Abstract

The study objectives are twofold: (i) combining the life cycle sustainability assessment (LCSA) framework and the multicriteria decision-making (MCDM) methodology for sustainability assessment and (ii) determining the most sustainable scenario for bioethanol production in China according to the preferences of the decision-makers/stakeholders. Life cycle assessment (LCA), life cycle costing (LCC), and social life cycle assessment (SLCA) are combined to collect the corresponding criteria data on environmental, economic, and social aspects, respectively. The study develops a novel SLCA method for quantifying the social criteria. The decision-makers/stakeholders can use linguistic terms to assess these criteria, and fuzzy theory is used to transform the linguistic variables into real numbers. Once the sustainability assessment criteria are determined, the study develops an MCDM method that combines the analytic hierarchy process (AHP) and the VIKOR method to prioritize the alternatives. The AHP is used to determine the criteria weights that are a prerequisite when using VIKOR; the VIKOR method is then used to determine the sustainability sequence of the scenarios. The study’s proposed method investigates an illustrative case about three alternative bioethanol production scenarios (wheat-based, corn-based, and cassava-based): The prior sequence (based on the sustainability performances) in descending order is cassava-based, corn-based, and wheat-based. The proposed methodology results allow Chinese decision-makers/stakeholders to select the most sustainable scenario among many alternatives. The proposed methodology is generic, meaning that further alternatives can be studied and the most sustainable option can be ultimately determined. The main study contribution is to test the combination of an MCDM methodology and LCSA for sustainability decision-making by studying three alternative pathways for bioethanol production in China. The proposed method feasibly enables the decision-makers/stakeholders to find the most sustainable scenario to achieve their objectives among various alternatives.

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