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Representativeness of environmental impact assessment methods regarding Life Cycle Inventories

Authors :
Antoine Esnouf
Jean-Philippe Steyer
Arnaud Hélias
Eric Latrille
Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE)
Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)
Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Pôle ELSA, Environmental Life Cycle and Sustainability Assessment (ELSA)
Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)
Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
GreenAlgOhol ANR-14-CE05-0043
ANR-14-CE05-0043,GreenAlgOhol,Evaluation des potentialités d'une filière de macroalgues vertes cellulosiques pour la production de bioethanol – preuve de concept technique et durabilité(2014)
Source :
Science of the Total Environment, Science of the Total Environment, Elsevier, 2018, 621, pp.1264-1271. ⟨10.1016/j.scitotenv.2017.10.102⟩
Publication Year :
2018
Publisher :
Elsevier BV, 2018.

Abstract

International audience; 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.

Details

ISSN :
00489697 and 18791026
Volume :
621
Database :
OpenAIRE
Journal :
Science of The Total Environment
Accession number :
edsair.doi.dedup.....3641e65a372a54e87b799f5e76a49de0