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Consequential Life Cycle Assessment With Market‐Driven Design
Authors:Kate S. Whitefoot  Hilary G. Grimes‐Casey  Carol E. Girata  W. Ross Morrow  James J. Winebrake  Gregory A. Keoleian  Steven J. Skerlos
Affiliation:1. University of Michigan in Ann Arbor, Michigan, USA;2. R.W. Beck, a SAIC company, in Albany, New York, USA;3. University of Michigan;4. Iowa State University in Ames, Iowa, USA;5. College of Liberal Arts and a professor of the Department of Science, Technology and Society/Public Policy at the Rochester Institute of Technology in Rochester, New York, USA;6. Center for Sustainable Systems at the University of Michigan
Abstract:This article describes the development of a consequential life cycle assessment (cLCA) with endogenous market‐driven design (MDD). Incorporation of MDD within cLCA (cLCA‐MDD) is beneficial because design decisions, influenced by market forces, are a major source of environmental emissions and resource consumption in many life cycle systems. cLCA‐MDD captures the environmental impact of these design responses resulting from industrial and policy decisions. We begin by developing the concept of cLCA‐MDD, then present a case study that demonstrates how design responses can be endogenously captured in a cLCA analysis. The case study is in two parts: First, we incorporate endogenous design responses into a cLCA of a mid‐size vehicle and, second, we conduct a policy analysis using a cLCA‐MDD approach. The case study illustrates that cLCA‐MDD can capture multiple “ripple effects” resulting from an industrial decision (e.g., downsizing a vehicle's engine) or a policy decision (e.g., raising gasoline taxes) and that these effects significantly influence results. A key challenge of the approach is appropriately managing and communicating uncertainties associated with the choice of economic parameters or models. We discuss sources of uncertainty in cLCA‐MDD and demonstrate a presentation scheme to facilitate communication of result sensitivity to uncertainties from input parameters, models, and model structure.
Keywords:design for environment (DfE)  industrial ecology  partial equilibrium analysis  policy analysis  sustainability assessment  systems modeling
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