IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i20p8950-d1499749.html
   My bibliography  Save this article

Research on the Carbon Emission Prediction and Reduction Strategies for the Civil Aviation Industry in China: A System Dynamics Approach

Author

Listed:
  • Wei Chen

    (College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China)

  • Yi Ai

    (College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China)

Abstract

With the continuous growth in the volume of global air transportation, the carbon emissions of the civil aviation industry have received increasing attention. Carbon emission reduction in civil aviation is an inevitable requirement for achieving sustainable social development. This article aims to use system dynamics (SD) methods to establish a carbon emission model for the civil aviation industry that includes economic, demographic, technological, policy, and behavioral factors; analyze the key factors that affect carbon emissions; and explore effective emission reduction strategies. Researchers have found that SD-based carbon emission prediction has a high accuracy and is suitable for predicting carbon emissions in civil aviation. Through different scenario simulations, it has been found that any single emission reduction measure will struggle to effectively contribute to the expected carbon reductions in China’s civil aviation. Simultaneously adopting measures such as improving fuel efficiency, adopting clean energy, and using new-power aircraft is an effective way to reduce carbon emissions from civil aviation. In addition, policy intervention and technological innovation are equally crucial for achieving long-term emission reduction goals. The research results not only provide a scientific basis for the sustainable development of the aviation industry but also provide a reference for policymakers to formulate comprehensive emission reduction strategies.

