Zhu Yuan-Yuan, Gao Yu-Xiao, Chai Wen-Xuan, Wang Shuai, Li Liang, Wang Wei, Wang Guang, Liu Bing, Wang Xiao-Yan, Li Jian-Jun
China National Environmental Monitoring Centre, Beijing 100012, China.
School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Huan Jing Ke Xue. 2020 Feb 8;41(2):574-586. doi: 10.13227/j.hjkx.201908123.
This study discusses the concentration characteristics of PM and PM, as well as pollution meteorology in large-scale and long-term heavy pollution in the Beijing-Tianjin-Hebei region and its surrounding areas from November 23 to December 4, 2018, where the primary pollutants are comprised of PM and PM. The monitoring results obtained from ground-based and vehicle-mounted lidars, as well as the HYSPLIT-4 backward trajectory combined with meteorological factors analysis are discussed. The accuracy and uncertainty of the air quality forecast model of NAQPMS, CMAQ, and CAMx during heavy air pollution were analyzed retrospectively. The results show that PM and sand dust in most cities in the south-central region contribute to severe pollution levels. The hourly peak concentrations of PM in Zhangjiakou, Beijing, Shijiazhuang, Handan, and Zhengzhou were 1589, 864, 794, 738, and 766 μg·m, respectively. The respective hourly peak concentrations of PM were 239, 319, 387, 321, and 380 μg·m. Ground static pressure field, high humidity, inversion, and other static and stable conditions, as well as sand dust transmitted from the northwest, were important pollution meteorological and weather factors. The monitoring data of ground-based lidar and vehicle-mounted lidar combined with the HYSPLIT-4 backward trajectory analysis showed that the air pollutant transmitted from the Southwest and Southeast during the heavy pollution period was primarily PM. The air pollutant transmitted from the Northwest during the two sand dust processes. Moreover, the model of NAQPMS, CMAQ, and CAMx performed well in forecasting the heavy pollution process in the Beijing-Tianjin-Hebei region and its surrounding areas. However there are slight deviations for some individual cities, related to uncertainty in the meteorological model prediction, atmospheric chemical reaction mechanism, and pollution source list. Furthermore, the reduction in pollution source emissions caused by pollution emergency measures was also one of the main reasons for the overestimation.
本研究探讨了2018年11月23日至12月4日京津冀地区及其周边地区大规模、长期重度污染期间细颗粒物（PM）和可吸入颗粒物（PM）的浓度特征以及污染气象情况，其中主要污染物为PM和PM。讨论了地基和车载激光雷达的监测结果，以及结合气象因素分析的HYSPLIT - 4后向轨迹。回顾性分析了NAQPMS、CMAQ和CAMx空气质量预报模型在重污染期间的准确性和不确定性。结果表明，中南部地区多数城市的PM和沙尘导致了重度污染水平。张家口、北京、石家庄、邯郸和郑州的PM小时峰值浓度分别为1589、864、794、738和766μg·m，PM的小时峰值浓度分别为239、319、387、321和380μg·m。地面静压场、高湿度、逆温等静稳条件以及从西北传输来的沙尘是重要的污染气象和天气因素。地基激光雷达和车载激光雷达的监测数据结合HYSPLIT - 4后向轨迹分析表明，重污染期间从西南和东南传输来的空气污染物主要是PM，在两次沙尘过程中从西北传输来的空气污染物也是如此。此外，NAQPMS、CMAQ和CAMx模型在京津冀地区及其周边地区重污染过程的预报中表现良好。然而，对于一些个别城市存在轻微偏差，这与气象模型预测、大气化学反应机制和污染源清单的不确定性有关。此外，污染应急措施导致的污染源排放减少也是高估的主要原因之一。
