Public health costs accounting of inorganic PM2.5 pollution in metropolitan areas of the United States using a risk-based source-receptor model.

In order to design effective strategies to reduce the public health burden of ambient fine particulate matter (PM2.5) imposed in an area, it is necessary to identify the emissions sources affecting that location and quantify their contributions. However, it is challenging because PM2.5 travels long distances and most constituents are the result of complex chemical processes. We developed a reduced-form source-receptor model for estimating locations and magnitudes of downwind health costs from a source or, conversely, the upwind sources that contribute to health costs at a receptor location. Built upon outputs from a state-of-the-art air quality model, our model produces comprehensive risk-based source apportionment results with trivial computational costs. Using the model, we analyzed all the sources contributing to the inorganic PM2.5 health burden in 14 metropolitan statistical areas (MSAs) in the United States. Our analysis for 12 source categories shows that 80-90% of the burden borne by these areas originates from emissions sources outside of the area and that emissions sources up to 800 km away need to be included to account for 80% of the burden. Conversely, 60-80% of the impacts of an MSA's emissions occurs outside of that MSA. The results demonstrate the importance of regionally coordinated measures to improve air quality in metropolitan areas.