| 成都冬季PM2.5化学组分污染特征及来源解析 |
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| 引用本文： | 吴明,吴丹,夏俊荣,赵天良,杨清健.成都冬季PM2.5化学组分污染特征及来源解析[J].环境科学,2019,40(1):76-85. |
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| 作者姓名： | 吴明 吴丹 夏俊荣 赵天良 杨清健 |
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| 作者单位： | 南京信息工程大学大气物理学院, 气象灾害教育部重点实验室, 气候与环境变化国际合作联合实验室, 气象灾害预报预警与评估协同创新中心, 中国气象局气溶胶与云降水重点开放实验室, 南京 210044;南京信息工程大学环境科学与工程学院, 江苏省大气环境与装备技术协同创新中心, 江苏省大气环境监测与污染控制高技术研究重点实验室, 南京 210044 |
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| 基金项目： | 国家重点研发计划项目（2016YFC0203304）；国家自然科学基金项目（91544109） |
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| 摘 要： | 2017年1月1~20日在成都地区分昼夜对PM_(2.5)进行连续膜样品采集,并在实验室测定了其主要化学组分(水溶性离子和碳质组分)的质量浓度.观测期间,PM_(2.5)的平均质量浓度为(127.1±59.9)μg·m~(-3);总水溶性离子的质量浓度为(56.5±25.7)μg·m~(-3),其中SO2-4、NO-3和NH+4是最主要的离子,质量浓度分别为(13.6±5.5)、(21.4±12.0)和(13.3±5.7)μg·m~(-3),一共占到了水溶性离子的85.6%;有机碳(OC)和元素碳(EC)的平均质量浓度分别为34.0μg·m~(-3)和6.1μg·m~(-3),分别占PM_(2.5)质量浓度的26.8%和4.8%.昼夜污染对比显示,PM_(2.5)白天和夜晚质量浓度分别为(120.4±56.4)μg·m~(-3)和(133.8±64.0)μg·m~(-3),夜间污染更为严重.SO2-4、NO-3和NH+4白天浓度高于夜间,这与白天光照促进了二次离子的形成有关;而Cl-、K+、OC和EC浓度夜间明显升高,可能是受夜间煤和生物质燃烧排放增加的影响.通过对近年来成都冬季PM_(2.5)化学组分的研究进行文献总结和比较后发现,SO2-4浓度显著降低,从2010年的50.6μg·m~(-3)降低到2017年的13.6μg·m~(-3);而NO-3浓度变化不大,维持在20μg·m~(-3)左右.PM_(2.5)中离子酸碱平衡分析表明,成都冬季PM_(2.5)由于NH+4的相对过剩而呈现出碱性,与以往呈偏酸性结果存在差异.对成都冬季NO-3/SO2-4的比值进行计算,NO-3/SO2-4平均值为1.57,表明移动源对PM_(2.5)污染影响更大.OC与EC的相关性表明,白天和夜间OC与EC的相关系数分别为0.82和0.90(P0.01),OC与EC来源具有一致性.SOC估算结果显示,白天和夜间SOC浓度分别为8.5μg·m~(-3)和11.9μg·m~(-3),占到OC的28.1%和31.8%.K+/EC平均值为0.31,并且K+与OC之间相关系数为0.87(P0.01),说明生物质燃烧对成都冬季碳质气溶胶有一定影响.主成分分析表明,成都冬季PM_(2.5)主要来源于燃烧源(燃煤、生物质燃烧等)、二次无机污染源以及土壤和扬尘源,其贡献率分别为32.8%、34.5%和21.5%.
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| 关 键 词： | 成都 细颗粒物 水溶性离子 OC/EC 昼夜差异 源解析 |
| 收稿时间： | 2018/5/7 0:00:00 |
| 修稿时间： | 2018/7/12 0:00:00 |
Analysis of Pollution Characteristics and Sources of PM2.5 Chemical Components in Chengdu in Winter |
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| WU Ming,WU Dan,XIA Jun-rong,ZHAO Tian-liang and YANG Qing-jian.Analysis of Pollution Characteristics and Sources of PM2.5 Chemical Components in Chengdu in Winter[J].Chinese Journal of Environmental Science,2019,40(1):76-85. |
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| Authors: | WU Ming WU Dan XIA Jun-rong ZHAO Tian-liang and YANG Qing-jian |
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| Institution: | Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China,Jiangsu Collaborative Innovation Center for Atmospheric Environment and Equipment Technology, Jiangsu Provincial Key Laboratory of High-tech Research on Atmospheric Environmental Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China,Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China,Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China and Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China |
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| Abstract: | |
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| Keywords: | Chengdu PM2 5 water-soluble ion OC/EC day-night difference source apportionment |
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