引用本文:陈露露,陈东林,杨伟波,邵帅,凌静怡,李雪妍,王丽玮,张妍,朱腾,朱丽,张洁.连云港市冬季霾污染成因分析及应急管控效果评估[J].环境监控与预警,2023,15(5):43-50
CHEN Lulu,CHEN Donglin,YANG Weibo,SHAO Shuai,LING Jingyi,LI Xueyan,WANG Liwei,ZHANG Yan,ZHU Teng,ZHU Li,ZHANG Jie.Cause Analysis and Emergency Control Effect Evaluation of Winter Haze Pollution in Lianyungang[J].Environmental Monitoring and Forewarning,2023,15(5):43-50
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连云港市冬季霾污染成因分析及应急管控效果评估
陈露露1,陈东林2*,杨伟波3,邵帅1,凌静怡2,李雪妍2,王丽玮2,张妍2,朱腾1,朱丽1,张洁2
1.连云港市环境监测监控中心,江苏 连云港 222000;2.江苏省环保集团,江苏省环境工程技术有限公司,江苏省重点行业减污降碳协同控制工程研究中心,江苏 南京 210019;3.江苏省连云港环境监测中心,江苏 连云港 222000
摘要:
针对2022年1月5—14日连云港发生的细颗粒物(PM2.5)连续污染事件(PM2.5超标共计5 d),基于常规空气质量参数、气象要素、颗粒物组分参数等数据资料,系统分析了污染期间PM2.5时空变化特征及污染成因,结合大气化学与天气预测模式(WRF Chem)和敏感性试验方法,定量评估了应急减排措施对连云港各区县PM2.5浓度的影响。结果表明,5 d超标日中有3 d为轻度污染,2 d为中度污染,全市PM2.5浓度呈现先上升后下降的趋势。不利的气象条件(静稳、小风、高湿)、本地排放(机动车尾气、工业工艺源)和二次生成共同导致了PM2.5污染的发生。实施黄色预警管控后,ρ(PM2.5)平均值下降了4.6μg/m3,降幅为5.2%,其中东海县和灌云县ρ(PM2.5)的降幅最大,分别为6.1%和8.3%,同时污染天ρ(PM2.5)峰值平均下降了9.4μg/m3(6.0%)。通过PM2.5过程分析方法发现,应急减排导致人为排放、化学过程和背景浓度对近地面ρ(PM2.5)正贡献的减少量要显著大于垂直混合、区域输送和对流过程负贡献的增加量。
关键词:  细颗粒物  污染成因  气象条件  大气化学与天气预测模式  应急管控  连云港
DOI:10.3969/j.issn.1674-6732.202305.007
分类号:X823
基金项目:江苏省级生态环境科研成果转化与推广项目(2022004);江苏省环保集团科研计划项目(JSEP-TZ-2021-2002-RE)
Cause Analysis and Emergency Control Effect Evaluation of Winter Haze Pollution in Lianyungang
CHEN Lulu1, CHEN Donglin2*, YANG Weibo3, SHAO Shuai1, LING Jingyi2, LI Xueyan2, WANG Liwei2, ZHANG Yan2, ZHU Teng1, ZHU Li1, ZHANG Jie2
1.Lianyungang Environmental Monitoring and Control Center, Lianyungang, Jiangsu 222000, China;2.Jiangsu Provincial Key Industry Pollution Reduction and Carbon Reduction Collaborative Control Engineering Research Center, Jiangsu Environmental Engineering Technology Co., Ltd., Jiangsu Environmental Protection Group Co., Ltd., Nanjing, Jiangsu 210019, China; 3.Jiangsu Lianyungang Environmental Monitoring Center, Lianyungang,Jiangsu 222000,China
Abstract:
Based on the data of conventional air quality parameters, meteorological elements, particulate matter components and other data, this paper systematically analyzed the spatial temporal variation characteristics of PM2.5 and the causes of pollution during the continuous PM2.5 pollution events in Lianyungang from January 5 to 14, 2022 (PM2.5 exceeded the standard for 5 days in total). Combined with WRF-Chem model and sensitivity test method, the impact of emergency emission reduction measures on PM2.5 concentration in each district of Lianyungang was quantitatively assessed. The results showed that among the 5 days exceeding the standard,3 days were mildly polluted and 2 days were moderately polluted. The PM2.5 concentration of the whole city showed a trend of first increasing and then decreasing. Adverse meteorological conditions (calm,low wind, high humidity), local emissions (vehicle exhaust, industrial process sources) and secondary generation combine to cause PM2.5 pollution. After the implementation of yellow warning control, the average ρ(PM2.5 ) decreased by 4.6μg/m3 (5.2%), and the decrease value of ρ(PM2.5 ) in Donghai County and Guanyun County decreased the most, which were 6.1% and 8.3%, respectively. Meanwhile, the peak ρ(PM2.5 ) of pollution days decreased by 9.4 μg/m3 (6.0%) on average. Through the PM2.5 process analysis method, it is found that the positive contribution of anthropogenic emissions, chemical processes and background concentration to near surface ρ(PM2.5) reduced by emergency emission reduction is significantly greater than the negative contribution of vertical mixing, regional transport and convective processes.
Key words:  PM2.5  Cause of pollution  Meteorological conditions  WRF Chem  Emergency control  Lianyungang