Literature DB >> 26752618

Integrating Hybrid Life Cycle Assessment with Multiobjective Optimization: A Modeling Framework.

Dajun Yue1, Shyama Pandya1, Fengqi You1.   

Abstract

By combining life cycle assessment (LCA) with multiobjective optimization (MOO), the life cycle optimization (LCO) framework holds the promise not only to evaluate the environmental impacts for a given product but also to compare different alternatives and identify both ecologically and economically better decisions. Despite the recent methodological developments in LCA, most LCO applications are developed upon process-based LCA, which results in system boundary truncation and underestimation of the true impact. In this study, we propose a comprehensive LCO framework that seamlessly integrates MOO with integrated hybrid LCA. It quantifies both direct and indirect environmental impacts and incorporates them into the decision making process in addition to the more traditional economic criteria. The proposed LCO framework is demonstrated through an application on sustainable design of a potential bioethanol supply chain in the UK. Results indicate that the proposed hybrid LCO framework identifies a considerable amount of indirect greenhouse gas emissions (up to 58.4%) that are essentially ignored in process-based LCO. Among the biomass feedstock options considered, using woody biomass for bioethanol production would be the most preferable choice from a climate perspective, while the mixed use of wheat and wheat straw as feedstocks would be the most cost-effective one.

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Year:  2016        PMID: 26752618     DOI: 10.1021/acs.est.5b04279

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  1 in total

1.  Optimization of multi-pathway production chains and multi-criteria decision-making through sustainability evaluation: a biojet fuel production case study.

Authors:  Eduardo Vyhmeister; Gerardo J Ruiz-Mercado; Ana I Torres; John A Posada
Journal:  Clean Technol Environ Policy       Date:  2018       Impact factor: 3.636

  1 in total

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