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湛江市夏季大气挥发性有机物污染特征及来源解析
摘要点击 1961  全文点击 1206  投稿时间:2022-05-16  修订日期:2022-07-22
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中文关键词  湛江市  挥发性有机物(VOCs)  臭氧生成潜势(OFP)  污染特征  来源解析
英文关键词  Zhanjiang  volatile organic compounds(VOCs)  ozone formation potential(OFP)  pollution characteristics  source apportionment
作者单位E-mail
庞晓蝶 中国环境科学研究院, 北京 100012
生态环境部华南环境科学研究所, 国家环境保护城市生态环境模拟与保护重点实验室, 广州 510535 
2292269448@qq.com 
高博 生态环境部华南环境科学研究所, 国家环境保护城市生态环境模拟与保护重点实验室, 广州 510535  
陈来国 生态环境部华南环境科学研究所, 国家环境保护城市生态环境模拟与保护重点实验室, 广州 510535 chenlaiguo@scies.org 
刘明 生态环境部华南环境科学研究所, 国家环境保护城市生态环境模拟与保护重点实验室, 广州 510535  
陆海涛 生态环境部华南环境科学研究所, 国家环境保护城市生态环境模拟与保护重点实验室, 广州 510535  
王硕 生态环境部华南环境科学研究所, 国家环境保护城市生态环境模拟与保护重点实验室, 广州 510535  
赵伟 生态环境部华南环境科学研究所, 国家环境保护城市生态环境模拟与保护重点实验室, 广州 510535  
梁小明 生态环境部华南环境科学研究所, 国家环境保护城市生态环境模拟与保护重点实验室, 广州 510535  
郭送军 广西大学资源环境与材料学院, 南宁 530004  
中文摘要
      臭氧污染在全国呈加剧态势,在非重点区域和非重点城市其相关研究薄弱.在湛江市选取3个采样点,使用苏玛罐和2,4-二硝基苯肼(DNPH)吸附管采样,并利用气相色谱-质谱/氢离子火焰检测器(GC-MS/FID)和高效液相色谱(HPLC)分析了101种挥发性有机物(VOCs),分析其主要组分和变化特点,计算VOCs的臭氧生成潜势(OFP),并利用正定矩阵因子分解模型(PMF)进行源解析.结果表明,采样期间湛江市φ(TVOCs)平均值为1.28×10-7,其中OVOCs占比最高,为52%,其次为烷烃(36%)、烯烃(7%)、卤代烃(2.42%)、芳香烃(1.61%)和炔烃(0.78%).VOCs组分日变化特征表明,芳香烃和烷烃早晚体积分数高而中午低,受光化学反应影响大;而OVOCs在光化学反应强烈的中午体积分数低而傍晚高,表明傍晚采样点附近OVOCs直接排放增多或受到上风向污染源输送的影响.湛江市TVOCs的OFP为3.28×10-7,优势物种为甲醛、1-丁烯、正丁烷、2-丁酮和乙醛.表征气团老化程度的X/E值和气团后向轨迹分析表明,采样期间,当受来自南或西南方向气团影响时,X/E小,气团老化程度高,受到远距离传输影响;当受来自东或东南方向气团影响时,X/E大,气团新鲜,VOCs主要来自本地排放.根据PMF源解析,湛江市VOCs的来源主要有:工业排放源、汽油车尾气及油气挥发排放源、区域背景及远距离传输源、生物质燃烧源、船舶及柴油车排放源和溶剂使用排放源,贡献率分别为:36.05%、28.99%、13.84%、10.13%、7.05%和3.95%.湛江市应加强对甲醛、1-丁烯、正丁烷和2-丁酮等物种的监管,工业源和移动源是管控重点.
英文摘要
      Ozone pollution is intensifying in China, and its related studies are weak in non-focus regions and non-focus cities. Here, we investigated the characteristics and sources of volatile organic compounds (VOCs) at three sampling sites in Zhanjiang. We analyzed 101 VOCs using a gas chromatography-mass spectrometry/hydrogen ion flame detector (GC-MS/FID) and high-performance liquid chromatography (HPLC) using a Summa canister and DNPH adsorption tube. We calculated the ozone formation potential (OFP) of VOCs and used the positive matrix factorization (PMF) model for source apportionment. The results showed that the mean φ(TVOCs) was 1.28×10-7, and the dominant contributors were OVOCs (52%), followed by alkanes (36%), alkenes (7%), halogenated hydrocarbons (2.42%), aromatic hydrocarbons (1.61%), and alkynes (0.78%). The diurnal variation in VOCs was influenced by photochemical reactions; the ratio of aromatic hydrocarbons and alkanes was high in the morning and evening and low at noon, whereas OVOCs had a low ratio in the morning and noon and high in the evening, influenced by primary emissions and the upwind transport of pollutants. The OFP was 3.28×10-7, and the dominant species were formaldehyde, butene, n-butane, butanone, and acetaldehyde.The analysis of X/E values (characterizing the aging degree of air masses) and backward trajectories of air masses showed that during the sampling, when influenced by air masses from the south or southwest, X/E was small, and the aging degree of air masses was high, indicating the influence of regional transport; when influenced by air masses from the east or southeast direction, X/E was large, and the air masses were fresh, and VOCs were mainly from local emissions. Six emission sources of VOCs, including industrial emissions, gasoline vehicle exhaust and gasoline evaporation, regional background and transport sources, biomass combustion, diesel vehicles and marine shipping emissions, and solvent use emission sources, were resolved using the PMF model, with contributions of 36.05%, 28.99%, 13.84%, 10.13%, 7.05%, and 3.95%, respectively.Zhanjiang should strengthen the supervision of formaldehyde, butene, n-butane and butanone, industry sources, and mobile sources as the focus of control.

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