【作者】 王晓宁； 任歌； 李小亭； 方立德；

【Author】 Wang Xiaoning;Ren Ge;Li Xiaoting;Fang Lide;School of Quality and Technical Supervision,Hebei University;Urban intelligence and green laboratory of National Institute of Metrology;Model inversion and big data laboratory of Zhengzhou Institute of Metrology;

【机构】 河北大学质量技术监督学院； 中国计量科学研究院城市绿色和智慧实验室； 郑州计量先进技术研究院模式反演与大数据研究所；

【摘要】 利用郑州市2019年1,4,7,10月气象数据和大气污染物浓度实时监测数据,分析不同月份风速、相对湿度等气象要素对颗粒物浓度的影响。将WRF模式应用于Traj Stat后向轨迹分析,在城市尺度上获取更准确的气团轨迹和传输特征,并运用潜在源贡献因子法（PSCF）和浓度权重法（CWT）,解析郑州市PM_2.5的潜在污染源和各区域贡献大小。结果表明:郑州市PM_2.5浓度季节性特征显著,高湿度和低风速的气象条件更易造成严重污染; WRF模式很好地模拟出气象要素随时间的变化特征,结合轨迹分析,发现郑州市1月和10月受西北和东北方向气团影响较大,4月主要由西南和东北方向气团主导,7月气团主要来自南方向;在污染严重的1月,郑州市PM_2.5潜在贡献源主要为郑州市西北部的晋城附近,南部的许昌、平顶山和南阳地区,以及北部的安阳、新乡、邯郸等地。更多还原

【Abstract】 Based on the monitoring data of meteorology and air pollutant concentration in January,April,July and October2019,analyzed the influence of meteorological factors,such as wind speed and relative humidity,on particulate matter concentration in different seasons of Zhengzhou. WRF was applied to Traj Stat analysis in order to more accurately obtain the transport characteristics of air mass trajectory on an urban scale. The potential pollution sources and regional contribution of PM_{2. 5} in Zhengzhou were assessed by using potential source contribution factor（ PSCF） and concentration weight trajectory（ CWT）. The results showed significant seasonal variation of PM_{2. 5} concentration in Zhengzhou,and the high humidity and low wind speed were easier to cause severe air pollution. WRF model well simulated the changes of meteorological elements over time. Combined with the trajectory analysis,we found that air masses from northwest and northeast have a greater impact on Zhengzhou in January and October; but the air masses mainly come from southwest and northeast in April and south in July. In January that air was heavily polluted,the potential sources of PM2. 5 in Zhengzhou were mainly from Jincheng which located in the northwest of Zhengzhou. Additionally,the regions in the south（ including Xuchang,Pingdingshan and Nanyang） and north of Zhengzhou（ including Anyang,Xinxiang,Handan） also made great contribution on the PM2. 5 of Zhengzhou.更多还原