Calculating maritime shipping emissions per traded commodity

This briefing describes a new data-driven methodology developed by the Stockholm Environment Institute (SEI) and University College London (UCL) to calculate maritime shipping emissions per traded commodity. By combining satellite-based automatic identification system (AIS) data with ship operational characteristics and shipping manifests, the approach allocates greenhouse gas and air pollutant emissions to specific commodities, exporters, importers, and traders. The method was piloted using 2014 Brazilian export data to demonstrate its ability to provide precise, transparent accounting for supply chain environmental footprints.

• A new methodology developed by SEI and University College London (UCL) enables the precise allocation of maritime shipping emissions to specific commodities and the actors involved in the supply chain, including exporters, importers, traders, and owners.
• The calculation approach utilizes satellite-gathered automatic identification system (AIS) data—covering position, bearing, draft, and speed—and matches it with ship operational data such as engine and fuel type to estimate emissions along a journey.
• In a 2014 pilot study of Brazilian exports, maritime shipping emissions were calculated at 26 million tonnes of CO2, which added 5% to the country's total reported CO2 emissions for that year.
• The Brazilian pilot analysis revealed that more than 50% of shipping emissions came from the 'ores, slag and ash' category (primarily destined for China), while soybeans accounted for 12% of emissions (3.0 million tonnes of CO2).
• Analysis of Brazilian exports showed that China was responsible for 45.6% of the associated CO2 emissions, followed by Japan and South Korea.
• The methodology identifies that emissions intensity varies based on commodity density, distance, and vessel type; for instance, container ships often generate more emissions due to indirect routes with multiple stops.
• The approach can be applied to improve lifecycle assessments (LCA) for soy supply chains in the global South, as preliminary results suggest traditional LCA methods oversimplify shipping emissions by ignoring vessel efficiency and actual journey paths.

APA

Trimmer, C., & Godar, J. (2019). Calculating maritime shipping emissions per traded commodity. Stockholm Environment Institute. https://www.sei.org/wp-content/uploads/2019/04/sei-2019-brief-shipping-emissions-per-commodity-2.pdf

Chicago

Trimmer, Caspar, and Javier Godar. Calculating maritime shipping emissions per traded commodity. Stockholm Environment Institute, 2019. https://www.sei.org/wp-content/uploads/2019/04/sei-2019-brief-shipping-emissions-per-commodity-2.pdf.

Wikipedia

{{cite report |last1=Trimmer |first1=Caspar |last2=Godar |first2=Javier |title=Calculating maritime shipping emissions per traded commodity |publisher=Stockholm Environment Institute |date=April 2019 |url=https://www.sei.org/wp-content/uploads/2019/04/sei-2019-brief-shipping-emissions-per-commodity-2.pdf |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{trimmer2019calculating, author = {Trimmer, Caspar and Godar, Javier}, title = {{Calculating maritime shipping emissions per traded commodity}}, institution = {Stockholm Environment Institute}, year = {2019}, month = apr, url = {https://www.sei.org/wp-content/uploads/2019/04/sei-2019-brief-shipping-emissions-per-commodity-2.pdf}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }