Multiregional accounting of corporate carbon emissions

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Authors

Steven J. Davis, Andrew Dumit, Mo Li, Yohanna Maldonado, Michael Steffen, Martha Stevenson, Tatiana Boldyreva, Sangwon Suh

Abstract

Corporations routinely use environmentally-extended input-output models to estimate and report greenhouse gas emissions upstream in their supply chain. However, the most widely used of such models assume that the structure of supply chains and the emissions intensity of industries match those of a single region—usually the U.S. or the U.K. Here, we use a high-resolution multiregional input-output model to demonstrate the scale and pattern of emissions that may be missed when using these single-region models. We find that the upstream emissions of all the companies who report to CDP are in the aggregate 2.0 GtCO2e greater when estimated by a multiregional model instead of a U.S.-based single-region model, with especially substantial differences related to manufacturing sectors of moderate emissions intensity (i.e., 0.4-0.8 kgCO2e/$). Although the magnitude of emissions embodied in international trade is well-recognized in the context of national inventories, our results underscore the importance of international differences in emissions for corporate carbon accounting. High-resolution, multiregional models can both improve the accuracy of corporate emissions inventories and help companies to prioritize both primary data collection and emissions reduction efforts.

DOI

https://doi.org/10.31223/X5MX4T

Subjects

Environmental Monitoring, Environmental Sciences, Natural Resources and Conservation, Physical Sciences and Mathematics, Sustainability

Keywords

Emissions accounting, Corporate climate action, supply chain

Dates

Published: 2024-11-26 09:46

Last Updated: 2024-11-26 17:46

License

CC-BY Attribution-NonCommercial 4.0 International

Additional Metadata

Conflict of interest statement:
Some authors are employees of Watershed, which licenses a commercial version of the model used for the study.

Data Availability (Reason not available):
Data will be available upon publication of peer-reviewed study