Towards Sustainable Product Carbon Footprint Accounting Through Green Electricity and Green Certificate Mechanisms
グリーン電力とグリーン証書メカニズムを通じた持続可能な製品カーボンフットプリント会計に向けて (AI 翻訳)
Xiaoxuan Bai, Li J, Runpeng Tan, Kaiyun Liu
🤖 gxceed AI 要約
日本語
本論文は、グリーン電力取引とグリーン証書制度の拡大に伴い、従来の地域平均排出係数では企業の実際の電力消費に伴う炭素排出責任を正確に反映できず、再生可能電力属性の二重計上や削減効果の過大評価が生じる問題を指摘する。電気機器製品を対象に、残余電力排出係数を構築し、グリーン電力・証書の属性検証と組み合わせたライフサイクル会計フレームワークを提案。変圧器や電力量計など11製品の実証分析により、50%のグリーン電力代替シナリオでの炭素削減ポテンシャルを評価し、本手法が製品カーボンフットプリントの精度と透明性を向上させることを示した。
English
This paper addresses the issue of double counting of renewable electricity attributes in product carbon footprint accounting due to traditional regional average emission factors. Focusing on electrical equipment, it proposes a method using provincial residual emission factors coupled with green electricity and certificate verification. An empirical analysis of 11 product types shows that the proposed approach improves accuracy and transparency, and evaluates carbon reduction potential under a 50% green electricity substitution scenario.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本でもグリーン電力証書や非化石証書の活用が進んでおり、Scope 2排出量の算定における二重計上防止は重要な課題。本論文で提案される残余排出係数の考え方は、日本のサプライチェーン排出量算定や製品CFP制度にも示唆を与える。
In the global GX context
Globally, as more companies use renewable energy certificates and power purchase agreements, avoiding double counting in Scope 2 emissions is critical. This method of constructing residual mix emission factors supports accurate carbon footprinting for supply chain disclosure and aligns with GHG Protocol Scope 2 Guidance updates.
👥 読者別の含意
🔬研究者:Provides a methodological framework for residual emission factors that can be adapted to other regions and product categories.
🏢実務担当者:Offers a practical approach for companies to improve the accuracy of product carbon footprints and avoid double counting of renewable attributes in Scope 2 accounting.
🏛政策担当者:Highlights the need for transparent residual mix factors to support credible green procurement and product carbon footprint standards.
📄 Abstract（原文）
Against the global transition toward sustainable energy systems and the rapid development of green electricity trading and green certificate systems, traditional regional average electricity emission factors are no longer sufficient to accurately reflect the carbon emission responsibilities associated with enterprises’ actual electricity consumption. This may lead to the double counting of renewable electricity attributes and the overestimation of emission reduction effects. To address this issue, this study focuses on electrical equipment products. Building upon the existing life-cycle accounting framework, a method for constructing provincial residual electricity emission factors coupled with green electricity and green certificate attribute verification mechanisms is proposed. By excluding non-fossil electricity volumes whose environmental attributes have already been claimed through market-based mechanisms, an accounting factor capable of characterizing the actual emission intensity of “residual electricity” is established, together with an accounting model for indirect electricity emissions during the production stage. Furthermore, eleven typical categories of electrical equipment, including transformers, electricity meters, conductors, and power cables, are selected to conduct an empirical cradle-to-gate carbon footprint analysis and evaluate their carbon reduction potential under a 50% green electricity substitution scenario. The results indicate that provincial residual electricity emission factors incorporating renewable electricity attributes can improve the accuracy and transparency of product carbon footprint accounting. This approach provides methodological support for sustainable manufacturing, green procurement, low-carbon supply chain management, and the development of product carbon footprint standards.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18147353first seen 2026-07-22 05:17:12
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。