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

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 3km in 1hr. 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.

Validation and sensitivity study of Micro-SWIFT SPRAY against wind tunnel experiments for air dispersion modeling with both heterogeneous topography and complex building layouts.

Micro-SWIFT SPRAY (MSS) is a 3D Lagrangian particle dispersion model that maintains a good balance between accuracy and computational cost. However, its capabilities for air dispersion modeling in the presence of both complex topography and high building densities have not been investigated for nuclear emergency response. In this study, MSS is systematically evaluated against two wind tunnel experiments that simulate a typical Chinese nuclear power plant with the above two features. The MSS predictions are compared with both 2D horizontal and vertical measurements. Sensitivity studies are performed with respect to the particle number, the lower bound of the turbulence intensity, and the horizontal and vertical grid size. The results demonstrate that ground-level predictions of both wind and radionuclide concentrations are in satisfactory agreement with the measurements under optimized parameter values. The vertical predictions exhibit site-dependent accuracy, but generally consistent tendencies. The default lower bound of the turbulence intensity in MSS may be insufficient for reproducing the correct plume width observed in the wind tunnel experiments. An increased lower bound is suggested to solve this problem. In addition, artificially high concentrations may arise near steep slopes if large horizontal/vertical grid sizes are used. Suitable parameters for preventing this problem are also provided.