Abstract
The increasing interest in environmentally sustainable aviation has led to the topic becoming popular in aviation management literature. However, to the best of our knowledge, no research analyzes aviation environmental management (AEM) literature in a comprehensive manner. This study aims to bridge this gap by conducting a retrospective examination of environmental sustainability studies in literature using the bibliometric analysis method. Identifying potentially important gaps and drawing a comprehensive picture of the dynamics and the state of the literature is an important task to drive future studies in the field. Results drawn from 511 publications indexed in the Web of Science (WoS) database indicate a recent and rapid growth in the literature. Greenhouse gas emissions and noise emissions are dominant research themes while waste and water management topics are not well established. Studies investigating alternative fuels, emission mitigation strategies, energy conservation, and noise abatement are prevalent in the literature.
Keywords
One of today’s prominent global concerns is the environmental impact of industries, such as the effect of climate change, and air and noise pollution. Although technological and industrial advancements have undoubtedly improved human lives and wellbeing, they have also played a role in exacerbating contemporary environmental challenges ( 1 ). One such advancement is air transportation, a pivotal innovation that is widely used throughout the world, providing a fast and efficient way of moving people and goods across long distances. According to data from ATAG (Air Transport Action Group), before the COVID-19 pandemic, 4.5 billion passengers traveled by air in a calendar year with over 45 million scheduled commercial flights, employing more than 80 million people directly and indirectly ( 2 ). However, the environmental impact of the industry is evident. According to data published by the IPCC (Intergovernmental Panel on Climate Change), the transportation sector is responsible for around 25% of the world’s greenhouse gas emissions, with the aviation sector contributing 13% of those emissions ( 3 , 4 ).
Although the aviation sector has come out of past crises stronger, debates on the sustainability of the sector’s growth have become increasingly common in recent years ( 5 ), which seems to be because this crisis, which is an environmental challenge, is different and more severe than others. As the effects of climate change become more visible each year, various recommendations and targets from international aviation organizations directing the future of the industry have caused this issue to become increasingly important and popular for all stakeholders in the sector and the scientific community ( 6 ). To the best of the authors’ knowledge, despite the increasing number of studies, the literature on aviation environmental management (AEM) is still in its developmental stage, with a limited understanding of how the body of knowledge has been established and how it can be advanced. Therefore, an in-depth review of the literature is needed to reveal the structure of the research domain and to identify research themes that have emerged.
Among the limited number of review studies in the context of the environmental sustainability of air transport, Elhmoud and Kutty ( 7 ) reviewed sustainability methods and tools, Gratton et al. ( 8 ) and Ryley et al. ( 9 ) reviewed the impacts of climate change on air transportation, Greer et al. ( 10 ) reviewed the literature on environmental sustainability metrics for airports. Calisir et al. ( 11 ) reviewed the environmental impacts of aviation using life cycle analysis. However, such review studies analyze relatively few publications and lack a quantitative methodology which could mitigate potential biases. Moreover, we found no study that quantitatively examines the literature on the environmental sustainability of air transport management. Among the existing literature, we believe that there is a need to map out published studies in a systematic order to capture current and past trends and potential gaps for future studies and that this study is significant and original in this sense. In this context, this study aims to investigate the air transport management literature on environmental sustainability with the bibliometric analysis method. Accordingly, after refinement and data cleaning processes, 511 publications indexed in the Web of Science (WoS) database encompassing the period of 1980 to 2022 were analyzed via the R-based Bibliometrix software. First, we applied performance analysis to present a descriptive picture of the literature by examining the authors, institutions, and countries as research units. Subsequently, a science mapping analysis was employed to demonstrate the relationship network between research units and the general trends in the research area. Finally, salient research themes, application areas (airlines, airports, etc.), and the most used methods were also explored to support the performance analysis and the science mapping network analysis. By doing so, the most contributive and impactful research units, the relationship between the top research units, the emerging themes, methods, and so forth, were made apparent.
Literature Review
Through the technical lens of environmental sustainability in aviation, the literature focuses on subjects such as the evaluation of sustainable aviation fuels ( 12 , 13 ), greenhouse gas (GHG) emission calculations ( 14 ), comparisons and reporting of sustainability performances across the industry ( 15 – 19 ), evaluation of the emission trading system ( 20 ), assessments of green air traffic management actions and operational interventions to reduce emissions ( 21 – 23 ), green fleet management ( 1 ), noise abatement, mapping, modeling ( 24 – 27 ), renewable energy assessment ( 28 ), and energy consumption in airports ( 29 , 30 ).
The managerial aspects of aviation environmental sustainability are mainly discussed in the context of air traffic management (ATM) operational measures, green fleet planning and management, operational inefficiencies, green airport practices, emission trading scheme (ETS or EU-ETS) assessments, energy, and waste and water management. The IPCC detected a 6% inefficiency in aircraft operations ( 1 ). Since 2005, IATA’s (International Air Transport Association) Green Teams have been working with airlines to reduce this inefficiency. In recent years, both IATA and ICAO (International Civil Aviation Organization) have been collaborating on the carbon emission reduction agreement known as CORSIA (Carbon Offsetting and Reduction Scheme for International Aviation), which incorporates operational and technological measures as well as the utilization of alternative fuels. For operational measures, Myhre and Stordal ( 31 ) suggested that shifting heavy traffic periods toward sunrise and sunset would reduce the condensation trail effect behind the aircraft. Williams et al. ( 32 ) on the other hand, determined that lowering the altitude of flight levels would reduce the condensation trace but this would increase CO2 emissions by 4%, which they stated was a form of tradeoff. Krstić and Babić ( 33 ) stated that different ATM strategies and tactical measures (airport airside infrastructure development and applied air traffic control tactics) will significantly reduce traffic complexity and increase time and environmental efficiency at the airport. From the airline perspective, Lee et al. ( 1 ) compared different green fleet management programs by multicriteria decision methods. The study found the emission trading program as the main factor in achieving green fleet goals. The study by Wu et al. ( 34 ) investigated the willingness of 615 airline passengers to switch to eco-friendly services offered by China Airlines. The research identified the “green perceived value” as the primary factor in green experiential satisfaction. The analysis also revealed the significance of physical environmental quality and the airline’s green corporate image.
