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某石油化工园区秋季VOCs污染特征及来源解析
引用本文:胡天鹏,李刚,毛瑶,郑煌,秦世斌,闵洋,张家泉,邢新丽,祁士华.某石油化工园区秋季VOCs污染特征及来源解析[J].环境科学,2018,39(2):517-524.
作者姓名:胡天鹏  李刚  毛瑶  郑煌  秦世斌  闵洋  张家泉  邢新丽  祁士华
作者单位:中国地质大学(武汉)环境学院, 生物地质与环境地质国家重点实验室, 武汉 430074;湖北理工学院环境科学与工程学院, 矿区污染控制与修复湖北省重点实验室, 黄石 435003,克拉玛依市环境科研监测中心站, 克拉玛依 834000,中国地质大学(武汉)环境学院, 生物地质与环境地质国家重点实验室, 武汉 430074,中国地质大学(武汉)环境学院, 生物地质与环境地质国家重点实验室, 武汉 430074,中国地质大学(武汉)环境学院, 生物地质与环境地质国家重点实验室, 武汉 430074,中国地质大学(武汉)环境学院, 生物地质与环境地质国家重点实验室, 武汉 430074,湖北理工学院环境科学与工程学院, 矿区污染控制与修复湖北省重点实验室, 黄石 435003,中国地质大学(武汉)环境学院, 生物地质与环境地质国家重点实验室, 武汉 430074,中国地质大学(武汉)环境学院, 生物地质与环境地质国家重点实验室, 武汉 430074
基金项目:国家自然科学基金项目(2015053079);盆地水文过程与湿地生态恢复创新基地开放课题项目(BHWER201503A)
摘    要:利用快速连续在线自动监测系统对某典型石油化工园区2014年秋季(9、10、11月)大气中VOCs进行监测,并对其组成、光化学反应活性、时间变化特征和来源进行解析.结果表明:秋季大气中VOCs的混合体积分数明显高于国内外其他城市和工业地区,且烷烃是大气中VOCs的最主要成分.研究区秋季3个月份大气中VOCs的混合体积分数之间差异不显著,但各种烃类的日夜变化特征明显:烷烃、烯烃和芳香烃呈现"单峰单谷"变化趋势,乙炔的变化趋势呈"W"型.PMF受体模型解析结果表明主要来源于天然气交通及溶剂、炼油厂的泄漏或挥发等过程,其次为其他交通来源,沥青对于研究区VOCs来源也有一定的贡献.等效丙烯体积和最大臭氧生成潜势对VOCs的光化学反应活性计算结果表明,烯烃和烷烃分别是各自混合体积分数的最主要的贡献者.

关 键 词:挥发性有机物  组成  变化趋势  源解析  光化学反应活性
收稿时间:2017/4/10 0:00:00
修稿时间:2017/5/16 0:00:00

Characteristics and Source Apportionment of VOCs of a Petrochemical Industrial Park During Autumn in China
HU Tian-peng,LI Gang,MAO Yao,ZHENG Huang,QIN Shi-Bin,MIN Yang,ZHANG Jia-quan,XING Xin-li and QI Shi-hua.Characteristics and Source Apportionment of VOCs of a Petrochemical Industrial Park During Autumn in China[J].Chinese Journal of Environmental Science,2018,39(2):517-524.
Authors:HU Tian-peng  LI Gang  MAO Yao  ZHENG Huang  QIN Shi-Bin  MIN Yang  ZHANG Jia-quan  XING Xin-li and QI Shi-hua
Institution:State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geoscience, Wuhan 430074, China;Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation, School of Environmental Science and Engineering, Hubei Polytechnic University, Huangshi 435003, China,Karamay Environmental Monitoring Center Station, Karamay 834000, China,State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geoscience, Wuhan 430074, China,State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geoscience, Wuhan 430074, China,State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geoscience, Wuhan 430074, China,State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geoscience, Wuhan 430074, China,Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation, School of Environmental Science and Engineering, Hubei Polytechnic University, Huangshi 435003, China,State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geoscience, Wuhan 430074, China and State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geoscience, Wuhan 430074, China
Abstract:An online continuous monitoring system was used to determine the volatile organic carbons (VOCs) in the ambient air of a typical petrochemical industrial park in autumn (Sep., Oct., Nov.) of 2014. The composition, photochemical reactivity, temporal variation, and source of VOCs were analyzed. The results indicated that the mixing ratio of VOCs in autumnal ambient air of the study area was higher than those of other cities and industrial areas. Alkanes were the most abundant group in the VOC mixing ratio, and no significant temporal difference was observed among the three months studied. However, the alkanes, alkenes, and aromatics presented obvious diurnal variation, with single peak and trough values, while the acetylene exhibited "W"-shaped variation, with two minimum and one maximum values. Source apportionment using positive matrix factorization (PMF) indicated that the sources of VOCs in the study area of natural gas transportation and solvents, such as from leakage or volatile oil refinery processing, followed by other traffic sources and asphalt have some contribution. Alkenes and alkanes were the dominant groups of the source apportionment composition, as expressed by the propylene-equivalent (Propy-Equiv) and maximum incremental reactivity (MIR) methods, respectively.
Keywords:volatile organic carbons (VOCs)  composition  variation trend  source apportionment  photochemical reactivity
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