Quality assessment for LCA

Abstract

For the acceptance of LCA results, it is crucial that the level of confidence in outcomes is appropriate for the decision to be made. Currently, there is no general method for establishing the level of confidence in LCA results. A framework for such a general method has been established, distinguishing between reliability and validity of results, and combining these with a number of elements of pedigree. This framework has been used to assess current approaches to data quality assessment in LCA. Most quality assessment methods consider only the quality of input data. Moreover, they generally concentrate on the inventory phase. This paper widens the scope of quality considerations. Besides inventory data characteristics, it is also important to assess the quality of the input data for the impact assessment and the overall model, and, given the restricted nature of quality assessment in LCA, to employ circumstantial evidence from a broader quality perspective: the pedigree. A second paper addresses the operationalisation of this framework.