长三角地区秋冬季大气PM_(2.5)含量空间变异特征

Spatial variations of atomspheric PM_(2.5) concentration in autumn and winter in Yangtze River Delta

利用长三角地区的128个国控大气监测站2014年11月到2015年1月的PM_(2.5)浓度逐时数据,采用地统计学方法进行了ρ(PM_(2.5))的空间异质性分析,并讨论了其动态变化的影响因素.结果表明,研究时段内ρ(PM_(2.5))的基底效应值在0.07—0.26之间,空间自相关性较强.块金值呈逐步变大趋势,表明PM_(2.5)人为源对其空间异质性的影响逐渐加强.ρ(PM_(2.5))变程值在217.1—336.2 km之间,东-西方向大于南-北方向.可依据各季节空气PM_(2.5)含量空间自相关距离的1/4—1/2进一步优化环境空气质量监测网点.根据普通克里格法空间插值结果得出,研究区PM_(2.5)污染呈片状分布,且PM_(2.5)污染程度持续加重,污染重心在苏锡常都市圈、南京都市圈和徐州都市圈,是空气PM_(2.5)污染防治的关键区域.南京都市圈和徐州都市圈可能受到WSW上风向外源输送的强烈影响,苏锡常都市圈则对SSE下风向的城市群构成较大的潜在影响.PM_(2.5)还与SO2、CO、NO2均呈显著正相关,表明研究区空气PM_(2.5)污染与化石能源燃烧和机动车尾气均有较大关系,也可能与SO2或NO2在不利气象条件下形成的二次气溶胶有关.

The real-time PM2.5 concentration data of 128 state-controlled monitoring stations from November 2014 to January 2015 in Yangtze River Delta Region were used to analyze spatial heterogeneity based on geostatistics method, and the factors affecting the dynamic were discussed. The results indicate that the base effect values of p（ PM2.5 ） were between 0.07 and 0.26, and the degree of spatial autocorrelation was strong. The nugget values showed an increasing trend, which indicated that the anthropogenic PM2.5 source gradually enhanced the impact on the spatial heterogeneity. The range values ofp（PM2.5） were between 217.1 km and 336.2 km, and the range value of the east-west direction was larger than that of north-south. The air quality monitoring network can be further optimized according to the 1/4-1/2 autocorrelation concentration. The spatial interpolation results with ordinary kriging distance of each season PM2.5 showed a patchy distribution of air PM2.5 pollution in the study area, and the pollution level continued to increase. The bary center of air PM2.5 pollution was in Su-xi-chang metropolitan area, Nanjing metropolitan area and Xuzhou Metropolitan area, which are the key areas of air PM2.5 pollution control. Nanjing metropolitan area and Xuzhou metropolitan area may be affected by the external PM2.5 transmission from WSW direction, while Su-xi-chang metropolitan area had a great potential impact on cities in the SSE direction. PM2.5 showed a significant positive correlation with SO2, CO, NO2, which indicated that the air PM2.5 pollution in the study area may be not only affected by emission of fossil energy combustion and vehicle exhaust, but also affected by the secondary aerosols related to SO2 or NO2 under adverse weather conditions.