Analysis of improvement effect of PM2.5 and gaseous pollutants in Beijing based on self-organizing map network

The efforts in controlling PM2.5 have made achievements in China, whereas O-3 increased when PM2.5 reduced. We used Pearson correlation analysis, self-organizing map, and least squares method to analyze the spatiotemporal characteristics of PM2.5, SO2, CO, NO2, and O-3 in Beijing from 2014 to 2019 under the atmospheric control measures. The influence of land surface temperature (LST) on pollution was also explored. PM2.5 was strongly correlated with CO and NO2 and moderately correlated with SO2. The four pollutants were negatively correlated with O-3. The correlation strengthened in winter and changed significantly in summer. Notably, PM2.5 showed the most obvious decline and also exhibited seasonal variability, with higher levels in autumn and winter. Spatially, PM2.5 was higher in the south and lower in the north. PM2.5 levels were higher in urban zones. For gaseous pollutants, CO, SO2, and NO2 levels decreased with a small decrease in NO2, and their spatiotemporal characteristics showed consistency with PM2.5, whereas O-3 showed the opposite trend. CO and SO2 in all districts declined, but NO2 and O-3 increased in some areas. O-3 pollution was higher in the ecological conservation development zone than in urban zones. Finally, only O-3 was significantly correlated with LST in 2019.

Automated summary

Analysis of the spatiotemporal characteristics of air pollutants in Beijing from 2014 to 2019 reveals strong correlations between PM2.5 and CO/NO2, moderate correlation with SO2, and negative correlations with O-3. The pollutants show significant seasonal variability and different trends in different seasons, with PM2.5 exhibiting the most obvious decline.