Other studies focused on specific aspects of the environmental impacts and practices of airports. Kılkış and Kılkış ( 35 ) created and employed a sustainability ranking index for airports that consists of five dimensions and 25 indicators. The index was implemented on a group of nine of the best and busiest airports in the world, taking into consideration passenger satisfaction and traffic data. Amsterdam Schiphol was found to be the best-performing airport in the sample. Monsalud et al. ( 6 ) presented effective sustainable practices at airports using the impact matrix. They evaluated lighting and ground vehicles at the airport as GHG mitigation areas. They found that light-emitting diodes (LEDs) and vehicles using alternative fuels would reduce the carbon footprint. While airports’ operationality requires energy and water, the natural outputs of the operations emerge as emissions, noise, solid waste, and wastewater. Dos Santos et al. ( 36 ) developed a waste management index to support and evaluate airport waste management. The index measured the process in the recycling and disposal of waste specified at Congonhas Airport, which revealed that the airport is in a suitable condition with regard to collection, transportation, and temporary storage, but the location of waste at the airport needs to be improved. Sarbassov et al. ( 37 ) conducted a compositional analysis of the municipal solid waste generated at Astana International Airport and assessed various waste management approaches in relation to GHG emissions. The comparative analysis revealed that the incineration of airport waste provides better environmental output but is costly. As well as waste management, water management is also important for improving the environmental success of an airport. Using an exploratory research design, Baxter et al. ( 38 ) examined the sustainable water management strategies and systems at Kansai International Airport from 2002 to 2016. According to their findings, by reclaiming water for non-potable water uses and processing onsite wastewater, the airport was able to reduce total water consumption as well as water consumption per passenger and movement despite the increase in traffic. As one of the important obstacles to expansion of ATM, noise stands as another environmental dimension that needs to be analyzed. Rodríguez-Díaz et al. ( 39 ) indicated the necessity of improving noise modeling, simulation, and monitoring evaluation tools. According to the study, to achieve a comprehensive noise management strategy, it is important to apply ICAO’s “Balanced Approach” which involves minimizing noise at source, implementing land-use planning and management, noise abatement through operational procedures, and noise-based operating restrictions. Heyes et al. ( 40 ) highlighted the importance of the role of communication and engagement in airport noise management and proposed a European policy that explicitly advocates for these as a noise management tool.
The economic performance that IATA deems necessary for sustainability creates another approach to reducing the environmental impact of air transport. In this context, ETS is a framework to cut emissions. In this system, each enterprise can choose the lowest cost option to meet its emission quota, thereby reducing its production, increasing energy efficiency, or receiving extra allowances from other organizations that emit less emissions or quotas ( 41 ). Thus, the buyer has to pay to emit more, while the seller is paid for reducing their emissions. The ecological impact of the ETS system assumes that higher costs in aviation will reduce the demand for air transport and result in less air traffic density, and thus less emissions. Vespermann and Wald ( 42 ) measured both the economic and ecological impacts of the inclusion of the air transport industry in the ETS within the European Union. The research showed that the current system design will not cause a significant reduction in emissions from air transport and proposed a more restrictive system design.
In addition to our study, there is are relatively few papers reviewing the literature on the environmental sustainability of air transport. Sebastian and Louis ( 43 ) reviewed airport waste management trends and practices conducted. Noting that there are limited studies of waste management, they indicated that even though numerous major airports have successfully converted to become zero-waste airports, despite an increase in the number of passengers, some airports are still disposing of 75% of their waste in landfills. Waste-to-energy management can become an effective strategy and the authors identified five challenges related to sustainable waste management: the stakeholder role, segregation inefficiency and contamination, circular economy challenges, the influence of regional policy, and the effect of COVID-19. Elhmoud and Kutty ( 7 ) reviewed the tools and methods used for sustainability assessment in the aviation industry, from the socioeconomic and environmental sustainability aspects. For environmental impacts, they addressed life cycle analysis (LCA) as a framework that has become widely recognized by regulators and businesses as the most effective method to quantitatively evaluate the industry’s environmental position. Greer et al. ( 10 ) synthesized the current state of environmental sustainability metrics and methods, especially for airports. They proposed six important practices that airports can apply in the short term with minimal disruption, namely local or onsite renewable electricity, the electrification of vehicle fleets, gates, and ground service equipment, water conservation applications, installation of energy-efficient building components, and the selection of durable interior building components. Calisir et al. ( 11 ) reviewed the environmental impacts of aircraft, related processes, their operations, and unmanned aerial vehicles based on the LCA approach. Their study concluded that studies investigating the negative environmental impacts of aviation using the LCA are limited. While data collection and verification are among salient issues in the literature, LCA approaches have the potential to put forward the harmful effects in all aspects of the aviation industry, potentially guiding aviation managers ( 11 ). On the other hand, unlike the common approach in the literature, Ryley et al. ( 9 ) reviewed the effects of climate change on the aviation industry and the need for adaptation. Their study included 46 papers selected according to variables such as methodology, paper outcomes, and industry stakeholders. According to their findings, many of the industry stakeholders represented within the climate adaptation literature were larger airports in developed regions that had limited funding options and had adopted a short-term approach in their adaptation planning process. In a similar vein, Gratton et al. ( 8 ) addressed how climate change has impacts on aviation such as increase in the take-off distances where there is adequate runway length, an increase in bird strike risks, and increase in en-route flight times because of wind and temperature effects, and so forth, all of which require managerial adaptation.
