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dc.contributor.authorGarcía Herrero, María Isabel 
dc.contributor.authorLaso Cortabitarte, Jara 
dc.contributor.authorMargallo Blanco, María 
dc.contributor.authorBala Gala, Alba
dc.contributor.authorGazulla Santos, Cristina
dc.contributor.authorFullana i Palmer, Pere
dc.contributor.authorVázquez Rowe, Ian
dc.contributor.authorIrabien Gulías, Ángel 
dc.contributor.authorAldaco García, Rubén 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2018-02-14T14:31:16Z
dc.date.available2018-09-30T02:45:07Z
dc.date.issued2017-09
dc.identifier.issn1618-954X
dc.identifier.issn1618-9558
dc.identifier.otherCTM2013-43539-Res_ES
dc.identifier.urihttp://hdl.handle.net/10902/13042
dc.description.abstractLife 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.es_ES
dc.description.sponsorshipAuthors 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.es_ES
dc.format.extent39 p.es_ES
dc.language.isoenges_ES
dc.publisherSpringer Verlages_ES
dc.rights© Springer. The final publication is available at Springer via https://doi.org/10.1007/s10098-017-1373-6es_ES
dc.sourceClean Technologies and Environmental Policy, 2017, 19(7), 1897-1912es_ES
dc.subject.otherAnchovyes_ES
dc.subject.otherCanning industryes_ES
dc.subject.otherLife cycle assessmentes_ES
dc.subject.otherOptimisationes_ES
dc.subject.otherLinear programinges_ES
dc.titleIncorporating linear programing and life cycle thinking into environmental sustainability decision-making: a case study on anchovy canning industryes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1007/s10098-017-1373-6es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1007/s10098-017-1373-6
dc.type.versionacceptedVersiones_ES


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