4.7 Article

Life cycle sustainability decision-support framework for ranking of hydrogen production pathways under uncertainties: An interval multi-criteria decision making approach

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 175, Issue -, Pages 222-236

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2017.12.070

Keywords

Life cycle sustainability assessment; Hydrogen production; Multi-criteria decision making; Interval decision making; Uncertainties

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Hydrogen as a clean energy carrier has been recognized as a promising alternative for emissions mitigation and environmental protection. Life cycle sustainability assessment (LCSA) of hydrogen can help the decision-makers/stakeholders to select the most sustainable pathway for hydrogen production in life cycle perspective among several alternatives. This study aims at developing a life cycle sustainability decision-support framework for ranking hydrogen production pathways by combining LCSA and interval multi-criteria decision making (MCDM) method. A novel interval MCDM method which can handle interval numbers in the decision-making matrix was developed by combining the improved decision-making trial and evaluation laboratory (DEMATEL) and interval evaluation based on distance from average solution (EDAS). Four pathways for hydrogen production, including coal gasification (CG), stream reforming of methane (SMR), biomass gasification (BG), and wind turbine electrolysis (WEL), have been studied by the proposed method. BG was recognized as the most sustainable one among these four scenarios, following by SMR, WEL, and CG in the descending order. Sensitivity analysis was carried out to investigate the effects of the weights of the indicators for sustainability assessment on the final ranking. The interval sum weighted method (ISWM) and interval TOPSIS method were also employed to validate the results determined by the proposed interval EDAS in this study and the results reveal that BG was recognized as the most sustainable scenario by all these three methods. (C) 2017 Elsevier Ltd. All rights reserved.

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