Research Methodology
Bibliometric analysis was applied in this study as it enables the collection of additional data statistics of relevant literature including authors, affiliations, abstracts, and keywords ( 44 ), thus allowing visualization of results ( 45 ). The other traditional research methods for the analysis of the literature are meta-analysis and systematic literature reviews. While meta-analysis aims to extract a broad body of knowledge from quantitative studies, it requires a researcher to select studies to be analyzed, causing a limitation in the type and breadth of studies to be examined ( 46 ). A systematic literature review, on the other hand, allows a wide range of studies that can handle a broad diversity of publications and methodologies, ensuring a thorough literature analysis that helps the understanding of contextual issues. This approach, however, takes relatively more time, resulting in few analyzed studies and the exposure to researcher biases, creating a possibility that some important publications may be missing ( 47 ). Accordingly, the bibliometric analysis method was preferred because it is easy to use and reliable for handling many papers at the same time when the dataset is too large to allow manual review. Another reason for employing this approach is that bibliometric analysis has a strong visualization ability that helps to identify a group of research interests, emerging trends, and the state of the intellectual nature in the field ( 47 , 48 ). Additionally, it is a suitable method when the review scope is broad. To support a robust bibliometric analysis, this paper analyzes the literature focused on aviation management and environmental sustainability, including similar terms across the WoS. The WoS database was chosen because it has a high quality index coverage compared with other databases ( 49 ) and is the most widely accepted and frequently used database ( 50 , 51 ).
Various software packages such as R-based Bibliometrix, VOSviewer, HistCite, CiteSpace, and BibExcel have been used for bibliometric analysis. Each has different features and limitations ( 44 , 52 , 53 ). We preferred the R-based Bibliometrix software because it is functional in displaying large bibliometric maps with ease of use through a web browser. It is a widely used software developed to highlight research units from the scientific production and citation perspective and for the visualization graphs that cover co-citation, co-author, and co-occurrence analysis ( 54 ).
The first and an important step when carrying out queries in databases is the keyword selection that will allow all papers relevant to the research objective to be captured ( 45 ). We benefited from Bartolini et al.’s ( 55 ) study that deals with environmental sustainability in the area of warehousing along with Aldemir and Sengur’s ( 56 ) study that reviews postgraduate theses in air transportation. We then expanded the keywords listed in these studies with new keywords to access all relevant documents. These keywords were divided into two groups as shown in Table 1.
Search Strings and Keywords
To increase the coverage, the query was run for all document types for the defined search term without a date limitation on August 13, 2022. The query was executed on the titles, abstracts, and keywords. Documents from different research domains such as engineering and health sciences were excluded from the review using the research area filter in the WoS. All the inclusion and exclusion criteria can be seen in Table 2. After all the applicable search criteria filters were applied, the initial result gave us 1,521 documents. However, only the documents that focused specifically on environmental sustainability in air transport with the managemental aspect were considered relevant. Documents that just mentioned topics related to the same subject in different areas or documents dealing with the same topic but from a technical or engineering perspective were excluded from the review in the data cleaning phase which is important in bibliometric analyses to ensure the validity of the results ( 47 , 49 ). Along with the results that did not meet the search criteria, we cleaned erroneous entries and duplicates after carefully reading the titles and abstracts. A crosscheck was also made by us to make sure all relevant documents were included in the review. After cleaning the irrelevant documents, we obtained a total of 511 documents ready for analysis, published over four decades (1980–2022) from 184 different sources. The bibliometric analysis flow diagram adopted in this study is depicted in Figure 1.
Refinement Through Inclusion and Exclusion Criteria
Bibliometric analysis flow diagram.
Bibliometric analysis is generally divided into two different phases: performance analysis and science mapping ( 47 , 57 ). Performance analysis gives descriptive information with regard to the contributions of a research component such as individuals, organizations, and countries ( 58 ). Productivity and the impact of the research unit are obtained under the performance analysis phase. Productivity can be explained by the total or average number of publications, while the impact is calculated by citations per year or the h-index. Hirsh’s h-index is a citation-based impact and productivity index for researchers defined as the h number of publications of a researcher where each paper has been cited h times or more ( 59 ). On the other hand, science mapping techniques include analysis such as co-citation, co-authorship, and co-word. Since there is no generic acceptance as which bibliometric analysis tools are required ( 60 ), we used various frequently used metrics that are well established in the literature ( 61 – 63 ). Co-citation occurs when a document cites two separate documents at the same time. Co-authorship deals with the connection structure between research units, namely authors, authors’ organizations, and countries. Co-occurrence analyzes the linkages between the most frequently used keywords ( 64 , 65 ).
We used the Louvain community detection algorithm among the other clustering algorithms to perform science mapping analyses because of its minimal computation time in large networks ( 66 ). It is a repetitive optimization model that aims to maximize the modularity index through the optimum number of partitions ( 65 ). The method favors intensively interconnected clusters while neglecting edges that connect clusters.
Research Results
Performance Analysis
Our bibliometric analysis began by analyzing the performance-based data of the documents, authors, institutions, countries, journals, and citations.
