High-resolution Estimation of Spatio-temporal Variation in PM2.5 Concentrations in the Beijing-Tianjin-Hebei Region

Abstract

This study developed a two-stage statistical model (linear mixed effect (LME) model+geographical weight regression (GWR) model) to determine the spatio-temporal variation of PM2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) region with full-coverage, high resolution, and high accuracy. The model employs multi-angle implementation of atmospheric correction aerosol optical depth (MAIAC AOD) data, with a 1 km spatial resolution, as the main predictor and meteorological data/land-use data as the auxiliary predictors. To determine the characteristics of heavy PM2.5 pollution in the BTH region, unique predictors such as AOD2 were also introduced into the two-stage model. The two-stage model was used to estimate the daily PM2.5 concentrations with a 1 km resolution. After being cross-validated against ground observations, the R2 of PM2.5 was found to be 0.94, with a slope value of 0.95 and RMSPE value of 13.14 μg·m-3. Compared to previous studies such as LME, the two-stage model has much higher accuracy, suitable for estimating PM2.5 concentrations. The PM2.5 concentration in the BTH region ranged from 0 to 89.89 μg·m-3 in 2017, with a mean value of 44.96 μg·m-3. The spatio-temporal variability of PM2.5 over the BTH region was significant, exhibiting high values over the southwestern plain, moderate values over the northeastern plain, and low values over the mountainous plateau. In terms of seasonal variation, PM2.5 concentrations were high in winter, low in summer, and moderate in spring and autumn. The estimated PM2.5 concentrations, with high spatio-temporal resolution, are useful for exposure assessments in epidemiological studies and identifying the spatio-temporal variation of pollution sources at a fine spatial scale. The results show that the locations of vital pollution sources over the severely polluted south-central Hebei piedmont plain may have changed since the implementation of the Air Pollution Prevention and Control Action Plan. This study could provide a scientific basis for the prevention and control of air pollution in the BHT region.