Visualizing the Effects of Parameter Variability on Comparative LCA Results

Abstract

Bar charts and other usual ways of presenting LCA results depict one average or typical situation, lacking to represent the diversity of individual cases and the uncertainties associated to input data or modelling assumptions. This paper presents ways of visualizing variable results in comparative LCA. The main concept is to perform at once calculations representing this variability. Based on Monte Carlo analysis, the approach is enabled by the LCA software RangeLCA, developed by RDC Environment. Results of all simulations can be plotted in function of one or two influential parameters. A clear and complete view can hence be obtained as well as more reliable conclusions. Instead of answering the question “Is a system better than another one in specific cases?”, the presented graphs help LCA studies to answer a much broader question: “In which range of situations is a system better than another?”.