Calculating maritime shipping emissions per traded commodity

The Stockholm Environment Institute (SEI) and University College London (UCL) have developed a method to eliminate the opacity of cargo shipping emissions by matching satellite-based automatic identification system (AIS) data with vessel operational characteristics and shipping manifests. This approach allows for the precise allocation of greenhouse gases and air pollutants to individual commodity shipments, exporters, importers, and traders. A pilot study of Brazilian exports in 2014 revealed that shipping emissions added 5% to the country's reported CO2 emissions, with the largest shares attributed to iron ore and soybean exports to China. The authors argue that scaling this approach can inform international climate negotiations, improve lifecycle assessments, and enhance shipping industry efficiency.

• A new methodology developed by SEI and University College London (UCL) uses satellite-gathered automatic identification system (AIS) data—including position, bearing, draft, and speed—combined with vessel operational data (such as engine and fuel type) to estimate emissions of greenhouse gases and air pollutants along a ship's journey.
• The approach enables the allocation of proportional shares of a vessel's emissions to specific commodity shipments and their associated exporters, importers, traders, and owners by linking shipping manifests to the transporting vessel.
• In a 2014 pilot study of Brazilian exports, which totaled approximately 520 million tons of cargo, the associated maritime shipping emissions were 26 million tonnes of CO2, representing an additional 5% over Brazil's reported CO2 emissions for that year.
• The pilot analysis identified that over 50% of the emissions from Brazilian exports 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).
• Exports to China were responsible for 45.6% of the CO2 emissions associated with Brazilian exports, despite representing less than 20% of the total export value.
• The research indicates that traditional lifecycle assessment (LCA) approaches for soy supply chains in the global South tend to oversimplify shipping emissions by ignoring real vessel journeys and varying vessel efficiencies.

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} }