| 2015~2020年中国城市PM2.5-O3复合污染时空演变特征 |
| 摘要点击 2298 全文点击 1624 投稿时间：2022-05-03 修订日期：2022-07-11 |
| 查看HTML全文
查看全文 查看/发表评论 下载PDF阅读器 |
| 中文关键词 PM2.5 臭氧(O3) 复合污染 时空演变 中国 |
| 英文关键词 PM2.5 ozone(O3) compound pollution spatiotemporal evolution China |
| 作者 | 单位 | E-mail | | 牛笑笑 | 武汉大学资源与环境科学学院, 地理信息系统教育部重点实验室, 武汉 430079 | 1437230945@qq.com | | 钟艳梅 | 武汉大学资源与环境科学学院, 地理信息系统教育部重点实验室, 武汉 430079 | | | 杨璐 | 武汉大学资源与环境科学学院, 地理信息系统教育部重点实验室, 武汉 430079 | | | 易嘉慧 | 武汉大学资源与环境科学学院, 地理信息系统教育部重点实验室, 武汉 430079 | | | 慕航 | 武汉大学资源与环境科学学院, 地理信息系统教育部重点实验室, 武汉 430079 | | | 吴倩 | 武汉大学资源与环境科学学院, 地理信息系统教育部重点实验室, 武汉 430079 | | | 洪松 | 武汉大学资源与环境科学学院, 地理信息系统教育部重点实验室, 武汉 430079 | songhongpku@126.com | | 何超 | 长江大学资源与环境学院, 武汉 430100 | hechao@yangtzeu.edu.cn |
|
| 中文摘要 |
| 基于2015~2020年中国333个城市PM2.5和O3浓度监测数据，利用空间聚类、趋势分析和地理重力模型等方法，定量分析我国主要城市的PM2.5-O3复合污染特征和时空演变格局.结果表明：① PM2.5和O3浓度存在协同变化规律，当ρ（PM2.5_mean）≤85 μg ·m-3时，ρ（PM2.5_mean）和ρ（O3_perc90）存在同步增长的现象；当ρ（PM2.5_mean）处于国家Ⅱ级限值（35±10）μg ·m-3时，ρ（O3_perc90）平均值的峰值增速最快；当ρ（PM2.5_mean）>85 μg ·m-3时，ρ（O3_perc90）平均值出现显著下降趋势.②我国城市PM2.5和O3浓度空间聚类格局类似，ρ（PM2.5_mean）和ρ（O3_perc90）的6 a平均值热点区域集中分布在京津冀、山西、河南和安徽等地区.③ PM2.5-O3复合污染城市数量的年际变化趋势为先增（2015~2018年）后降（2018~2020年），季节变化趋势为从春到冬持续减少，复合污染现象主要发生在暖季（4~10月）.④ PM2.5-O3复合污染城市数量的空间分布呈现扩散（2015~2017年）-聚集（2017~2020年）的规律.⑤ PM2.5和O3浓度重心的迁移方向相似，存在明显的西移和北移趋势，高浓度复合污染问题在中国中北部城市更明显. |
| 英文摘要 |
| Based on the monitoring data of PM2.5 and O3 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 PM2.5-O3 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 PM2.5 and O3 concentrations. When ρ(PM2.5_mean) ≤ 85 μg·m-3, for every 10 μg·m-3 increase in ρ(PM2.5_mean), the peak of the mean value of ρ(O3_perc90) increased by 9.98 μg·m-3. When ρ(PM2.5_mean) exceeded the national Grade II standards of (35±10) μg·m-3, the peak of the mean value of ρ(O3_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 ρ(PM2.5_mean) in the range of 45 to 85 μg·m-3. When ρ(PM2.5_mean)>85 μg·m-3, the mean value of ρ(O3_perc90) showed a significant decreased trend. ② The spatial clustering pattern of PM2.5 and O3 concentrations in Chinese cities was similar, and hot spots of the six-year mean values of ρ(PM2.5_mean) and ρ(O3_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 PM2.5-O3 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 PM2.5-O3 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 PM2.5 and O3 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 PM2.5 and O3 concentrations in the compound polluted areas had been significantly reduced, with a reduction of nearly 50%. |
|
|
|
