阳泉市COVID-19期间主要大气污染物的传输及来源分布  

Transport and Source Distribution Characteristics of Major Air Pollutants During COVID-19 in Yangquan,China

作　　者：任皓 REN Hao(Shanxi Ecological Environment Monitoring and Emergency Response Centre(Shanxi Academy of Eco-Environmental Sciences),Taiyuan 030027,China)

机构地区：[1]山西省生态环境监测和应急保障中心(山西省生态环境科学研究院),山西太原030027

出　　处：《中国环境监测》2024年第6期94-103,共10页Environmental Monitoring in China

基　　金：安徽省自然科学基金资助项目(2008085QD183)。

摘　　要：2020年初,COVID-19在国内暴发,在相关管控措施下研究了区域性大气污染特征与传输之间的关系。选取山西省阳泉市的6个大气环境质量国控站点,获取了2019—2021年主要大气污染物(NO_(2)、PM_(2.5)和O_(3))在时间尺度上的变化特征。重点评估了2020年2月管控措施对主要大气污染物的影响,并结合HYSPLIT模型模拟的48 h后向轨迹以及潜在源贡献因子法(PSCF)和浓度权重轨迹法(CWT),量化了该研究时间段内阳泉市3种大气污染物的潜在源及贡献。结果表明:在研究时间段内,NO_(2)和PM_(2.5)平均浓度呈现整体下降的趋势,2021年NO_(2)浓度较2020年稍有回升,但整体水平低于2019年。O_(3)浓度则逐年上升,推测是O_(3)在对流层的光化学反应导致。后向轨迹聚类分析发现,2019年2月和2021年2月,大气污染物主要来源于东部气团的输送,而2020年则主要来源于西部。NO_(2)和PM_(2.5)在聚类轨迹上的平均质量浓度与聚类轨迹呈正相关关系,O_(3)则没有明显的相关性。结合2月污染物平均浓度特征来看,管控措施使得2020年主要大气污染物浓度降低,而2021年主要污染物浓度的降低则归因于当地与周边地区实施的大气环境治理措施。NO_(2)和PM_(2.5)的潜在源分布呈现逐年区域化的态势。NO_(2)的潜在源主要是阳泉市本地、晋中市和太原市,而PM_(2.5)的潜在源分布则呈现山西本地、山东、京津冀、河南以及陕西区域贡献的特征。O_(3)的潜在源主要来自阳泉市本地和石家庄市的贡献,这也在一定程度上验证了其来源于本地光化学反应的说法。At the beginning of 2020,COVID-19 pandemic took the lead in China.The Chinese government imposed unprecedented lockdown measures,which provides an opportunity to study the relationship between regional air pollution characteristics and transport.The daily and hourly mean mass concentrations of the main atmospheric pollutants(NO_(2),PM_(2.5) and O_(3))from six statecontrolled stations for atmospheric environmental quality in Yangquan City,Shanxi Province were selected to obtain the variation characteristics of the atmospheric pollutant concentrations from 2019 to 2021.The impact of the lockdown on the main air pollutants in February 2020 was analyzed,and the potential source contributions of these three air pollutants in Yangquan City during the research period were quantified by combining the 48 h backward trajectory simulated by HYSPLIT model,the potential source contribution factor method(PSCF)and the concentration weighted trajectory(CWT).The results showed that during the study period,the average concentration of NO_(2) and PM_(2.5) showed a downward trend overall,and the mean concentration of NO_(2) in 2021 rose slightly compared with that in 202,but the overall level was lower than that in 2019.The concentration of O_(3) was rising year by year,which was speculated to be caused by the photochemical formation of O_(3) in the troposphere.The cluster analysis of backward trajectory showed that the atmospheric pollutants in February 2019 and 2021 mainly came from the transport of the eastern air mass,while in 2020 mainly came from the west.The mean mass concentration of NO_(2) and PM_(2.5) on the cluster track was positively correlated with the cluster track of the track,while O_(3) had no obvious correlation.According to the characteristics of monthly mean level of pollutants in February,it was speculated that the lockdown could reduce the concentration of these three major pollutants in 2020,and the reduction in 2021 could be attributed to the role of atmospheric environment control measures implemented in lo

关 键 词：NO_(2) PM_(2.5) O_(3) 后向轨迹 聚类分析 潜在源贡献因子法 浓度权重轨迹法 

分 类 号：X823[环境科学与工程—环境工程]