Correlations in Life Cycle Impact Assessment methods (LCIA) and indicators for construction materials: What matters?. (August 2016)

• Record Type: Journal Article
• Authors: Lasvaux, S.; Achim, F.; Garat, P.; Peuportier, B.; Chevalier, J.; Habert, G.
• Is Part Of: Ecological indicators. Volume 67(2016)
• Page Start: 174
• Page End: 182
• Publication Date: 2016-08
• Subjects: Life Cycle Impact Assessment (LCIA) indicators -- Statistical correlations -- Principal component analysis -- Construction materials -- Buildings; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2016.01.056
• Languages: English
• ISSNs: 1470-160X

Abstract

Graphical abstract: Highlights: In this study, a principal component analysis (PCA) with a varimax rotation is conducted for six Life Cycle Impact Assessment (LCIA) methods on a large set of Life Cycle Inventory (LCI) data of construction materials. Results of the PCA with varimax showed that between 4–6 components are sufficient to explain the original indicators. A clear distinction of cluster of LCA indicators is found and similarities among existing LCIA methods are shown. The results are similar when applied at the building scale. A sensitivity analysis on a selected set of 5 LCI flows still show 5 components after the PCA highlighting that may be possible to have uncorrelated indicators or flows in the LCIA methods. Abstract: Different Life Cycle Impact Assessment (LCIA) methods have been developed over the past twenty years. While the use of a single score indicator may, on the one hand, ease the decision making it may also induce a loss of information. On the other hand, the use of a large set of environmental indicators may increase the difficulty of decision making due to the high number of parameters. In this paper, a statistical methodology is used to identify a simplified set of environmental indicators. This methodology applies Principal Component Analysis (PCA) to five LCIA methods (CML'01, Eco-indicator99, IMPACT 2002+, ecological scarcity, EPD) using a building products database. For each method, the results show that only 4–6 dimensions are sufficient to explain at least 90–95% of the variance for each set of indicators. They refer to the following environmental themes: fossil-fuel consumption, ecotoxicity, ionising radiation, land use and mineral resources. The use of a selected set of five LCI flows is found to be as relevant as current LCIA methods from a statistical point of view. Furthermore, PCA applied to a building LCA case study shows similar trends as for the database results. Further studies are now needed to confirm these findings for going towards simplified structural relationships among LCIA indicators for building materials.