Overview and recommendations for regionalized life cycle impact assessment

Chris Mutel (), Xun Liao, Laure Patouillard, Jane Bare, Peter Fantke, Rolf Frischknecht, Michael Hauschild, Olivier Jolliet, Danielle Maia de Souza, Alexis Laurent (), Stephan Pfister and Francesca Verones
Additional contact information
Chris Mutel: IPS - Institut Paul Scherrer
Xun Liao: EPFL - Ecole Polytechnique Fédérale de Lausanne
Laure Patouillard: CIRAIG - Centre international de référence sur l’analyse du cycle de vie et la transition durable - EPM - École Polytechnique de Montréal, IFPEN - IFP Energies nouvelles, ECO-PUB - Economie Publique - INRA - Institut National de la Recherche Agronomique - AgroParisTech
Jane Bare: United States Environmental Protection Agency [Cincinnati]
Peter Fantke: DTU - Danmarks Tekniske Universitet = Technical University of Denmark
Rolf Frischknecht: Treeze Ltd
Michael Hauschild: DTU - Danmarks Tekniske Universitet = Technical University of Denmark
Olivier Jolliet: University of Michigan [Ann Arbor] - University of Michigan System
Danielle Maia de Souza: University of Alberta, UQAM - Université du Québec à Montréal = University of Québec in Montréal
Alexis Laurent: DTU - Danmarks Tekniske Universitet = Technical University of Denmark
Stephan Pfister: Geological Institute [ETH Zürich] - D-ERDW - Department of Earth Sciences [Swiss Federal Institute of Technology - ETH Zürich] - ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
Francesca Verones: NTNU - Norwegian University of Science and Technology

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Abstract: Purpose Regionalized life cycle impact assessment (LCIA) has rapidly developed in the past decade, though its widespread application, robustness, and validity still face multiple challenges. Under the umbrella of UNEP/SETAC Life Cycle Initiative, a dedicated cross-cutting working group on regionalized LCIA aims to provide an overview of the status of regionalization in LCIA methods. We give guidance and recommendations to harmonize and support regionalization in LCIA for developers of LCIA methods, LCI databases, and LCA software. Methods A survey of current practice among regionalized LCIA method developers was conducted. The survey included questions on chosen method's spatial resolution and scale, the spatial resolution of input parameters, the choice of native spatial resolution and limitations, operationalization and alignment with life cycle inventory data, methods for spatial aggregation, the assessment of uncertainty from input parameters and model structure, and the variability due to spatial aggregation. Recommendations are formulated based on the survey results and extensive discussion by the authors. Results and discussion Survey results indicate that majority of regionalized LCIA models have global coverage. Native spatial resolutions are generally chosen based on the availability of global input data. Annual modeled or measured elementary flow quantities are mostly used for aggregating characterization factors (CFs) to larger spatial scales, although some use proxies, such as population counts. Aggregated CFs are mostly available at the country level. Although uncertainty due to input parameter, model structure, and spatial aggregation are available for some LCIA methods, they are rarely implemented for LCA studies. So far, there is no agreement if a finer native spatial resolution is the best way to reduce overall uncertainty. When spatially differentiated model CFs are not easily available, archetype models are sometimes developed. Conclusions Regionalized LCIA methods should be provided as a transparent and consistent set of data and metadata using standardized data formats. Regionalized CFs should include both uncertainty and variability. In addition to the native-scale CFs, aggregated CFs should always be provided and should be calculated as the weighted averages of constituent CFs using annual flow quantities as weights whenever available. This paper is an important step forward for increasing transparency, consistency, and robustness in the development and application of regionalized LCIA methods.

Keywords: variability; uncertainty; archetypes; impact assessment; regionalization; spatial differentiation; standardization (search for similar items in EconPapers)
Date: 2019-05
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Citations: View citations in EconPapers (7)

Published in International Journal of Life Cycle Assessment, 2019, 24 (5), pp.856-865. ⟨10.1007/s11367-018-1539-4⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02177362

DOI: 10.1007/s11367-018-1539-4

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