小波分析在郑州市供暖期PM_(2.5)浓度相关性分析中的应用

Application of wavelet analysis in correlation analysis of PM_(2.5) concentration in Zhengzhou City during heating period

为分析供暖期内各种物质与PM2.5的相关性和变化规律,以郑州市供暖期为例,运用Morlet小波分别对PM2.5、PM10、CO、NO2、和SO2的浓度进行分析,并对比各自主周期的小波系数模。结果表明,PM10与PM2.5波动主周期均为33 d,主周期小波系数模差值为0,与PM2.5相关性最高;SO2波动主周期为12 d,与PM2.5相差最大,相关性最低。由于燃煤中各成分含量不同,供暖期SO2与CO、NO2呈中度相关,相关系数依次为0.6045和0.6949;SO2与PM10呈低度相关,相关系数为0.4010。供暖期污染最严重的污染物是PM10和NO2,与非供暖期相比,两者与PM2.5相关系数增量分别为:0.1255和0.2858,相关性提高幅度较大。

To analyze the correlations and variations between different atmospheric substances and PM2.5 during heating period, taking Zhengzhou as example, Morlet wavelet was employed to analyze the concentrations of PM2.5 , PM10, CO, NO2 , and SO2 ,respectively, and the wavelet coefficient modulus of each independent cy- cle were compared. The results showed that the wave primary cycles of both PM10 and PM25 were 33 days, and their wavelet coefficient modulus difference in primary eycle was 0, so PM10 had the highest correlation with PM2.5 ; the wave primary cycle of SO2 was 12 days which showed the greatest variance with PM2.5 , so SO2 had the lowest correlation with PM25. During heating period, due to the different composition contents in coal-fired, the concentration of SO2 was moderately correlated with that of CO and NO2, the correlation coefficients being 0. 6045 and 0. 6949, respectively ; the concentration of 502 was lowly correlated with that of PM10, the correla- tion coefficient being 0. 4010. PM10 and NO2 were the most serious pollutants during heating period, their coeffi- cient increments of correlation with PM2.5 were 0. 1255 and 0. 2858, which increased considerably compared with non - heating period.