Implications of Arctic shipping emissions for marine environment

ABSTRACT

To investigate the distribution and behaviour of ocean vessels in the Arctic region and determine the impacts of their emissions, we examine vessel characteristics in conjunction with a series of Automatic Identification System (AIS) data between 2012 and 2016. These datasets, combined with a bottom-up model for estimating pollution emissions, enable us to analyse the level of pollution generated by vessels in the Arctic region. The results indicate that the movements of the vessels and their emissions increase in frequency and continue to do so unless clean energy or technologies are adopted. More than 80% of the emissions are found to be concentrated in the Norwegian and Barents Seas. Emissions from the Northern Sea Route are comparatively low and those from the Northwest Passage are similarly insignificant. Besides, an empirical analysis of the emissions in the Arctic region is carried out following the more restrictive International Maritime Organization (IMO)’s regulations on sulphur emissions that is implemented in 2020. This investigation supplements the literature analysing Arctic’s pollution emission inventory.

KEYWORDS:

• Arctic region
• pollution emissions
• ais
• bottom-up pollution emission model

Acknowledgments

The authors would like to thank the anonymous referees for their very helpful comments and suggestions. This work was supported by the National Natural Science Foundation of China (Grants#: 72031005, 72074141) and the National Social Science Foundation of China (Grant#: 18ZDA052). The authors are also grateful for the support of the Lloyd’s Register Foundation (Grant: G\100111), a charity that helps to protect life and property by supporting engineering-related education, public engagement, and the application of research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Arctic Policy Framework. https://www.eia.gov.nt.ca/en/arctic-policy-framework, retrieved on 4 August 2021.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [72031005, 72074141, 71671110]; National Social Science Foundation of China [18ZDA052]; Lloyd’s Register Foundation [G\100111].