Zhao Na, Wang Gang, Li Guohao, Lang Jianlei, Zhang Hanyu
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, China.
Department of Environmental and Safety Engineering, College of Chemical Engineering, China University of Petroleum (East China), Qingdao, 266580, China.
Environ Pollut. 2020 Dec;267:115617. doi: 10.1016/j.envpol.2020.115617. Epub 2020 Sep 8.
Although anthropogenic emissions decreased, polluted days still occurred in the Beijing-Tianjin-Hebei (BTH) region during the initial outbreak of the coronavirus disease (COVID-19). Analysis of the characteristics and source distribution of large-scale air pollution episodes during the COVID-19 outbreak (from 23 January to April 8, 2020) in the BTH region is helpful for exploring the efficacy of control measures and policy making. The results indicated that the BTH region suffered two large-scale air pollution episodes (23-28 January and 8-13 February), which were characterized by elevated PM, SO, NO, and CO concentrations, while the O concentration decreased by 1.5%-33.9% (except in Shijiazhuang, where it increased by 16.6% during the second episode). These large-scale air pollution episodes were dominated by unfavorable meteorological conditions comprising a low wind speed and increased relative humidity. The transport pathways and source distribution were explored using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT), potential source contribution function (PSCF), and concentration weighted trajectory (CWT) models. The air pollution in the BTH region was mainly affected by local emission sources during the first episode, which contributed 51.6%-60.6% of the total trajectories in the BTH region with a PM concentration ranging from 146.2 μg/m to 196.7 μg/m. The short-distance air masses from the southern and southwestern areas of the BTH region were the main transport pathways of airflow arriving in the BTH region during the second episode. These contributed 51.9%-57.9% of the total trajectories and originated in Hebei, Henan, central Shanxi, and Shaanxi provinces, which were the areas contributing the most to the PM level and exhibited the highest PSCF and CWT values. Therefore, on the basis of local emission reduction, enhancing regional environmental cooperation and implementing a united prevention and control of air pollution are effective mitigation measures for the BTH region.
尽管人为排放有所减少，但在冠状病毒病（COVID-19）初期爆发期间，京津冀（BTH）地区仍出现了污染天。分析COVID-19爆发期间（2020年1月23日至4月8日）京津冀地区大规模空气污染事件的特征和源分布，有助于探索控制措施的效果和政策制定。结果表明，京津冀地区遭受了两次大规模空气污染事件（1月23日至28日和2月8日至13日），其特征是PM、SO、NO和CO浓度升高，而O浓度下降了1.5%-33.9%（石家庄除外，在第二次事件期间O浓度上升了16.6%）。这些大规模空气污染事件主要受不利气象条件影响，包括风速低和相对湿度增加。利用混合单粒子拉格朗日积分轨迹（HYSPLIT）、潜在源贡献函数（PSCF）和浓度加权轨迹（CWT）模型探索了传输路径和源分布。京津冀地区第一次事件期间的空气污染主要受本地排放源影响，这些源在京津冀地区总轨迹中占51.6%-60.6%，PM浓度范围为146.2μg/m至196.7μg/m。第二次事件期间，来自京津冀地区南部和西南部地区的短距离气团是气流到达京津冀地区的主要传输路径。这些气团在总轨迹中占51.9%-57.9%，起源于河北、河南、山西中部和陕西省，这些省份对PM水平贡献最大，PSCF和CWT值最高。因此，在本地减排的基础上，加强区域环境合作并实施空气污染联合防治是京津冀地区有效的缓解措施。
