京津冀地区PM2.5时空变异性规律研究

Spatial-temporal Characteristics of the PM2.5 in Beijing-Tianjin-Hebei Region

空气污染已成为全球关注的重要问题,亦是当前中国大气质量面临的主要问题.本文基于2014年6月-2017年8月京津冀地区13个城市的PM2.5监测站点数据,利用数理统计、GIS空间自相关和克里金插值等方法研究了不同时间尺度下PM2.5的时空变化规律.研究结果表明:(1)PM2.5在时间上的分布特征为,季均值冬高夏低,春秋居中,季均值与月均值表现为连续平缓U型模式,日均值呈峰、谷交替变化,每日最低值在16点左右出现;(2)PM2.5空间分布差异较大,中南部城市浓度远高于北部城市,具有空间自相关性和聚类特征,表现为污染区域关联性;(3)不同时间尺度下PM2.5浓度均呈南高北低分布,各季节高浓度区域面积逐年缩减并向南转移,在秋冬季节形成以石家庄为高浓度中心向外逐渐降低的阶梯式分布模式.

Air pollution has become a global issue, which is also the major challenge of air quality in China. This paper analyzed the spatial-temporal characteristics of PM2.5 using mathematical statistics methods and spatial analysis tools, based on the collected PM2.5 data that obtained from the monitoring stations of 13 cities in BTH region from June 2014 to August 2017. Results showed:(1) The concentration of PM2.5 was high in winter, low in summer and at a medium level in spring and autumn. The continuous U-shape distributions were observed both in the monthly and seasonal average of PM2.5 concentration. The daily average of PM2.5 concentration changed alternately from peak to valley, with the lowest value appearing at about 16:00 pm.(2) The spatial distribution of PM2.5 concentration was quite heterogeneous. The concentrations of PM2.5 in the central and southern cities were significantly higher than those in the northern part. And the PM2.5 concentrations had spatial autocorrelation and clustering characteristics, which reflecting the regional correlation of air pollution.(3) The concentrations of PM2.5 at different time scales all showed a high concentration in the south and low in the north. The areas with high PM2.5 concentration decreased year by year and shifted to the south. Especially, the PM2.5 concentrations showed a spatial pattern that high value concentrated in Shijiazhuang region and gradually decreasing outward in autumn and winter.