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保定市大气污染特征和潜在输送源分析
引用本文:郑悦,程方,张凯,唐伟,孟凡,李朋远,郭志强.保定市大气污染特征和潜在输送源分析[J].环境科学研究,2020,33(2):260-270.
作者姓名:郑悦  程方  张凯  唐伟  孟凡  李朋远  郭志强
作者单位:1.天津城建大学环境与市政工程学院, 天津 300384
基金项目:大气重污染成因与治理攻关项目(No.DQGG0304-05);中央级公益性科研院所基本科研业务专项(No.2016YSKY-025)
摘    要:保定市是京津冀地区重要城市之一.为了解保定市大气污染物质量浓度特征和潜在输送源,对保定市国控点2017年1月1日-12月31日PM10、PM2.5、SO2、NO2、O3、CO等常规大气污染物数据进行分析,并利用TrajStat后向轨迹模型进行区域传输研究.结果表明:①ρ(PM10)、ρ(PM2.5)、ρ(SO2)、ρ(NO2)分别为(138±96)(84±66)(29±23)和(50±24)μg/m3,与2016年相比分别下降5.9%、9.1%、25.5%和13.1%;ρ(CO)较2016年下降了14.0%;ρ(O3)较2016年增长了25.2%.ρ(PM10)、ρ(PM2.5)、ρ(NO2)和ρ(O3)分别超过GB 3095-2012《环境空气质量标准》二级标准限值的0.97、1.40、0.25和0.34倍,ρ(SO2)和ρ(CO)未超标.②除ρ(O3)外,其他污染物质量浓度均呈冬季最高、夏季最低的季节性特征,其中,冬季PM2.5污染最为严重,春季PM2.5~10(粗颗粒物)污染严重.③空气质量模型源解析结果显示,保定市ρ(PM2.5)约60.0%~70.0%来自本地污染源排放.后向轨迹结果表明,在外来区域传输影响中,保定市主要受到西北方向气团(占比为21.7%~60.0%)远距离传输和正南方向气团(占比为34.8%~50.5%)近距离传输的影响.④PSCF(潜在源贡献因子分析法)和CWT(浓度权重轨迹分析法)分析表明,除保定市及周边区县本地污染贡献外,位于太行山东麓沿线西南传输通道的邯郸市、邢台市、石家庄市是影响保定市PM2.5的主要潜在源区.研究显示,PM2.5为保定市大气中的主要污染物,并呈冬季高、夏季低的变化特征,其主要来自西北远距离输送和南部近距离传输. 

关 键 词:大气污染物    特征分析    季节性变化    保定市    潜在源区
收稿时间:2019/1/8 0:00:00
修稿时间:2019/4/25 0:00:00

Characteristics and Potential Transport Source Identification of Atmospheric Pollution in Baoding City
ZHENG Yue,CHENG Fang,ZHANG Kai,TANG Wei,MENG Fan,LI Pengyuan,GUO Zhiqiang.Characteristics and Potential Transport Source Identification of Atmospheric Pollution in Baoding City[J].Research of Environmental Sciences,2020,33(2):260-270.
Authors:ZHENG Yue  CHENG Fang  ZHANG Kai  TANG Wei  MENG Fan  LI Pengyuan  GUO Zhiqiang
Institution:1.School of Environmental and Municipal Engineering, Tianjin Chengjian University, Tianjin 300384, China2.State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China3.Baoding Environmental Monitoring Center of Hebei Province, Baoding 071000, China4.Baoding Meteorological Bureau, Baoding 071000, China
Abstract:In order to study the characteristics and potential transport source identification of atmospheric pollution in Baoding City, ρ(PM10), ρ(PM2.5), ρ(SO2), ρ(NO2), ρ(CO) and ρ(O3) were measured from January 2017 to December 2017 and regional transport was investigated using the TrajStat model. The results showed that clear days accounted for 43.3% during the study period, increasing by 3 days in contrast to that in 2016. However, severe polluted days accounted for 15.1% and decreased by 3 days. The annual values of ρ(PM10), ρ(PM2.5), ρ(SO2), ρ(NO2), ρ(CO) was (138±96)μg/m3, (84±66)μg/m3, (29±23)μg/m3, (50±24)μg/m3 and 4.0 mg/m3 respectively, with the concentration decrease by 5.9%, 9.1%, 25.5%, 13.1% and 14.0%, respectively, while ρ(O3) increased by 25.2% compared to those in 2016. The annual values of ρ(PM10), ρ(PM2.5), ρ(NO2) and ρ(O3) exceeded the National Ambient Air Quality Standards (GB 3095-2012, grade Ⅱ) by 0.97, 1.40, 0.25 and 0.34 times, respectively, except ρ(SO2) and ρ(CO). Except O3, the concentrations of other air pollutants showed the highest concentration in winter and the lowest concentration in summer. Fine particles (PM2.5) showed the highest concentration in winter, but coarse particles (PM2.5-10) concentration reached the maximum in spring. The source apportionment based on air quality model showed that PM2.5 was mainly attributed to local emission, accounting for 60.0%-70.0%. The backward trajectory analysis demonstrated that the regional transport was mainly occurred in the Northwesterly (21.7%-60.0%) and the Southerly (34.8%-50.5%) air masses. According to the results of PSCF (Potential Source Contribution Function) and CWT (Concentration Weighted Trajectory) methods, the potential source regions of PM2.5 in Baoding City were found in the southwest pathway including Handan City, Xingtai City and Shijiazhuang City. 
Keywords:air pollutant  characteristic analysis  seasonal variation  Baoding City  source identification
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