australia
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(12), 9741; https://doi.org/10.3390/su15129741
Submission received: 8 May 2023 / Revised: 13 June 2023 / Accepted: 14 June 2023 / Published: 19 June 2023
(This article belongs to the Special Issue Microenvironmental Air Pollution Control, Comfort and Health Risk)
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Abstract

:
Aircraft operations from above ground level to 3000 feet impact air quality and cause health issues, particularly for people working and living in and around airports. This paper evaluates the current emission calculation methods to identify the most accurate way to generate an emission inventory. Journal articles on aircraft influence on air quality were selected for a systematic literature review (SLR). After screening 277 articles written in English, 60 articles on emission calculation methods were included in the analysis. Based on the analysis, air quality can be more accurately assessed when considering direct emissions from an aircraft than when measuring atmospheric pollutant concentrations. While the International Civil Aviation Organization’s (ICAO) advanced approach was the most widely used from the literature reviewed, airport-specific, time-in-mode, and actual atmospheric conditions where aircraft operate offer the potential for significant improvement. The SLR demonstrates a need for more accurate emission calculation methods to assess the aircraft’s influence on air quality. The SLR guides airlines and airports to maintain an accurate emission inventory, which will set future targets to improve air quality.

1. Introduction

Airports and airlines are required nationally to maintain a precise inventory to set evidence-based targets for sustainable aviation [1]. Aircraft emissions adversely influence local air quality and climate change. Aircraft operations above 3000 ft contribute to climate change through emissions of carbon dioxide (CO2), nitrogen oxides (NOX), volatile organic compounds (VOC), sulfur dioxide (SO2), and water vapor (H2O) [2]. Aircraft operations below 3000 ft damage local air quality through the emissions of nitrogen oxides (NOX), black carbon (BC), hydrocarbons [3], and carbon monoxide (CO) [4], sulfur oxides (SOX), and particulate matter (PM) [5]. Aircraft emissions comprise about 70% CO2, with less than 30% water vapor and less than 1% other remaining gases [6]. Due to the higher emission impacts of CO2, aviation impacts on climate change have been highly researched [7,8,9]. The aviation industry is also collaboratively working with stakeholders to adopt decarbonization strategies to reduce the climate change effects due to their operations [10]. Climate change is a principal focus of the aviation industry when contributing to the achievement of the Sustainable Development Goals (SDGs) [11]. However, focus should still be given to local air quality impacts due to aircraft operations, both by the scientific community and the aviation industry, given that it is also a major problem.
The degradation of air quality has a myriad of impacts. A higher concentration of CO can cause heart disease; exposure to emissions of NOX and SOX can damage the human respiratory system; and HC can harm the immune system and cause neurological, reproductive, developmental, and respiratory problems [12]. Aircraft impacts on air quality should also be considered due to their adverse effects on health when exposure is at high concentrations. Airport development is required with the growth in demand, and it often links with urban development due to job availability, well-developed infrastructure, and public transit [13]. Fast-growing airports can cause encroachment issues too [14].
In 2015, the Paris Agreement, an international treaty on climate change, committed 196 parties to limiting global warming to between 1.5 °C and 2 °C [15]. The Paris Agreement requires each party to maintain nationally determined contributions (NDCs), which represent the commitments to reduce national emissions. Parties should adopt domestic mitigation measures and set national emission reduction targets. The current status of aviation emissions in a country must be identified to set the targets for NDCs [1]. Therefore, an emission inventory of each airport should be maintained by the member country. However, the Paris Agreement does not provide a specific emission calculation method to evaluate climate change or air quality impacts. Therefore, various methods are used to calculate emissions according to their local capabilities.
The 2006 IPCC Guidelines for National Greenhouse Gas Inventories provide internationally agreed methodologies to estimate greenhouse gas (GHG) inventories [16]. The United Nations Framework Convention on Climate Change [1] stipulates that member states report their GHG inventories following IPCC guidelines. Three methodological tiers for estimating emissions are presented in the guidelines. Tier 1 is purely based on the fuel supplied to the aircraft, while Tier 2 is based on the number of landing/take-off cycles (LTOs) and fuel supplied to the aircraft. However, Tiers 1 and 2 are basic methods with minimal required data. Tier 1 and Tier 2 methods use fuel supplied by the airport. However, the actual fuel consumption differs from the fuel supplied, as an aircraft carries enough extra fuel to reach the nearest airport if there is an emergency at the destination [17]. Tier 3 uses operational data for individual flights, with Tier 3A based on origin and destination (OD) pairs and Tier 3B using sophisticated models. The drawback of the Tier 3 method is obtaining the required data, as it can either be outside the public domain or challenging to obtain. Moreover, the computational emissions process of Tier 3 is more complicated than the other two methods.
The International Civil Aviation Organization (ICAO), as the leading United Nations (UN) agency in matters related to international civil aviation, guides its member states (193 national governments) in implementing the best practices concerning airport-related air quality [18]. The ICAO invites member states to support environment-related activities by providing reasonable voluntary contributions, noting the importance of maintaining an updated emission inventory to support decision making on environmental matters. The ICAO suggests three emission calculation methods: (1) simple approach, (2) advanced approach, (3) sophisticated approach [19]. The simple approach has easily accessible data and available standards. The advanced approach requires airport-specific data and other additional sources. The sophisticated approach requires in-depth knowledge of aircraft performance with cooperation among various entities to access the data. The ICAO guidance material was developed to assist all ICAO member states, and it is broad and extensive. However, it cannot be expected to provide the level of detail necessary to assist states in addressing every issue.
This paper aims to identify the emission calculation methods used to assess air quality around airports, investigating their limitations and ways of overcoming them. It also determines the best emission calculation method to generate a more accurate emission inventory for airports and airlines.

