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    崔继宪, 郎建垒, 陈添, 张大伟, 王占山, 程水源. 2016年北京市空气质量特征及PM2.5传输规律[J]. 北京工业大学学报, 2018, 44(12): 1547-1556. DOI: 10.11936/bjutxb2017070007
    引用本文: 崔继宪, 郎建垒, 陈添, 张大伟, 王占山, 程水源. 2016年北京市空气质量特征及PM2.5传输规律[J]. 北京工业大学学报, 2018, 44(12): 1547-1556. DOI: 10.11936/bjutxb2017070007
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    CUI Jixian, LANG Jianlei, CHEN Tian, ZHANG Dawei, WANG Zhanshan, CHENG Shuiyuan. Characteristics of Beijing's Air Quality and Regional Transport of PM2.5 in 2016[J]. Journal of Beijing University of Technology, 2018, 44(12): 1547-1556. DOI: 10.11936/bjutxb2017070007
    Citation: CUI Jixian, LANG Jianlei, CHEN Tian, ZHANG Dawei, WANG Zhanshan, CHENG Shuiyuan. Characteristics of Beijing's Air Quality and Regional Transport of PM2.5 in 2016[J]. Journal of Beijing University of Technology, 2018, 44(12): 1547-1556. DOI: 10.11936/bjutxb2017070007
    shu

    2016年北京市空气质量特征及PM2.5传输规律

    Characteristics of Beijing's Air Quality and Regional Transport of PM2.5 in 2016

      摘要
    • 摘要: 为研究北京市空气质量特征以及PM2.5区域传输影响，通过对比分析北京不同类型空气质量评价点——昌平、官园、古城、东四环、榆垡等监测点的2016年监测数据，探讨了PM2.5、SO2、NO2、CO及O3-1h污染的时空变化特征及其与气象因素的相关性.采用HYSPLIT模型分析了不同季节的气流来向，并利用WRF-CAMx-PSAT模型定量估算了北京不同季节典型污染过程的区域PM2.5传输贡献.结果表明，与2011-2015年相比，2016年北京市气象扩散条件较为有利，气温、能见度、湿度、风速、气压年均值分别增加了5.6%、8.7%、3.6%、-4.0%、0.03%.此外，春、夏、冬三季偏南气流轨迹占比较小，分别为14%、9%和4%.年内变化显示，O3-1h 4-9月份质量浓度水平较高，PM2.5、NO2、CO和SO2冬季日均质量浓度明显高于其他季节，NO2、PM2.5和CO 2月份月均质量浓度最低.从空间分布来看，PM2.5、SO2、O3-1h和CO呈现南高北低且非均匀分布，而NO2则城区高于郊区.从气象因素与污染物的相关性来看，PM2.5与相对湿度、O3与温度、CO与相对湿度均呈明显正向线性相关，与SO2相比，NO2与相对湿度的相关性较好.同时，通过对典型污染过程进行PM2.5传输规律的分析发现，北京市PM2.5主要来自本地源排放，贡献率达36.4%~56.8%，而河北、天津以及京津冀地区对北京区域传输也较为明显，贡献率分别为22.6%~47.9%、3.16%~17.8%和9.7%~16.7%.

       

      Abstract: The pollutants concentration data of five automatic air quality monitoring stations from Beijing in 2016, including Changping monitoring station, West Park Officials monitoring station, Shijingshan city monitoring station, Yufa monitoring station and East 4th Ring Road traffic monitoring station, were analyzed to investigate the air quality and the regional transport characteristics of PM2.5 from outside of Beijing. The HYSPLIT and WRF-CAMx-PSAT model were used to analyze the air flow of different seasons and the trans-boundary contribution of PM2.5 to Beijing in different seasons, respectively. Results show that the temperature, visibility, relative humidity, wind speed and barometric pressure increase by 5.6%, 8.7%, 3.6%, -4.0% and 0.03%, respectively, in 2016 compared with that in 2011-2015. Moreover, southward air flow trajectory of spring, summer and winter accounts for 14%, 9% and 4%, respectively, indicating the favorable meteorological conditions. Further investigation show that the month average concentration of O3-1 h is higher from April to September than that of other months. The monthly average concentrations of PM2.5, NO2, CO and SO2 are the highest in winter, while the average concentrations of PM2.5, CO and NO2 are the lowest in February. The spatial distribution analysis indicates that the concentrations of PM2.5, SO2, O3-1h and CO display non-uniform distribution and decline from south to north, while the NO2 concentration is higher in urban than that in suburb. Based on the analysis of the relationship between meteorological factors and the pollutants, it is found that PM2.5 and relative humidity, O3 and temperature, CO and relative humidity are significantly positive linear correlation, and the NO2 exhibits dramatically relationship with relative humidity compared with that of SO2. Meanwhile, through the analysis on the PM2.5 transport characteristics of typical pollution process, it is found that the PM2.5 of Beijing is mainly from local emission sources, with percentages of 36.4%-56.8%. The contributions from Hebei, Tianjin and other regions are also considerable, with proportion ranges of 22.6%-47.9%, 3.16%-17.8%, and 9.7%-16.7%, respectively.

       

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