Survey of approaches to improve reliability in lca

Abstract

Limitations of data quality and difficulties to assess uncertainty are long since acknowledged problems in LCA. During recent years a range of tools for improvement of reliability in LCA have been presented, but despite this there is still a lack of consensus about how these issues should be handled. To give basic understanding of data quality and uncertainty in LCA, key concepts of data quality and uncertainty in the context of LCA are explained. A comprehensive survey of methods and approaches for data quality management, sensitivity analysis, and uncertainty analysis published in the LCA literature is presented. It should serve as a guide to further reading for LCA practitioners interested in improving data quality management and uncertainty assessment in LCA projects. The suitability of different tools for addressing different types of uncertainty and future needs in this field is discussed.