2. Methods

This section provides an outline of the methods undertaken for the systematic literature review (SLR). The emission calculation methods used in the aviation industry to assess air quality are analyzed through a SLR. The PRISMA framework was adopted for this SLR [20]. As a method, a SLR follows comprehensive, reproducible, and transparent steps to summarize relevant information [21,22]. Figure 1 presents the steps used as the framework for this SLR.

2.1. Formulate the Research Questions and Scope

Prior knowledge and experience supported the research questions [23]. In this paper, they were reframed as two research aims. Subsequently, a preliminary search was conducted to ensure the validity of the proposed idea and to avoid duplication of previously researched questions. Aircraft, emissions, and local air quality were the three broad areas selected to identify the research scope. A Venn diagram, shown in Figure 2, highlights the main topics within the research scope.

2.2. Identify Keywords and Databases

The keywords identified within the three broad areas were the search term. When conducting a systematic review, at least two databases should be searched [24]. However, three databases were used in this study to generate more comprehensive results. The primary scholarly databases of Web of Science, Scopus, and ProQuest were reviewed, as most of the related journals (aviation + environment) are published in these databases. Clearly set inclusion and exclusion criteria were established for screening. The inclusion criteria were (1) any peer-reviewed journal articles on aircraft influence on local air quality (2) published in English from 2011 to 2021 (December). The exclusion criteria were (1) study of aircraft influence on climate change; (2) study without the emissions of NOx, CO, and HC; (3) abstract-only papers as preceding papers, conference, editorial, and author response theses and books; and (4) articles without full text. The keywords used with Boolean operators were “aviation”, “aircraft”, “emission”, “GHGs”, “air quality”, and “LTO cycle”. Table 1 shows the search term combinations used to identify the relevant literature. Firstly, the papers were chosen, including search terms in the title, abstract, and keywords. The purpose was to develop a broad understanding of aviation emissions. The search under these criteria in all three databases resulted in a total number of 1376 publications.
Since the focus of this study is emissions from aircraft only, papers which addressed emissions from other aviation sources were removed. The search terms were merged to form “aircraft emission”, so that other emission sources could be excluded. The GHG search term was initially identified as another appropriate search term for emissions. However, GHG was later determined to be out of scope, given the focus on air quality. The search continued with the second combination, which generated 270 papers. EndNote 20 software was used to manage the research database.

