強制開示データから惑星境界に導かれた組織的意思決定へ
From mandatory disclosure data to organisational decision-making guided by planetary boundaries. (原題)
D. Déda, Helena Gervásio, M. Quina, M. Hauschild, Anders Björn
🤖 gxceed AI 要約
日本語
EUのCSRD/ESRS強制開示データを出発点に、環境フットプリント手法で惑星境界内の絶対環境持続可能性評価(AESA)を行う統合枠組みを提示。コインブラ大学のケースでは、平等主義的配分で鉱物枯渇・土地利用・粒子状物質・気候変動が配分容量を超過し、功利主義的配分では超過幅が約4分の1に縮小したが問題の順位は不変。総影響の88%超が上流バリューチェーン由来で、優先課題は運用効率から調達ガバナンスへ移る。
English
The study builds an integrated framework that uses mandatory EU CSRD/ESRS disclosure data as the starting point for an Absolute Environmental Sustainability Assessment via the Environmental Footprint Method. A University of Coimbra case shows transgressions in mineral depletion, land use, particulate matter, and climate change under egalitarian allocation; utilitarian allocation cuts exceedance magnitudes ~fourfold without changing the ranking. Over 88% of impacts originate upstream, shifting priorities from operational efficiency to procurement governance.
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
SSBJ基準や有報でのサステナビリティ開示が進む日本企業にとって、開示データを絶対的環境評価・調達ガバナンスへ接続する実装例として示唆が大きい。特にScope3上流影響の管理と、透明性報告から絶対的持続可能性ガバナンスへの規制進化を考える上で参考になる。
In the global GX context
This work directly addresses the gap between CSRD/ESRS compliance reporting and science-based absolute sustainability assessment, offering a pathway from transparency-based disclosure toward planetary-boundary governance. It is highly relevant to ISSB/TCFD-aligned disclosure scholarship seeking to connect reported data to environmental limits and value-chain accountability.
👥 読者別の含意
🔬研究者:開示データと惑星境界科学を接続するAESA手法の実装例として、配分原理の感度分析とバリューチェーン影響評価の研究に有用。
🏢実務担当者:既存のCSRD/ESRS開示データを活用し、調達ガバナンスと上流サプライチェーン管理を優先する意思決定に転換する示唆を提供。
🏛政策担当者:透明性ベースの報告から絶対的持続可能性ガバナンスへの規制進化が技術的・運用的に可能であることを示す。
📄 Abstract(原文)
Organisations currently lack operational methods to assess how their activities contribute to returning society to within Earth's safe operating space, considering that seven of the nine planetary boundaries are currently exceeded. Although the mandatory Corporate Sustainability Reporting Directive of the European Union generates extensive compliance data, these disclosures remain disconnected from planetary boundary science. In this context, the study addresses two key knowledge gaps: (i) the methodological disconnect between mandatory sustainability reporting requirements and science-based environmental impact assessment frameworks, and (ii) the absence of implementation pathways in real organisational contexts. To bridge these gaps, an integrated framework was developed that exclusively uses mandatory European Sustainability Reporting Standards disclosure data as a starting point for an Absolute Environmental Sustainability Assessment following the Environmental Footprint Method. A case study focusing on the University of Coimbra demonstrates the framework. Results reveal significant environmental transgressions that are sensitive to the allocation principle applied. Under egalitarian allocation, impacts related to mineral depletion, land use, particulate matter, and climate change exceeded allocated capacity. Under the utilitarian allocation approach, the absolute magnitudes of exceedances decreased by about fourfold, while the ranking of the environmental problems remained the same. More than 88% of total environmental impacts originated from upstream value chain activities. This finding shifts sustainability priorities away from a narrow focus on operational efficiency towards procurement governance, particularly for infrastructure, equipment, food, and mobility. The study demonstrates that organisations already collecting compliance data possess the underlying data required for Absolute Environmental Sustainability Assessment, suggesting that an evolution in sustainability regulation, from transparency-based reporting towards absolute sustainability governance, is both technically achievable and operationally feasible.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1016/j.jenvman.2026.131033first seen 2026-10-12 05:26:36 · last seen 2026-10-14 05:56:05
🔔 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。