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Elementary flow mapping across life cycle inventory data systems: A case study for data interoperability under the Global Life Cycle Assessment Data Access (GLAD) initiative. | LitMetric

Purpose: Limited availability of life cycle assessment (LCA) data poses a significant challenge to its mainstream adoption, rendering it a central issue within the LCA community. The Global LCA Data Access (GLAD) network aims to increase the accessibility and interoperability of LCA data and offers benefits for different use cases. GLAD is an intergovernmental collaboration involving different stakeholders organized into working groups. The GLAD Nomenclature Working Group (NWG) developed a procedure and a set of criteria to map elementary flows among major nomenclature systems and reviewed bidirectional mappings. This paper provides an overview of the methodological approach followed by the NWG to achieve the resulting mapping files.

Methods: The mapping procedure involves several steps of flow and compartment matches and bilateral review. The procedure is supported by an ad hoc software tool called the "GLAD Mapper Tool" developed with the NWG and which is made available for free by the European Commission. The input files for the procedure are the properly formatted source and target flow lists and a file containing the mapping criteria. The four nomenclature systems mapped are those used in ecoinvent, Environmental Footprint, IDEA, and the U.S. Federal LCA Commons. The procedure included representatives from each of these nomenclature systems to ensure a multilateral agreement on the approach to verifying and assessing the quality of the results. The iterative mapping process included different stages of bidirectional reviews to achieve a balance between mapping coverage (i.e., percentage of source flows covered by the target list) and accuracy.

Results And Discussion: The mapping procedure proved to be an efficient approach for LCA practitioners in mappings between different nomenclature systems. After a relatively low number of iterations, mapping coverages higher than 90% were achieved, which is driven by the availability of unique substances (flow names) and the granularity of environmental compartments. Overall, none of the four flow lists achieved full coverage and the use of approximated matches (proxy matches) for environmental compartments and/or substances was necessary when a perfect matches between flows were not possible.

Conclusions: The NWG's mapping activities may serve as a starting point towards defining a central hub for mapping impact assessment methods and datasets, improving data accessibility and interoperability for the LCA community as a step towards defining a unified nomenclature system. The GLAD mapping approach is open and transparent. The approach fosters traceability in the mapping process and offers the potential for greater interoperability across the LCA community, underlining the commitment to openness and collaboration.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11684518PMC
http://dx.doi.org/10.1007/s11367-024-02286-xDOI Listing

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