Title of article :
An integrated approach for the consideration of uncertainty in decision
making supported by Life Cycle Assessment
Author/Authors :
L. Basson، نويسنده , , b، نويسنده , , *، نويسنده , , J.G. Petrie a، نويسنده , , b، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2007
Abstract :
This paper presents an approach for the integrated consideration of both technical and valuation uncertainties during decision making supported
by environmental performance information based on Life Cycle Assessment (LCA). Key elements of this approach include ‘‘distinguishability
analysis’’ to determine whether the uncertainty in the performance information is likely to make it impossible to distinguish between the
activities under consideration, and the use of a multivariate statistical analysis approach, called principal components analysis (PCA), which
facilitates the rapid analysis of large numbers of parallel sets of results, and enables the identification of choices that lead to similar and/or opposite
evaluations of activities. The integrated approach for the management of uncertainty is demonstrated for a technology selection decision
for the recommissioning of a coal-based power station. The results of the case study decision suggest that stakeholder involvement in preference
modelling is important, and that the ‘‘encoding’’ of value judgements and preferences into LCA environmental performance information is to be
avoided. The approach presented in this paper provides a foundation for the consideration of the implications of diversity in values and preferences
as part of an overall approach to promote effective decision making based on LCA environmental performance information. However,
the approach is more universally applicable e it can be used wherever multiple criteria decision analysis is used to assist in the resolution of
complex decision situations.
Keywords :
Decision Making , Life Cycle Assessment , multivariate statistical analysis , Uncertainty , Valuation
Journal title :
Environmental Modelling and Software
Journal title :
Environmental Modelling and Software