Correlation analysis between PM2.5 concentration and meteorological, vegetation and topographical factors in the urbanized ecosystem in Beijing, China

Abstract

With the economic growth and massive industrialization, the air quality of China in general and industrial regions in specific has saturated with different health hazard pollutants. Among the pollutants, PM2.5 is posing some serious threats to the society. In this study we evaluated the correlation between PM2.5 concentration and 12 different meteorological, vegetation and topographical factors in Beijing, China. We used the Difference Index (DI) method and dark pixel method to retrieve the PM2.5 concentration of 30m and 1km spatial resolution. Spearman correlation analysis method was used to analyse the correlation between PM2.5 concentration and three types of 12 factors. The results showed that the forest land can play a major role in decreasing the PM2.5 concentration in the air, as in this study a significant drop of (18.78%) was observed in PM2.5 concentration in the regions having coniferous forest. Moreover, the PM2.5 reduction rate was positively correlated with forest vegetation coverage (FVC). Our results demonstrated that relative humidity, air pressure and water vapour pressure were positively correlated with PM2.5, while air temperature and wind speed were negatively correlated. The altitude and slope showed a weak negative correlation with PM2.5 concentration, while, aspect was very weakly correlated with the PM2.5 concentration. The findings of this study could help design the urban green space planning and air pollutioncontrol in the heavily populated urban ecosystems.