According to the descriptive statistics presented in Table 3, the oldest documents in our search dated back to 1980, which is anticipated, as environmental impact debates in aviation dated back to the 1980s when ICAO organized the Committee on Aviation Environmental Protection (CAEP) to formulate new policies on the environmental impact of aviation. The average citation of each document was 13.68. There were 1,337 unique authors contributing to 511 documents from 184 sources. Roughly, every three authors contributed to each document. Out of 511 documents, 421 of them were multi-authored. Collaboration among authors was calculated by dividing the total number of authors by multi-authored documents (i.e., 1,337/421), indicating that collaboration among authors is high. As expected, nearly 70% of the documents were research articles while nearly 20% of them were papers from conference proceedings.
Descriptive Statistics of the Data
The publication trend of the AEM literature between 1980 and 2021 is shown in Figure 2. The data for 2022 were not included since they were partial data. From the depiction in Figure 2, it was clearly seen that the research area has been on a growing trend especially after 2010. While there were ups and downs in the citation graph, its trend was also on the rise. Accordingly, the annual growth rate was identified as 5.76%. The most productive year for publications was 2021 (n = 54), and 2017 for citations (n = 807). Nevertheless, scientific production from 1980 to the mid 1990s remained limited. Moreover, the citation figure was substantially increased between 2012 and 2016, then decreased to somewhat the same levels after 2017. For the average citation per document (total citations/total documents), depicted in Figure 3, there were some noticeable peaks in 1997, 2001, and 2006; this was the effect of certain predominant papers rather than a collective impact as there were only a total of five documents published in those years. Average citation per year, however, showed an increase throughout the years.
Number of publications and citations per year.
Average citations per document per year.
Portraying the most productive authors is an important element of performance analysis as the scientific production of authors is major indicator of the scientific development of a research area. Among the authors listed in Table 4, Cui, Li, and Asensio are the top three scientific contributors to the AEM literature, with eleven, nine, and seven studies, respectively. Han ranks first for citation per document, with Cui and Kılkış following, indicating that their influence per document is higher than other authors. We also provided the top 10 contributing authors based on their total number of citations. According to Table 5, Cui and Li are the first and second most contributing authors, while Tao is the third most contributing author. It is seen that the rest of the authors are listed here based on a single paper with high impact.
Top Contributing Authors Based on the Total Number of Studies.
Top Contributing Authors Based on Total Citations
In a similar manner, we examine the most contributing organizations, countries, and journals. Table 6 provides all three units that rank in the top 10. Massachusetts Institute of Technology (MIT), Universidad Politecnica de Madrid, and Delft University of Technology are prominent organizations with 14, 14, and 12 studies respectively. MIT tops again in total citations, followed by University of Cambridge (n = 242) and Vrije Universiteit Amsterdam (n = 240). In country-specific performance, the USA, China, and the UK are listed in the top three. While the USA (n = 134) tops the list for total studies, the UK is more impactful with a total of 1,133 citations from 77 studies. As for the journals, the Journal of Air Transport Management (JATM) with 77 studies, dominantly produces more studies than others. Following JATM, Applied Acoustics and Renewable & Sustainable Energy Reviews (RSER) contribute to the research field with 37 and 25 studies respectively. Studies published in these three journals constitute roughly 27% of the total number of studies examined. From the scientific impact perspective, while JATM receives the most citations (n = 1,516), RSER ranks second with 1,153 total citations from only 25 studies, followed by Transport Policy with 516 total citations from 22 studies. Additionally, Transportation Research Part A-Policy and Practice (JTRA) is another impactful journal with a total of 461 citations from just 12 studies. The average impact factor of the journals in the top 10 shows that the literature on environmental management in aviation is composed of journals of high influence (mean = 5.762).
Top Contributing Organizations, Countries, and Journals
Note: TS = total studies; TC = total citations; IF = impact factor.
Another facet of the AEM literature is the most cited studies, shown in Table 7. All documents in the top 10 most cited studies are research articles. The most cited study is Wang and Tao’s ( 67 ) “Bio-Jet Fuel Conversion Technologies” with 217 citations. It also tops the list for average citations per year (n = 31), which makes it the most influential study among 511 studies. Hari et al.’s ( 13 ) “Aviation Biofuel from Renewable Resources: Routes, Opportunities and Challenges” is ranked second in influence, receiving 176 citations since 2015. Moore et al. ( 68 ) is cited 144 times with “Biofuel Blending Reduces Particle Emissions from Aircraft Engines at Cruise Conditions,” placing it third in total citations. It is evident that six out of ten studies focus on alternative/renewable jet fuel topics in the sense of proposing ways to mitigate carbon emissions and the climate change effect of aviation. Moreover, the arithmetic mean of the average citation per year of the top 10 documents is 18.95 which demonstrates that the top studies have a great impact to shape the research area. Six studies in the top 10 are cited more than 100 times. While the publication date of the most cited studies ranges between 2010 and 2019, their average age is 6.5 years, indicating that the recent studies come into prominence in a really short period of time in the AEM literature.
Most Cited Documents
The authors’ keywords can be depicted by a word cloud to show the top research concepts in the field. We prepared the raw data to be ready for the analysis via text normalization techniques, namely stop word removal, lowercase conversion, stemming, and tokenization ( 76 ). Stop word removal is another useful text normalization technique that removes the common words that do not contribute to the content of the document such as conjunctions and prepositions ( 77 ). Lowercase conversion is applied to classify uppercase and lowercase words in the same pocket. Stemming aims to obtain root forms of derived words by stripping the suffixes. Tokenization is resolving a series of text into small analysis units such as words, symbols, phrases, or other elements which are named tokens. After the text normalization process, the keyword cloud was obtained utilizing the keyword frequencies. As a result, the most used keywords are airport (48 times), followed by aviation (37 times), aircraft noise (36 times), climate change (25 times), and sustainability (20 times), all of which are depicted in Figure 4.
