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| 用扫描电镜技术识别广州市大气颗粒物主要种类 | |
| 引用本文： | 董树屏,刘涛,等.用扫描电镜技术识别广州市大气颗粒物主要种类[J].岩矿测试,2001,20(3):202-207. |
| 作者姓名： | 董树屏 刘涛 |
| 作者单位： | 1. 国家环境分析测试中心, 2. 广州市环境保护局, 3. 广州市环境监测中心, 4. Antwerp大学化学系, |
| 基金项目： | 国家自然科学基金(29777029) |
| 摘 要： | 利用扫描电镜技术对大气颗粒物的来源进行识别，采取手动分析与自动分析两种方法，得出的结果在总趋势上相互一致。手动方法和自动方法各有特点。自动分析在细颗粒，特别是含硫颗粒分析方面有优势，而手动分析在形貌观测和确定有机粗颗粒污染状况方面有独到之处。实验结果表明，大气颗粒物的来源是多样的，治理措施也应是综合性的，既要注意工业点源的污染治理和排放控制，如燃煤飞灰，钙质颗粒富铁颗粒等，也要注意面源排放，如土壤扬尘和碳质颗粒，碳质颗粒的来源复杂，可以是工业过程，燃烧过程，机动车尾气，生物质燃，树木自然排放。 |
| 关 键 词： | 扫描电镜 大气颗粒物 来源识别 聚类分析 广州市 燃煤灰 土壤扬尘 |
| 文章编号： | 0254-5357(2001)03-0202-06 |
| 修稿时间： | 2001年3月26日 |
Identification of Major Particle Classes in Guangzhou Aerosol by Scanning Electron Microscopy |
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| DONG Shu ping,LIU Tao,SUN Da yong,QI Hui,DUAN Feng kui,WU Qing zhu,LIU Xian de,F.Adams.Identification of Major Particle Classes in Guangzhou Aerosol by Scanning Electron Microscopy[J].Rock and Mineral Analysis,2001,20(3):202-207. | |
| Authors: | DONG Shu ping LIU Tao SUN Da yong QI Hui DUAN Feng kui WU Qing zhu LIU Xian de FAdams |
| Affiliation: | DONG Shu ping 1,LIU Tao 2,SUN Da yong 3,QI Hui 1,DUAN Feng kui 1,WU Qing zhu 3,LIU Xian de 1,F.Adams 4 |
| Abstract: | Identification of major particle classes in Guangzhou aerosol was performed by using scanning electron microscopy(SEM). Results obtained in both manual mode and automatic mode are consistent with each other, even featured differently. Automatic mode is superior in fine particle analysis, such as various sulfur containing particles. Manual mode is preferable in morphological observation and identifying coarse organic aerosols. It has been shown that urban aerosols come from a variety of sources. The control and remedy measures should be comprehensive in nature. Not only industrial point sources emissions such as coal combustion fly ash, calcium containing particles, iron enriched particles, but also non point sources emissions such as soil dust and carbonaceous particles, are important for emission abatement and control. Carbonaceous particles are generated by many sources, including industrial processes, combustion processes, vehicle exhaust, biomass burning and natural vegetation emissions. |
| Keywords: | atmospheric aerosol scanning electron microscopy identification cluster analysis |
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