2.3. Retrieve Potential Literature and Screen

The systematic review process was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [20]. The PRISMA method was followed to maintain a clear record of selected journal articles, and its guidelines help report systematic reviews transparently. A PRISMA diagram (Figure 3) shows the steps followed in screening the relevant documents. At the title and abstract screening stage, the research team selected retrieved articles for further assessment according to the eligibility criteria. A manual search was undertaken by following the references from already included papers to identify whether some relevant papers may have been dropped from the first search. At the stage of full paper screening, three reviewers discussed the reasons for excluding papers. Table 2 summarizes nine separate PRISMA framework reasons for paper exclusion. Finally, 60 relevant journal articles were filtered for review in this study.

2.4. Synthesize Findings

Finally, all 60 papers were collected into one Endnote library to delete duplicates and then exported into an Excel spreadsheet. The variables within the database were (1) authors’ names; (2) publication year; (3) journal; (4) country where research was conducted; (5) types of pollutants; and (6) method of emission calculation. The emission calculation methods used in 60 papers were synthesized to identify the emission calculation methods and generate a more accurate emission inventory.
The 60 papers were then reviewed to determine the emission calculation method used to assess aircraft impacts on local air quality. Those articles were categorized according to their content (Figure 4). Some of the analyzed papers quantified emissions directly emitted from the aircraft, while others quantified the atmosphere’s pollutant concentration. Nonetheless, eight articles quantified the concentration of pollutants, including the dispersion from other nearby sources. Infrastructure or stationary sources, vehicle traffic sources, and aircraft handling sources are other nearby sources influencing the local air quality [19]. Air quality in the vicinity of the airport is typically affected by a range of sources and factors outside the airport’s control and boundary. For example, bushfires, controlled burns, wind-blown dust, and smog from the city-wide motor vehicles are not within the airport’s management [25]. Therefore, 52 articles that solely quantified aircraft emissions were included for further analysis. Of these 52 articles, 30 papers further examined the concentration of pollutants to identify their spatial distribution. The spatial distribution of emissions helps identify the areas where immediate actions are required. However, the IPCC Tier process was used to categorize 52 journal articles following the emission calculation method. The analysis focused on the variables used in the calculation, the limitations of the current methods, and the ways to improve the methods applied.

3. Results and Discussion

3.1. Descriptive Analysis of Findings

A descriptive analysis was initially conducted to identify the current state of aircraft impacts on air quality. Figure 5 illustrates the number of publications per year between 2011 and 2021, which is fairly even across the eleven-year timeframe. The result highlights the extent to which this topic is popular among researchers, emphasizing the relevance of this SLR.
Of the 60 articles published on air quality around airports, Figure 6 shows the countries involved in research on it. According to Figure 6, a concern expressed in the literature is that research tends to be limited to the three regions of North America, Europe, and Asia. However, these are the highest emission-contributing continents [26] and where most research was conducted. According to this SLR, the United States, China, and the United Kingdom have the highest publication rate in the sample. The nature of aircraft emissions means that it is a global issue; yet, researchers from only a small, selected group of countries have focused on it.

3.2. Local, Regional, and Global Aircraft Operation and Air Quality

The papers can be categorized according to the data obtained for assessing air quality. Local, regional, and global aircraft operational data were the three types. A particular airport typically provides local data, while a few airports in a specific wider area provide regional data. All airports together represent global data. Most of the 60 papers covered local data (31), 20 used regional data, and 9 used global data. However, many researchers limit their study by quantifying the emissions of a particular airport due to the limitations in technology and data accessibility. Some airport-specific factors should be considered when assessing air quality around an airport. Some of them are meteorological factors, runway taxiway configurations, airport policies, and air traffic management strategies. Furthermore, among those using regional data, most papers used the Federal Aviation Administration’s [5] Aviation Environmental Design Tool (AEDT) or Emissions and Dispersion Modeling System (EDMS). AEDT and EDMS are software, which can quantify aircraft emissions by considering their actual operational values. These types of software are required to generate a more accurate emission inventory, since a more extensive dataset with airport-specific factors is analyzed compared to local data. Among the papers which addressed global operations, most papers used the AEDT-2006 dataset. Maintaining a global dataset of aircraft operation is a substantial cost, so researchers often use the available AEDT-2006 dataset even if it is not up to date.

