Keywords
decision-making, valuation, uncertainty, multivariate statistical analysis
Start Date
1-7-2004 12:00 AM
Abstract
This paper presents an approach for the integrated consideration of both technical and valuation uncertainties during decision making supported by LCA-type environmental performance information. 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. Distinguishability analysis showed that it was not possible to obtain a conclusive answer with regard to the preferred technology due to the extensive uncertainty in the LCA-based environmental performance information. PCA of the ranking of the design scenarios demonstrated that valuation uncertainties associated with choices made during intra- and inter-criterion preference modelling had a more significant effect on the ranking of the design scenarios than the inclusion/exclusion of environmental indicators reflecting local concerns or the choice of the position of the LCIA impact indicators in the cause-effect network. The results suggest that stakeholder involvement in intraand inter-criterion preference modelling is important, and that the “encoding” of value judgements and preferences into LCA environmental performance information is to be avoided. As a whole, the paper supports a call for diversity in LCA methodology rather than one for greater standardisation, and provides a foundation for the consideration of the implications of such methodological diversity as part of an overall approach to promote effective decision making based on LCA environmental performance information.
An Integrated Approach for the Management of Uncertainty in Decision Making Supported by LCA-Based Environmental Performance Information
This paper presents an approach for the integrated consideration of both technical and valuation uncertainties during decision making supported by LCA-type environmental performance information. 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. Distinguishability analysis showed that it was not possible to obtain a conclusive answer with regard to the preferred technology due to the extensive uncertainty in the LCA-based environmental performance information. PCA of the ranking of the design scenarios demonstrated that valuation uncertainties associated with choices made during intra- and inter-criterion preference modelling had a more significant effect on the ranking of the design scenarios than the inclusion/exclusion of environmental indicators reflecting local concerns or the choice of the position of the LCIA impact indicators in the cause-effect network. The results suggest that stakeholder involvement in intraand inter-criterion preference modelling is important, and that the “encoding” of value judgements and preferences into LCA environmental performance information is to be avoided. As a whole, the paper supports a call for diversity in LCA methodology rather than one for greater standardisation, and provides a foundation for the consideration of the implications of such methodological diversity as part of an overall approach to promote effective decision making based on LCA environmental performance information.
