Deriving life cycle assessment coefficients for application in integrated assessment modelling. (January 2018)

• Record Type: Journal Article
• Authors: Arvesen, Anders; Luderer, Gunnar; Pehl, Michaja; Bodirsky, Benjamin Leon; Hertwich, Edgar G.
• Is Part Of: Environmental modelling & software. Volume 99(2018)
• Page Start: 111
• Page End: 125
• Publication Date: 2018-01
• Subjects: Life cycle assessment (LCA) -- Integrated assessment model (IAM) -- THEMIS -- Climate change mitigation -- Transformation pathways -- Sustainability assessment; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.09.010
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The fields of life cycle assessment (LCA) and integrated assessment (IA) modelling today have similar interests in assessing macro-level transformation pathways with a broad view of environmental concerns. Prevailing IA models lack a life cycle perspective, while LCA has traditionally been static- and micro-oriented. We develop a general method for deriving coefficients from detailed, bottom-up LCA suitable for application in IA models, thus allowing IA analysts to explore the life cycle impacts of technology and scenario alternatives. The method decomposes LCA coefficients into life cycle phases and energy carrier use by industries, thus facilitating attribution of life cycle effects to appropriate years, and consistent and comprehensive use of IA model-specific scenario data when the LCA coefficients are applied in IA scenario modelling. We demonstrate the application of the method for global electricity supply to 2050 and provide numerical results (as supplementary material) for future use by IA analysts. Highlights: We present a novel method to derive LCA coefficients suitable for use in IAM. The method decomposes energy into life cycle stages, energy carriers and industries. It can be applied to study any product at any data resolution. It enables consistent scenario modelling when the LCA coefficients are used in IAM. We demonstrate the application of the method for global electricity supply to 2050.