Advertisement

Maritime Economics & Logistics

, Volume 21, Issue 4, pp 524–542 | Cite as

Speed optimization versus speed reduction: Are speed limits better than a bunker levy?

  • Harilaos N. PsaraftisEmail author
Original Article

Abstract

The purpose of this paper is to shed some light on the speed limit debate, and specifically to look into whether reducing speed by imposing a speed limit is better than achieving the same by imposing a bunker levy. This debate, along with the various issues of speed optimization versus speed reduction, is currently ongoing at the International Maritime Organization (IMO), in the quest to reduce greenhouse gas (GHG) emissions from ships. In that context, “speed optimization” and “speed reduction” have been included in the set of candidate short-term measures under discussion at the IMO. However, there is much confusion on what either speed optimization or speed reduction may mean, and some stakeholders have proposed mandatory speed limits as a measure to achieve GHG emissions reductions. To investigate this issue, the speed limit option is compared with the option of reducing speed via a bunker levy. The latter option is not under immediate discussion at the IMO, to be potentially included in the set of medium-term measures. The main result of the paper is that the speed limit option exhibits a number of deficiencies as an instrument aiming to reduce GHG emissions, at least vis-à-vis the bunker levy option.

Keywords

Greenhouse gases Ocean shipping International Maritime Organization Speed reduction Speed optimization Speed limits Bunker levy 

Notes

Acknowledgements

Work reported in this paper was funded in part by project ShipCLEAN (Energy efficient marine transport through optimization of coupled transportation logistics and energy systems analysis), supported by the Swedish Energy Agency (project number 2017-003265, Chalmers University of Technology project leader). The author would like to thank two anonymous reviewers for their comments which helped improve the paper.

