Hybrid Application of LCA to Analyze the Global Warming Potential of Food Supply Chain

Abstract

Life cycle assessment (LCA) is one of the best, most practical, and most standardized approaches for evaluating the environmental consequences of a food supply chain (FSC). It covers a comprehensive range of impact categories in which the global warming potential (GWP) is the main impact category that is included in almost all LCA’s impact assessment methodologies. LCA has been applied to investigate the GWP of various FSCs worldwide. Recent studies show that the hybrid application of LCA is more powerful than single LCA. LCA can be combined with other methodologies to model, and optimize processes and decision-making purposes as well. In this regard, LCA has been coupled with mathematical approaches (regression, Cobb–Douglas, and data envelopment analysis), artificial-based intelligence (artificial neural networks, adaptive neuro-fuzzy based interface, particle swarm optimization, and genetic algorithms), and multi-criteria decision making (analytic hierarchy process, and fuzzy analytic hierarchy process). This chapter provides the relevant literature regarding the joint application of LCA in analyzing the GWP effects of FSCs, along with the pros and cons of hybrid approaches.