Article 2026-04-21 under-review v1

Structural attribution of embodied carbon emissions using a regional input–output framework

Y
Yao TONG Akita Prefectural University
Y
Yoshiaki SHIMAZAKI Akita Prefectural University
K
Ken-ichi HASEGAWA Akita Prefectural University
S
Shin-ichi MATSUMOTO Akita Prefectural University
J
Jin-ya TAKEUCHI Akita Prefectural University

Abstract

Understanding how carbon emissions are structurally generated within production systems remains a central challenge in environmental accounting. While previous approaches can estimate total embodied emissions, they provide limited insight into how individual production inputs contribute to emissions at a given point in time, particularly when inputs originate from different regions. This study introduces the Regional Embodied Carbon Share (RECS), a formally defined analytical framework that decomposes a product’s emission factor into proportional contributions from local inputs, non-local inputs, and direct emissions within a consistent Input–Output (IO) framework. The method enables static structural attribution of embodied emissions while preserving full supply-chain interdependencies. The framework is applied to the lumber and wood products sector across five Japanese prefectures using regional IO tables combined with emissions data. Results show that although overall emission factors are similar across regions, their underlying contribution structures differ substantially, especially for forestry resources, electricity, intermediate wood products, and transport services. These findings demonstrate that embodied emissions depend on production structure rather than local sourcing alone, highlighting the importance of structural emission attribution for comparative analysis of production systems.

Citation Information

@article{yaotong2026,
  title={Structural attribution of embodied carbon emissions using a regional input–output framework},
  author={Yao TONG and Yoshiaki SHIMAZAKI and Ken-ichi HASEGAWA and Shin-ichi MATSUMOTO and Jin-ya TAKEUCHI},
  journal={Scientific Reports},
  year={2026},
  doi={https://doi.org/10.21203/rs.3.rs-9288106/v1}
}
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