Developing National Exposure Models for Source-Specific Primary Particulate Matter Concentrations Using Aerosol Mass Spectrometry Data

PROVAT SAHA, Albert A. Presto, Steven Hankey, Benjamin Murphy, Julian Marshall, Allen Robinson, Carnegie Mellon University

     Abstract Number: 269
     Working Group: Aerosol Exposure

Abstract
In this study, we investigate the feasibility of developing national empirical models to predict ambient concentrations of sparsely monitored air pollutants at high spatial resolution. We measured cooking organic aerosol (COA) and hydrocarbon-like organic aerosol (HOA; traffic primary organic PM) using High-Resolution Aerosol Mass Spectrometry (HR-AMS) in twelve states, eleven cities, and eleven sub-urban/remote locations across the continental US. To characterize intra-urban spatial patterns we performed high-resolution mobile monitoring in three cities. The monitoring locations were carefully selected to span the national distribution of land-use and source-activity covariates commonly used for land-use regression models (e.g. road length, restaurant count, etc.). Empirical models developed through supervised linear regression select predictor variables that are physically meaningful. Restaurant density and commercial land use-related variables are important predictors for the spatial variability of COA. Transportation and urbanicity-related variables are important predictors for the spatial variability of HOA. Extensive cross-validation suggests the models are robust with reasonable transferability. The models predict large urban-rural and intra-urban variability with hotspots in urban areas and along the road corridors. The predicted national concentration surfaces show a reasonable spatial correlation with source-specific national chemical transport model (CTM: CMAQ) simulations. The measured data, empirical models, and CTM predictions all show that cooking emitted primary organic aerosol concentrations are higher than traffic primary organic aerosol. This highlights the potential importance of controlling commercial cooking emissions for air quality management in the US.