Primary data share indicator for social life cycle assessment
ソーシャルライフサイクルアセスメントのための一次データシェア指標 (AI 翻訳)
Lindsey Roche, Peter Holzapfel, Matthias Finkbeiner
🤖 gxceed AI 要約
日本語
本研究は、プロダクトカーボンフットプリントの一次データシェア(PDS)を社会LCAに拡張し、データ特異性を評価する3つの指標(PDS、サイト別データシェア、企業別データシェア)を提案。チリのリチウム生産のフォアグラウンドシステムに適用し、全体でPDS 32%、SDS 50%、CDS 95%を達成した。データ透明性向上による一次データ利用促進が狙い。
English
This study extends the primary data share (PDS) indicator from product carbon footprinting to social LCA, proposing three data specificity indicators (PDS, site-specific, and company-specific). Applied to lithium production in Chile, the foreground system achieved PDS of 32%, SDS of 50%, and CDS of 95%. The indicators enhance transparency on data quality and encourage use of specific data in S-LCA.
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
社会LCAのデータ品質透明化は、日本企業のサステナビリティ報告における非財務情報の信頼性向上に資する手法。SSBJ等の気候中心の開示とは距離があるが、サプライチェーン上の社会的影響評価に関心のある企業には参考になる。
In the global GX context
This work adds to global sustainability assessment scholarship by transferring carbon footprint data transparency tools to social LCA. The proposed indicators could complement corporate sustainability reporting frameworks (e.g., CSRD, GRI) that increasingly demand primary data and supply-chain specificity.
👥 読者別の含意
🔬研究者:Provides a transferable methodology for quantifying data specificity in S-LCA, with application in lithium production.
🏢実務担当者:For LCA and sustainability teams, offers clear indicators to increase data transparency in social assessments.
📄 Abstract（原文）
Social life cycle assessment (S-LCA) is a methodology to assess social impacts of products and organizations from a life cycle perspective, but data specificity and quality vary, and transparency regarding these aspects is often lacking. The product carbon footprint (PCF) industry initiatives have recently developed the primary data share (PDS) indicator to assess supply chain specificity and encourage primary data usage to better reflect specific emissions. This concept extends to social impacts, where site-specific data better reflects actual social impacts than generic data, which only indicates social risk. To transfer this concept to S-LCA, primary and site-specific data definitions were reviewed from various sustainability guidelines and three indicators were proposed: primary data share (PDS S-LCA ), site-specific data share (SDS S-LCA ), and company-specific data share (CDS S-LCA ). These indicators were then applied to a case study on the foreground system of lithium production in Chile. Differences in the data specificity indicators were seen between the considered stakeholder groups. The Local community surrounding the lithium mining production site had the highest PDS (48%) due to a strong focus on interview-based primary data collection for this stakeholder. The CDS was above 90% for all stakeholder groups due to high data availability for secondary, company-specific data. Overall, the PDS S-LCA was 32%, 50% for SDS S-LCA , and reached 95% for CDS S-LCA . The proposed data specificity indicators were found to be applicable within the case study and increased transparency on data specificity, thereby encouraging increased use of primary and site- or company-specific data to more accurately reflect actual social impacts. • Primary data share adapted from carbon footprinting to social life cycle assessment. • Data specificity indicators increase transparency on this aspect of data quality. • Transparency encourages the use of specific data in social life cycle assessment.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.jclepro.2025.145051first seen 2026-08-02 17:33:25
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