Impact of regional versus local resolution air quality modeling on particulate matter exposure health impact assessment

As much of the population lives in close proximity to high-traffic roads, there is the potential for health impact assessments based on regional air quality modeling to underpredict health impacts. We compare the estimated health impacts from fine particulate matter (PM2.5) using local (0.04 x 0.04 km upscaled to census block group resolution) compared to regional (12 x 12 km resolution) modeled concentrations for three locations in Connecticut: Hartford, New Haven, and Willimantic. We use concentration estimates from the Comprehensive Air Quality Model with Extensions (CAMx) regional model and a hybrid model combining CAMx with a near road model (HYCAMR) in the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) to calculate the difference in estimated human health impacts using different resolution air quality estimates from PM2.5 exposure including mortality, emergency room visits, hospitalizations, and asthma exacerbation. This provides an estimate of the potential underprediction of health impacts resulting from not accounting for the sharp concentration gradients in near road environments in urban areas. The fine-scale estimates capture the elevated concentrations near the roadways leading to increased estimates of overall mortality and morbidity in the population. We find an increase in the estimated likelihood of emergency department visits and mortality in the urban core. We also compare the impact of model resolution on the health impact estimates for different demographic groups. Of the locations investigated, we see the largest differences between demographic groups in Willimantic, CT. Our results indicate that using regional air pollutant concentrations may lead to an underprediction of human health impacts from air pollution exposure.