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Streamlined column-based disaggregation method for carbon footprint quantification for multi-regional input–output (MRIO) models

多地域産業連関(MRIO)モデルのカーボンフットプリント定量化のための効率的な列ベース分割手法 (AI 翻訳)

Abdulrahman Bakindi, Jonathan Norman, Aoife Houlihan Wiberg, Stephen Allen

Journal of Industrial Ecology📚 査読済 / ジャーナル2026-06-18#炭素会計Origin: Global経営インパクト: 調達リスク対象セクター: manufacturing
DOI: 10.1007/s44498-026-00102-3
原典: https://doi.org/10.1007/s44498-026-00102-3
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🤖 gxceed AI 要約

日本語

本研究では、多地域産業連関(MRIO)モデルのカーボンフットプリント精度向上のため、列のみに焦点を当てた簡素化された分割手法を提案する。従来の行・列両方の分割に比べ、データ要件と技術的負担を大幅に削減する。EXIOBASE v3.9.5を用いて英国のセメント・石灰・石膏部門とアルミニウム部門に適用し、サブセクター間で炭素集約度に-50%から+220%のばらつきがあることを示した。本手法は、実務者がより正確な環境係数を得るための実用的な手段を提供する。

English

This study proposes a streamlined column-based disaggregation method for MRIO models to improve carbon footprint precision. Unlike conventional methods, it requires less data and reduces technical burden by focusing only on columns. Applied to EXIOBASE for Great Britain's cement and aluminum sectors, results show carbon intensity variations from -50% to +220%. This enables practitioners to obtain more accurate environmental coefficients with minimal effort.

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Scope3算定にMRIOが活用されており、本手法は産業連関表の分割負荷を軽減し、より精緻なカーボンフットプリントを可能にする。特にサプライチェーン排出量の算定精度向上に寄与し、SSBJや有報での開示要求に対応する企業にとって有用である。

In the global GX context

Globally, MRIO models are key for Scope 3 reporting under TCFD/ISSB and CSRD. This method lowers the barrier to using high-resolution carbon multipliers, enabling companies to report more accurate product-level footprints. It is especially relevant for industries with diverse product mixes within single sectors.

👥 読者別の含意

🔬研究者:Provides a computationally efficient alternative to full MRIO disaggregation, reducing data needs and reconciliation complexity.

🏢実務担当者:Enables obtaining refined carbon multipliers for products with minimal data, improving supply chain carbon reporting.

🏛政策担当者:Supports development of more accurate sectoral carbon intensity databases for policy analysis and regulation.

📄 Abstract(原文)

Abstract Multi-regional input–output (MRIO) models are a valuable source of data for environmental assessments. They encompass all products in an economy and capture the full inter-relationships of global supply chains. This provides a comprehensive set of environmental coefficients (e.g., kgCO 2 e) that are complete and free from truncation. However, the environmental coefficients in these models are highly aggregated, meaning all products within a sector share the same coefficient value. This can mis-represent the true environmental impacts of individual products. To rectify this, disaggregation methods may be employed to break down both the rows and columns in MRIO tables to obtain a more precise representation of products. However, the conventional disaggregation method is data-intensive, time-consuming, technically demanding, and requires complex reconciliation, which undermines efficiency and broader practical use. This study addresses this limitation and introduces a streamlined and data-efficient disaggregation method to derive sector-specific impact factors (multipliers). The method simplifies the disaggregation process by focusing solely on the columns. This results in a partial matrix augmentation (rectangular matrix) that yields refined subsector multipliers without requiring the full reconstruction of the MRIO system. Therefore, it requires less data than the typical disaggregation method, reduces technical burden, and eliminates the need for complex reconciliation techniques. The method was applied to the EXIOBASE database v3.9.5 2022 $$(\text{P}\times \text{P})$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>(</mml:mo> <mml:mtext>P</mml:mtext> <mml:mo>×</mml:mo> <mml:mtext>P</mml:mtext> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> for Great Britain (GB). With minimal data, the cement, lime, and plaster sector, as well as the aluminium and aluminium products sector, were disaggregated into subsectors. The results reveal variations ranging from − 50% to + 220% in total embodied carbon intensities. The method shows promise in streamlining disaggregation, enabling sustainability practitioners, corporations and policymakers to obtain more precise environmental coefficients for informed decision-making and guiding sustainability efforts.

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