Reducing greenhouse gas emissions and energy consumption using pavement maintenance and rehabilitation: Refinement and application of a life cycle assessment approach

The national pavement network is a key component of the transportation infrastructure that the U.S. economy depends on for mobility and movement of goods. Minimization of the environmental and social impact of its maintenance and operation is an important goal. In this dissertation study, a life cycle assessment (LCA) approach was used to evaluate the effects of the selection and timing of pavement maintenance and rehabilitation (M&R) strategies on reducing energy consumption and greenhouse gas (GHG) emissions.;Four project-level case studies of Caltrans Capital Preventive Maintenance (CAPM) treatments were evaluated. In the case studies, the CAPM treatments were compared with an alternative strategy where no treatment occurs ( Do Nothing), except for routine maintenance of damaged pavement. The results showed that for highways with high traffic volumes, the energy and CO2 emission reductions accrued during the use phase due to the reduced rolling resistance can outweigh the energy use and CO2 emissions from the material production and construction phases. The extent of the benefit was dependent on constructed smoothness with a much smaller portion of the benefit coming from change of texture compared with change of roughness. For low traffic volume highways, the smoothness obtained by the contractors and the materials used in the pavement had a significant effect on the result. On these segments, the CAPM treatments may result in a net increase in energy use and CO2 emissions if low traffic volumes and rough pavement produced by construction occur together.;This LCA methodology was then used in a simplified form to evaluate the potential life cycle energy savings and CO2 emission reduction at a network level for the state of California. The analysis considered applying CAPM treatments at optimal IRI triggering values for minimizing CO2 emissions compared to the Do Nothing case. The optimal triggering IRI values are a function of the traffic volume of each segment. A factorial approach was used to evaluate the impact of pavement-induced rolling resistance under different pavement and traffic conditions. With the optimal IRI triggering, a total CO2 emission reduction of 10.57 million metric tons (MMT) over the 10-year analysis period compared to Do Nothing can be achieved. However, the cost-effectiveness analysis showed that implementing such a strategy can result in a cost-effectiveness factor of ;Finally, this dissertation study assessed how pavement roughness influences driving behavior with respect to free-flow speed on freeways. The purpose was to verify the assumption that driving behavior does not change after a pavement becomes smoother. A free-flow speed model using linear regression was developed based on a set of explanatory variables, including the total number of lanes, lane number, day of week, gasoline price, IRI, and Caltrans district to check regional behavior. The result showed that pavement roughness, as indicated by IRI, has very limited impact on free-flow speed in all datasets examined. 1 m/km (63 inches/mile) change of IRI can result in about 0.3 to 0.4 miles per hour change in free-flow speed. Considering that most CAPM projects reduce the IRI value by less than 3 m/km (289 inches/mile), changes in pavement smoothness have limited effect on vehicle speed, and therefore little impact on vehicle emissions and energy consumption. (Abstract shortened by UMI.).