Ozone Atmospheric Chemistry In Southeast Michigan

Surface ozone (O3) levels in Southeast Michigan (SEMI) have often exceeded U.S. National Ambient Air Quality Standards (NAAQS), posing threats to human and ecosystem health, and air quality. Although SEMI is generally small in comparison to the rest of the state, it is home to most businesses and industries, as well as more than half of the state’s population. With current advancements in high-resolution global chemistry-climate modeling, studying the impacts of O3 at exposure relevant scales has become more feasible. The central objective of this dissertation is to contribute to the understanding of O3 atmospheric chemistry in urban and semi-urban areas, using a high-resolution global modeling approach. To achieve this, an optimized high resolution modeling approach is used with observations to determine scenarios for mitigating O3 air pollution. To do this, two approaches are followed, using the summer of 2021 as a reference period: (i) to explore the distribution of O3 and its precursors (e.g., NOx and VOCs) in SEMI, I evaluate the global chemistry-climate model, MUSICAv0 (Multi-Scale Infrastructure for Chemistry and Aerosols, Version 0), with a custom regionally refined grid mesh over the state of Michigan and diurnally applied anthropogenic NO emissions, with field campaign measurements from the Michigan-Ontario Ozone Source Experiment (MOOSE); and (ii) use the optimized and evaluated model to understand the contribution of different anthropogenic emission sectors (e.g., power generation, transportation) and transport on O3 photochemical production and loss processes, and inform policy makers on different methods for mitigating O3 pollution in the region. In approach (i), the regional refinement capabilities of MUSICAv0 are used to create and test a custom grid over the state of Michigan of ~7 km (1/16˚). In addition, a diurnal cycle for anthropogenic emissions of NOx is applied within the simulation to better optimize and simulate O3 in the region, using sector- and country-specific temporal profiles. The model is then evaluated with stationary, mobile, and aircraft-based remote sensing during the MOOSE field campaign. This work shows that grid resolution is important for simulated O3, but becomes far more important for O3 precursors. Additionally, applying a diurnal cycle for anthropogenic NO emissions from CAMSv5.1 (Copernicus Atmosphere Modeling System Version 5.1) can play a large role in nighttime O3 formation. In the complementary approach (ii), I use the optimized MUSICAv0 model and configuration to explore the different impacts of anthropogenic sectors on O3 atmospheric chemistry in SEMI. This is done by removing global and Michigan-based anthropogenic emissions from different sectors and assessing their impact on O3 concentrations. This work showed that by removing global anthropogenic emissions from sectors, such as transportation, power, generation and industry, leads to large decreases in O3 due to reduced O3 precursors. Michigan-based anthropogenic emission reductions showed minimal changes to peak O3, and moderate changes to O3 in the early mornings. This is indicative that transport plays a key role in driving O3 processes in the region. This also highlights the need for local emission controls, in conjunction with more regional controls in nearby areas. The modeling framework and results described in this thesis are important for the design of effective O3 mitigation strategies in SEMI.

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