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\begin{document}

\title{Using Linear Optimization To Model Spatially Resolute Emissions Of CO2
From Gasoline Flows Across The United States}



\author[1]{Taha Moiz}%
\author[2]{Kevin Gurney}%
\author[2]{Richard Rushforth}%
\author[2]{Benjamin Ruddell}%
\author[2]{Deborah Huntzinger}%
\author[1]{Nathan Parker}%
\affil[1]{Arizona State University}%
\affil[2]{Northern Arizona University}%


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  \date{May 29, 2024}


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\begin{abstract}
Publicly accessible data has been used to construct a county-scale
supply chain model of United States gasoline consumption and quantify
the scope 3 CO2; emissions from gasoline consumption. Our model tracks
the movement of refined fuels from county of refinement to county of
blending and eventually to county of consumption via multiple
infrastructure networks -- pipelines, tankers, trains, and trucks. Where
quantities of the fuel moved across different linkages and different
transportation modes are known, they are used as is. However, for the
vast majority of the country, the exact quantities of fuel moved between
county of refining and county of blending or county of blending and
county of consumption, as well as the mode of transportation, is not
known with certainty. Linear optimization is used to model those links
with constraints related to total supply and demand at lower spatial
resolutions (State-level and Petroleum Administration for Defense (PAD)
Districts). This is the first real attempt at a spatially-resolved scope
3 style CO2 emissions data product specific to United States gasoline
consumption. This model can improve understanding of the complex liquid
fuel supply chain, and has significant implications for local policy.
With a complete model of scope 3 CO2 emissions, it is also possible to
analyze how the differences between scope 1 and scope 3 emissions vary
across the country. Finally, this model lays the foundation to model the
evolution of the U.S. gasoline supply chain -- its dependencies,
critical linkages, and pinch points -- and the evolution of scope 1 and
scope 3 CO2 emissions using the full extent of available public data.%
\end{abstract}%



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