Literature DB >> 29055597

Representativeness of environmental impact assessment methods regarding Life Cycle Inventories.

Antoine Esnouf1, Éric Latrille2, Jean-Philippe Steyer2, Arnaud Helias3.   

Abstract

Life Cycle Assessment (LCA) characterises all the exchanges between human driven activities and the environment, thus representing a powerful approach for tackling the environmental impact of a production system. However, LCA practitioners must still choose the appropriate Life Cycle Impact Assessment (LCIA) method to use and are expected to justify this choice: impacts should be relevant facing the concerns of the study and misrepresentations should be avoided. This work aids practitioners in evaluating the adequacy between the assessed environmental issues and studied production system. Based on a geometrical standpoint of LCA framework, Life Cycle Inventories (LCIs) and LCIA methods were localized in the vector space spanned by elementary flows. A proximity measurement, the Representativeness Index (RI), is proposed to explore the relationship between those datasets (LCIs and LCIA methods) through an angular distance. RIs highlight LCIA methods that measure issues for which the LCI can be particularly harmful. A high RI indicates a close proximity between a LCI and a LCIA method, and highlights a better representation of the elementary flows by the LCIA method. To illustrate the benefits of the proposed approach, representativeness of LCIA methods regarding four electricity mix production LCIs from the ecoinvent database are presented. RIs for 18 LCIA methods (accounting for a total of 232 impact categories) were calculated on these LCIs and the relevance of the methods are discussed. RIs prove to be a criterion for distinguishing the different LCIA methods and could thus be employed by practitioners for deeper interpretations of LCIA results.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Angular distance; Dimension reduction; LCA; Life Cycle Impact Assessment method; Life Cycle Inventory; Representativeness

Year:  2017        PMID: 29055597     DOI: 10.1016/j.scitotenv.2017.10.102

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

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Journal:  Sensors (Basel)       Date:  2021-10-29       Impact factor: 3.576

2.  Influence of the Composition on the Environmental Impact of Soft Ferrites.

Authors:  Patricia Gómez; Daniel Elduque; Carmelo Pina; Carlos Javierre
Journal:  Materials (Basel)       Date:  2018-09-20       Impact factor: 3.623

  2 in total

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