A method to predict PM2.5 resulting from compliance with national ambient air quality standards

Abstract

Area-wide composite monitor time series of daily PM2.5 (particulate matter with aerodynamic diameter < 2.5 μm) that correspond to just meeting U.S. National Ambient Air Quality Standards (NAAQS) have been used in risk assessments conducted during periodic reviews of PM NAAQS by U.S. EPA. Such time series were developed by adjusting ambient PM2.5 over an area according to a prescribed spatial pattern. A new technique for this purpose based on photochemical grid modeling for the continental U.S. is demonstrated here. The method uses a spatial prediction model to impute missing data and PM2.5 relative response factors based on simulations with reductions in anthropogenic emissions of primary PM2.5 and PM2.5 precursors (i.e., NOx and SO2). Case study results indicate that relatively urban sites are generally more responsive to primary PM2.5 reductions, while outlying sites are more responsive to NOx and SO2 reductions. The method enables the sensitivity of outcomes to be examined by quickly implementing PM2.5 adjustments based on different combinations of primary PM2.5 and NOx and SO2 emission reductions for areas of the U.S.