Toward a more accurate regionalized life cycle inventory

Yi Yang

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Regionalization can improve the accuracy of life cycle assessment (LCA) results and make it more relevant for decision makers. There has been a growing body of regionalized LCA research, and in particular many regionalized life cycle impact assessment (LCIA) models have been developed. However, insufficient attention has been paid to regionalized life cycle inventory (LCI), the study of the geographic location and quantity of environmental emissions that occur throughout the life cycle of a product. Previous studies have often used a simplistic approach based on regional output percentages (ROP) to regionalize an LCI, but with little justification for the use of the approach or discussion of its limitations. This paper first reviews the ROP approach, analyzes its strengths and weaknesses, and in so doing demonstrates the importance of interregional commodity flows in compiling regionalized LCIs. Next, this paper discusses ways in which LCIs can be more accurately regionalized. Incorporating the multiregional Input-Output (MRIO) models that are widely used in the Input-Output Analysis (IOA) literature, even when there are limited data on interregional commodity flows, can improve the accuracy of regionalized LCI results as derived by the ROP approach. Also discussed are circumstances in which the ROP approach can be used to compile a relatively accurate regionalized LCI. One important implication of this paper is for selecting a proper spatial scale for both regionalized LCI and LCIA analyses.

Original languageEnglish (US)
Pages (from-to)308-315
Number of pages8
JournalJournal of Cleaner Production
Volume112
DOIs
StatePublished - Jan 20 2016

Bibliographical note

Publisher Copyright:
© 2015 Elsevier Ltd. All rights reserved.

Keywords

  • Interregional commodity flows
  • Life cycle inventory
  • Multiregional input-output models
  • Regional LCA
  • Regional LCIA
  • Spatial scale

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