Particulate matter pollution in Kunshan High-Tech zone： Source apportionment with trace elements, plume evolution and its monitoring  

作　　者：Suwei Zhang Qijie Zhang Armand Albergel Didier Buty Liangmin Yu Haiting Wang Wuxia Bi Peng Cheng Fu Chen Jun Fang Ruirui Hou Xudong Luan Changgan Shu Jingjing Su 

机构地区：[1]Jiangsu Skyray Instrument Co., Ltd., Kunshan 215300, China [2]ARIA Technologies SA,Boulogne-Billancourt 92100, France [3]Kunshan Environment Monitoring Station, Kunshan 215300, China [4]State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control,College of Environmental Science and Engineering, Nankai University, Tianjin 300000, China [5]Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300000, China [6]Ecole Nationale Superieure des Mines de Douai, Douai, France [7]Kinton Environmental Technology Co., Ltd., Nanjing 210000, China [8]Chengdu University of Information Science and Technology, Chengdu 610000, China [9]Hohai Uniuersity, Nanjing 210000, China

出　　处：《Journal of Environmental Sciences》2018年第9期119-126,共8页环境科学学报（英文版）

基　　金：supported by the Ministry of Science and Technology of China under grant number 2014DFG92630;by BPIFrance of France under grant number A1305005Z

摘　　要：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.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.

关 键 词：Particulate matter pollution Trace elements Online pollution monitoring in a industrial zone Source apportionment Plume evolution 

分 类 号：X513[环境科学与工程—环境工程]