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Abstract The southern Lake Michigan region of the United States, home to Chicago, Milwaukee, and other densely populated Midwestern cities, frequently experiences high pollutant episodes with unevenly distributed exposure and health burdens. Using the two‐way coupled Weather Research Forecast and Community Multiscale Air Quality Model (WRF‐CMAQ), we investigate criteria pollutants over a southern Lake Michigan domain using 1.3 and 4 km resolution hindcast simulations. We assess WRF‐CMAQ's performance using data from the National Climatic Data Center and Environmental Protection Agency Air Quality System. Our 1.3 km simulation slightly improves on the 4 km simulation's meteorological and chemical performance while also resolving key details in areas of high exposure and impact, that is, urban environments. At 1.3 km, we find that most air quality‐relevant meteorological components of WRF‐CMAQ perform at or above community benchmarks. WRF‐CMAQ's chemical performance also largely meets community standards, with substantial nuance depending on the performance metric and component assessed. For example, hourly simulated NO₂and O₃are highly correlated with observations (r > 0.6) while PM_2.5is less so (r = 0.4). Similarly, hourly simulated NO₂and PM_2.5have low biases (<10%), whereas O₃biases are larger (>30%). Simulated spatial pollutant patterns show distinct urban‐rural footprints, with urban NO₂and PM_2.520%–60% higher than rural, and urban O₃6% lower. We use our 1.3 km simulations to resolve high‐pollution areas within individual urban neighborhoods and characterize seasonal changes in O₃regimes across tight spatial gradients. Our findings demonstrate both the benefits and limitations of high‐resolution simulations, particularly over urban settings.