Suggested Citation

  • Wei Chen & Yi Ai, 2024. "Research on the Carbon Emission Prediction and Reduction Strategies for the Civil Aviation Industry in China: A System Dynamics Approach," Sustainability, MDPI, vol. 16(20), pages 1-15, October.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:8950-:d:1499749
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/20/8950/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/20/8950/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Lu & Li, Xin & Liu, Wei & Kang, Xinyu & Zhao, Yifei & Wang, Minxi, 2024. "System dynamics-multiple the objective optimization model for the coordinated development of urban economy-energy-carbon system," Applied Energy, Elsevier, vol. 371(C).
    2. Ang, B.W & Zhang, F.Q & Choi, Ki-Hong, 1998. "Factorizing changes in energy and environmental indicators through decomposition," Energy, Elsevier, vol. 23(6), pages 489-495.
    3. Li, Fangyi & Li, Fei & Cai, Bofeng & Lyu, Chen & Xie, Wu, 2024. "Role of Chinese cities in abating aviation carbon emissions based on gridded population data and power law model," Energy, Elsevier, vol. 288(C).
    4. Timilsina, Govinda R. & Shrestha, Ashish, 2009. "Why have CO2 emissions increased in the transport sector in Asia ? underlying factors and policy options," Policy Research Working Paper Series 5098, The World Bank.
    5. Brueckner, Jan K. & Abreu, Chrystyane, 2017. "Airline fuel usage and carbon emissions: Determining factors," Journal of Air Transport Management, Elsevier, vol. 62(C), pages 10-17.
    6. Lu, Binbin & Dong, Jintao & Wang, Chun & Sun, Huabo & Yao, Hongyu, 2024. "High-resolution spatio-temporal estimation of CO2 emissions from China's civil aviation industry," Applied Energy, Elsevier, vol. 373(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Manel Daldoul & Ahlem Dakhlaoui, 2018. "Using the LMDI Decomposition Approach to Analyze the Influencing Factors of Carbon Emissions in Tunisian Transportation Sector," International Journal of Energy Economics and Policy, Econjournals, vol. 8(6), pages 22-28.
    2. M'raihi, Rafaa & Mraihi, Talel & Harizi, Riadh & Taoufik Bouzidi, Mohamed, 2015. "Carbon emissions growth and road freight: Analysis of the influencing factors in Tunisia," Transport Policy, Elsevier, vol. 42(C), pages 121-129.
    3. Geoffrey Udoka Nnadiri & Anthony S. F. Chiu & Jose Bienvenido Manuel Biona & Neil Stephen Lopez, 2021. "Comparison of Driving Forces to Increasing Traffic Flow and Transport Emissions in Philippine Regions: A Spatial Decomposition Study," Sustainability, MDPI, vol. 13(11), pages 1-17, June.
    4. Yuzhuo Huang & Yosuke Shigetomi & Andrew Chapman & Ken’ichi Matsumoto, 2019. "Uncovering Household Carbon Footprint Drivers in an Aging, Shrinking Society," Energies, MDPI, vol. 12(19), pages 1-18, September.
    5. Sobrino, Natalia & Monzon, Andres, 2014. "The impact of the economic crisis and policy actions on GHG emissions from road transport in Spain," Energy Policy, Elsevier, vol. 74(C), pages 486-498.
    6. Yue, Xuanyu & Byrne, Julie, 2024. "Identifying the determinants of carbon emissions of individual airlines around the world," Journal of Air Transport Management, Elsevier, vol. 115(C).
    7. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    8. Suyi Kim, 2019. "Decomposition Analysis of Greenhouse Gas Emissions in Korea’s Transportation Sector," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    9. Löschel, Andreas & Pothen, Frank & Schymura, Michael, 2015. "Peeling the onion: Analyzing aggregate, national and sectoral energy intensity in the European Union," Energy Economics, Elsevier, vol. 52(S1), pages 63-75.
    10. Lu, I.J. & Lin, Sue J. & Lewis, Charles, 2007. "Decomposition and decoupling effects of carbon dioxide emission from highway transportation in Taiwan, Germany, Japan and South Korea," Energy Policy, Elsevier, vol. 35(6), pages 3226-3235, June.
    11. Ronald E. Miller & Umed Temurshoev, 2017. "Output Upstreamness and Input Downstreamness of Industries/Countries in World Production," International Regional Science Review, , vol. 40(5), pages 443-475, September.
    12. Li, Aijun & Hu, Mingming & Wang, Mingjian & Cao, Yinxue, 2016. "Energy consumption and CO2 emissions in Eastern and Central China: A temporal and a cross-regional decomposition analysis," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 284-297.
    13. GUPTA Monika, 2019. "Decomposing The Role Of Different Factors In Co2 Emissions Increase In South Asia," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 14(1), pages 72-86, April.
    14. Reham Alhindawi & Yousef Abu Nahleh & Arun Kumar & Nirajan Shiwakoti, 2020. "Projection of Greenhouse Gas Emissions for the Road Transport Sector Based on Multivariate Regression and the Double Exponential Smoothing Model," Sustainability, MDPI, vol. 12(21), pages 1-18, November.
    15. Zhou, Xiaoyan & Zhang, Jie & Li, Junpeng, 2013. "Industrial structural transformation and carbon dioxide emissions in China," Energy Policy, Elsevier, vol. 57(C), pages 43-51.
    16. Chen, Yufeng & Miao, Jiafeng, 2023. "What Determines China’s Agricultural Non-Point Source Pollution? An Improved LMDI Decomposition Analysis," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 48(2), May.
    17. de Freitas, Luciano Charlita & Kaneko, Shinji, 2011. "Decomposition of CO2 emissions change from energy consumption in Brazil: Challenges and policy implications," Energy Policy, Elsevier, vol. 39(3), pages 1495-1504, March.
    18. Mayeres, Inge & Proost, Stef & Delhaye, Eef & Novelli, Philippe & Conijn, Sjaak & Gómez-Jiménez, Inmaculada & Rivas-Brousse, Daniel, 2023. "Climate ambitions for European aviation: Where can sustainable aviation fuels bring us?," Energy Policy, Elsevier, vol. 175(C).
    19. Jiandong Chen & Ping Wang & Jixian Zhou & Malin Song & Xinyue Zhang, 2022. "Influencing factors and efficiency of funds in humanitarian supply chains: the case of Chinese rural minimum living security funds," Annals of Operations Research, Springer, vol. 319(1), pages 413-438, December.
    20. Yang, Jing & Song, Kaihui & Hou, Jian & Zhang, Peidong & Wu, Jinhu, 2017. "Temporal and spacial dynamics of bioenergy-related CO2 emissions and underlying forces analysis in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1323-1330.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:8950-:d:1499749. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.