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Trade-linked shipping CO2 emissions


The ambitious targets for shipping emissions reduction and challenges for mechanism design call for new approaches to encourage decarbonization. Here we build a compound model chain to deconstruct global international shipping emissions to fine-scale trade flows and propose trade-linked indicators to measure shipping emissions efficiency. International maritime trade in 2018 contributes 746.2 Tg to shipping emissions of CO2, of which 17.2% is contributed from ten out of thousands of trade flows at the country level. We argue that potential unfairness exists if allocating shipping emissions responsibility to bilateral traders due to external beneficiaries. However, a huge shipping emissions-reduction potential could be expected by optimizing international trade patterns, with a maximum reaching 38% of the current total. Our comprehensive modelling system can serve as a benchmark tool to support the construction of a systematic solution and joint effort from the shipping industry and global trade network to address climate change.

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Fig. 1: Distribution of international shipping emissions resulting from the VoySEIM and the GTEMS model.
Fig. 2: International shipping CO2 emissions and trade-emissions efficiency matrix.
Fig. 3: Characteristics of shipping CO2 emissions of international trade commodities.
Fig. 4: Shipping emissions changes in CO2 by optimizing trade partners.

Data availability

The AIS data and STSD are restricted to the third party and used under licence for the current study. Trade data including the BACI database (, UN Comtrade database (, the US census ( and the Eurostat database ( are all publicly available, with details described in the Methods. Emissions data are available from the corresponding author upon request. Source data are provided with this paper.

Code availability

Python codes used during the current study are available from the corresponding author on reasonable request.


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This work is supported by the National Natural Science Foundation of China (grant nos. 41822505 and 42061130213 to H.L.). H.L. is supported by the Royal Society of the United Kingdom through a Newton Advanced Fellowship (NAF\R1\201166).

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Authors and Affiliations



X-T.W. and H.L. designed the research and wrote the manuscript. X-T.W., Z-F.L. and F-Y.D. developed the VoySEIM model and conducted the shipping efficiency estimation. X-T.W. and H-L.X. developed the GTEMS model. Z-F.L., F-Y.D., L-J.Q., M-S.S. and S-X.Z. performed the analyses. H-Y.M. and K-B.H. provided insights into the scenario design. All authors contributed to the writing.

Corresponding author

Correspondence to Huan Liu.

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The authors declare no competing interests.

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Peer review information Nature Climate Change thanks James Corbett and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Discussion 1 and 2, Methods 1–4, Figs. 1–11, Tables 1–7 and references.

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Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

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Wang, XT., Liu, H., Lv, ZF. et al. Trade-linked shipping CO2 emissions. Nat. Clim. Chang. 11, 945–951 (2021).

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