Simulation of Neighborhood-Scale Air Quality With Two-Way Coupled WRF-CMAQ Over Southern Lake Michigan-Chicago Region

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 NO2 and O-3 are highly correlated with observations (r > 0.6) while PM2.5 is less so (r = 0.4). Similarly, hourly simulated NO2 and PM2.5 have low biases (<10%), whereas O-3 biases are larger (>30%). Simulated spatial pollutant patterns show distinct urban-rural footprints, with urban NO2 and PM2.5 20%-60% higher than rural, and urban O-3 6% lower. We use our 1.3 km simulations to resolve high-pollution areas within individual urban neighborhoods and characterize seasonal changes in O-3 regimes across tight spatial gradients. Our findings demonstrate both the benefits and limitations of high-resolution simulations, particularly over urban settings.Plain Language Summary In this study we use an air quality model to simulate air pollution at very fine spatial scales over a central midwestern U.S. domain that includes Chicago, IL and Milwaukee, WI. We assess our model's performance relative to meteorological and air quality observations and then characterize the spatial patterns of modeled pollutants. We find large differences in air pollution between urban and rural settings. Because our model operates at fine spatial scales, we are also able to discuss differences in air pollution in different neighborhoods in individual cities. In Chicago, we find elevated pollution near highways and in south and west side neighborhoods, findings that are consistent with previous reports of disparate air quality related health impacts.