References

  1. Cariou, P. 2011. Is slow steaming a sustainable means of reducing CO2 emissions from container shipping? Transportation Research Part D 16 (3): 260–264.CrossRefGoogle Scholar
  2. Cariou, P., and A. Cheaitou. 2012. The effectiveness of a European speed limit versus an international bunker-levy to reduce CO2 emissions from container shipping. Transportation Research Part D 17: 116–123.CrossRefGoogle Scholar
  3. CE Delft. 2017. Regulating speed: A short term measure to reduce maritime GHG emissions, study by CE Delft for the Clean Shipping Coalition, Oct 18.Google Scholar
  4. Cheaitou, A., and P. Cariou. 2012. Liner shipping service optimisation with reefer containers capacity: An application to northern Europe-South America trade. Maritime Policy & Management 39 (6): 589–602.CrossRefGoogle Scholar
  5. CSC. 2018. The regulation of ship operational speed: An immediate GHG reduction measure to deliver the IMO 2030 target, submitted by the Clean Shipping Coalition (CSC) to the 4th Intersessional Working Group on GHGs, IMO doc. ISWG-GHG 4/2/8. IMO: London, UK.Google Scholar
  6. Devanney, J.W. 2011. Speed limits versus slow steaming. Center for Tankship Excellence. https://www.c4tx.org. Accessed 22 Oct 2019.
  7. Du, Y., Q. Chen, X. Quan, L. Long, and R.Y.K. Fung. 2011. Berth allocation considering fuel consumption and vessel emissions. Transportation Research Part E 47: 1021–1037.CrossRefGoogle Scholar
  8. Fagerholt, K., N. Gausel, J. Rakke, and H. Psaraftis. 2015. Maritime routing and speed optimization with emission control areas. Transportation Research Part C 52: 57–63.CrossRefGoogle Scholar
  9. Fagerholt, K., and H.N. Psaraftis. 2015. On two speed optimization problems for ships that sail in and out of emission control areas. Transportation Research Part D 39: 56–64.CrossRefGoogle Scholar
  10. FMC. 2012. Bureau of trade analysis. In Study of the 2008 repeal of the liner conference exemption from European Union competition law. Washington, DC: Federal Maritime Commission.Google Scholar
  11. Giovannini, M., and H.N. Psaraftis. 2018. The profit maximizing liner shipping problem with flexible frequencies: Logistical and environmental considerations. Flexible Services and Manufacturing Journal.  https://doi.org/10.1007/s10696-018-9308-z.CrossRefGoogle Scholar
  12. Gkonis, K.G., and H.N. Psaraftis. 2012. Modelling tankers’ optimal speed and emissions. Archival paper, 2012 SNAME transactions, vol. 120: 90–115. Annual Meeting of the Society of Naval Architects and Marine Engineers, Providence, RI, USA, Oct 2012.Google Scholar
  13. Golias, M., M. Boile, S. Theofanis, and C. Efstathiou. 2010. The berth-scheduling problem: maximizing berth productivity and minimizing fuel consumption and emissions production. Transportation Research Record: Journal of the Transportation Research Board 2166: 20–27.CrossRefGoogle Scholar
  14. Haralambides, H.E. 2019. Gigantism in container shipping, ports and global logistics: a time-lapse into the future. Maritime Economics & Logistics 21 (1): 1–60.CrossRefGoogle Scholar
  15. IMO. 2018. Resolution MEPC.304(72) (adopted on 13 April 2018), initial IMO strategy on reduction of GHG emissions from ships, IMO doc MEPC 72/17/Add. 1, Annex 11.Google Scholar
  16. Magirou, E.F., H.N. Psaraftis, and T. Bouritas. 2015. The economic speed of an oceangoing vessel in a dynamic setting. Transportation Research Part B 76: 48–67.CrossRefGoogle Scholar
  17. Mills, J., A. Donnison, and G. Brightwell. 2014. Factors affecting microbial spoilage and shelf-life of chilled vacuum-packed lamb transported to distant markets: a review. Meat Science 98 (1): 71–80.CrossRefGoogle Scholar
  18. Psaraftis, H.N. 2012. Market based measures for green house gas emissions from ships: a review. WMU Journal of Maritime Affairs 11: 211–232.CrossRefGoogle Scholar
  19. Psaraftis, H.N. 2016. Green maritime transportation: market based measures. In Green transportation logistics: in search for win-win solutions, ed. H.N. Psaraftis. Cham: Springer.CrossRefGoogle Scholar
  20. Psaraftis, H.N., and C.A. Kontovas. 2009. Ship emissions: logistics and other tradeoffs. In Proceedings of 10th international marine design conference. Trondheim, Norway, May 26–29.Google Scholar
  21. Psaraftis, H.N., and C.A. Kontovas. 2010. Balancing the economic and environmental performance of maritime transportation. Transportation Research Part D 15 (8): 458–462.CrossRefGoogle Scholar
  22. Psaraftis, H.N., and C.A. Kontovas. 2013. Speed models for energy-efficient maritime transportation: a taxonomy and survey. Transportation Research Part C 26: 331–351.CrossRefGoogle Scholar
  23. Psaraftis, H.N., and C.A. Kontovas. 2015. Slow steaming in maritime transportation: fundamentals, trade-offs, and decision models. In Handbook of ocean container transportation logistics: making global supply chains effective, ed. C.-Y. Lee and Q. Meng. New York: Springer.Google Scholar
  24. Psaraftis, H.N., and C.A. Kontovas. 2016. Green maritime transportation: speed and route optimization. In Green Transportation Logistics: in Search for Win-Win Solutions, ed. H.N. Psaraftis. Springer.Google Scholar
  25. Vilas, R.F. 2018. Container shipping performance: a case study on a transpacific service. M.Sc. thesis, Technical University of Denmark.Google Scholar
  26. Zis, T., R.J. North, P. Angeloudis, W.Y. Ochieng, and M.G.H. Bell. 2014. Evaluation of cold ironing and speed reduction policies to reduce ship emissions near and at ports. Maritime Economics & Logistics 16 (4): 371–398.CrossRefGoogle Scholar
  27. Zis, T., and H.N. Psaraftis. 2017. The implications of the new sulphur limits on the European Ro-Ro sector. Transportation Research Part D 52: 185–201.CrossRefGoogle Scholar
  28. Zis, T., and H.N. Psaraftis. 2018. Operational measures to mitigate and reverse the potential modal shifts due to environmental legislation. Maritime Policy & Management.  https://doi.org/10.1080/03088839.2018.1468938.CrossRefGoogle Scholar

Copyright information

© Springer Nature Limited 2019

Authors and Affiliations

  1. 1.Department of Technology, Management and EconomicsTechnical University of DenmarkLyngbyDenmark

Personalised recommendations