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Incorporating linear programing and life cycle thinking into environmental sustainability decision-making: a case study on anchovy canning industry
Authors:I Garcia-Herrero  J Laso  M Margallo  A Bala  C Gazulla  P Fullana-i-Palmer  I Vázquez-Rowe  A Irabien  R Aldaco
Affiliation:1.Departamento de Ingenierías Química y Biomolecular,Universidad de Cantabria,Santander,Spain;2.UNESCO Chair in Life Cycle and Climate Change, Escola Superior de Comer? Internacional (ESCI),Universitat Pompeu Fabra (UPF),Barcelona,Spain;3.Lavola Cosostenibilidad. Rbla,Barcelona,Spain;4.Peruvian LCA Network, Department of Engineering,Pontificia Universidad Católica del Perú,San Miguel,Peru
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.
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