The importance of incorporating uncertainty into pavement life cycle cost and environmental impact analyses
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2017 Taylor & Francis Group, London, UK. We present an approach for conducting probabilistic Life Cycle Cost Analyses (LCCA) and Life Cycle Assessments (LCA) and demonstrate its value with case study results. We define uncertainty quantities and methods for characterizing uncertainty for different types of parameters. The approach includes leveraging outputs from Pavement-ME to characterize uncertainty in pavement performance over time. Uncertainty in the input data and scenarios is used in a Monte Carlo analysis to quantify the uncertainty in life cycle costs and environmental impacts. The probabilistic results are then used to calculate several comparative metrics, including the statistical confidence that one alternative has a lower cost or environmental impact than another alternative, and to determine the parameters that contribute most to the variance of the results. The approach enables a wide analysis of the scenario space to determine which scenarios are most relevant to the comparison of alternatives, and iterative analyses that feature refined data selected in the influential parameter analysis. We demonstrate the value of the approach and the benefits of incorporating uncertainty into LCCAs and LCAs via results from cases in the literature.
