"A primary input into any life cycle assessment (LCA) for pavements is the set of rehabilitation activities that are used to maintain the system over the analysis period. For the LCA to be meaningful and reliable, the analysis must reflect the most likely activities for each alternative over that analysis period. Currently, most state highway agencies (SHA) apply a single standard rehabilitation scenario to all pavements, which may or may not be representative of the actual set of activities that will be done. The fact is that there are many different rehabilitation scenarios that could be performed when the pavement requires rehabilitation, and which one is selected will impact the results. This creates inherent uncertainty and variability in the LCA results solely due to the selection of which standard rehabilitation scenario is used in the analysis.
This paper shows how SHAs can use probability and decision tree analysis to evaluate different rehabilitation scenarios in order to determine the range of LCA results as well as an expected value LCA result. This information helps quantify the underlying risk assumptions that the rehabilitation selection has on the LCA results so that a more informed decision can be made when comparing the LCA results of pavement designs. A case study based on alternative designs and rehabilitation scenarios used by a SHA demonstrates the extent to which the decision tree analysis could affect the outcome of an LCA. In this case, the risk profiles for the two alternatives considered are not equivalent and therefore, the probability-adjusted LCA results are different than the results based on a single maintenance schedule."
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