2017年京津冀地区PM2.5污染特征及潜在来源分析

京津冀及周边地区大气污染问题突出，秋、冬季重污染天气频发。为探讨该地区PM_2.5污染来源，分析其污染状况和气象因素的关系，利用2017年京津冀地区空气质量监测站的气象资料如气压、风速、相对湿度、温度、降水量等，结合ArcGIS软件空间插值法、SPSS 21.0的Pearson相关性分析等方法，采用拉格朗日混合型的扩散模型HYSPLIT后向轨迹聚类分析方法，探讨北京地区主要气团传输轨迹，结合GDAS气象资料计算潜在源贡献因子。结果表明:1）2017年京津冀地区ρ（PM_2.5）年均为64.4μg/m3，比2016年下降11.5%，全年达标天数占比为74.2%。2）京津冀地区PM_2.5与气压、相对湿度呈正相关，其中气压与PM_2.5相关性最高；与风速、日照时长、温度、降水量呈负相关，其中日照时长与PM_2.5相关性最高。冬季比其他季节影响更为显著。3）从时间尺度看，冬季污染最严重，秋、春季稍好，夏季PM_2.5优、良级占92.4%；其中，1月平均ρ（PM_2.5）最高。4）从空间范围看，整体上京津冀地区呈现南高北低，南北差异相对明显，其中其北部承德、张家口、秦皇岛地区ρ（PM_2.5）最低，石家庄、邯郸PM_2.5污染较严重。5）源解析结果表明，冬季北京地区主要受本地污染源影响，在春、秋季节受周边区域源贡献因子PSCF值>0.4，河北、山东、河南等地对北京PM_2.5的污染有一定的源贡献。

CHARACTERISTICS AND POTENTIAL SOURCES OF PM2.5 POLLUTION IN BEIJING-TIANJIN-HEBEI REGION IN 2017

The problem of air pollution in Beijing-Tianjin-Hebei region (B-T-H region) and its surrounding area is prominent, and heavy pollution weather occurs frequently in autumn and winter, which is the main battlefield of air pollution prevention and control in China. In order to understand the source of PM_2.5 pollution in this area and analyze the relationship between PM_2.5 pollution and meteorological factors, this paper engaged the air quality monitoring stations in Beijing, Tianjin and Hebei region in 2017 to achieve meteorological data such as air pressure, wind speed, relative humidity, temperature and precipitation. In combination with the spatial interpolation method of ArcGIS software and Pearson correlation analysis of SPSS 21.0, the cluster analysis of backward trajectory of Lagrangian mixed diffusion model HYSPLIT was adopted. The main air mass transmission tracks in Beijing were discussed, and the potential source contribution factors were calculated with GDAS meteorological data. The results showed:1) In 2017, the average annual mass concentration of PM_2.5 in the B-T-H region was 64.4 μg/m3, which was 11.5% lower than that in 2016, and the proportion of days meeting the air quality standard for the whole year was 74.2%. 2) There was a positive correlation between the mass concentration of PM_2.5 and air pressure and relative humidity, of which the correlation between air pressure index and PM_2.5 was the highest. There was a negative correlation between mass concentration of PM_2.5 and wind speed, sunshine duration, temperature and precipitation, and the correlation between sunshine duration and PM_2.5 was the highest. From the relationship between PM_2.5 and meteorological factors in different seasons, winter was the most significant. 3) In terms of time scale, most serious pollution took place in winter and released in autumn and spring. And PM_2.5 in summer, excellent/good grade accounted for 92.4% above. Average PM_2.5 concentration was the highest in January. 4) In the spatial range, the whole B-T-H region showed a higher level in the south and lower in the north, with the lowest concentration of PM_2.5 in Chengde, Zhangjiakou and Qinhuangdao in the north, and the serious pollution in Shijiazhuang and Handan. 5) The results of source analysis showed that Beijing was mainly affected by local pollution sources in winter. In the spring and winter, the PSCF value of the source contribution factor in the surrounding region was greater than 0.4, and there was a certain source contribution of PM_2.5 pollution to Beijing in Hebei, Shandong and Henan.