Addressing global environmental impacts including land use change in life cycle optimization: Studies on biofuels

• Published in: Journal of cleaner production Vol. 182; no. C; pp. 313 - 330
• Main Authors: Garcia, Daniel J., You, Fengqi
• Format: Journal Article
• Language: English
• Published: United Kingdom Elsevier Ltd 01.05.2018; Elsevier
• Subjects: Biofuel; Economic modeling; Land use change; Life cycle optimization; Multi-objective optimization; Sustainability; Life cycle optimization; Multi-objective optimization; Biofuel; Economic modeling; Land use change; Sustainability
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2018.02.012

Life cycle environmental impacts of a product or process may be global and/or spatially-explicit, such as land use change (LUC) and LUC greenhouse gas (GHG) emissions. Life cycle optimization (LCO) usually does not account for these impacts. However, for a product or process to be truly sustainable, they must be considered. We integrate computable general equilibrium (CGE)-based LUC modeling and LCO to create a novel multiobjective CGE-LUC-LCO framework to account for global environmental impacts and production costs. The framework is then applied to case studies on life cycle GHG emissions throughout the bioethanol life cycle, considering regional and global agricultural practices, land use, technological impacts, and global economic forces. The framework considers emissions from feedstock production, transportation, direct/indirect processing emissions, end use, and LUC. The model allows for selection of 16 bioethanol production pathways from 5 feedstocks, and 3 case studies with US and EU bioethanol demands are examined. The methodology identifies cleaner production strategies by considering global, spatially-explicit life cycle environmental impacts like LUC and LUC GHG emissions for the first time in LCO. [Display omitted] •Computable general equilibrium models and life cycle optimization are integrated.•Land use change is considered for first time in life cycle optimization.•Novel modeling framework is applied to global bioethanol production.•Results inform global cleaner production strategies and policy.•Proposed integrated framework can analyze variety of global production systems.