Niu Xiao-Xiao, Zhong Yan-Mei, Yang Lu, Yi Jia-Hui, Mu Hang, Wu Qian, Hong Song, He Chao
Key Laboratory of Geographic Information System, Ministry of Education, School of Resources and Environmental Sciences, Wuhan University, Wuhan 430079, China.
College of Resources and Environment, Yangtze University, Wuhan 430100, China.
Huan Jing Ke Xue. 2023 Apr 8;44(4):1830-1840. doi: 10.13227/j.hjkx.202205018.
Based on the monitoring data of PM and O concentrations in 333 cities in China from 2015 to 2020, using spatial clustering, trend analysis, and the geographical gravity model, this study quantitatively analyzed the characteristics of PM-O compound pollution concentrations and its spatiotemporal dynamic evolution pattern in major cities in China. The results showed that:① there was a synergistic change in PM and O concentrations. When (PM_mean) ≤ 85 μg·m, for every 10 μg·m increase in (PM_mean), the peak of the mean value of (O_perc90) increased by 9.98 μg·m. When (PM_mean) exceeded the national Grade II standards of (35±10) μg·m, the peak of the mean value of (O_perc90) increased the fastest, with an average growth rate of 11.81%. In the past six years, on average, 74.97% of Chinese cities with compound pollution had a (PM_mean) in the range of 45 to 85 μg·m. When (PM_mean)>85 μg·m, the mean value of (O_perc90) showed a significant decreased trend. ② The spatial clustering pattern of PM and O concentrations in Chinese cities was similar, and hot spots of the six-year mean values of (PM_mean) and (O_perc90) were distributed in the Beijing-Tianjin-Hebei urban agglomeration and other cities in the Shanxi, Henan, and Anhui provinces. ③ The number of cities with PM-O compound pollution showed an interannual variation trend of increasing first (2015-2018) and then decreasing (2018-2020) and a seasonal trend of gradually decreasing from spring to winter. Further, the compound pollution phenomenon mainly occurred in the warm season (April to October). ④ The spatial distribution of PM-O compound polluted cities was changing from dispersion to aggregation. From 2015 to 2017, the compound polluted areas spread from the eastern coastal areas to the central and western regions of China, and by 2017, a large-scale polluted area centered on the Beijing-Tianjin-Hebei urban agglomeration, the Central Plains urban agglomeration, and surrounding areas was formed. ⑤ The migration directions of PM and O concentration centers were similar, and there were obvious trends of moving westward and northward. The problem of high-concentration compound pollution was concentrated and highlighted in cities in central and northern China. In addition, since 2017, the distance between the centers of gravity of PM and O concentrations in the compound polluted areas had been significantly reduced, with a reduction of nearly 50%.
基于2015—2020年中国333个城市的PM和O浓度监测数据，运用空间聚类、趋势分析及地理重心模型，本研究定量分析了中国主要城市PM-O复合污染浓度特征及其时空动态演变格局。结果表明：①PM和O浓度存在协同变化。当(PM_mean)≤85 μg·m时，(PM_mean)每升高10 μg·m，(O_perc90)均值峰值升高9.98 μg·m。当(PM_mean)超过国家二级标准(35±10) μg·m时，(O_perc90)均值峰值升高最快，平均增长率为11.81%。过去六年，中国复合污染城市平均74.97%的(PM_mean)处于45~85 μg·m范围。当(PM_mean)>85 μg·m时，(O_perc90)均值呈显著下降趋势。②中国城市PM和O浓度的空间聚类格局相似，(PM_mean)和(O_perc90)六年均值热点分布于京津冀城市群及山西、河南、安徽等省份的其他城市。③PM-O复合污染城市数量呈先增加(2015—2018年)后减少(2018—2020年)的年际变化趋势及从春季到冬季逐渐减少的季节趋势。此外，复合污染现象主要发生在温暖季节(4月至10月)。④PM-O复合污染城市的空间分布正从分散向聚集转变。2015—2017年，复合污染区域从东部沿海地区向中国中西部地区扩散，到2017年，形成了以京津冀城市群、中原城市群及周边地区为中心的大规模污染区域。⑤PM和O浓度中心的迁移方向相似，存在明显的向西和向北移动趋势。高浓度复合污染问题在中国中部和北部城市集中凸显。此外，自2017年以来，复合污染区域内PM和O浓度重心之间的距离显著缩短，减少了近50%。
