A life-cycle assessment framework for pavement management considering uncertainties

Abstract

Life cycle assessment (LCA) is a methodology widely endorsed by the pavement community and increasingly adopted by transportation agencies worldwide to account for the environmental impacts of pavements throughout their entire life cycle. LCA studies in this context are prone to the effects of uncertainties due to (1) the long analysis periods that stretch across numerous maintenance and rehabilitation (M&R) cycles, (2) the need of different types and sources of data and additional models and (3) multiple methodological decisions to be made by the analyst. Nevertheless, LCA studies are often done deterministically and omit important phases and phenomena from the systems boundaries, thereby reducing the reliability and representativity of the results. To overcome this challenge and to foster the integration of LCA models with existing pavement management systems, this paper presents the development and application of a LCA framework that evaluates the environmental performance of pavement M&R treatments. Further, it incorporates the effects of pavement-vehicle interaction into the analysis and accounts for multiple types of uncertainties, namely those associated with the value of parameters, methodological choices and data quality. Probability distributions and value scenarios are used to characterize the uncertainties which are propagated into the results using Latin hypercube sampling and scenario analysis. A sensitivity analysis using tree-ensemble methods is adopted to unveil the most influential parameters on the variance of the outputs. The outcomes of this research work aim to advance the applicability of LCA in the context of pavement management, and to improve the understanding of the effects of uncertainties in the outcomes of the analysis.