Word cloud.
Another important indicator showing the evolution of research trends is the thematic map analysis depicted in Figure 5. This is a strategic diagram that reveals the evolution of research clusters based on a keyword co-occurrence analysis ( 78 ). While the x-axis shows the relevance degree (centrality), the y-axis indicates the development degree (density). The greater the intensity of the links that bond clusters, the more central are the clusters ( 78 ). This basically indicates the importance of the theme. On the other hand, the strength of links between keywords in a cluster denotes density which also shows the capacity of a cluster to develop ( 79 ). We use authors’ keywords as a basis for the thematic map analysis. The upper left quadrant addresses the niche themes that are of minor importance. Major themes are portrayed in the upper right quadrant. They represent motor research themes that feed the main structure of the research area. While the themes in the lower left quadrant are either emerging or disappearing, the lower right section indicates the fundamentals of the field. Accordingly, energy, airport, and CO2 emission emerge as motor themes, whereas aircraft noise, environment, environmental impact, and aviation are fundamental themes in the examined literature. On the other hand, optimization, constructed wetlands, and aircraft noise synthesis are niche themes that are specifically studied. Here, we can emphasize that aircraft noise is a broad concept which found ample ground in the literature. Noise synthesis can be grouped under the aircraft noise, however, it was found important enough to be among the niche themes as it appeared in the thematic map. Biofuel, electric airplane, and sustainable development are grouped in the emerging or declining themes. Since R’s Bibliometrix software does not make a distinction between emerging and declining themes, these themes may be emerging or disappearing in the research field. However, it gives an analysis of trending topics. Based on the trending topic analysis in Figure 6, we believe that biofuel is emerging while sustainable development is declining as there has been no study since 2016 on sustainable development.
Thematic map.
Trending topic.
In the last step of the performance analysis, we executed a trending topic analysis to cyclically demonstrate emerging research topics in the literature. A keyword that is repeated at least five times in a year is considered trending in the analysis. Since authors’ keywords produce more inclusive keywords than KeyWords Plus in representing the contents of the publications ( 80 ), authors’ keywords are used in the trending topic analysis as well as in the thematic map and the word cloud analysis. According to Clarivate, the data in KeyWords Plus are words or phrases that frequently appear in the titles of an article’s references, but do not appear in the title of the article itself. Based on a special algorithm that is unique to Clarivate databases, KeyWords Plus enhances the power of cited-reference searching by searching across disciplines for all the articles that have cited references in common. Figure 6 depicts the evolution of emerging topics throughout the years starting from 2008. As a result, aircraft noise and annoyance are the first emerging topics that appeared in the literature with the frequency of aircraft noise being materially high. Annoyance, on the other hand, appears from 2008 to 2019 despite its low frequency. Emission trading appears just before 2012 and afterward as it came into effect in 2012 in the aviation sector. GHG emission, airport noise, and energy efficiency are prominent topics in the mid 2010s. In recent years, renewable energy, energy consumption, willingness to pay, and generic topics such as noise pollution and aviation emissions are popular.
Science Mapping Analysis
To build a relationship between research units, a science mapping analysis is performed. It includes co-citation network analysis for documents, co-occurrence analysis for keywords, and co-authorship analysis for authors, organizations, and countries. The colors in the figures imply different clusters; the size of the node represents the frequency; and the distance corresponds to the relatedness ( 48 , 81 ). Isolated nodes are ignored for all science mapping analyses. The number of nodes is usually set to a threshold of 50 (or more in some cases) based on the clearness and intelligibility of the presented results.
Co-citation analyses are based on the anticipation of a shared theme between co-cited studies. Two different studies are co-cited when they are cited by at least one study ( 82 ). Using the 25 most cited studies as nodes, four research clusters are revealed, calculated with the Louvain algorithm (Figure 7). Co-citation network analysis creates four clusters. The first cluster consists of documents of researchers such as Anger, Vespermann, and Scheelhase. The common topic undertaken is EU-ETS in those studies ( 20 , 42 , 74 , 83 ). Some of the researchers in the second cluster are Lee, Miyoshi, Morrell, and Givoni, with topics such as carbon emission measurement ( 19 ), carbon emission reduction potential ( 84 ), climate change impacts ( 85 ), and environmental implications of aircraft sizes ( 86 ). The third cluster includes streams such as carbon footprint mitigation ( 70 ), examination of potential carbon emission reductions ( 87 ), and environmental limits of airport operations ( 88 ). Hagmann, Gössling, and Kılkış are some of the researchers appearing in the fourth cluster with research streams on the green image of airlines ( 89 ), voluntary carbon offsetting ( 90 ), and benchmarking of airports’ sustainability ( 35 ). These references and authors are well known in the relevant literature with high total citations, aiming to analyze the most critical streams of the environmental issues in the aviation industry. Thus, we can argue that co-cited references are feeding the AEM literature with rich research themes and reliable research outputs.
Co-citation network analysis.
A co-occurrence analysis is carried out to enlighten the potential trends and intellectual structure of the AEM literature as shown in Figure 8. The top 50 keywords with the most frequency are analyzed via the Louvain algorithm. Four different clusters are revealed as a result. The main cluster, colored blue, consists of major issues along with generic terms such as aviation, air transport, CO2 emission, and sustainability. The second cluster, colored green, generally includes noise-related keywords: aircraft noise, airport noise, noise annoyance, and modeling. The third cluster, colored red, contains energy-related keywords along with the centered keyword: airport. The fourth cluster is comprised of emission trading, environment, air transport policy, and aircraft emission.
