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Energy Effectiveness of Jet Fuel Utilization in Brazilian Air Transport

Author

Listed:
  • Manoela Cabo

    (IBGE Brazilian Institute of Geography and Statistics, Av. República do Chile, 500-Centro, Rio de Janeiro-RJ 20031-170, Brazil
    COPPE Production and Transport Engineering Program, Federal University of Rio de Janeiro, Av. Pedro Calmon, 550-Cidade Universitária da Universidade Federal do Rio de Janeiro, Rio de Janeiro-RJ 21941-901, Brazil)

  • Elton Fernandes

    (COPPE Production and Transport Engineering Program, Federal University of Rio de Janeiro, Av. Pedro Calmon, 550-Cidade Universitária da Universidade Federal do Rio de Janeiro, Rio de Janeiro-RJ 21941-901, Brazil)

  • Paulo Alonso

    (Electronics and Communication Engineering Department, UERJ Rio de Janeiro State University, R. São Francisco Xavier, 524-Maracanã, Rio de Janeiro-RJ 20550-000, Brazil)

  • Ricardo Rodrigues Pacheco

    (COPPE Production and Transport Engineering Program, Federal University of Rio de Janeiro, Av. Pedro Calmon, 550-Cidade Universitária da Universidade Federal do Rio de Janeiro, Rio de Janeiro-RJ 21941-901, Brazil)

  • Felipe Fagundes

    (COPPE Production and Transport Engineering Program, Federal University of Rio de Janeiro, Av. Pedro Calmon, 550-Cidade Universitária da Universidade Federal do Rio de Janeiro, Rio de Janeiro-RJ 21941-901, Brazil)

Abstract

Since World War I, the commercial aviation industry has seen many improvements that now allow people and goods to reach the other side of the world in a few hours, consuming much less fuel than in recent decades. Improvements in cargo capacity and energy efficiency were significant, and in this scenario, commercial airlines were able to thrive and bring great benefits to the world economy. However, this sector is facing environmental challenges due to the intensive use of jet fuel. Brazil is one of the largest domestic air passenger markets in the world and still has great growth potential, considering its economic potential and territorial dimensions, which are roughly the same size as the US and twice the size of the European Union. This paper discusses the partial productivity of jet fuel in Brazilian domestic aviation and proposes an econometric method to support public regulators and airline decisions. The proposed model uses variables, such as aircraft size, route characteristics, and idle flight capacity, in a panel data analysis. The results show that reducing idle capacity is one of the best ways to achieve better short-term fuel efficiency, and therefore will reduce the environmental impacts and have positive economic effects on commercial air transport activities. This paper brings a new approach to the discussion of airline performance, focusing on the use of jet fuel, with economic and environmental consequences.

Suggested Citation

  • Manoela Cabo & Elton Fernandes & Paulo Alonso & Ricardo Rodrigues Pacheco & Felipe Fagundes, 2019. "Energy Effectiveness of Jet Fuel Utilization in Brazilian Air Transport," Sustainability, MDPI, vol. 12(1), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:12:y:2019:i:1:p:303-:d:303422
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    References listed on IDEAS

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    1. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521828284, November.
    2. Park, Yongha & O’Kelly, Morton E., 2014. "Fuel burn rates of commercial passenger aircraft: variations by seat configuration and stage distance," Journal of Transport Geography, Elsevier, vol. 41(C), pages 137-147.
    3. Gaolu Zou & K. W. Chau, 2019. "Long- and Short-Run Effects of Fuel Prices on Freight Transportation Volumes in Shanghai," Sustainability, MDPI, vol. 11(18), pages 1-12, September.
    4. Zou, Bo & Elke, Matthew & Hansen, Mark & Kafle, Nabin, 2014. "Evaluating air carrier fuel efficiency in the US airline industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 306-330.
    5. Chèze, Benoît & Gastineau, Pascal & Chevallier, Julien, 2011. "Forecasting world and regional aviation jet fuel demands to the mid-term (2025)," Energy Policy, Elsevier, vol. 39(9), pages 5147-5158, September.
    6. 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.
    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. Park, Yongha & O'Kelly, Morton E., 2018. "Examination of cost-efficient aircraft fleets using empirical operation data in US aviation markets," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 224-234.
    9. repec:dau:papers:123456789/6792 is not listed on IDEAS
    10. Azam, Muhammad, 2016. "Does environmental degradation shackle economic growth? A panel data investigation on 11 Asian countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 175-182.
    11. Cui, Qiang & Li, Ye, 2017. "Airline efficiency measures using a Dynamic Epsilon-Based Measure model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 121-134.
    12. González, Rodrigo & Hosoda, Eiji B., 2016. "Environmental impact of aircraft emissions and aviation fuel tax in Japan," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 234-240.
    13. Li, Tingting & Wang, Yong & Zhao, Dingtao, 2016. "Environmental Kuznets Curve in China: New evidence from dynamic panel analysis," Energy Policy, Elsevier, vol. 91(C), pages 138-147.
    14. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521535380, November.
    15. Kasman, Adnan & Duman, Yavuz Selman, 2015. "CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: A panel data analysis," Economic Modelling, Elsevier, vol. 44(C), pages 97-103.
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