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AS3在线污染监督,预警预报和溯源系统的开发及其对昆山市高新区颗粒物污染的应用测试
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作者 张苏伟 张祺杰 +3 位作者 方军 栾旭东 didier buty 程鹏 《四川环境》 2017年第4期66-74,共9页
介绍了AS3在线污染监测,预警预报和溯源系统,及其在昆山市高新区的实测应用。自2013年开始,中国江苏天瑞仪器股份有限公司和法国ARIA科技有限公司结合各自在大气重金属监测仪器和大气环境模拟软件上的优势,共同研发了AS3系统,用于针对... 介绍了AS3在线污染监测,预警预报和溯源系统,及其在昆山市高新区的实测应用。自2013年开始,中国江苏天瑞仪器股份有限公司和法国ARIA科技有限公司结合各自在大气重金属监测仪器和大气环境模拟软件上的优势,共同研发了AS3系统,用于针对工业园区的大气颗粒物,尤其是重金属颗粒物的在线污染监测,预警预报和溯源。该系统包含仪器设备,信息处理,以及视图和结果分析3大模块。2015年6月在昆山市高新区的测试结果表明AS3系统能够实时有效地监测PM_(10),PM_(2.5),以及30种重金属元素。利用重金属元素示踪的方法对2015年6月11~13日,21日和24日天瑞仪器空气站监测到的浓度峰值进行源解析,分析得到这3个时间段分别可能受到沙尘、船只、以及工业生产或燃油的重要影响。利用系统中的扩散模型对混凝土生产排放和交通源排放进行模拟,结果显示,混凝土生产排放比交通源排放造成的颗粒物污染要多3个量级,影响范围可以达到3km以上。然而,由于局地气象条件变化的影响,混凝土生产排放的烟流扩散是不稳定的,随气象条件变化而不断变化。固定监测点没能捕捉最大污染烟流,因此,分散在几百米之外的监测点并不能够实时反映工业园区真实的大气污染情况。而大气环境模型的使用增加了空间污染监测的范围,提高了监测点位的实用性。上述结果表明,AS3系统这样的结合监测设备和污染模拟的系统的开发,对园区实时污染监管十分有利且必要。 展开更多
关键词 在线污染监测 预警预报和溯源系统AS3 重金属元素 颗粒物 工业园区污染监测
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Particulate matter pollution in Kunshan High-Tech zone: Source apportionment with trace elements, plume evolution and its monitoring 被引量:3
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作者 Suwei Zhang Qijie Zhang +11 位作者 Armand Albergel didier buty Liangmin Yu Haiting Wang Wuxia Bi Peng Cheng Fu Chen Jun Fang Ruirui Hou Xudong Luan Changgan Shu Jingjing Su 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2018年第9期119-126,共8页
Particulate matter (PM} in the Kunshan High-Tech zone is studied during a three-month campaign. PM and trace elements are measured by the online pollution monitoring, forecast-warning and source term retrieval system... Particulate matter (PM} in the Kunshan High-Tech zone is studied during a three-month campaign. PM and trace elements are measured by the online pollution monitoring, forecast-warning and source term retrieval system AS3. Hourly measured concentrations of PM10, PM2.5 and 16 trace elements in the PM2.5 section (Ca, Pb, Cu, C1, V, Cr, Fe, Ti, Mn, Ni, Zn, Ga, As, Se, Sr, Ba) are focused. Source apportionment of trace elements by Positive Matrix Factorization modeling indicates that there are five major sources, including dust, industrial processing, traffic, combustion, and sea salt with contribution rate of 23.68%, 21.66%, 14.30%, 22.03%, and 6.89%, respectively. Prediction ofptume dispersion from concrete plant and traffic emissions shows that PM20 pollution of concrete plant is three orders of magnitude more than that of the traffic. The influence range can extend to more than 3 km in 1 hr. Because the footprint of the industrial plumes is constantly moving according to the local meteorological conditions, the fixed monitoring sites scattered in a few hundred meters haven't captured the heaviest pollution plume at the local scale of a few km2. As a more intensive monitoring network is not operationally possible, the use of online modeling gives accurate and quantitative information of plume location, which increases the spatial pollution monitoring capacity and improves the understanding of measurement data. These results indicate that the development of the AS3 system, which combines monitoring equipment and air pollution modeling systems, is beneficial to the real-time pollution monitoring in the industrial zone. 展开更多
关键词 Particulate matter pollution Trace elements Online pollution monitoring in a industrial zone Source apportionment Plume evolution
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