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Purpose <p>Life Cycle Impact Assessment (LCIA) has traditionally applied characterization factors (CFs) to elementary flows in isolation, treating impacts as fixed properties of substances, regardless of where and how they occur within the life cycle product system. While recent advances have introduced regionalized LCIA methods and GIS-based spatial modeling frameworks, these remain difficult to operationalize in routine assessments and are often limited to differentiation at the elementary flow level. This paper presents a methodological advancement in LCIA: the application of CFs at the level of exchanges—the resolved biosphere and technosphere flows between processes.</p> Methods <p>Shifting the CF unit from elementary flows to exchanges enables CFs to reflect the full context of each exchange, including the geographic origin and destination, the identity of the emitting process and environmental recipient, and prospective, scenario-dependent parameters. The method offers a flexible, intermediate solution between traditional elementary flow-based LCIA and full spatially explicit models, supporting national and subnational regionalization without requiring high-resolution GIS integration.</p> Results <p>The approach is implemented in the open-source Python library <i>edges</i>, which extends the <i>Brightway</i> LCA framework to support exchange-specific and symbolic CFs. We illustrate its capabilities through four applications: 1) Regionalized LCIA, using the AWARE water scarcity method with dynamic handling of region aggregation and disaggregation; 2) Technosphere-based LCIA, via a new implementation of the GeoPolRisk indicator, which assigns CFs based on country-to-country commodity trade relationships; and scenario-sensitive prospective LCIAs, enabling alignment with climate scenarios, where CFs are defined by symbolic expressions that depend on scenario-specific variables, with application 3) focusing on global warming potential based on atmospheric gas concentration, and application 4) addressing fossil resource scarcity through dynamic fossil fuels extraction rates.</p> Conclusions <p>Together, these examples demonstrate how exchange-resolved LCIA expands the methodological space of impact modeling, offering a scalable, exchange-aware framework for regional, relational, and future-oriented life cycle assessments.</p>

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Contextual LCIA without the overhead: an exchange-based framework for flexible impact assessment

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月13日

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  • Romain Sacchi,
  • Alvaro Hahn Menacho,
  • Georg Seitfudem,
  • Maxime Agez,
  • Joanna Schlesinger-Martinat,
  • Anish Koyamparambath,
  • Jair Santillan Saldivar,
  • Philippe Loubet,
  • Christian Bauer

摘要

Purpose

Life Cycle Impact Assessment (LCIA) has traditionally applied characterization factors (CFs) to elementary flows in isolation, treating impacts as fixed properties of substances, regardless of where and how they occur within the life cycle product system. While recent advances have introduced regionalized LCIA methods and GIS-based spatial modeling frameworks, these remain difficult to operationalize in routine assessments and are often limited to differentiation at the elementary flow level. This paper presents a methodological advancement in LCIA: the application of CFs at the level of exchanges—the resolved biosphere and technosphere flows between processes.

Methods

Shifting the CF unit from elementary flows to exchanges enables CFs to reflect the full context of each exchange, including the geographic origin and destination, the identity of the emitting process and environmental recipient, and prospective, scenario-dependent parameters. The method offers a flexible, intermediate solution between traditional elementary flow-based LCIA and full spatially explicit models, supporting national and subnational regionalization without requiring high-resolution GIS integration.

Results

The approach is implemented in the open-source Python library edges, which extends the Brightway LCA framework to support exchange-specific and symbolic CFs. We illustrate its capabilities through four applications: 1) Regionalized LCIA, using the AWARE water scarcity method with dynamic handling of region aggregation and disaggregation; 2) Technosphere-based LCIA, via a new implementation of the GeoPolRisk indicator, which assigns CFs based on country-to-country commodity trade relationships; and scenario-sensitive prospective LCIAs, enabling alignment with climate scenarios, where CFs are defined by symbolic expressions that depend on scenario-specific variables, with application 3) focusing on global warming potential based on atmospheric gas concentration, and application 4) addressing fossil resource scarcity through dynamic fossil fuels extraction rates.

Conclusions

Together, these examples demonstrate how exchange-resolved LCIA expands the methodological space of impact modeling, offering a scalable, exchange-aware framework for regional, relational, and future-oriented life cycle assessments.