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The energy efficiency effects of periodic ship hull cleaning

Author

Listed:
  • Roar Adland

    (NHH - Norwegian School of Economics and Business Administration, Department of Economics - Norwegian School of Economics and Business Administration)

  • Pierre Cariou

    (Kedge Business School [Talence])

  • Haiying Jia
  • François-Charles Wolff

    (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - IEMN-IAE Nantes - Institut d'Économie et de Management de Nantes - Institut d'Administration des Entreprises - Nantes - UN - Université de Nantes, INED - Institut national d'études démographiques)

Abstract

This paper investigates the impact of periodic hull cleaning on oil tankers' energy efficiency using real 2012–2016 fleet performance and weather data extracted from noon reports for a fleet of eight identical Aframax-size crude oil tankers. The impact of changes in fuel consumption is estimated around the discontinuity when a vessel is cleaned and rely on both before-after and difference-in-differences estimators. The main results show that (i) periodic hull cleaning leads to a significant reduction in the daily fuel consumption; (ii) dry-docking leads to greater and significantly different reductions in fuel consumption than underwater hull cleaning, approximately −17% versus −9%; (iii) hull cleaning energy efficiency effect is greater when the vessel is sailing laden rather than in the ballast condition. These findings represent a key building block for the optimization of maintenance intervals.

Suggested Citation

  • Roar Adland & Pierre Cariou & Haiying Jia & François-Charles Wolff, 2018. "The energy efficiency effects of periodic ship hull cleaning," Post-Print hal-03732129, HAL.
  • Handle: RePEc:hal:journl:hal-03732129
    DOI: 10.1016/j.jclepro.2017.12.247
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    Cited by:

    1. Tino Vidović & Jakov Šimunović & Gojmir Radica & Željko Penga, 2023. "Systematic Overview of Newly Available Technologies in the Green Maritime Sector," Energies, MDPI, vol. 16(2), pages 1-26, January.
    2. Granado, Igor & Hernando, Leticia & Uriondo, Zigor & Fernandes-Salvador, Jose A., 2024. "A fishing route optimization decision support system: The case of the tuna purse seiner," European Journal of Operational Research, Elsevier, vol. 312(2), pages 718-732.
    3. Kyriakos Skarlatos & Andreas Fousteris & Dimitrios Georgakellos & Polychronis Economou & Sotirios Bersimis, 2023. "Assessing Ships’ Environmental Performance Using Machine Learning," Energies, MDPI, vol. 16(6), pages 1-21, March.
    4. Dalian Wu & Jian Hua & Shun-Yao Chuang & Junseng Li, 2023. "Preventative Biofouling Monitoring Technique for Sustainable Shipping," Sustainability, MDPI, vol. 15(7), pages 1-13, April.

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