CHARACTERIZING NEAR-SURFACE OZONE ACROSS THE UNITED STATES: PRODUCTION REGIMES, PRECURSOR MONITORING AND MODEL EVALUATION

Abstract

Exposure to elevated concentrations of surface ozone poses significant risks to human health, contributes to premature mortality, and disproportionately impacts socioeconomically disadvantaged communities. Identifying factors influencing surface ozone formation is complicated because ozone photochemical production rates are non-linearly dependent on concentrations of precursors such as nitrogen oxides (NOx) and volatile organic compounds (VOCs). Surface ozone regulation policies rely heavily on air quality models, such as CAMx and CMAQ, for guidance. Comparison with observations is crucial to evaluating a model's ability to represent ozone production chemistry and predict exceedance events. This work analyses ozone production regimes (OPRs) identified from satellite observations and model simulations. CAMx simulations for the summer of 2016 over the Contiguous United States (CONUS) are compared against OMI NO2 and formaldehyde (HCHO) retrievals, exploiting the model's hourly and vertically resolved output to examine the diurnal and vertical evolution of OPR. A new metric is developed to highlight areas where satellite measurements of OPR may not accurately represent near-surface chemistry and where additional ground-based or aircraft measurements are needed. To further assess model capabilities, CMAQ ozone predictions across CONUS from 2003-2019 are evaluated, focusing on exceedance detection capability above the National Ambient Air Quality Standards (NAAQS) threshold. Using a quadrant-based framework, regional and seasonal patterns in model performance are assessed, revealing significant disparities in hit rates across regions. To address monitoring coverage gaps, TEMPO satellite observations were integrated with the US EPA's Environmental Justice Screening and Mapping Tool (EJScreen). A flexible framework for optimal Air Quality System (AQS) sites placement is developed that integrates socioeconomic variables, population density, and satellite retrieved concentrations of NO2 and HCHO. These findings underscore the necessity for targeted policies and interventions to address environmental justice concerns and expand monitoring coverage in underserved areas. This thesis enhances our understanding of ozone production chemistry, model performance limitations and monitoring network gaps, demonstrating the value of integrating air quality models with satellite observations, surface monitors and socioeconomic data to inform equitable and effective air quality management strategies.