基于ESDA的省域空气污染空间特征研究

运用探索性空间数据分析(ESDA)方法,对中国31个省份的空气质量指数和PM2.5进行了空间分布和时空演化分析,结果显示,中国省域空气综合污染存在较强的空间自相关性,可对相邻区域空气质量造成影响.PM2.5污染与空气综合污染的空间相关趋势保持了高度的一致性,体现主导污染物的地位.辽宁与华北省份北京、天津、河北、山东,以及部分华中省份河南、湖北及江苏形成了较为稳定的高污染集聚区,较轻污染的集聚大多分布在西部、西南和东南沿海区域.基于空间特征的污染治理措施,可实现功效发挥的最大化.

Spatial Characteristic Study of Provincial Air Pollution in China Based on ESDA

By the method of exploratory spatial data analysis( ESDA) , spatial characteristics and temporal and spatial evolu-tion of air quality index and PM2. 5 of 31 provinces in China are analyzed. Results show that provincial comprehensive air pollution in our country exists strong spatial correlation, which can affect the air quality of adjacent areas. Trends of spatial correlation of PM2. 5 pollution and air comprehensive pollution are in a high degree of consistency, reflecting the PM2. 5 's dominant position. Lia-oning, Beijing, Tianjin, Hebei, Shandong, Henan, Hubei and Jiangsu form a relatively stable area with high pollution concentra-tion. There is also a agglomeration phenomenon of lighter pollution, mostly distributes in the west, the southwest and southeast coastal area. Pollution control measures based on spatial characteristics can maximize the performance.