Particulate matter pollution in Kunshan High-Tech zone: Source apportionment with trace elements, plume evolution and its monitoring
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
DOI:10.1016/j.jes.2018.03.022
Received August 04, 2017,Revised , Accepted March 20, 2018, Available online March 27, 2018
Volume 30,2018,Pages 119-126
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, Cl, 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 of plume dispersion from concrete plant and traffic emissions shows that PM10 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.
