Incorporating linear programing and life cycle thinking into environmental sustainability decision-making: a case study on anchovy canning industry
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Abstract
Life cycle assessment (LCA) is a powerful tool to support environmental informed decisions among product and process alternatives. LCA results reflect the process stage contributions to several environmental impacts, which should be made mutually comparable to help in the decision-making process. Aggregated environmental indexes enable the translation of this set of metrics into a one final score, by defining the attached weights to impacts. Weighting values reflect the corresponding relevance assigned to each environmental impact. Current weighing schemes are based on pre-articulation of preferences, without considering the specific features of the system under study. This paper presents a methodology that combines LCA methodology and linear programming optimisation to determine the environmental improvement actions that conduct to a more sustainable production. LCA was applied using the environmental sustainability assessment methodology to obtain two main indexes: natural resources (NR) and environmental burdens (EB). Normalised indexes were optimised to determine the optimal joint of weighting factors that lead to an optimised global Environmental Sustainability Index. The proposed methodology was applied to a food sector, in particular, to the anchovy canning industry in Cantabria Region (Northern Spain). By maximising the objective function composed of NR and EB variables, it is possible to find the optimal joint of weights that identify the best environmental sustainable options. This study proves that LCA can be applied in combination with linear programing tools as a part of the decision-making process in the development of more sustainable processes and products.
Keywords
Anchovy Canning industry Life cycle assessment Optimisation Linear programingNotes
Acknowledgements
Authors thank to Ministry of Economy and Competitiveness of Spanish Government for the financial support through the project GeSAC-Conserva (CTM2013-43539-R). Jara Laso also thanks to the Ministry of Economy and Competitiveness of Spanish Government for the financial support through the research fellowship BES-2014-069368.
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