Which emissions belong to us? The case for contributory value-chain emissions accounting

Christian Barry & Garrett Cullity

Politics, Philosophy & Economics2025https://doi.org/10.1177/1470594x241312425article
ABDC B
Weight
0.37

What the paper says

States and other climate actors now commonly set ‘net zero’ targets – pledging that, by a certain date, they will put no more carbon into the atmosphere than they take out. However, there is controversy over what exactly should count as attaining such targets. The method of emissions accounting that states currently use – territorial emissions accounting – is often criticized as problematic, but a fully satisfactory explanation of the problem is needed. We argue that the key both to understanding the problem and to solving it is that there is a specific kind of cooperative contribution – a mereological contribution – that a national net zero commitment needs to make to global climate action in order to meet the standards that global citizens should hold states to. On this basis, we propose an alternative method – Contributory Value-Chain Accounting – showing how it can be qualified to reflect trade relationships between net-zero-aligned countries, and defending it against the objections that it involves double counting, is infeasible and too informationally demanding, and that it would send the wrong incentive signals.

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https://doi.org/https://doi.org/10.1177/1470594x241312425

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@article{christian2025,
  title        = {{Which emissions belong to us? The case for contributory value-chain emissions accounting}},
  author       = {Christian Barry & Garrett Cullity},
  journal      = {Politics, Philosophy & Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/1470594x241312425},
}

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Which emissions belong to us? The case for contributory value-chain emissions accounting

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.