Liu, X, Ziv, G orcid.org/0000-0002-6776-0763 and Bakshi, BR (2018) Ecosystem services in life cycle assessment - Part 1: A computational framework. Journal of Cleaner Production, 197 (Part 1). pp. 314-322. ISSN 0959-6526
Abstract
Explicit inclusion of the role of ecosystems in life cycle assessment(LCA) is needed to prevent the selection of alternatives that depend on or degrade scarce ecosystem services (ES), and to help identify opportunities for enhancing sustainability by not just reducing impact but also protecting and restoring ecosystems and the diverse goods and services they supply. Various approaches have been suggested for including ES in LCA but a general computational framework is not yet available. This paper extends the framework of conventional process LCA to assess and encourage techno-ecological synergies in life cycle assessment (TES-LCA). It includes ecosystem modules along with process modules in LCA. Analogous to the technology matrix in conventional LCA, TES-LCA defines a “techno-ecological” matrix. It consists of four components: a technology matrix defined by economic flows, an intervention matrix interpreted as the ES demanded by technological activities, an ecosystem matrix interpreted as the capacity of ecosystems to supply these services, and a management matrix to capture the interaction between technological and ecological systems. This work demonstrates the computational structure through a toy example and discuss the major challenges of TES-LCA in terms of data availability for an exhaustive array of ES. This work suggests that such data need to be made available and included in future versions of life cycle inventory databases. The computational structure of TES-LCA is able to capture the interactions between and within technological and ecological systems. It enables including of the role and capacity of ecosystems in a life cycle. The framework can encourage development of data and models to enable practical use of TES-LCA, which can provide unique insights into absolute environmental sustainability by quantifying overshoots for specific ES, and help identify improvement strategies based on improving technological efficiency and restoring ecosystems.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Elsevier Ltd. This is an author produced version of a paper published in Journal of Cleaner Production. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Computational structure; Life cycle assessment; Ecosystem service; Environmental sustainability |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Ecology & Global Change (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Apr 2019 11:26 |
Last Modified: | 19 Jun 2019 00:42 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jclepro.2018.06.164 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144760 |