Abstract View
Disparities in Air Quality Downscaler Model Uncertainty across Socioeconomic and Demographic Indicators in North Carolina
SHAN ZHOU, Robert Griffin, Alexander Bui, Mercedes Bravo, Claire Osgood, Marie Lynn Miranda, Rice University
Abstract Number: 564
Working Group: Translating Aerosol Research for Societal Impact: Science Communication and Public Outreach
Abstract
An increasing number of studies uses output from the EPA’s Fused Air Quality Surface Downscaler (“downscaler”), which provides spatial predictions of daily ozone and PM2.5 concentrations at the census tract level, to study the health and societal impacts of exposure to air pollution. It has been shown that lower socioeconomic status (SES) and higher proportion minority populations typically are exposed to higher levels of fine particulate matter (PM2.5) and lower levels of ozone (O3). 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 the predictions and standard deviations of daily concentrations of PM2.5 and O3 between 2002 and 2016 at the 2010 census tract centroids across North Carolina in association with SES, the racial isolation of non-Hispanic blacks, educational isolation of non-college educated individuals, and the Neighborhood Deprivation Index. Results showed that there were socioeconomic and demographic disparities in surface concentrations of O3 and PM2.5. The reliability of air quality predictions also showed socio-demographic inequality; more disadvantaged neighborhoods with lower SES suffered from less reliable predictions. Overall, PM2.5 and O3 levels decreased between 2002 and 2016; the uncertainty of O3 predictions also has decreased since 2002. However, the uncertainties associated with predicted PM2.5 concentrations have increased since 2009. Substantial spatial variability was observed in these temporal changes; the disadvantaged, lower SES, and higher proportion minority population experienced greater improvements in air quality and O3 prediction reliability. Although PM2.5 uncertainty increased over the years, these populations experienced a less significant absolute increase.