3.3. Tier Method

According to the papers selected in this SLR, 52 discussed the calculation methods used only for direct aircraft emissions. Therefore, the following sections discuss the analysis results of these 52 papers. There were 15 different emission calculation methods identified within these papers. Figure 7 shows the calculation methods used in the previous literature and their categorization under the Tiers. According to the 52 papers, 45 used the Tier 3 method, while 6 used Tier 2, and 1 used Tier 1. The ICAO advanced approach is the most used method. However, emissions from different flight phases below 3000 ft needed to be segregated for initiating more accurate mitigation methods. Then, airlines can identify the inefficiencies under different flight phases and take corrective actions. Only the Tier 3 methods identify aircraft emissions under different flight phases. Therefore, Tier 3 is the most used method due to its accuracy when assessing aircraft impacts on air quality.
Table 3 presents a summary of the 52 reviewed papers according to the emission calculation method used. These methods were categorized according to the IPCC Tier method. The number of LTO cycles is a critical variable in Tiers 1 and 2. However, Tiers 1 and 2 calculate the aggregate aircraft emissions from the LTO cycle without segregating them into different flight phases. The emission factor (EF), time-in-mode (TIM), and fuel flow (FF) are the critical variables under Tier 3A methods, which use average fuel consumption and emissions for a representative aircraft category. Tier 3B measures the fuel burnt and emissions throughout the entire trajectory of each flight using aircraft and engine-specific aerodynamic performance data. The following sub-sections discuss Tier 3 methods, which generate a more accurate emission inventory.

3.3.1. Tier 3A

When assessing aircraft emissions, the Tier 3A methods focus on three main variables (time-in-mode (TIM), fuel flow (FF), and the emission index (EI)). The average values of the variables according to the engine type were used for the calculation. According to the SLR articles, some researchers attempt to improve the accuracy of the variables using various methods. This section discusses the ICAO advanced approach, since it is a highly used method and has credibility, given that ICAO is the primary organization in matters related to international civil aviation.
The ICAO advanced approach was used by 17 papers out of 52 reviewed articles. Equation (1) states how ICAO’s advanced approach used the four variables to calculate aircraft emissions [19].
E i j = T I M j k × 60 × F F j k ÷ 1000 × E I j k × N j
In Equation (1), i is the pollutant type (NOx, CO, or HC), j is the aircraft type, and k indicates the aircraft mode (take-off, climb-out, approach, idle). Eij is the emissions of pollutant i in grams produced by aircraft type j per LTO cycle. TIMjk is time-in-mode for mode k and aircraft type j in minutes. FFjk is the fuel flow for mode k and each engine in aircraft type j in kilograms per second. EIjk is the emission index for mode k and each engine in aircraft type j in grams per pollutant per kilogram of fuel. Nj is the number of engines used on aircraft type j. The ICAO provides standard values for TIM, EI, and fuel flow according to the engine type.
The ICAO standard TIMs are 0.7 min, 2.2 min, 4 min, and 26 min for take-off, climb-out, approach, and idle modes, respectively [19]. Kuzu [30] and Khardi [31] used ICAO standard TIM values. However, these values cannot be applied to each airport, especially as the taxiing time does not directly match every airport [32]. Actual TIMs are affected by factors such as aircraft type, taxiway and runway layout, and meteorological conditions [19]. In this SLR, some papers addressed this issue by considering actual movement data. Li, Yang [33] and Taghizadeh, Shafabakhsh [34] evaluated the real taxiing time of each aircraft and modeled an average value instead of the ICAO’s standard TIM for taxiing. They used ICAO standard TIM values for other modes. Hu, Zhu [35], Kafali and Altuntas [36], Yang, Cheng [37], Yin, Ma [38], Synylo and Duchene [39] used actual movement data for all modes and estimated airport-specific average TIM values. Therefore, airport-specific TIM values can produce a more accurate emission inventory than the ICAO standard TIM values.
