| 长春秋季细颗粒物中有机气溶胶组成特征及来源 |
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| 引用本文： | 吴瑕,曹芳,翟晓瑶,范美益,张世春,章炎麟.长春秋季细颗粒物中有机气溶胶组成特征及来源[J].环境科学,2019,40(8):3438-3446. |
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| 作者姓名： | 吴瑕 曹芳 翟晓瑶 范美益 张世春 章炎麟 |
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| 作者单位： | 南京信息工程大学应用气象学院, 气候与环境变化国际合作联合实验室大气环境中心, 南京 210044;南京信息工程大学气象灾害预报预警与评估协同创新中心, 气象灾害教育部重点实验室, 南京 210044;中国科学院东北地理与农业生态研究所,长春,130102 |
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| 基金项目： | 国家重点研发计划;国家自然科学基金;国家自然科学基金;江苏省自然科学基金杰出青年基金 |
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| 摘 要： | 利用大流量采样器采集了长春城郊2016年10月至2016年11月大气细颗粒物(PM_(2.5))样品共40套,分析了颗粒物中的有机碳(OC)、元素碳(EC)以及非极性有机化合物(主要包括正构烷烃、多环芳烃以及藿烷类化合物)和生物质燃烧标志物左旋葡聚糖的质量浓度,并用分子标记物、特征比值及主成分分析-多元线性回归(PCA-MLR)模型等方法探讨了有机气溶胶的主要来源.结果表明,观测期间PM_(2.5)的平均质量浓度为(79. 0±55. 7)μg·m~(-3),OC和EC的平均质量浓度分别为(20. 7±15. 6)μg·m~(-3)和(2. 2±1. 1)μg·m~(-3),分别占PM_(2.5)的26. 2%和2. 8%.所测非极性有机化合物的总平均浓度为(186. 3±104. 5) ng·m~(-3),浓度高低顺序为正构烷烃(101. 3±67. 0) ng·m~(-3)]多环芳烃(81. 4±46. 0) ng·m~(-3)]藿烷类化合物(3. 8±1. 9) ng·m~(-3),其主要来源包括煤燃烧源、生物质燃烧源以及交通源.主成分分析-多元线性回归模型得出该地区有机气溶胶主要排放源的相对贡献依次是煤燃烧源(47. 0%)、生物质燃烧源(42. 6%)和交通源(10. 4%).本研究结果可为我国东北地区有机气溶胶污染防控提供科学依据.
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| 关 键 词： | PM2.5 有机碳(OC) 元素碳(EC) 非极性有机化合物 主成分分析-多元线性回归(PCA-MLR)模型 来源解析 |
| 收稿时间： | 2019/1/3 0:00:00 |
| 修稿时间： | 2019/2/14 0:00:00 |
Molecular Composition and Source Apportionment of Fine Organic Aerosols in Autumn in Changchun |
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| WU Xi,CAO Fang,ZHAI Xiao-yao,FAN Mei-yi,ZHANG Shi-chun and ZHANG Yan-lin.Molecular Composition and Source Apportionment of Fine Organic Aerosols in Autumn in Changchun[J].Chinese Journal of Environmental Science,2019,40(8):3438-3446. |
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| Authors: | WU Xi CAO Fang ZHAI Xiao-yao FAN Mei-yi ZHANG Shi-chun and ZHANG Yan-lin |
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| Institution: | Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change(ILCEC), School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China,Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change(ILCEC), School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China,Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change(ILCEC), School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China,Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change(ILCEC), School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China,Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China and Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change(ILCEC), School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China |
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| Abstract: | |
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| Keywords: | PM2 5 organic carbon (OC) elemental carbon (EC) non-polar organic compounds PCA-MLR model source apportionment |
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