Decision Analysis for Comparative Life Cycle Assessment
abstract: Life Cycle Assessment (LCA) quantifies environmental impacts of products in raw material extraction, processing, manufacturing, distribution, use and final disposal. The findings of an LCA can be used to improve industry practices, to aid in product development, and guide public policy. Un...
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ndltd-asu.edu-item-178482018-06-22T03:03:52Z Decision Analysis for Comparative Life Cycle Assessment abstract: Life Cycle Assessment (LCA) quantifies environmental impacts of products in raw material extraction, processing, manufacturing, distribution, use and final disposal. The findings of an LCA can be used to improve industry practices, to aid in product development, and guide public policy. Unfortunately, existing approaches to LCA are unreliable in the cases of emerging technologies, where data is unavailable and rapid technological advances outstrip environmental knowledge. Previous studies have demonstrated several shortcomings to existing practices, including the masking of environmental impacts, the difficulty of selecting appropriate weight sets for multi-stakeholder problems, and difficulties in exploration of variability and uncertainty. In particular, there is an acute need for decision-driven interpretation methods that can guide decision makers towards making balanced, environmentally sound decisions in instances of high uncertainty. We propose the first major methodological innovation in LCA since early establishment of LCA as the analytical perspective of choice in problems of environmental management. We propose to couple stochastic multi-criteria decision analytic tools with existing approaches to inventory building and characterization to create a robust approach to comparative technology assessment in the context of high uncertainty, rapid technological change, and evolving stakeholder values. Namely, this study introduces a novel method known as Stochastic Multi-attribute Analysis for Life Cycle Impact Assessment (SMAA-LCIA) that uses internal normalization by means of outranking and exploration of feasible weight spaces. Dissertation/Thesis Prado-Lopez, Valentina (Author) Seager, Thomas P (Advisor) Landis, Amy E (Committee member) Chester, Mikhail (Committee member) White, Philip (Committee member) Arizona State University (Publisher) Sustainability Environmental management Engineering Decision Analysis Life Cycle Assessment normalization outranking stochastic valuation eng 82 pages M.S. Civil and Environmental Engineering 2013 Masters Thesis http://hdl.handle.net/2286/R.I.17848 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2013 |
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English |
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Dissertation |
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Sustainability Environmental management Engineering Decision Analysis Life Cycle Assessment normalization outranking stochastic valuation |
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Sustainability Environmental management Engineering Decision Analysis Life Cycle Assessment normalization outranking stochastic valuation Decision Analysis for Comparative Life Cycle Assessment |
description |
abstract: Life Cycle Assessment (LCA) quantifies environmental impacts of products in raw material extraction, processing, manufacturing, distribution, use and final disposal. The findings of an LCA can be used to improve industry practices, to aid in product development, and guide public policy. Unfortunately, existing approaches to LCA are unreliable in the cases of emerging technologies, where data is unavailable and rapid technological advances outstrip environmental knowledge. Previous studies have demonstrated several shortcomings to existing practices, including the masking of environmental impacts, the difficulty of selecting appropriate weight sets for multi-stakeholder problems, and difficulties in exploration of variability and uncertainty. In particular, there is an acute need for decision-driven interpretation methods that can guide decision makers towards making balanced, environmentally sound decisions in instances of high uncertainty. We propose the first major methodological innovation in LCA since early establishment of LCA as the analytical perspective of choice in problems of environmental management. We propose to couple stochastic multi-criteria decision analytic tools with existing approaches to inventory building and characterization to create a robust approach to comparative technology assessment in the context of high uncertainty, rapid technological change, and evolving stakeholder values. Namely, this study introduces a novel method known as Stochastic Multi-attribute Analysis for Life Cycle Impact Assessment (SMAA-LCIA) that uses internal normalization by means of outranking and exploration of feasible weight spaces. === Dissertation/Thesis === M.S. Civil and Environmental Engineering 2013 |
author2 |
Prado-Lopez, Valentina (Author) |
author_facet |
Prado-Lopez, Valentina (Author) |
title |
Decision Analysis for Comparative Life Cycle Assessment |
title_short |
Decision Analysis for Comparative Life Cycle Assessment |
title_full |
Decision Analysis for Comparative Life Cycle Assessment |
title_fullStr |
Decision Analysis for Comparative Life Cycle Assessment |
title_full_unstemmed |
Decision Analysis for Comparative Life Cycle Assessment |
title_sort |
decision analysis for comparative life cycle assessment |
publishDate |
2013 |
url |
http://hdl.handle.net/2286/R.I.17848 |
_version_ |
1718700052311965696 |