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北京地区大气颗粒物输送路径及潜在源分析
引用本文:李颜君,安兴琴,范广洲.北京地区大气颗粒物输送路径及潜在源分析[J].中国环境科学,2019,39(3):915-927.
作者姓名:李颜君  安兴琴  范广洲
作者单位:1. 成都信息工程大学大气科学学院, 四川 成都 610225;2. 中国气象科学研究院大气成分研究所, 北京 100081
基金项目:国家重点研发计划(2017YFC0210006,2016YFA0602000)
摘    要:利用TrajStat软件和全球资料同化系统数据,计算了2005~2016年北京市逐日72h气流后向轨迹,采用聚类分析方法,结合北京同期PM2.5逐日质量浓度数据,分析北京市年及四季后向气流轨迹特征及其对北京市颗粒物浓度的影响,运用潜在源贡献因子分析法(PSCF)和浓度权重轨迹分析法(CWT),探讨研究时期内不同季节影响北京市颗粒物质量浓度的潜在源区以及不同源区对北京颗粒物质量浓度的贡献.结果表明,就全年而言,西北输送气流占总轨迹的比例最高,达59.97%,且其输送距离最远、输送高度最高、移速最快.输送高度最低、距离最短、移速最慢的东南气流占比次之,为27.64%,东北气流占比最低为12.40%,其移速和输送距离介于前两者之间.主要污染轨迹来自山东、河北,其次为来自俄罗斯、蒙古国和内蒙古荒漠戈壁地区的西北气流.PSCF和CWT分析发现,蒙中、晋中、冀西南、豫北及鲁西是影响北京PM2.5的主要潜在区域.而不同季节、不同输送路径对北京PM2.5污染影响的差异显著,春季主要受来自蒙晋交界区域的短距离输送气流影响,潜在源区位于冀南、鲁西、豫东和皖西北地区,夏季污染轨迹来自鲁、晋地区,潜在源区为豫东北、皖北和苏北地区;秋季主要受来自冀南地区的短距离气流影响,潜在源区为晋北、冀南、豫北和鲁西地区,冬季主要受来自蒙古国中西部和蒙中地区的远距离输送气流影响,潜在源区主要在冀南、鲁西、豫北、晋和蒙西地区.

关 键 词:大气颗粒物  后向轨迹聚类分析  潜在源贡献  浓度权重轨迹  北京  
收稿时间:2018-06-30

Transport pathway and potential source area of atmospheric particulates in Beijing
LI Yan-jun,AN Xing-qin,FAN Guang-zhou.Transport pathway and potential source area of atmospheric particulates in Beijing[J].China Environmental Science,2019,39(3):915-927.
Authors:LI Yan-jun  AN Xing-qin  FAN Guang-zhou
Affiliation:1. School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China;2. Institute of Atmospheric Composition, Chinese Academic of Meteorological Sciences, Beijing 100081, China
Abstract:The TrajStat software and data from global data assimilation system were used to calculate the 72 hour backward trajectories of air pollutants in Beijing from 2005 to 2016. The cluster analysis method was used to analyze the characteristics of the backward airflow trajectories and their effects on the concentration of particles over Beijing in the whole year and different seasons, combining with the daily concentration data of PM2.5, during the same period in Beijing. Meanwhile, Potential Source Contribution Factor Analysis (PSCF) and Concentration Weight Trajectory Analysis (CWT) combined with weight factors were utilized to calculate the potential source regions and the contribution of different source regions to Beijing particle concentration in different seasons during the study period. The results showed that, for the whole year, the air flow form northwest with the longest transmission distance, highest transmission height, and fastest transfer speed, occupying 59.97% of the total trajectories. The southeast airflow with the lowest transportation altitude, the shortest distance and the slowest moving speed accounted for 27.64%, and the lowest proportion of the northeast airflow was 12.40%, whose moving speed and transportation distance were between the first two. The main pollution trajectories came from Shandong and Hebei, followed by the northwestern airstreams from Russia, Mongolia, and Inner Mongolia's desert Gobi region. PSCF and CWT analysis found that central inner Mongolia, central Shanxi, southwest Guizhou, northern Henan and Shandong were the main potential areas affecting PM2.5 in Beijing. However, the differences in the impacts of different seasons and different backward trajectories on PM2.5 pollutions in Beijing were significant. In the spring, it was mainly affected by the short-distance transmission air flow from the border area of Mongolian and Shanxi. The potential source areas were located in southern Hebei, western Shandong, eastern Henan, and northwestern Anhui. The pollution trajectories in summer come from Shandong and Shanxi, and the potential source areas were northeastern Henan, northern Hebei, and northern Jiangsu. In the autumn, it was mainly affected by short-range air currents from southern Hebei. The potential source areas were northern Shanxi, southern Hebei, northern Henan, and western Shandong. In the winter, it was mainly affected by long-distance air currents from the central and western regions of Mongolia and central inner Mongolia. The potential source areas were mainly in southern Hebei, western Shandong, northern Henan, Shanxi, and western Inner Mongolia.
Keywords:atmospheric particles  back trajectory cluster analysis  potential source contribution  concentration weighted trajectory  Beijing  
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