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Measuring the environmental efficiency of the global aviation fleet

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  • Adler, Nicole
  • Martini, Gianmaria
  • Volta, Nicola

Abstract

This research analyses the environmental footprint of the airline industry in an attempt to highlight potential paths for improvement. We develop a directional economic-environmental distance function (DEED) which accounts for the production of both desirable and undesirable output and the potential for constrained increases in input utilization. This research applies the modeling framework to analyze the potential to reduce noise and airborne pollutants emitted by aircraft–engine combinations given the current state of aeronautical technology. The global aircraft–engine market is viewed from the regulatory perspective in order to compare the single environmental and operational efficient frontier to that of the airline carriers, and environmental objectives. The results of DEED are then applied in order to substitute the fleets serving Schipol, Amsterdam and Arlanda, Stockholm airports in June 2010 with the benchmark aircraft. The results highlight the inefficiencies of the current airline fleets and that the IPCC values of externalities are a magnitude of TEN too low to encourage changes in the global fleet hence the need for government intervention.

Suggested Citation

  • Adler, Nicole & Martini, Gianmaria & Volta, Nicola, 2013. "Measuring the environmental efficiency of the global aviation fleet," Transportation Research Part B: Methodological, Elsevier, vol. 53(C), pages 82-100.
  • Handle: RePEc:eee:transb:v:53:y:2013:i:c:p:82-100
    DOI: 10.1016/j.trb.2013.03.009
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    References listed on IDEAS

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    Cited by:

    1. Tiziana D'Alfonso & Changmin Jiang & Valentina Bracaglia, 2015. "Air transport and high-speed rail competition: environmental implications and mitigation strategies," DIAG Technical Reports 2015-15, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    2. Marchetti, Dalmo & Wanke, Peter F., 2019. "Efficiency in rail transport: Evaluation of the main drivers through meta-analysis with resampling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 83-100.
    3. Sheu, Jiuh-Biing, 2014. "Airline ambidextrous competition under an emissions trading scheme – A reference-dependent behavioral perspective," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 115-145.
    4. Tsionas, Efthymios & Assaf, A. George & Gillen, David & Mattila, Anna S., 2017. "Modeling technical and service efficiency," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 113-125.
    5. Santos, Alexsander José dos & Mancini, Sandro Donnini & Frutuoso Roveda, José Arnaldo & Ewbank, Henrique & Roveda, Sandra Regina Monteiro Masalskiene, 2020. "A fuzzy assessment method to airport waste management: A case study of Congonhas Airport, Brazil," Journal of Air Transport Management, Elsevier, vol. 87(C).
    6. D’Alfonso, Tiziana & Jiang, Changmin & Bracaglia, Valentina, 2016. "Air transport and high-speed rail competition: Environmental implications and mitigation strategies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 261-276.
    7. Cui, Qiang & Wei, Yi-Ming & Li, Ye, 2016. "Exploring the impacts of the EU ETS emission limits on airline performance via the Dynamic Environmental DEA approach," Applied Energy, Elsevier, vol. 183(C), pages 984-994.
    8. Tianbo Tang & Jianxin You & Hui Sun & Hao Zhang, 2019. "Transportation Efficiency Evaluation Considering the Environmental Impact for China’s Freight Sector: A Parallel Data Envelopment Analysis," Sustainability, MDPI, Open Access Journal, vol. 11(18), pages 1-24, September.
    9. Cui, Qiang & Li, Ye, 2017. "Airline efficiency measures under CNG2020 strategy: An application of a Dynamic By-production model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 130-143.
    10. Adler, Nicole & Volta, Nicola, 2016. "Accounting for externalities and disposability: A directional economic environmental distance function," European Journal of Operational Research, Elsevier, vol. 250(1), pages 314-327.
    11. Ming Zhang & Qianwen Huang & Sihan Liu & Huiying Li, 2019. "Multi-Objective Optimization of Aircraft Taxiing on the Airport Surface with Consideration to Taxiing Conflicts and the Airport Environment," Sustainability, MDPI, Open Access Journal, vol. 11(23), pages 1-27, November.
    12. Cui, Qiang & Li, Ye & Lin, Jing-ling, 2018. "Pollution abatement costs change decomposition for airlines: An analysis from a dynamic perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 96-107.
    13. Miyoshi, Chikage & Fukui, Hideki, 2018. "Measuring the rebound effects in air transport: The impact of jet fuel prices and air carriers’ fuel efficiency improvement of the European airlines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 112(C), pages 71-84.

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