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The Impact of Bunker Risk Management on CO2 Emissions in Maritime Transportation Under ECA Regulation

In: Sustainable Logistics and Transportation

Author

Listed:
  • Yewen Gu

    (Norwegian School of Economics)

  • Stein W. Wallace

    (Norwegian School of Economics)

  • Xin Wang

    (Norwegian University of Science and Technology)

Abstract

The shipping industry carries over 90% of the world’s trade, and is hence a major contributor to CO2 and other airborne emissions. As a global effort to reduce air pollution from ships, the implementation of the ECA (Emission Control Areas) regulations has given rise to the wide usage of cleaner fuels. This has led to an increased emphasis on the management and risk control of maritime bunker costs for many shipping companies. In this paper, we provide a novel view on the relationship between bunker risk management and CO2 emissions. In particular, we investigate how different actions taken in bunker risk management, based on different risk aversions and fuel hedging strategies, impact a shipping company’s CO2 emissions. We use a stochastic programming model and perform various comparison tests in a case study based on a major liner company. Our results show that a shipping company’s risk attitude on bunker costs has impacts on its CO2 emissions. We also demonstrate that, by properly designing its hedging strategies, a shipping company can sometimes achieve noticeable CO2 reduction with little financial sacrifice.

Suggested Citation

  • Yewen Gu & Stein W. Wallace & Xin Wang, 2017. "The Impact of Bunker Risk Management on CO2 Emissions in Maritime Transportation Under ECA Regulation," Springer Optimization and Its Applications, in: Didem Cinar & Konstantinos Gakis & Panos M. Pardalos (ed.), Sustainable Logistics and Transportation, pages 199-224, Springer.
    • Handle: RePEc:spr:spochp:978-3-319-69215-9_9
    DOI: 10.1007/978-3-319-69215-9_9
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    Cited by:

    1. Tzeu-Chen Han & Chih-Min Wang, 2021. "Shipping Bunker Cost Risk Assessment and Management during the Coronavirus Oil Shock," Sustainability, MDPI, vol. 13(9), pages 1-12, April.

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    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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