The scale of the climate crisis is immense and solutions are urgently needed. This dissertation develops tools to provide highly tailored carbon footprint information and place-based solutions to U.S. households and communities in three complimentary studies. The first study quantifies the greenhouse gas (GHG) savings potential of different U.S. metropolitan areas and household types within locations, developing average household carbon footprint (HCF) profiles for 28 metropolitan areas, 6 household sizes and 12 income brackets. The model includes emissions embodied in transportation, energy, water, waste, food, goods, and services, and further quantifies GHG and financial savings from potential mitigation actions across all locations and household types. The size and composition of carbon footprints vary dramatically between geographic regions (38 to 52 tCO2e) and within regions based on basic demographic characteristics (<20 to >80 tCO2e). Despite these differences, large cash-positive carbon footprint reductions are evident across all household types and locations.
Using national household surveys, the second study develops econometric models to estimate HCF for essentially all U.S. zip codes, cities, counties, and metropolitan areas. The results demonstrate consistently lower HCF in urban core cities (∼40 tCO2e) and higher carbon footprints in outlying suburbs (∼50 tCO2e), with a range from ∼25 to >80 tCO2e in the 50 largest metropolitan areas. In contrast to a vast literature demonstrating GHG savings in more dense cities, analysis of all U.S. locations presents a more complex picture. Population density exhibits a weak but positive correlation with HCF until a density threshold is met, after which range, mean, and standard deviation of HCF decline. While population density contributes to relatively low HCF in the central cities of large metropolitan areas, the more extensive suburbanization in these regions contributes to an overall net increase in HCF compared to smaller metropolitan areas. Suburbs alone account for ∼50% of total U.S. HCF.
Results from this quantitative research have informed the development of "smart" online carbon management tools that allow users to quickly calculate, compare and manage household carbon footprints, and to visualize average community carbon footprints using high spatial resolution interactive maps. Yet, the potential benefits of such tools are limited to those who find them, and the information may often do little to increase intrinsic motivation to adopt new low carbon technologies and practices. Following lessons from behavioral sciences, a subsequent study engaged ∼2,700 residents in eight participating cities to track and reduce household carbon footprints and compete for the title of "Coolest California City." The yearlong pilot project achieved an estimated 14% reduction in electricity consumption, lending evidence that community-scale climate initiatives, enabled by sophisticated information and communication technologies and motivated local program implementers, can help scale up tailored, place-based climate solutions. Together, this research and accompanying tools and programs provide a framework for individuals and communities to prioritize GHG mitigation opportunities and stimulate collective climate action.
|Adviser||Daniel M. Kammen|
|School||UNIVERSITY OF CALIFORNIA, BERKELEY|
|Subjects||Behavioral psychology; Environmental engineering; Urban planning|
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