Different methods were used to capture actual operational data and estimate more accurate airport-specific TIM values. A flight data recorder (FDR) is a device, which records specific aircraft performance data to assess engine performance and fuel consumption [40]. A quick access recorder (QAR), as used by Zhu, Hu [41], is an onboard storage device for capturing flight status. Meteorological factors, flight trajectory information, and aircraft performance data can be extracted from this device. Xu, Xiao [42] Xu, Fu [43] used the Aircraft Communication Addressing and Reporting System (ACARS) to transmit data between aircraft and ground via very high frequency (VHF) radio or satellite. ACARS sends aircraft performance and fuel consumption data. Sherry [44] used FAA’s Aviation Environmental Design Tool (AEDT) to compute the mode-specific durations for each flight by processing radar or simulation data. Stettler, Eastham [45], Yim, Stettler [46] used the National Atmospheric Emissions Inventory, which includes the emissions of UK airports. Creţu, Dobre [47] used the Automatic Dependent Surveillance–Broadcast (ADS-B), which is a system with electronic equipment onboard. This system can provide the precise location of the aircraft. Therefore, some researchers used the above technologies to obtain precise TIMs and improved the accuracy of emission inventory instead of directly using the ICAO’s standard TIMs.
The ICAO Engine Exhaust Emissions Databank (EEDB) provides the emission index (EI) according to the engine type. The ICAO standard EI is based on standard mode-specific trust settings and the International Standard Atmosphere (ISA). While standard trust settings are 7%, 30%, 85%, and 100%, representing engine operation during the taxi/idle, approach, climb-out, and take-off phases of the flight, the ISA assumes sea-level standard atmospheric conditions [19]. However, aircrafts often deviate from this standard trust setting. Therefore, researchers do not model the emission inventory using ICAO’s EI to improve the accuracy of their emission inventory. Xu, Fu [43], Stettler, Eastham [45], Yim, Stettler [46] used the Boeing Fuel Flow Method 2 (BFFM2) to correct the EI of NOx, CO, and HC. The BFFM2, which models EI using aircraft performance data, has been validated by the ICAO Committee on Aviation Environmental Protection [48]. QAR and ACARS, the other methods found in this SLR, were deployed to correct the EI of NOx, CO, and HC. These methods can capture the actual meteorological conditions (temperature, pressure, and humidity of the air) and real engine trust settings for the correction of EI.
ICAO EEDB provides the fuel flow according to the engine type. Since this value is also based on standard trust settings at ISA, obtaining the actual operational values can increase the accuracy level of Equation (1). Fuel flow was adjusted using methods such as ACARS, AEDT, EDMS, FDR, and QAR. These methods can capture the actual meteorological conditions (temperature, pressure, and humidity of the air) and operational conditions for the fuel flow correction. To summarize, most papers in this SLR used the ICAO advanced approach with modifications to TIM, EI, and fuel flow. Some researchers have therefore developed a more accurate emission inventory using the ICAO’s advanced method with modifications.

