Spatiotemporal PM2.5 variations and its response to the industrial structure from 2000 to 2018 in the Beijing-Tianjin-Hebei region

The economy has developed rapidly in China during recent decades, especially in the Beijing-Tianjin-Hebei (BTH) region. Environmental problems have thus become increasingly prominent, particularly the presence of fine particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5). High-quality and high-resolution PM2.5 data is urgently needed. Therefore, based on the newly released Moderate Resolution Imaging Spectroradiometer (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol optical depth products, a high-quality PM2.5 data set with a high spatial resolution of 1 km is first reconstructed covering 2000 to 2018 in the BTH region using the linear mixed effect (LME) model. This model shows an excellent performance with a high cross-validation coefficient of determination (R2) of 0.85, a small root mean square error of 21.49 μg/m3, and a small mean absolute error of 15.26 μg/m3 from 2013 to 2018. It also has strong predictive power in estimating historical PM2.5 concentrations, with a monthly R2 equal to 0.72. There was a significant decreasing trend (i.e., −1.53 μg/m3, p