[Space-Time Estimations and Mapping of PM Fine Particulates Based on Multi-source Data].

PM pollution in China has become an extreme environmental and social problem and has generated widespread public concern. We estimate ground-level PM from satellite-derived aerosol optical depth (AOD), topography data, meteorological data, and pollutant emissions using a new technique, Bayesian maximum entropy (BME) combined with geographically weighted regression (GWR), to evaluate the spatial and temporal characteristics of PM exposure in an eastern region of China in winter. The overall 10-fold cross-validation is 0.