Keyword co-occurrence network map.
Finally, collaboration networks that emerged between research units are analyzed based on the author, organization, and country facets. Figure 9 delineates the status of the author collaboration in the examined literature. Twelve research groups appear with two main collaboration groups, colored purple and green. One is Asensio, Ruiz, Recuero, Pavon, and Pagan, who are connected with Gagliardi and Licitra through Asensio. Asensio also appears as the most collaborative author in the investigated literature. The other main cluster consists of eight researchers; Benito, Alonso, Lonza, Staples, Barrett, Malina, Waitz, and Winchester. Moreover, each of the remaining collaboration groups includes two researchers, except that of Wild, Baxter, and Srisaeng.
Author collaboration map.
Figure 10 portrays the collaboration network of authors’ organizations. Seven collaboration clusters exist between contributing organizations. Delft University of Technology and Southeast University are prominent collaborative organizations. The strongest collaboration appears between Southeast University and Nanjing University of Finance and Economics (blue shaded), as shown by the thickness of the edges. In general terms, collaboration groups of two to four indicate the existence of micro-level collaborations between organizations.
Authors’ organizational collaboration.
The collaboration network between the authors’ countries is illustrated in Figure 11. To obtain a clearer and essential result, the minimum number of edges between nodes is adjusted to two. After the adjustment, five clusters of countries surface for their collaboration. The USA, UK, and China are the top three collaborative countries. The first evident cluster includes the UK, China, Australia, Thailand, Norway, and Pakistan. Furthermore, the USA, South Korea, Malaysia, Canada, Japan, and India create another significant cluster, colored red. High degrees of collaboration between UK and China, USA and South Korea, Italy and Spain, Malaysia and India, and Australia and Thailand, are also worth mentioning.
Country collaboration.
Classification of Literature
We classify the AEM literature according to the theme, the method, and the application area apart from the performance analysis and science mapping. We manually checked all the records to confirm whether they can be grouped under certain clusters. Note that a document may be included in more than one cluster group, therefore the numbers indicate the total frequency of certain themes. Common themes are specified as GHG emission, energy, noise, waste/water, and biodiversity. Studies examining alternative jet fuels, electric aircraft, carbon reduction or offsetting policies, technological and operational efficiency measures for GHG emissions, and all kinds of pollutant gas emission performance evaluations are handled under the GHG emission theme. The energy theme includes documents focusing on renewable energy sources, energy consumption, energy management, and so forth. The noise theme consists of studies analyzing noise levels of airports, noise around the vicinity of airports, aircraft noise in landing and take-off phases, noise mapping, noise modeling, and so forth. The waste/water theme involves waste and water management strategies and tools, water-saving implications, waste disposal techniques, and so forth. Furthermore, airlines, airports, and air traffic appear as application area themes. In the case that a study encapsulates more than one dimension under the same cluster, it is counted for each relevant dimension. Namely, if a study discusses the research problem within the aviation system as a whole, it is added to the frequency of airlines, airports, and air traffic separately.
Figure 12 portrays the most common research themes across the AEM literature. GHG emission stands as the major research theme with the highest frequency (n = 257), followed by noise (n = 174), and energy (n = 135). Figure 13 shows the most used methods and application areas. Econometric/economic, optimization, analytical, and prediction models (EOAP) are grouped under the same method dimension which is the top method in the examined literature, with 88 documents employing at least one of the abovementioned models. The other methods worthy of mention are review and multicriteria decision making (MCDM). There are 55 documents using review method and 46 documents using at least one of the MCDM techniques. Finally, documents are divided into three main application areas based on their focus sector. The airline area tops the list with the highest frequency (n = 276). All aircraft-related documents are handled in the airline category as aircraft are seen as airline assets. Airport area is another significant application area with a frequency of 182, followed by the air traffic area with a frequency of 48.
Distribution of documents by research theme.
Distribution of documents by (a) method and (b) application area.
Discussion
The first study in our review dates back to 1980, when environmental issues in aviation were first beginning to be discussed on an international level through CAEP. This is no surprise as the pivotal environmental debates around environmental governance started in the 1970s, which includes the United Nations Conference on the Human Environment in Stockholm in 1972. In our study, a total of 1,337 unique authors have contributed to the AEM literature with 1,120 of them contributing 389 publications since 2010. Additionally, the top 20% of the total documents by most citations constitute 72% of total citations, meaning that the Pareto phenomenon is almost present in the AEM literature ( 91 ). The average citation rate accrues as 13.68 with a 5.76% annual growth rate. This is an indicator that the literature is growing at a great pace. The reason behind this surge could be attributed to the pressing environmental concerns on aviation from international regulators, governments, scientific groups, and so forth. Another reason could be the implementation of ETS in the air transport sector which began across Europe in 2012. In this regard, the number of studies in the literature is expected to continue growing in the future with the increasing attention being paid to sustainable air transport operations.
Our bibliometric analysis shows that most of the publications in the AEM literature are sourced from JATM, as are the studies by Bakır et al. ( 57 ) on the airport service quality literature and Dixit and Jakhar ( 61 ) on airport capacity management. That being said, JATM is a prominent journal among AEM studies as well as aviation management studies. Along with JATM, RSER is also worth mentioning since it published the two most impactful papers, namely Wang and Tao ( 67 ) and Hari et al. ( 13 ). Furthermore, the most productive journals are quite impactful with an average impact factor of 5.762, which corresponds to around Q1 and Q2 levels in the transport category of WoS.
