High-Spatial-Resolution Estimates of Ultrafine Particle Concentrations across the Continental United States
Provat K. Saha, Steve Hankey, Julian Marshall, Allen L. Robinson, Albert A. Presto
Abstract
There is growing evidence that ultrafine particles (UFP; particles smaller than 100 nm) are likely more toxic than larger particles. However, the health effects of UFP remain uncertain due in part to the lack of large-scale population-based exposure assessment. We develop a national-scale empirical model of particle number concentration (PNC; a measure of UFP) using data from mobile monitoring and fixed sites across the United States and a land-use regression (LUR) modeling framework. Traffic, commercial land use, and urbanicity-related variables explain much of the spatial variability of PNC (base model R2 = 0.77, RMSE = 2400 cm–3). Model predictions are robust across a diverse set of evaluations [random 10-fold holdout cross-validation (HCV): R2 = 0.72, RMSE = 2700 cm–3; spatially defined HCV: R2 = 0.66, RMSE = 3000 cm–3; evaluation against an independent data set: R2 = 0.54, RMSE = 2600 cm–3]. We apply our model to predict PNC at ∼6 million residential census blocks in the contiguous United States. Our estimates are annual average concentrations for 2016–2017. The predicted national census-block-level mean PNC ranges between 1800 and 26 600 cm–3 (population-weighted average: 6500 cm–3), with hotspots in cities and near highways. Our national PNC model predicts large urban–rural, intra-, and inter-city contrasts. PNC and PM2.5 are moderately correlated at the city scale, but uncorrelated at the regional/national scale. Our high-spatial-resolution national PNC estimates are useful for analyzing population exposure (socioeconomic disparity, epidemiological health impact) and environmental policy and regulation.