Methods for uncertainty propagation in life cycle assessment

E.A. Groen, R. Heijungs, E.A.M. Bokkers, I.J.M. de Boer

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Life cycle assessment (LCA) calculates the environmental impact of a product over its entire life cycle. Uncertainty analysis is an important aspect in LCA, and is usually performed using Monte Carlo sampling. In this study, Monte Carlo sampling, Latin hypercube sampling, quasi Monte Carlo sampling, analytical uncertainty propagation and fuzzy interval arithmetic were compared based on e.g. convergence rate and output statistics. Each method was tested on three LCA case studies, which differed in size and behaviour. Uncertainty propagation in LCA using a sampling method leads to more (directly) usable information compared to fuzzy interval arithmetic or analytical uncertainty propagation. Latin hypercube and quasi Monte Carlo sampling provide more accuracy in determining the sample mean than Monte Carlo sampling and can even converge faster than Monte Carlo sampling for some of the case studies discussed in this paper.
Original languageEnglish
Pages (from-to)316-325
JournalEnvironmental Modelling & Software
Volume62
Issue numberDecember
DOIs
Publication statusPublished - 2014

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Life cycle
life cycle
Sampling
sampling
Uncertainty analysis
Uncertainty
method
uncertainty analysis
Environmental impact
environmental impact
Statistics

Cite this

Groen, E.A. ; Heijungs, R. ; Bokkers, E.A.M. ; de Boer, I.J.M. / Methods for uncertainty propagation in life cycle assessment. In: Environmental Modelling & Software. 2014 ; Vol. 62, No. December. pp. 316-325.
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Methods for uncertainty propagation in life cycle assessment. / Groen, E.A.; Heijungs, R.; Bokkers, E.A.M.; de Boer, I.J.M.

In: Environmental Modelling & Software, Vol. 62, No. December, 2014, p. 316-325.

Research output: Contribution to JournalArticleAcademicpeer-review

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