Similar to the findings of Ryley et al. ( 9 ) within the context of climate change and aviation literature, our study acknowledges that AEM literature is mostly contributed to by authors from developed countries rather than developing countries. Only three out of the 10 countries given in Table 6 of our study are developing countries. Furthermore, the USA, China, and the UK play a dominant role in the AEM literature as they are the top three in country contributions, constituting the biggest country collaboration cluster. They also form the two major clusters out of the five that emerged in the country collaboration in Figure 11. Additionally, Italy, Germany, and the Netherlands are significant collaborative countries in the remaining three clusters. While the authors’ collaborative index is 3.18, only 90 out of 511 documents were published by single authors. This indicates that there is a high collaboration level across the AEM literature. This can also be an indication that the literature is improving with collaborations between researchers as noted by Tahamtan et al. ( 92 ). As for the authors, there are two major collaboration groups while the remaining clusters are smaller, consisting of two or three researchers. Cui is the most productive author, working on energy efficiency and EU-ETS, while Asensio stands as the most collaborative author, working on noise-related studies. In organizations’ productivity, MIT and the Universidad Politecnica de Madrid are the most productive. However, neither appears to be collaborative with other organizations. Additionally, despite Asensio and Recuero being the most collaborative authors (green shaded in Figure 9), their organizations are not among the most collaborative ones. On the other hand, Delft University of Technology and Southeast University are the most collaborative universities. Only four out of 10 of the most productive countries host the most collaborative organizations depicted in Figure 10. This result indicates that there is a partial relation between productivity and collaboration in the AEM literature. In this sense, this result gives evidence that author-level collaborations can sometimes be limited to a local network based on the tendency of cooperating with a fellow researcher or a colleague ( 92 ).
Based on the thematic classification, one of the most salient research outputs of our study is that there are three distinctive research streams throughout the AEM literature: GHG emission, noise, and energy. The most dominant theme in the literature is GHG emission. In a similar manner, the subject of CO2 emissions stands among the most frequent author keywords in the word cloud. This may be because we clustered topics such as alternative fuels, route optimization, GHG emission reduction strategies, and so forth, under the GHG emission theme. In this regard, GHG emission acts as a pioneering topic that will be analyzed in future studies so as to guide all stakeholders in achieving the ambitious emission targets set by international regulators. Being among one of the four quadrants revealed in the co-occurrence analysis, the noise theme is also a prominent theme in our bibliometric analysis while noise mapping techniques are dominant methods within this theme. Noise-related studies mainly examine the assessment of noise impacts ( 93 ), noise abatement ( 25 , 94 ), and noise annoyance ( 95 ). The weight of noise studies would have been much higher if we had included studies investigating the relationship between noise and health. Additionally, it is important to note that noise first became a regulated environmental issue after carbon emissions ( 96 ). In parallel with our research findings, the extant literature argues that GHG and noise emissions are the main causes of aviation’s environmental impact, as GHG emissions are responsible for both air pollution and the climate change impact of aviation ( 97 – 99 ). The energy theme ranks third in frequency and these studies are generally airport related. Specifically, energy consumption ( 30 ), energy performance analysis ( 100 ), and the assessment of renewable energy sources ( 28 ) are among the widespread research aims. However, one of the most important results of our analysis indicates that there is a lack of studies investigating waste and water management-related topics. As noted by Sebastian and Louis ( 43 ), such studies are still immature. The same finding is present in Greer et al.’s ( 10 ) work with regard to airports. While waste and water management studies have mostly been deployed for airports, we emphasize that this topic needs more attention in further studies as waste and water themes are significant constituents of environmental sustainability in the air transport industry.
The word cloud results in Figure 4 justify the findings from the thematic classification (Figure 12) we conducted. Apart from the keywords “airport” and “aviation,” which are generic keywords in the field, aircraft noise is the most frequently appearing keyword, followed by climate change, sustainability, and CO2 emission. The literature has already proved that these are all well-structured conceptual components of environmental sustainability studies in aviation. CO2 emission evaluations seem to be at the forefront among the GHG emission evaluations in the literature. This can be attributed to the most harmful impact coming from CO2 rather than other harmful gases as its lifetime is considerably longer ( 101 ), which is also a factor for why ICAO considers it a principal GHG. Therefore, it is no surprise that CO2 is more widely adopted by scholars. Similarly, in the literature, the calculation of CO2 has attracted more attention than the calculation of other pollutants such as CO, NOx, and PM2.5 ( 102 ). The significance of other air pollutants has not received much attention in the reviewed literature, as was also indicated by Van Fan et al. ( 3 ).
While aircraft noise synthesis, constructed wetlands, and optimization are niche themes, bio-jet fuel and electric airplanes are grouped under emerging or declining themes. By taking a closer look at the trending topic analysis, we see that renewable energy is the hottest topic, and bio-jet fuel is present between 2015 and 2020. Thus, bio-jet fuel and electric airplanes can be considered emerging rather than declining themes. In this regard, it is also noteworthy that our findings support the observation that aviation biofuels research globally is arousing significant interest from the public and private sectors with increasing sources of funds, as noted by Anderson et al. ( 103 ). Additionally, the majority of the top 10 most impactful documents in Table 6 are studies on sustainable aviation fuel. On the other hand, noise annoyance and pollution have maintained their status as trending topics over a relatively extended period. Alongside the emergence of COVID-19, the willingness to pay and energy-related keywords have gained prominence in the literature in recent years. Unsurprisingly, ETS appears as a trending topic around 2012 when it came into effect in the airline industry.
