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The primary data share indicator for supply chain specificity in product carbon footprinting

製品カーボンフットプリントにおけるサプライチェーン特異性のための一次データシェア指標 (AI 翻訳)

Peter Holzapfel, Vanessa Bach, Florian Ansgar Jaeger, Matthias Finkbeiner

Ecological Indicators📚 査読済 / ジャーナル2024-08-30#炭素会計Origin: EU経営インパクト: 調達リスク対象セクター: cross_sector
DOI: 10.1016/j.ecolind.2024.112435
原典: https://doi.org/10.1016/j.ecolind.2024.112435

🤖 gxceed AI 要約

日本語

本論文は、製品カーボンフットプリント(PCF)の特異性を表す一次データシェア(PDS)指標を初めて体系的に分析する。Pathfinder/Catena-X/Together for Sustainabilityの3つの業界イニシアチブの定義を比較し、負の排出や多出力プロセス、マスバランス/ブック・アンド・クレームに関する課題を指摘。具体的な解決策を提案しており、実務的な示唆に富む。

English

This paper provides the first systematic analysis of the primary data share (PDS) indicator for product carbon footprint specificity. It compares definitions from Pathfinder, Catena-X, and Together for Sustainability, highlighting challenges around negative emissions, multi-output processes, and mass-balance/book-and-claim models. Potential solutions are proposed, offering practical guidance for companies reporting PCFs.

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

日本ではサプライチェーン排出量の開示が進み、PCFの信頼性が問われている。本論文のPDS指標は、日本企業がサプライヤーからの一次データ収集や開示の質を高める上で参考になる。また、国際的なイニシアチブとの整合性を確認する上でも有益。

In the global GX context

The study addresses a key gap in carbon accounting as global frameworks such as the Pathfinder Framework, CSRD, and Scope 3 reporting require credible product-level data. It informs how companies can increase PCF specificity and avoid double counting. Useful for standard-setters and industry initiatives developing data-sharing rules.

👥 読者別の含意

🔬研究者:Provides a research agenda for PDS standardization and unresolved methodological issues.

🏢実務担当者:Offers practical guidance for selecting PDS calculation methods and communicating product footprint specificity.

🏛政策担当者:Highlights the need for consistent definitions in carbon accounting standards to enable interoperable data sharing.

📄 Abstract（原文）

• First analysis of the primary data share (PDS) as an indicator for product carbon footprint specificity. • Consistent PDS calculation of PCFs involving negative emission require further definitions. • Further definition required regarding multi-output processes and market-based chain of custody models. • Potential double counting challenges of primary and secondary data require further investigation. Ongoing industry initiatives like Pathfinder / Partnership for Carbon Transparency from the World Business Council for Sustainable Development, Catena-X from the automotive industry, and Together for Sustainability from the chemical industry advocate for sharing primary product carbon footprint (PCF) data along the supply chain to increase specificity. All three initiatives agree on requesting a primary data share (PDS) alongside the PCF. The PDS as an indicator of PCF specificity has not yet been addressed in scientific literature. To address this gap, this research analyzes the PDS definitions and demonstrates remaining challenges and gaps for further research by means of a hypothetical case study. While the definitions for PDS calculations with exclusively positive PCF contributions are consistent across the three initiatives, the definitions differ regarding negative PCF contributions. Further, the definitions of negative emissions do not explicitly specify the system boundaries for PDS calculations. Different system boundary choices can influence PDS results. In addition, challenges regarding the PDS calculation of multi-output processes as well as products which have been modeled using the mass balance – credit method or book and claim are identified. We provide potential solutions to these challenges which can serve as a basis for further research and specification on the PDS calculation. Primary data potentially reflects “real” emissions in a product-specific supply chain more accurately than secondary data. Thus, the PDS is a relevant indicator for the reporting company. Nevertheless, conflicts of interest can occur between achieving a low PCF and high PDS.

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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。