Abstract

Fossil fuel carbon dioxide (FFCO2) emissions are the largest driver of anthropogenic climate change. Approximately three-quarters of the world’s fossil fuels carbon dioxide emissions are generated in urban areas. We used the Hestia high resolution approach to quantify FFCO2 for Salt Lake County, Utah, USA and demonstrate the importance of high resolution quantification to urban emissions mitigation policymaking. We focus on the residential and onroad sectors across both urbanized and urbanizing parts of the valley. Stochastic Impact by Regression on Population, Affluence, and Technology (STIRPAT) regression models using sociodemographic data at the census block group level shows that population, per capita income, and building age exhibit positive relationships while household size shows a negative relationship with FFCO2 emissions. Compact development shows little effect on FFCO2 emissions in this domain. FFCO2 emissions in high income block groups is twice as sensitive to income than low income block groups. Emissions are four times as sensitive to household size in low-income versus high-income block groups. These results suggest that policy options targeting personal responsibility or knowledge feedback loops may be the most effective strategies. Examples include utility bill performance comparison or publicly available energy maps identifying high-emitting areas. Within the onroad sector, high emissions density (FFCO2/km) is associated with primary roads, while high emissions intensity (FFCO2/VMT) is associated with secondary roads. Opportunities exist for alignment of public transportation extension with remaining high emission road segments, offering a prioritization of new onroad transportation policy in Salt Lake County.

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