Predicting gridded winter PM_2.5 concentration in the east of China

Abstract. Exposure to high concentration levels of fine particle matter with diameter ?2.5 µm (PM2.5) can lead great threats human health in the east China. Air pollution control has greatly reduced PM2.5 and entered a crucial stage that required support like seasonal prediction. In this study, we analyzed contributions emission predictors climate variability prediction concentration. The socioeconomic PM2.5, isolated by atmospheric chemical models, could well describe gradual increasing trend during winters 2001–2012 sharp decreasing since 2013. preceding have successfully simulated interannual winter Based on year-to-year increment approach, model for gridded (10 km × 10 km) China was trained integrating predictors. area-averaged percentage same sign 81.4 % (relative 2001–2019) leave-one-out validation. three densely populated heavily polluted regions, correlation coefficients were 0.93 (North China), 0.95 (Yangtze River Delta) 0.87 (Pearl 2001–2019, root-mean-square errors 6.8, 4.2 4.7 µg m?3. More important, significant decrease concentration, resulting from implementation strict measures recent years, also reproduced. recycling independent tests, developed study maintained accuracy robustness. Furthermore, accurate had potential air regional city scales.