Abstract:

In recent years, there have been frequent smog and heavy pollution incidents in the Beijing-Tianjin-Hebei (Jing-Jin-Ji) area, which have caused widespread concern in the country and society. Based on the data of 68 monitoring stations in the Jing-Jin-Ji area , this paper studied the main variation patterns of the annual data of PM2.5 hours in the Jing-Jin-Ji area, and the characteristics of the temporal and spatial changes. The effect of cumulative annual emissions of sulfur dioxide and nitrogen oxides on changes in PM2.5 concentrations has also been studied. The results show that the emission of nitrogen oxides contributes more to the concentration of PM2.5. The reduction of nitrogen oxides and other pollutants can effectively reduce the concentration of PM2.5 and improve air quality. In this paper, a functional data analysis method is used. Compared with the traditional statistical mean method, it can more effectively use the different data types collected to perform more detailed analysis and thus obtain more reliable conclusions.

Key words: functional data analysis, Beijing-Tianjin-Hebei area, PM2.5