3.3.2. Tier 3B

Tier 3B methods include emission modeling software. This software can be used to model the 4D trajectory of the latitude, longitude, altitude, and time of aircraft. The software models aircraft fuel consumption and emission using aerodynamic performance data. Some researchers who used Tier 3B methods extended their local emission inventory to a regional or global scale due to the high accessibility of accurate data. Tier 3B generates a more precise emission inventory considering several meteorological and operational factors. Even though these methods reach a high level of accuracy by analyzing up-to-date operational data, only 22 papers out of 52 follow this Tier 3B method. AEDT and EDMS were the most used modeling software packages under Tier 3B. The lack of access to software could be the main reason researchers do not follow Tier 3B approaches.
Table 4 shows how the 52 reviewed papers were distributed among the Tier method and the continent where research was conducted. This research area is mainly limited to three continents, and most of the Tier 3B methods users are based in North America.

4. Conclusions

Measuring pollutant concentration is the most commonly used practice in environmental studies to assess air quality [49,50,51]. However, only limited efforts have been undertaken [52,53] to measure the concentration of pollutants to assess aircraft emissions. The dispersion from other nearby sources is affected when assessing the pollutant concentration, which means that the actual emissions from aircraft cannot be precisely determined. Emissions directly emitted from aircraft should be estimated rather than measuring the pollutant concentration in the atmosphere. According to the Paris Agreement, the exact level of emissions should be identified to set national reduction targets. Therefore, the aviation industry should measure emissions directly emitted from the aircraft to capture actual emissions. Then, the airport can compare their emissions with national standards, taking account of their aircraft operations.
Tier 3 methods facilitate identification of the aircraft emissions under different flight phases, while Tier 1 and Tier 2 methods enable calculation of the aggregate emission of the LTO cycle. Airlines and airports should be required to understand the emissions under different phases in order to recognize the inefficiencies in these phases and then take steps to improve performance. For example, suppose an airport or airline identifies the controllable aircraft idling delays at the taxiing phase. In that case, they will work to minimize the delay, providing both economic and environmental benefits. Therefore, emissions from flight phases below 3000 ft should be separately quantified for initiating mitigation methods. Consequently, Tier 3 methods are more beneficial for airports and airlines when estimating aircraft emissions.
The ICAO’s advanced approach under Tier 3A is the most frequently used method, incorporating the three critical variables of time-in-mode (TIM), emission factor (EF), and fuel flow (FF). The ICAO suggests that their TIM values are appropriate only for the engine certification process and do not represent the actual TIM in real-world aircraft operations [19]. However, some researchers [30,31] still use the ICAO standard TIM values for emission calculation. The ICAO Engine Exhaust Emissions Databank (EEDB) provides the EF and FF based on international standard atmospheric conditions. Therefore, estimates with ICAO values could deviate from actual emissions at a particular airport. However, some researchers [41,45] have tried to improve the accuracy level of the variables individually without directly applying the given methods. Therefore, airports and airlines should use airport-specific TIM values to produce a more accurate emission inventory than the ICAO standard TIM values. They should also adjust the ICAO Engine Exhaust Emissions Databank (EEDB)-given EF and FF, considering the actual operational values to generate a more accurate emission inventory.
Tier 3B contains the most suitable and accurate methods to generate an extended air quality inventory for regional or global operations. Tier 3B software uses airport-specific operational and meteorological data concerning each flight, while other methods lack the capacity to assess this detailed data. For example, when an airport operator operates multiple airports, they can use one of the Tier 3B methods to evaluate their contributions to the air quality within the region. Currently, authors in North America widely use Tier 3B methods. It is recommended that researchers and airports from other regions also use these methods to generate a more accurate emissions inventory.
Airports should report their emission levels to the national inventory to set future targets following the Paris Agreement. This should be in collaboration with other key stakeholders, such as airlines and other airport ground support services. When assessing aircraft emissions, Tier 3B methods use the actual operation of each flight, including the position of aircraft with the 4D trajectory of latitude, longitude, altitude, and time. The software models aircraft fuel consumption and emissions using aerodynamic performance data. However, while Tier 3B methods use the actual operational values of each aircraft, Tier 3A methods use operational value averages. Therefore, airlines and airports should use Tier 3B methods to generate the most accurate emission inventories. However, the drawback of this Tier 3B method is that it requires a greater knowledge of aircraft engine data and some proprietary data or models not generally available in the public domain.
Moving forward, the authors will evaluate the current Australian airport practices to improve air quality. This evaluation will focus on identifying the gap between academic publications and real-world applications. Further research will examine the emissions from other airport sources, such as auxiliary power units (APUs), ground power units (GPUs), and ground support equipment (GSE), influencing local air quality. The authors will propose a methodology to estimate the emissions from these airport sources by analyzing real-time data. The emission results will be presented in metrics such as emissions per aircraft, which would allow for meaningful comparisons between different airports. It is recommended that further research quantify and examine the environmental costs associated with aircraft emissions within an overall economic framework. They will therefore be able to generate an improved airport emission inventory, enabling practitioners to identify the emissions for which they are responsible.

