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Using Linear Optimization To Model Spatially Resolute Emissions Of CO2 From Gasoline Flows Across The United States
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  • Taha Moiz,
  • Kevin Gurney,
  • Richard Rushforth,
  • Benjamin Ruddell,
  • Deborah Huntzinger,
  • Nathan Parker
Taha Moiz
Arizona State University

Corresponding Author:tahamoiz@asu.edu

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Kevin Gurney
Northern Arizona University
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Richard Rushforth
Northern Arizona University
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Benjamin Ruddell
Northern Arizona University
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Deborah Huntzinger
Northern Arizona University
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Nathan Parker
Arizona State University
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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.