Estimation of hourly PM₁ concentration in China and its application in population exposure analysis

Particulate pollution is closely related to public health. PM₁ (particles with an aerodynamic size not larger than 1 μm) is much more harmful than particles with larger sizes because it goes deeper into the body and hence arouses social concern. However, the sparse and unevenly distributed ground-based observations limit the understanding of spatio-temporal distributions of PM₁ in China. In this study, hourly PM₁ concentrations in central and eastern China were retrieved based on a random forest model using hourly aerosol optical depth (AOD) from Himawari-8, meteorological and geographic information as inputs. Here the spatiotemporal autocorrelation of PM₁ was also considered in the model. Experimental results indicate that although the performance of the proposed model shows diurnal, seasonal and spatial variations, it is relatively better than others, with a determination coefficient (R²) of 0.83 calculated based on the 10-fold cross validation method. Geographical map implies that PM₁ pollution level in Beijing-Tianjin-Hebei is much higher than in other regions, with the mean value of ∼55 μg/m³. Based on the exposure analysis, we found about 75% of the population lives in an environment with PM₁ higher than 35 μg/m³ in the whole study area. The retrieval dataset in this study is of great significance for further exploring the impact of PM₁ on public health.