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Journal article

Defining Temporally Dynamic Life Cycle Assessment: A Literature Review

From

Sustainability, Department of Technology, Management and Economics, Technical University of Denmark1

Quantitative Sustainability Assessment, Sustainability, Society and Economics, Department of Technology, Management and Economics, Technical University of Denmark2

Department of Technology, Management and Economics, Technical University of Denmark3

Indian Institute of Technology Bombay4

University of Michigan5

University of Southern Denmark6

Durable goods last for years, decades, or even centuries. The environmental implications of the changing social, economic and material conditions in which these goods are embedded can be overlooked by conventional life cycle assessment that assumes a static world. In order to avoid these problems, methods such as Dynamic LCA (DLCA) are increasingly being used.

Despite the growing use of DLCA, numerous questions remain. These include how this dynamism is incorporated and what aspects of any given DLCA are dynamic. To answer these questions we perform a review of 56 DLCAs, of which 44 propose a framework for DLCA covering all ISO phases of an LCA or carry out a DLCA.

Three types of LCA dynamism are identified and assessed for the reviewed literature: dynamic process inventory, dynamic systems, and dynamic characterization, while a further two types of LCA dynamism, dynamic scope and dynamic weighting, are proposed, but not applied, in the assessed literature. We found that the implementation of DLCA varies widely, and inventories accounting for dynamic characteristics are by far the most prevalent expression of DLCA.

In order to reduce confusion surrounding the discussion of DLCA, we propose a definition of DLCA and its sub-types: Full DLCA, Partial DLCA, and Prospective LCA. It is concluded that, amongst the current array of DLCA definitions, the implementation of partially dynamic LCA (PDLCA), which apply dynamism in only some parts of the LCA, is common and likely to continue.

This is because PDLCA offers quantifiable marginal utility, in terms of increased validity of the assessment, in relation to conventional LCA methods, but caution is needed in applying PDLCA because of potential for introducing bias into the LCA. To avoid this problem, we propose incorporating system dynamism as part of a sensitivity analysis particularly in PDLCA that are limited by missing data.

This article is protected by copyright. All rights reserved.

Language: English
Year: 2020
Pages: 314-323
ISSN: 15513793 and 15513777
Types: Journal article
DOI: 10.1002/ieam.4235
ORCIDs: Sohn, Joshua , 0000-0002-1436-3609 and 0000-0003-0055-1323

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