近10年中国三大经济区太阳总辐射特征及其与O_3、PM_(2.5)的关系

Characteristics of GSR of China's three major economic regions in the past 10 years and its relationship with O_3 and PM_(2.5)

采用中国地面气象观测站网2007～2016年的辐射日值数据集和中国空气质量在线监测平台2014～2016年逐日观测数据,分析了京津冀、长三角和珠三角近10a太阳总辐射年际和季节变化,近3a臭氧日最大8h平均(O_(3_8h_max))和细颗粒物(PM_(2.5))的污染过程频次变化,通过不同因子及其不同强度等级的分型统计,探讨PM_(2.5)、O_(3_8h_max)与太阳总辐射的关系.结果表明:京津冀近10a太阳总辐射显著上升,京津冀春季和珠三角夏季太阳总辐射显著上升.三大经济区PM_(2.5)污染过程年频次均呈现逐年递减,且从北到南递减;O_3污染过程年频次时间上呈现先减后增,空间上京津冀多于长三角和珠三角.三大经济区O_(3_8h_max)与太阳总辐射相关系数均在0.71以上,有较强的正相关;而PM_(2.5)与太阳总辐射的相关性具有区域差异性.三大经济区不同季节不同太阳总辐射下O_(3_8h_max)与PM_(2.5)的相关关系差异显著,其中京津冀春夏秋三季O_(3_8h_max)与PM_(2.5)在强太阳总辐射下有较好的正相关,冬季则存在一定的负相关;长三角四季两者相关性均较弱;珠三角夏季两者正相关最为显著;不同PM_(2.5)浓度下O_(3_8h_max)与太阳总辐射的线性拟合效果较好,体现出较强的正相关关系,各经济区拟合曲线的倾向率均随PM_(2.5)升高而增大.PM_(2.5)>75μg/m^3时拟合优度均达到最大.

By using daily radiation data collected from ground meteorological observation stations（from 2007 to 2016） and daily observation data from China＇s air quality online monitoring platform（from 2014 to 2016）, the paper analyzed recent 10-year annual and seasonal variations of global solar radiation（GSR）, and recent 3-year frequency of pollution processes of the maximum 8 hour average ozone（O（38 hmax）） and fine particles（PM2.5） in Beijing-Tianjin-Hebei（BTH）, the Yangtze River Delta（YRD） and the Pearl River Delta（PRD）, respectively. The relationship among PM2.5, O（38 hmax） and GSR according to statistics of different factors and intensity were discussed. The results showed that： GSR in BTH had increased significantly in recent 10 years, spring GSR in BTH and summer GSR in PRD had increased significantly meanwhile. The annual frequency of PM2.5 pollution processes in the three major economic regions had been decreasing year by year. Besides, the frequency decreased from north to south. The annual frequency of O3 pollution processes had decreased firstly but then increased temporally, which was more significantly in BTH compared to that in YRD and PRD. The correlation coefficients between O（38 hmax） and GSR in the three economic regions were all above 0.71, reflecting a strong positive correlation, while the correlation between PM2.5 and GSR depicts regional differences. The correlation between O（38 hmax） and PM2.5 under different GSR in different seasons in the three major economic regions was significantly different. In BTH, positive correlation could be found under strong GSR in spring, summer and autumn, while negative correlation was seen in winter. The correlation was weak in all four seasons in YRD. Last but not least, noticeable positive correlation could be found in the summer of PRD. The linear fitting effect of O（38 hmax） and GSR under different PM2.5 concentrations in the three economic regions was well, reflecting a strong positive correlation. The fitting reaches maximum when PM2.5 concentration was over 75 μg/m^3. The tendency of the line fitting increases with the increase of PM2.5 interval.