Quantifying the environmental impacts of selected sustainable transportation policies
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On-road transportation policies could play a key role in reducing greenhouse gas (GHG) and air pollutant emissions via a wide range of strategies that can be classified into three groups: reduce, avoid, and replace. The objective of this dissertation is to prioritize on-road emission mitigation strategies for policy -level transportation funding allocation and to quantify the environmental impacts of first, High Occupancy Vehicle (HOV) lanes and carpooling as a realization of avoid strategies; and second, Plug-in Electric Vehicles (PEVs) as an example of replace strategies. The resulting models have a wide range of applications in evaluating the effectiveness of each strategy, including the potential to assist policymakers, and transportation planners in optimizing infrastructural investments by identifying regions where the response to a specific policy would be maximized. In chapter II, reduce, avoid, and replace strategies were prioritized based on transportation and climate science professionals’ opinions through Analytical Hierarchy Process (AHP), applied to the cities of Dallas and Lubbock in Texas. The results indicated that reduce strategies had the highest preference score of 40%, followed by avoid strategies with 36% and replace strategies with 24%. In chapter III, we developed a statistical model to relate HOV lanes and other potential factors to carpooling propensity in all 50 U.S. states and the District of Columbia. At the state level, we found HOV lane-kilometers together with higher-than-average gasoline prices to be effective in promoting carpooling. An in-depth analysis of 58 counties in California found that HOV lane-kilometers also positively impact carpooling rates for individual counties. For a hypothetical scenario where existing HOV lane-kilometers in each state are expanded by 0.5 meters for every hour of total daily travel time to work, we found this strategy has the greatest potential to reduce annual carbon dioxide equivalent (CO2e) in the District of Columbia, by 4.5%, followed by Hawaii and New York, and New Jersey. The smallest potential is found in North Dakota. Nationally, 1.83 MMT of CO2e or 0.16% of light duty vehicle emissions would be reduced under this scenario In chapter IV, we attributed PEV adoption rate in 58 California Counties to charging station infrastructure and other potential factors using statistical models. We found charging station per capita to be effective in promoting PEV adoption, particularly among male buyers in households with less number of vehicles available. For a hypothetical scenario where existing charging station infrastructures in each county are expanded by 2 charging station for every one million total daily miles travelled, we found this strategy has the greatest potential to reduce petroleum use, GHG and criteria air pollutant emissions in Modoc County, by 0.06%-0.03%, followed by Sierra, and Mono counties. For 20 counties, including Butte, San Joaquin, and San Francisco counties, the benefit to cost ratio is below one, indicating the incompatibility of the strategy in these counties.