Planning for sustainable transportation through the integration of technology, public policy, and behavioral change: A data-driven approach
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Planning for sustainable transportation through the integration of technology, public policy, and behavioral change: A data-driven approach


Transportation contributes importantly to the economy and society, but at substantial environmental cost. While much progress has been made to increase the energy efficiency of transportation systems, their continued expansion is a major threat to global climate change and urban air quality. Additional mitigation strategies are needed to reduce the negative environmental and public health impacts of transportation. In this dissertation, I tackle the complexity of achieving sustainable transportation by addressing questions arise at various stages of technology development and deployment. The first essay assesses the life cycle environmental impacts of technology pathways that convert waste resources into alternative transportation fuels and identifies the most efficient pathways for all US counties with respect to both energy production and climate benefits. I find that utilizing these resources in the contiguous US can generate 3.1 to 3.8 exajoules (EJ) of renewable energy annually, which would be a net energy gain of 2.4 to 3.2 EJ, and would displace GHG emissions of 103 to 178 million metric tons of CO2 equivalent every year. The second essay uses machine learning techniques to identify the most powerful socioeconomic, demographic, and geospatial predictors for plug-in electric vehicle (PEV) adoption across California census tracts. I find that the market penetration of PEVs is generally higher in more affluent neighborhoods with many homeowners and highly-educated residents. The lack of pro-environment intention and behaviors as well as the proportions of low-income households and low-value and high-density housing units negatively associate with PEV adoption. I also find that the deployment of workplace charging may be more effective than the deployment of public DC fast charging. The third essay analyzes the energy and environmental impacts of transit bus electrification and identifies strategies for charging infrastructure deployment at public transit agencies in Los Angeles County. I find that the transition to battery electric buses would increase particulate matter emissions from brake and tire wear in the near term and immediately reduce NOx, CO, and GHG emissions. Smart charging would be a critical element in the planning of transit bus electrification, as it reduces costs associated with charging infrastructure and electric demand by lowering charger needs and shaving peak load. In concert, the three essays in this dissertation expand the current literature in multiple fields and the findings presented in each of the three essays have important implications for research and practices in the area of sustainable transportation at various geographical scales.

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