電力炭素フットプリント係数における不確実性のパラメータ別帰属：中国某省の石炭火力・水力発電所のケーススタディ
Parameter-Level Attribution of Uncertainty in Electricity Carbon Footprint Factors: A Case Study of Coal-Fired and Hydropower Plants in a Chinese Province (原題)
Han Zhang, Fuxiang Li, Yang Wei, Hongli Liu, Wei Tang, Lingyu Chen
🤖 gxceed AI 要約
日本語
中国某省の石炭火力4基・水力4基の2025年会計ワークブックをパラメトリックモデルに再構築し、モンテカルロ法と分散ベース感度指標で不確実性を測定起源と会計慣行に分解した。石炭火力では測定由来の95%区間が約−11%〜+12%で石炭投入が支配的だが、バックグラウンドDB選択も同程度に影響し、会計慣行の影響は区間半幅の30%未満だった。水力では区間がより広く、土木工作物の償却期間の統一だけで半幅の1.5〜2.8倍変動する。発電種別に応じたデータ収集と係数公表の差別化を提言する。
English
Rebuilding 2025 accounting workbooks for four coal and four hydropower plants in a Chinese province into parametric models, the study decomposes uncertainty via Monte Carlo and variance-based sensitivity indices. For coal plants the measurement-driven 95% interval is about −11% to +12%, dominated by coal input, while database choice shifts the factor comparably and accounting conventions by under 30% of the half-width. For hydropower, harmonizing the amortization horizon of civil works alone moves the factor 1.5–2.8 times the half-width, suggesting data collection and factor publication should differ by generation type.
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
Scope2算定の基礎となる電力排出係数の不確実性構造を可視化する研究で、SSBJ・有報でのScope2開示や再計算方針の設計に示唆を与える。日本では電力係数の公表精度が企業のGHG算定品質を左右するため、係数公開の粒度を議論する材料になる。
In the global GX context
Speaks directly to disclosure infrastructure: grid emission factors underpin Scope 2, market-based instruments, and CBAM. Separating measurement uncertainty from accounting-convention effects is a methodological contribution relevant to ISSB/CSRD factor-quality debates and to how jurisdictions publish electricity factors.
👥 読者別の含意
🔬研究者:Provides a replicable framework for attributing factor uncertainty to measurement versus convention, transferable to other grids and factors.
🏢実務担当者:Helps Scope 2 teams understand which portion of an electricity factor's uncertainty their own data collection can actually reduce.
🏛政策担当者:Suggests factor publication and data-collection requirements should be differentiated by generation type.
📄 Abstract（原文）
Provincial carbon footprint factors of electricity underpin product carbon footprints, green certificate trading, and carbon border adjustment, yet their uncertainty is usually reported as one aggregate interval that does not show which part better measurement could reduce and which part an accounting convention fixes. This case study examines eight plants in one Chinese province with original 2025 accounting workbooks (four coal-fired, four hydropower). Each is rebuilt into a normalized parametric model reproducing the original total. Measurable quantities are propagated by Monte Carlo sampling and apportioned with variance-based sensitivity indices; database choices and accounting conventions are enumerated as discrete scenarios and compared with, rather than added to, the probabilistic interval. For the coal-fired plants, the measurement-driven 95% interval is about −11% to +12%, dominated by coal input; the background database shifts the factor by a comparable amount, whereas every accounting convention shifts it by less than 30% of the interval half-width. For the hydropower plants, the interval is wider, yet harmonizing the amortization horizon of civil works alone moves the factor by 1.5 to 2.8 times that half-width. The findings are specific to the sample and suggest differentiating data collection and factor publication by generation type.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/en19225458first seen 2026-11-14 05:17:18
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