| 京津冀PM2.5时空分布特征及其污染风险因素 |
| |
| 引用本文： | 周磊,武建军,贾瑞静,梁念,张凤英,倪永,刘明. 京津冀PM2.5时空分布特征及其污染风险因素[J]. 环境科学研究, 2016, 29(4): 483-493 |
| |
| 作者姓名： | 周磊 武建军 贾瑞静 梁念 张凤英 倪永 刘明 |
| |
| 作者单位： | 1.中国环境监测总站, 北京 100012 |
| |
| 基金项目： | 国家自然科学基金项目(41501556)；京津冀地区重要地理国情监测项目(GJ201503) |
| |
| 摘 要： | 为分析京津冀及其周边区域2013年典型污染事件中PM2.5的时空分布特征及污染风险因素,根据国家城市环境空气质量实时发布数据和京津冀地区地理国情信息监测成果,采用空间数据挖掘方法对PM2.5污染的热点区域进行了划分；并采用地理探测器定量分析了PM2.5污染风险因子及其影响程度. 结果表明:在选取的京津冀6个城市中,在PM2.5污染事件统计上存在保定—廊坊—北京—天津—承德—张家口的污染顺序. PM2.5污染在空间上呈河南省(山东省)—河北省—北京市(天津市)一线的带状分布特征,在单次污染事件中,城市间的PM2.5污染存在空间运移关系. 空间热点探测表明,京津冀及其周边区域主要分为5个热点聚集区,其中3个高值区分布在北京市、天津市、河北省和山东省的中部,面积分别为5.31×104、10.26×104、5.04×104 km2. 在8个污染风险因子中,污染企业总数(影响力为0.97,下同)、降水量(0.93)、地形坡度(0.89)对PM2.5污染的影响显著高于其他风险因子；其他风险因子影响力排序依次为人口数量(0.60)、降水量大于0.1 mm的降水日数(0.57)、地表覆盖类型(0.52)、年均相对湿度(0.51)、年均风速(0.33),但风险因子间相比没有显著性差异. 研究显示,京津冀地区PM2.5污染的主要因素是污染物排放,其次,气象要素中的年降水量和自然地理环境中的地形坡度也是影响PM2.5污染特征的重要风险因子.
|
| 关 键 词： | PM2.5 京津冀 时空特征 空间热点探测 地理探测器 |
| 收稿时间： | 2015-07-28 |
| 修稿时间： | 2016-01-13 |
Investigation of Temporal-Spatial Characteristics and Underlying Risk Factors of PM2.5 Pollution in Beijing-Tianjin-Hebei Area |
| |
| ZHOU Lei,WU Jianjun,JIA Ruijing,LIANG Nian,ZHANG Fengying,NI Yong and LIU Ming. Investigation of Temporal-Spatial Characteristics and Underlying Risk Factors of PM2.5 Pollution in Beijing-Tianjin-Hebei Area[J]. Research of Environmental Sciences, 2016, 29(4): 483-493 |
| |
| Authors: | ZHOU Lei WU Jianjun JIA Ruijing LIANG Nian ZHANG Fengying NI Yong LIU Ming |
| |
| Affiliation: | 1.China National Environmental Monitoring Center, Beijing 100012, China2.Academy of Disaster Reduction and Emergency Management, MOCA/MOE, Beijing Normal University, Beijing 100875, China3.Beijing Community Service Center for Science and Technology, Beijing 100088, China4.National Disaster Reduction Center, Beijing 100124, China |
| |
| Abstract: | Abstract: In order to investigate the temporal-spatial characteristics of typical PM2.5 pollution events in 2013 and the risk factors of PM2.5 pollution in Beijing-Tianjin-Hebei and surrounding areas, real-time, published data on the national urban environmental air quality and geographic national condition monitoring results were analyzed. The spatial data mining method was used to divide the hot spot areas of PM2.5 pollution in Beijing-Tianjin-Hebei and surrounding areas. Using the geographic detector model, the risk factors of PM2.5 pollution and the associated influence degree were quantitatively analyzed. The results showed that the pollution in selected cities in the Beijing-Tianjin-Hebei area followed the order Langfang-Beijing-Baoding-Tianjin-Chengde-Zhangjiakou. The PM2.5 pollution showed zonal distribution characteristics, and there was a spatial migration pattern among the cities in the Beijing-Tianjin-Hebei region during a single pollution event. The spatial hot spot detection indicated that Beijing-Tianjin-Hebei and its surrounding areas were divided into five hot spot areas, with the top three of them being distributed in Beijing, Tianjin, and Hebei-central Shandong regions, with areas of 53,0 square kilometers, 102,0 square kilometers and 50,0 square kilometers, respectively. Among the eight PM2.5 pollution risk factors, the number of industrial companies (influence index 0.94), precipitation (0.93) and topographic slope (0.89) had a significantly higher influence on PM2.5 pollution than other risk factors. The influence power index of the other risk factors were as follows:population (0.60), number of precipitation days (0.57), land cover (0.52), relative air humidity (0.51) and wind speed (0.33). The influence of population on PM2.5 pollution was slightly greater than that of number of precipitation days, land cover, relative air humidity and wind speed, but with no significant differences among them. The results showed that the main factor in PM2.5 pollution in the Beijing-Tianjin-Hebei region is pollutant emission. Secondly, the annual precipitation of meteorological elements and the terrain slope of the natural geography environment are the important risk factors that affect the PM2.5 pollution characteristics. |
| |
| Keywords: | PM2.5 Beijing-Tianjin-Hebei temporal-spatial characteristics spatial hot spot detection geographic detector |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《环境科学研究》浏览原始摘要信息 |
|
点击此处可从《环境科学研究》下载免费的PDF全文 |
|
