长三角城市群的PM_(2.5)和PM_(10)演变趋势及空间效应分析

Evolution trend and spatial differentiation characteristics of PM_(2.5) and PM_(10) in Yangtze River Delta urban agglomeration

为有效了解长三角城市群大气颗粒物的时空变化特征,选取区域内2005—2019年PM_(2.5)和PM_(10)数据探讨变化趋势和污染特征,并采用莫兰指数和局部自相关(LISA)聚类图剖析空间自相关性。结果表明:(1)长三角城市群空气质量逐年改善,整体PM_(10)在2018—2019年已达到了《环境空气质量标准》(GB 3095—2012)二级标准。(2)2019年箱线图中PM_(2.5)和PM_(10)月均值变化为“V”形,数据离散性与浓度变化规律一致,8月均值最低(分别为21、39μg/m^(3)),1月均值最高(分别为73、99μg/m^(3))。(3)长三角41个城市的PM_(2.5)和PM_(10)季均值的线性拟合效果各不相同,春、夏、秋、冬季的R^(2)分别为0.7807、0.5885、0.9027、0.8715。(4)长三角城市群PM_(2.5)、PM_(10)年均值在空间分布上的变化规律基本一致:年均值都是南部较低、北部较高;沿海地区污染比内陆城市小;浙江、上海的污染程度普遍低于江苏和安徽。(5)PM_(2.5)、PM_(10)的全局莫兰指数均大于0.6,莫兰散点图数据基本集中分布在第一、三象限,即高高和低低聚集,表明空间聚集特征显著,相应LISA聚类图分析结果的高高、低低聚类地区分别为皖北苏北部、浙江南部。

To effectively understand the temporal and spatial variation characteristics of atmospheric particulate matter in the Yangtze River Delta urban agglomeration,the concentration data of PM_(2.5)and PM_(10)were selected to explore the variation trend and pollution characteristics in the region from 2005 to 2019.In addition,Moran’s index and LISA cluster map were used to analyze the spatial autocorrelation.The results showed that:(1)the air quality in the Yangtze River Delta region had improved year by year,and the overall PM_(10)had reached the secondary standard of the“Ambient air quality standards”(GB 3095-2012)from 2018 to 2019.(2)The monthly mean values of PM_(2.5)and PM_(10)in the box plot in 2019 presented a“V”shape,and data scatter was consistent with the law of concentration changes.The mean values in August were the lowest(21,39μg/m^(3),respectively),and the mean values in January were the highest(73,99μg/m^(3),respectively).(3)The linear fitting effects of the seasonal mean values of PM_(2.5)and PM_(10)in 41 cities in the Yangtze River Delta region were different.The R^(2) of spring,summer,autumn,and winter were 0.7807,0.5885,0.9027,0.8715,respectively.(4)In the Yangtze River Delta urban agglomeration,the spatial variation law of PM_(2.5)and PM_(10)annual mean values was basically the same.The annual mean value was lower in the south and higher in the north.Coastal areas were less polluted than inland cities.And the pollution level of Zhejiang and Shanghai was generally lower than that of Jiangsu and Anhui.(5)The global Moran’s index of PM_(2.5)and PM_(10)were greater than 0.6,and scatter map data were basically concentrated in the first and third quadrants,that was high-high and low-low aggregation.It showed that the spatial aggregation characteristics were significant.The high-value clusters in the LISA map were concentrated in the northern areas of Anhui and Jiangsu,and the low-value clusters were concentrated in the southern areas of Zhejiang.