Integrating life-cycle assessment and multi-criteria decision analysis to compare alternative biodiesel chains

• Published in: Annals of operations research 2022-05, Vol.312 (2), p.1359-1374
• Main Authors: Dias, Luis C., Passeira, Carolina, Malça, João, Freire, Fausto
• Format: Article
• Language: English
• Subjects: Alternative fuels; Biodiesel fuels; Biofuels; Business and Management; Chains; Combinatorics; Comparative analysis; Decision analysis; Environmental assessment; Environmental impact; Fossil fuels; Life cycle assessment; Mcdm-Sd; Multiple criteria decision making; Multiple criterion; Operations research; Operations Research/Decision Theory; Production management; Rapeseed; Theory of Computation; Transesterification; Transportation industry; Weighting
• ISSN: 0254-5330; 1572-9338
• DOI: 10.1007/s10479-016-2329-7

The transport sector is highly dependent on fossil fuels with significant environmental impacts. This motivates the environmental assessment of alternative fuel options, including biodiesel based on agricultural crops. The assessment of biofuel alternatives for transportation can be facilitated by the integration of Life-Cycle Assessment (LCA) and Multi-Criteria Decision Analysis (MCDA). In this article, we compare four Rapeseed Methyl Ester biodiesel production chains, corresponding to four different feedstock origins. The environmental impact of each chain is assessed in the context of a LCA encompassing cultivation, transportation to Portugal, extraction and transesterification. We apply two different MCDA additive aggregation methodologies to aggregate various impact categories resulting from the Life Cycle Impact Assessment (LCIA) phase of the LCA. The chosen MCDA methodologies, Stochastic Multicriteria Analysis and Variable Interdependent Parameter Analysis, are two complementary approaches to address one of the main difficulties of MCDA: setting the relative weights of the evaluation criteria. Indeed, weighting the various impacts in the LCIA phase is a controversial issue in LCA research and studies. The LCIA–MCDA approach proposed in this work does not require choosing a specific weighting vector, seeking to assess which conclusions are robust given some freedom allowed in the choice of weights. To study further the robustness of the conclusions concerning the choice of the criteria, the effects of removing one criterion are analyzed, one at a time.