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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.19666 |
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| _version_ | 1866917102037762048 |
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| author | Avila, Nikky He, Hank Rastegar, Reza Tolan, Jamie Tiecke, Tobias White, Brian |
| author_facet | Avila, Nikky He, Hank Rastegar, Reza Tolan, Jamie Tiecke, Tobias White, Brian |
| contents | Carbon matching aims to improve corporate carbon accounting by tracking emissions rather than energy consumption and production. We present a mathematical derivation of carbon matching using marginal emission rates, where the unit of matching is tons of carbon emitted. We present analysis and open source notebooks showing how marginal emissions can be calculated on simulated electric bus networks. Importantly, we prove mathematically that distinct emissions rates can be assigned to all aspects of the electric grid - including transmission, storage, generation, and consumption - completely allocating electric grid emissions. We show that carbon matching is an accurate carbon accounting framework that can inspire ambitious and impactful action. This research fills a gap by blending carbon accounting expertise and power systems modeling to consider the effectiveness of alternative methodologies for allocating electric system emissions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_19666 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Catalyzing System-level Decarbonization: An Analysis of Carbon Matching As An Accounting Framework Avila, Nikky He, Hank Rastegar, Reza Tolan, Jamie Tiecke, Tobias White, Brian Optimization and Control Carbon matching aims to improve corporate carbon accounting by tracking emissions rather than energy consumption and production. We present a mathematical derivation of carbon matching using marginal emission rates, where the unit of matching is tons of carbon emitted. We present analysis and open source notebooks showing how marginal emissions can be calculated on simulated electric bus networks. Importantly, we prove mathematically that distinct emissions rates can be assigned to all aspects of the electric grid - including transmission, storage, generation, and consumption - completely allocating electric grid emissions. We show that carbon matching is an accurate carbon accounting framework that can inspire ambitious and impactful action. This research fills a gap by blending carbon accounting expertise and power systems modeling to consider the effectiveness of alternative methodologies for allocating electric system emissions. |
| title | Catalyzing System-level Decarbonization: An Analysis of Carbon Matching As An Accounting Framework |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2511.19666 |