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Leveraging Uncertainty to Improve Li...

Price, Lindsay.

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Leveraging Uncertainty to Improve Life Cycle Assessment for Decision Making.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Leveraging Uncertainty to Improve Life Cycle Assessment for Decision Making./
Author:	Price, Lindsay.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	105 p.
Notes:	Source: Dissertations Abstracts International, Volume: 81-09, Section: B.
Contained By:	Dissertations Abstracts International81-09B.
Subject:	Environmental engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27539881
ISBN:	9781658413275

Leveraging Uncertainty to Improve Life Cycle Assessment for Decision Making.
Price, Lindsay.

Leveraging Uncertainty to Improve Life Cycle Assessment for Decision Making. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 105 p.

Source: Dissertations Abstracts International, Volume: 81-09, Section: B.

Thesis (Ph.D.)--University of California, Davis, 2019.

This item must not be sold to any third party vendors.

Uncertainty analysis is integral to robust LCA-based decision making. It allows for enhanced model transparency, and can be used to emphasize the impact of commonly accepted data sets, assumptions, modeling simplifications, and system boundaries. Especially when an LCA model is employed in a forecasting context for policymaking and technology selection, the role of deep uncertainties (those which are not well-represented by probability distributions) should be considered. The objective of this dissertation is to review and improve the state of the practice of including uncertainty in LCA. To this end I survey the literature for a consensus on best practices and propose a protocol to ease the inclusion of these deep uncertainties in LCAs, thus promoting one of LCA's most useful functions when applied to policymaking and emerging technologies: identifying and characterizing possible unintended consequences of these interventions. In addition, this proposed protocol provides the ability to include incomplete data when it is the best accessible, a guide for model scope expansion, and an exploratory framework for the trade-off between research question scope and the time-requirements posed by data needs.

ISBN: 9781658413275Subjects--Topical Terms:

548583
Environmental engineering.
Subjects--Index Terms:

Decision-making

Leveraging Uncertainty to Improve Life Cycle Assessment for Decision Making.
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520 $a Uncertainty analysis is integral to robust LCA-based decision making. It allows for enhanced model transparency, and can be used to emphasize the impact of commonly accepted data sets, assumptions, modeling simplifications, and system boundaries. Especially when an LCA model is employed in a forecasting context for policymaking and technology selection, the role of deep uncertainties (those which are not well-represented by probability distributions) should be considered. The objective of this dissertation is to review and improve the state of the practice of including uncertainty in LCA. To this end I survey the literature for a consensus on best practices and propose a protocol to ease the inclusion of these deep uncertainties in LCAs, thus promoting one of LCA's most useful functions when applied to policymaking and emerging technologies: identifying and characterizing possible unintended consequences of these interventions. In addition, this proposed protocol provides the ability to include incomplete data when it is the best accessible, a guide for model scope expansion, and an exploratory framework for the trade-off between research question scope and the time-requirements posed by data needs.
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