https://hdl.handle.net/1721.1/102448 2026-04-03T21:50:06Z 2026-04-03T21:50:06Z Mack, James W. Xu, Xin Gregory, Jeremy Kirchain, Randolph https://hdl.handle.net/1721.1/110895 2025-02-11T19:49:08Z 2015-08-12T00:00:00Z

Accounting for Rehabilitation Activity Uncertainty in a Pavement Life Cycle Assessment using Probability and Decision Tree Analysis Mack, James W.; Xu, Xin; Gregory, Jeremy; Kirchain, Randolph In any life cycle assessment (LCA) for pavements, the designer must decide on which rehabilitation activities will be used to maintain the pavement over the analysis period. While this sounds simple, the fact is that there are many different rehabilitation scenarios that could be performed when the pavement requires rehabilitation, and which one is used will impact the LCA results. This creates inherent uncertainty and variability in the LCA results solely due to the selection of the rehabilitation scenario used in the analysis. Currently, most LCA’s apply a single standard rehabilitation scenario to all pavements. The problem with this approach is that because each project is unique, the activities may or may not be representative of the actual set of activities done on that particular pavement. The only way to get meaningful indication of a project’s pavement environmental impact is to look at the impact of all (or at least most) of the potential rehabilitation activities that could be used to maintain the pavement over the analysis period. This paper shows how State Highway Agencies (SHAs) can use probability and decision tree analysis to evaluate many rehabilitation scenarios in order to determine a range of LCA results, as well as a probability adjusted, expected value LCA result. This process quantifies the underlying uncertainty that different the rehabilitation selection can have on the LCA results so that a more informed decision can be made when comparing the alternate pavement designs. A case study based on alternative designs and rehabilitation scenarios used by a SHA demonstrates the decision tree analysis process and shows how the risk profiles for the two alternatives considered are not equivalent. For this case, this results in the probability-adjusted LCA results being different than the single standard rehabilitation scenario results.

2015-08-12T00:00:00Z Xu, Xin Gregory, Jeremy Kirchain, Randolph https://hdl.handle.net/1721.1/110894 2019-04-10T13:10:58Z 2017-08-01T00:00:00Z

 Evaluation of the Albedo-induced Radiative Forcing and CO2 Equivalence Savings: A Case Study on Reflective Pavements in Four Selected U.S. Urban Areas Xu, Xin; Gregory, Jeremy; Kirchain, Randolph There is a growing interest in developing cool pavement strategies to mitigate pavement’s impact on the global warming in recent years. One of the mitigation strategies is by increasing the solar reflectance (or albedo) of the pavement surface, which directly contributes to global cooling by adjusting radiative forcing and potentially reduces the energy demand in the urban areas. In this paper, the radiative energy budgets in four urban areas are investigated based on the data derived from NASA satellite measurements. The radiative forcing (RF) due to the change of urban surface albedo as a result of reflective pavements is estimated using a simplified engineering model. The carbon dioxide (CO2) equivalence savings are also calculated with reference to the 100-year global warming potential of CO2. Results show that the implementation of reflective pavement has a great potential to reduce global warming. The CO2 reduction is significant in the urban areas but also affects the surrounding regions to some extent. In the end, we recommend using a climate model incorporating site-specific information that enables the visualization of the outputs through spatial maps. The results from this work would be useful for guiding the implementation of the cool pavement strategies.

2017-08-01T00:00:00Z