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<p>Environmentally extended multi-regional input–output (EEMRIO) analysis provides a robust methodology for assessing economic, social, and environmental footprints across nations and regions. Increasing its geographical resolution is essential for addressing local environmental issues and informing targeted policy decisions. While subnational EEMRIOs ideally rely on survey data, such data are often unavailable or resource-intensive to process. As a result, partitioners resort to proxies and algorithms. Yet, the transparency of these algorithms and the underlying data are often suboptimal. Here, we present a novel, open-source, top-down regionalization approach applicable to any EEMRIO database. Our method builds on location quotients (LQ), extending their application to a multi-regional framework. This extension ensures calculations remain traceable, eliminates the need for supplemental balancing procedures, and requires minimal, readily available additional proxy data, making it highly accessible for practitioners. Using European steel trade as a proof-of-concept, we demonstrate how this approach assesses local impacts, highlights local–global trade interactions, and identifies opportunities that national IO data often obscure.</p>

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An open-source regionalization approach for subnational EEMRIO insights and proof-of-concept application to EU steel circularity

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月20日

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  • Anniek J. Kortleve,
  • Nicolas Navarre,
  • Paul Behrens,
  • Hale Cetinay,
  • Franco Donati,
  • Benjamin Sprecher,
  • Arnold Tukker,
  • José M. Mogollón

摘要

Environmentally extended multi-regional input–output (EEMRIO) analysis provides a robust methodology for assessing economic, social, and environmental footprints across nations and regions. Increasing its geographical resolution is essential for addressing local environmental issues and informing targeted policy decisions. While subnational EEMRIOs ideally rely on survey data, such data are often unavailable or resource-intensive to process. As a result, partitioners resort to proxies and algorithms. Yet, the transparency of these algorithms and the underlying data are often suboptimal. Here, we present a novel, open-source, top-down regionalization approach applicable to any EEMRIO database. Our method builds on location quotients (LQ), extending their application to a multi-regional framework. This extension ensures calculations remain traceable, eliminates the need for supplemental balancing procedures, and requires minimal, readily available additional proxy data, making it highly accessible for practitioners. Using European steel trade as a proof-of-concept, we demonstrate how this approach assesses local impacts, highlights local–global trade interactions, and identifies opportunities that national IO data often obscure.