Wang et al.: A Bayesian Downscaler Model to Estimate Daily PM2.5 levels in the Continental U.S

We proposed a statistically reliable and interpretable national modeling framework based on Bayesian downscaling methods to be applied to the calibration of the daily ground PM2.5 concentrations across the conterminous United States using satellite-retrieved aerosol optical depth (AOD) and other ancillary predictors

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