High-Spatial-Resolution Estimates of Ultrafine Particle Concentrations across the Continental United States

摘要

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 R~2 = 0.77, RMSE - 2400 cm~(-3)). Model predictions are robust across a diverse set of evaluations [random 10-fold holdout cross-validation (HCV): R~2 = 0.72, RMSE = 2700 cm~(-3); spatially denned HCV: R~2 = 0.66, RMSE = 3000 cm~(-3); evaluation against an independent data set: R~2 = 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 PM_(2.5) 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.