An Energy Systems Model Approach to US Decarbonization: Technological Solutions, Policy Pathways, and Equity Outcomes

 Energy system optimization models (ESOMs) are invaluable tools for researchers and policymakers studying the energy transition. Bottom-up ESOMs simulate technology-level decisions within an energy system, including interactions across economic sectors. These models include detailed techno-economic technological representation of individual technologies, requiring inputs including capital, fixed, and variable costs, energy consumption, technology lifetime, and emissions factors. The results provide insight into possible future energy systems, including the total system cost, technology capacity, energy use, and emissions, based on current techno-economic data and assumptions. In this thesis, I use the Tools for Energy Model Optimization and Analysis (Temoa), an open-source bottom-up ESOM, to simulate the US energy system under various decarbonization policies. In Chapter 2, I simulate the Inflation Reduction Act (IRA) in conjunction with various policy instruments to understand how the US can meet its stated climate goals. Specifically, I compare a carbon tax to a combination of technology and fuel standards, finding that the average GHG abatement cost under the modeled standards is comparable to a carbon tax set at ~$200/ton CO2-eq, and both policies achieve similar emissions reductions. In Chapter 3, I develop an algorithm to translate regional air pollution from the transportation and electric sectors to the county resolution, then link the results to an integrated assessment model. I then quantify air pollution exposure and disparity across racial groups under six different policies, including a 2050 net-zero target. I find that existing disparities persist until at least 2030, particularly for Black non-Hispanic Americans. After 2035, the strictest policies approach racial equity, achieving at least an 80% reduction in disparity and exposure for all racial groups relative to 2020. In Chapter 4, I explore the role of hydrogen in decarbonizing steel production in the US. I find that, despite industry and research attention on hydrogen-based direct reduced iron (H2DRI), this technology is only a cost-effective decarbonization strategy under a very narrow set of conditions. Under current capital and variable cost estimates of US steel decarbonization, we find that carbon capture technologies can achieve comparable emissions reductions relative to H2DRI at a lower price. We find that green hydrogen is deployed preferentially elsewhere in the economy under a net-zero constraint. Additionally, we find that IRA tax credits are insufficient to drive hydrogen use in steelmaking, and for sustained H2DRI use, a tax credit specifically aimed at promoting green steel production would need to be as high as $300 per tonne steel produced.