Journal of Korea Trade

Korea Trade Research Association (한국무역학회)
권호 표지
DOI QR코드

DOI QR Code

Is It Possible to Achieve IMO Carbon Emission Reduction Targets at the Current Pace of Technological Progress?

  • Choi, Gun-Woo (Maritime Big Data Analysis Center, Korea Maritime Institute) ;
  • Yun, Heesung (Graduate School of Maritime Finance, Korea Maritime & Ocean University) ;
  • Hwang, Soo-Jin (Maritime Big Data Analysis Center, Korea Maritime Institute)
  • Received : 2022.01.06
  • Accepted : 2022.02.11
  • Published : 2022.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose - The primary purpose of this study is to verify whether the target set out by the International Maritime Organization (IMO) for reducing carbon emissions from ships can be achieved by quantitatively analyzing the trends in technological advances of fuel oil consumption in the container shipping market. To achieve this purpose, several scenarios are designed considering various options such as eco-friendly fuels, low-speed operation, and the growth in ship size. Design/methodology - The vessel size and speed used in prior studies are utilized to estimate the fuel oil consumption of container ships and the pace of technological progress and Energy Efficiency Design Index (EEDI) regulations are added. A database of 5,260 container ships, as of 2019, is used for multiple linear regression and quantile regression analyses. Findings - The fuel oil consumption of vessels is predominantly affected by their speed, followed by their size, and the annual technological progress is estimated to be 0.57%. As the quantile increases, the influence of ship size and pace of technological progress increases, while the influence of speed and coefficient of EEDI variables decreases. Originality/value - The conservative estimation of carbon emission drawn by a quantitative analysis of the technological progress concerning the fuel efficiency of container vessels shows that it is not possible to achieve IMO targets. Therefore, innovative efforts beyond the current scope of technological progress are required.

Keywords

Acknowledgement

This work was supported by the Korea Maritime Institute in 2021.

References

  1. Bouman, E. A., E. Lindstad, A. I. Rialland, and A. H. Stromman (2017), "State-of-the-art technologies, measures, and potential for reducing GHG emissions from shipping", Transportation Research Part D, 52, 408-421. https://doi.org/10.1016/j.trd.2017.03.022
  2. Cameron, A. C. and P. K. Trivedi (2010), Microeconometrics Using Stata, pp. 1-917
  3. Cariou, P. (2011), "Is slow steaming a sustainable means of reducing CO2 emissions from container shipping?", Transportation Research Part D: Transport and Environment, 16(3), 260-264. https://doi.org/10.1016/j.trd.2010.12.005
  4. Chang, C. C. and C. H. Chang (2013), "Energy conservation for international dry bulk carriers via vessel speed reduction", Energy Policy, 59, 710-715. https://doi.org/10.1016/j.enpol.2013.04.025
  5. Clarkson (2021), Available from https://sin.clarksons.net/Timeseries (July, 8, 2021)
  6. Comer, B., N. Olmer, X. Mao, B. Roy and D. Rutherford (2017), Black Carbon Emissions and Fuel Use in Global Shipping 2015, International Council on Clean Transportation, pp. 1-107.
  7. Czermanski, E., G. T. Cirella, A. Oniszczuk-Jastrzabek, B. Pawlowska, and T. Notteboom, (2021), "An Energy Consumption Approach to Estimate Air Emission Reductions in Container Shipping", Energies 2021, 14(2), 278, 1-18.
  8. DNV.GL (2019), Available from https://www.dnv.com/expert-story/maritime-impact/How-newbuilds-can-comply-with-IMOs-2030-CO2-reduction-targets.html (August 30, 2021)
  9. Gilbert, P. (2014), "From reductionism to systems thinking: How the shipping sector can address sulphur regulation and tackle climate change", Marine Policy, 43, 376-378. https://doi.org/10.1016/j.marpol.2013.07.009
  10. IEA (2020), Energy Technology Perspectives, International Energy Agency.
  11. IMO (2014), Third IMO GHG Study 2014, International Maritime Organization.
  12. IMO (2020), Fourth IMO GHG Study 2020, International Maritime Organization.
  13. Johansson, L., J. P. Jalkanen, and J. Kukkonen (2017), "Global assessment of shipping emissions in 2015 on a high spatial and temporal resolution", Atmospheric Environment, 167, 403-415. https://doi.org/10.1016/j.atmosenv.2017.08.042
  14. Kwon, Young-Joong (2008), "Speed Loss Due to Added Resistance in Wind and Waves", The Naval Architect, 3, 14-16.
  15. Le, L. T., Gun-Woo Lee, Hwa-Young Kim and Su-Han Woo (2019), "Voyage-based statistical fuel consumption models of ocean-going container ships in Korea", Maritime Policy & Management, 47(3), 1-28.
  16. Lindstad, H., B. E. Asbjornslett, and A. H. Stromman (2011), "Reductions in greenhouse gas emissions and cost by shipping at lower speeds", Energy Policy, 39(6), 3456~3464 https://doi.org/10.1016/j.enpol.2011.03.044
  17. Lloydslist (2021), Available from https://lloydslist.maritimeintelligence.informa.com/LL1138591/Nobody-ever-won-an-argument-with-a-customer-Especially-not-when-hes-Jeff-Bezos (October, 22, 2021)
  18. Lu, R., O. Turan and E. Boulougouris (2013), "Voyage optimisation: prediction of ship specific fuel consumption for energy efficient shipping", In Low Carbon Shipping Conference, London, 1-11.
  19. Meng, Q., Y. Du, and Y. Wang (2016), "Shipping log data based container ship fuel efficiency modeling", Transportation Research Part B: Methodological, 83, 207-229. https://doi.org/10.1016/j.trb.2015.11.007
  20. Ministry of Oceans and Fisheries (2021), "Estimated results of EEXI of Korean outbound vessels due to strengthening regulations on energy efficiency of existing vessels", MACNET. 1-33
  21. Moreira, L., R. Vettor, and C. Guedes Soares (2021), "Neural network approach for predicting ship speed and fuel consumption", Journal of Marine Science and Engineering, 9(2), 119, 1-14. https://doi.org/10.3390/jmse9111191
  22. Psaraftis, H. N. and C. A. Kontovas (2009), "CO2 emission statistics for the world commercial fleet", WMU Journal of Maritime Affairs, 8(1), 1-25. https://doi.org/10.1007/BF03195150
  23. Riahi, K., D. P. van Vuuren, E. Kriegler, J. Edmonds, B. C. O'Neill, S. Fujimori et al. (2017), "The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: An overview", Global Environmental Change, 42, 153-168. https://doi.org/10.1016/j.gloenvcha.2016.05.009
  24. Tokuslu, A. (2020), "Analyzing the Energy Efficiency Design Index (EEDI) performance of a container ship", International Journal of Environment and Geoinformatics, 7(2), 114-119. https://doi.org/10.30897/ijegeo.703255
  25. Uyanik, T., C. Karatug, and Y. Arslanoglu (2020), "Machine learning approach to ship fuel consumption: A case of container vessel", Transportation Research Part D: Transport and Environment, 84, 1-14.
  26. van Vuuren, P. Detlef, J. Edmonds, M Kainuma, K. Riahi, A. Thomson, KHibbard et al. (2011), "The representative concentration pathways: an overview", Climatic Change, 109(5), 5-31. https://doi.org/10.1007/s10584-011-0148-z
  27. Wang, S., B. Ji, J. Zhao, W. Liu, and T. Xu, (2018), "Predicting ship fuel consumption based on LASSO regression", Transportation Research Part D: Transport and Environment, 65, 817-824. https://doi.org/10.1016/j.trd.2017.09.014