Based on the results of the co-occurrence analysis, climate, CO2 emission, and sustainable aviation fuel keywords are closely related, while airport, noise, and energy concepts emerge together in parallel with our findings from the thematic classification. Additionally, noise-based studies emerge as a distinct cluster including noise pollution, noise annoyance, and noise modeling concepts. This result shows that noise and carbon emission studies in the AEM literature tend to be separately discussed. This is expected since aircraft noise and emissions impacts have been traditionally addressed independently by ICAO’s CAEP through measures such as noise or engine emissions certification standards ( 96 ). Furthermore, energy-related concepts like renewable energy, energy efficiency, and energy consumption are clustered alongside airport-related keywords, as anticipated from our thematic classification. The fourth cluster emerges with air transport policy, ETS, aircraft emission, and environment keywords. This could be an indicator that policy-based studies including ETS as a featured concept generate another important domain in the AEM literature.
In classification based on application areas, airline-related studies emerge as the most dominant category. This result is different from Ryley et al.’s ( 9 ) findings which cover relatively more studies focusing on airports. This may be because we included studies on alternative/sustainable fuels, or fuel-efficiency studies within GHG emission, which are of major interest to airlines, while Ryley et al.’s ( 9 ) work only included climate change and aviation studies. Moreover, the inclusion of aircraft-related studies within the airline category in this study might contribute to this observed difference. Within the airline-related studies, there is a notable emphasis on topics such as fuel efficiency, assessment of alternative jet fuels, emission measurement, evaluation of green performance, strategies for emission mitigation, impacts of ETS inclusion, eco-labeling, and adaptation to environmental policies ( 104 ). Likewise, airport-based studies are also well established along with airline-based studies. The present analysis demonstrates that airport-related studies address environmental sustainability through sustainable airport infrastructure, environmental impact assessment, noise around airports, eco-friendly design, airport waste, water, and wildlife management, energy efficiency, and clean energy sources near airports. Many of these topics are discussed in airport-based studies ( 43 , 64 , 65 , 105–108). Specific to airports, energy and noise-related studies are clearly attracting more attention from researchers. It is an indication that airports are in a critical position with regard to the community’s exposure to the impacts of aircraft operations.
A further classification was carried out to examine the methods employed within the AEM literature. The most prevalent methods within the literature have been those that involve the establishment of models, which we refer to as EOAP models: economic/econometric, optimization, analytical, and prediction models ( 22 , 109–111). Review studies and studies using MCDM methods are supervening methodologies preferred in the literature. A similar result was also found in Ryley et al.’s ( 9 ) systematic literature review. This could be because quantitative models and methods are good options for researchers as long as the data is attainable while review studies have been important for researchers to present a detailed picture of literature. DEA attracts attention as a pioneering approach among MCDM methods, however, novel decision-making methods can be utilized for further studies as the research area is blooming at a great pace.
Conclusions
In conclusion, this is one of the first studies that has undertaken a comprehensive bibliometric analysis of the AEM literature. The findings of this paper are beneficial for future studies in the field with insights and guidance toward the dynamics and intellectual structure of the literature. We believe that one can find new avenues for future studies by means of the presented results on citation structure, productive and influential works, trending topics, dominant themes and methods, and the relationship network of the AEM literature. This study also contributes to the visualizations of the extant literature in the relationships between the research units such as authors, author organizations, and countries.
In summary, there is a clear tendency to study GHG-related issues, especially with regard to the airline industry. Studies on the themes of noise and energy are also salient among airport-based studies. However, there is room for new research to explore original topics rather than the traditional focus on emission performance analysis, mitigation assessments, and noise mapping. Studies on various aspects of environmental sustainability in the subsidiary sectors of aviation, for example, air cargo and ground handling, show that the other service suppliers are worthy of investigation in further studies. Moreover, while waste, water, and biodiversity topics have received some attention from scholars, there is the potential for further exploration. Despite there being some waste and water-oriented studies in the context of airports, airline practices can be further explored. Furthermore, disposal efficiency, water, and waste reduction practices, cost-benefit analysis of recycling, and field studies might be investigated to improve the understanding of the waste and water-specific literature. In addition, the participation of policymakers and practitioners across the literature might increase the opportunities for rich and authentic research fields to branch into within the AEM literature. With evolving environmental policies such as CORSIA, the attention to the AEM literature is anticipated to grow, further increasing the total scientific production in the near future. In this regard, studies on carbon pricing and taxing, route and maintenance planning, policy adaptation, and environmental awareness could be studied further. Additionally, it is evident that empirical studies are dominant in the extant literature. In this case, qualitative analyses can be further taken advantage of in behavioral studies such as the willingness to pay for “green,” and attitudes and cultures of environmental consciousness.
Finally, this study has some limitations in two aspects. Firstly, we may have bypassed some important documents as we only included documents in the WoS database. Scopus, for example, is another important database that potentially accommodates more documents. However, we preferred to use WoS as we intended to include only the highest quality sources over a wide range of periods. Secondly, we might have accidentally omitted some of the articles when we were manually checking the documents to clean for repeating results. In the future, meta-analyses or systematic literature reviews could improve the existing knowledge revealed by the present study in the AEM literature.
Footnotes
Acknowledgements
The authors would like to thank Mahmut Bakır and Temel Caner Ustaömer for reviewing the paper and providing input.
Author Contributions
The authors confirm contribution to the paper as follows: study conception and design: M. Uzgör, S. Ateş; data collection: M. Uzgör; analysis and interpretation of results: M. Uzgör, S. Ateş, H. Kafalı; draft manuscript preparation: M. Uzgör. All authors reviewed the results and approved the final version of the manuscript.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
