Disparities in air quality downscaler model uncertainty across socioeconomic and demographic indicators in North Carolina.

Studies increasingly use output from the Environmental Protection Agency's Fused Air Quality Surface Downscaler ("downscaler") model, which provides spatial predictions of daily concentrations of fine particulate matter (PM) and ozone (O) at the census tract level, to study the health and societal impacts of exposure to air pollution. Downscaler outputs have been used to show that lower income and higher minority neighborhoods are exposed to higher levels of PM and lower levels of O. However, the uncertainty of the downscaler estimates remains poorly characterized, and it is not known if all subpopulations are benefiting equally from reliable predictions. We examined how the percent errors (PEs) of daily concentrations of PM and O between 2002 and 2016 at the 2010 census tract centroids across North Carolina were associated with measures of racial and educational isolation, neighborhood disadvantage, and urbanicity. Results suggest that there were socioeconomic and demographic disparities in surface concentrations of PM and O, as well as their prediction uncertainties. Neighborhoods characterized by less reliable downscaler predictions (i.e., higher PE and PE) exhibited greater levels of aerial deprivation as well as educational isolation, and were often non-urban areas (i.e., suburban, or rural). Between 2002 and 2016, predicted PM and O levels decreased and O predictions became more reliable. However, the predictive uncertainty for PM has increased since 2010. Substantial spatial variability was observed in the temporal changes in the predictive uncertainties; educational isolation and neighborhood deprivation levels were associated with smaller increases in predictive uncertainty of PM. In contrast, racial isolation was associated with a greater decline in the reliability of PM predictions between 2002 and 2016; it was associated with a greater improvement in the predictive reliability of O within the same time frame.