Meta-comparisons: how to compare methods for LCA?

The International Journal of Life Cycle Assessment, vol. 27, pp. 993–1015

Abstract

Abstract Introduction Many methodological papers report a comparison of methods for LCA, for instance comparing different impact assessment systems, or developing streamlined methods. A popular way to do so is by studying the differences of results for a number of products. We refer to such studies as quasi-empirical meta-comparisons. Review of existing approaches A scan of the literature reveals that many different methods and indicators are employed: contribution analyses, Pearson correlations, Spearman correlations, regression, significance tests, neural networks, etc. Critical discussion We critically examine the current practice and conclude that some of the widely used methods are associated with important deficits. A new approach Inspired by the critical analysis, we develop a new approach for meta-comparative LCA, based on directional statistics. We apply it to several real-world test cases, and analyze its performance vis-à-vis traditional regression-based approaches. Conclusion The method on the basis of directional statistics withstands the tests of changing the scale and unit of the training data. As such, it holds a promise for improved method comparisons.

Authors 2

1. Reinout Heijungs corresponding Aachen Institute of Environmental Sciences (CML)

   Leiden University · Vrije Universiteit Amsterdam

   Affiliation as printed

   Department of Operations Analytics, Vrije Universiteit, Amsterdam, The Netherlands

   Institute of Environmental Sciences, Leiden University, Leiden, The Netherlands

2. Erik Dekker

   National Institute for Public Health and the Environment

   Affiliation as printed

   National Institute for Public Health and the Environment, Bilthoven, The Netherlands