Author Contributions

M.D. was involved in conceptualization, evaluating the key literature, data analysis, and writing; T.R., B.S. and S.C. provided the resources and project supervision and edited the drafts for paper submission and review, subject to checks and proofreading. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors acknowledge a writing circle within the Cities Research Institute, Griffith University (Brisbane, Australia), for providing assistance with the writing of this publication.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Research framework.
Figure 1. Research framework.
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Figure 2. The research scope as a Venn diagram.
Figure 2. The research scope as a Venn diagram.
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Figure 3. The framework applied for screening relevant documents. Source: Adapted from Moher et al. (2009) [20].
Figure 3. The framework applied for screening relevant documents. Source: Adapted from Moher et al. (2009) [20].
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Figure 4. The categorization of journal articles according to the content.
Figure 4. The categorization of journal articles according to the content.
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Figure 5. The number of publications per year of the 60 articles.
Figure 5. The number of publications per year of the 60 articles.
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Figure 6. Geographical distribution of research conducted concerning the specific airports and regions.
Figure 6. Geographical distribution of research conducted concerning the specific airports and regions.
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Figure 7. Methods used to estimate aircraft emissions within the reviewed papers.
Figure 7. Methods used to estimate aircraft emissions within the reviewed papers.
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Table
Table 1. The search term combinations.
Table 1. The search term combinations.
CombinationSearch TermsScopusWeb of ScienceProQuestTotal
1(Aviation OR aircraft) AND (Emission* OR GHGs) AND (“air quality” OR “LTO cycle”)4286542941376
2(“Aircraft emission*” OR “Emission* from aircraft” OR “emission* of aircraft”) AND (“air Quality”)10810161270
Note: The truncation symbol (*) was added to guide the database search for all possible word forms.
Table
Table 2. The exclusion criteria used in the PRISMA framework.
Table 2. The exclusion criteria used in the PRISMA framework.
Reason NumberDescription
1Papers that address soot, black carbon, particle matters (PM), and volatile organic compounds (VOCs)
2Papers that address the CO2 or emission from aircraft (above the LTO cycle)
3Papers that address the aircraft emission due to technological advances
4Papers that address the sustainable aviation
5Papers that address public opinion concerning aircraft emission
6Papers that address the health impact of aircraft emission
7Papers do not focus directly on the topic of review
8Papers that do not address the emission calculation methodology
9Papers with literature review
Table
Table 3. Categorization of emission calculation methods according to IPCC Tier.
Table 3. Categorization of emission calculation methods according to IPCC Tier.
Variables Used for Emission Calculations
LTO CycleEmission Factor (EF)DurationFuel Flow (FF)No of Engines per Aircraft TypeEmission Rate per LTO (Mode Specific)Pollutant LoadSoftware in Modeling Emissions Inventory
TierMethodsNo. of LTO No. of LTO per Engine TypeEF per LTOEF per Engine TypeEF per Engine Type (Mode Specific)Time = Distance/SpeedTime per Grid CellTIM per Engine TypeFuel UseFF per Engine TypeFuel Use per LTOFF per Engine Type (Mode Specific)
1Simple estimation approach of IPCC✓ ✓
2ICAO simple approach (option B) ✓ ✓ ✓ ✓ ✓
Kalidova and Kudrna method ✓ ✓ ✓ ✓
Medium approach of ADMS-airport User Guide ✓ ✓ ✓ ✓✓
3AICAO advanced approach ✓ ✓ ✓✓
Emission Inventory Guidebook of European Environment Agency ✓ ✓ ✓
New methodology (Ref [27]) ✓ ✓ ✓
New methodology (Ref [28]) ✓✓ ✓✓✓
New methodology (Ref [29]) ✓ ✓✓ ✓ ✓
3BAEDT ✓
EDMS ✓
APMI ✓
AEIC ✓
IESTA ✓
LASPORT version 1.5 ✓
Table
Table 4. The reviewed papers distributed among the tier method and the continent where research was conducted.
Table 4. The reviewed papers distributed among the tier method and the continent where research was conducted.
ContinentTier
123A3B
Asia14121
Europe0284
North America00316
Australia 0010
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Dissanayaka, M.; Ryley, T.; Spasojevic, B.; Caldera, S. Evaluating Methods That Calculate Aircraft Emission Impacts on Air Quality: A Systematic Literature Review. Sustainability 2023, 15, 9741. https://doi.org/10.3390/su15129741

AMA Style

Dissanayaka M, Ryley T, Spasojevic B, Caldera S. Evaluating Methods That Calculate Aircraft Emission Impacts on Air Quality: A Systematic Literature Review. Sustainability. 2023; 15(12):9741. https://doi.org/10.3390/su15129741

Chicago/Turabian Style

Dissanayaka, Manori, Tim Ryley, Bojana Spasojevic, and Savindi Caldera. 2023. "Evaluating Methods That Calculate Aircraft Emission Impacts on Air Quality: A Systematic Literature Review" Sustainability 15, no. 12: 9741. https://doi.org/10.3390/su15129741

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