Air pollution is a major issue in many megacities. In collaboration with Prof. David Pui and Dr. Qingfeng Cao in the Particle Technology Laboratory at University of Minnesota, we have validated the numerical model of Solar-Assisted Large-Scale Cleaning System (SALSCS), conducted parametric studies on SALSCS, and carried out atmosphere simulations in Beijing, China to study the effectiveness of SALSCS for mitigating PM2.5.
SALSCS is a novel air cleaning system filtering the air driven by solar energy. A SALSCS demo unit was built in Xi'an, China, and measurements were conducted in Jan 2017 to obtain the outflow rate and temperature. A numerical model was built accordingly, and our numerical simulation showed good agreement with our measurement results. We further used the validated numerical model to study the influence of the system geometry, solar irradiation, ambient-air temperature, and ground temperature on the system performance, and the parameters with considerable influence were identified.
The simulation in Beijing is conducted by the Weather Research and Forecasting (WRF) model which solves the three-dimensional Eulerian equations for compressible flows on a terrain-following hydrostatic pressure vertical coordinate. We use three nested computational domains, where the finest domain has a horizontal spatial resolution of 1 km. A third-order Runge-Kutta algorithm is applied to advance the meteorological-significant low-frequency modes, and a smaller time step is used to advance the high-frequency modes, such as acoustic and gravity waves. A temperature tendency term is added to the energy equation for simulating the solar energy collection effect of SALSCS. The passive tracer model is adopted to simulate the transport of PM2.5 as well as the clean air delivered by SALSCS. Eight SALSCSs are installed in the suburb areas around Beijing, and each SALSCS has a low flow rate and a high flow rate for comparison. We tested seven real air pollution episodes in the 2015-2017 winter of Beijing, and each of the episodes lasts for 72 hours. We concluded that SALSCS can reduce the average PM2.5 concentration by ~10%, and the higher flow rate of SALSCS brings higher PM2.5 reduction in all the tested episodes. Also, SALSCS has the capability to deliver clean air to the downtown, but the capability is limited. The following two movies show the transport of PM2.5 and the clean air delivered by SALSCSs during January 1-2, 2016.
Also, as a response to the global COVID-19 pandemic, we are also interested in studying the transport of aerosols in the indoor environment to help understand and reduce the risk of virus spread. We used large-eddy simulation to simulate the airborne aerosol transport as well as the deposition of aerosols onto surfaces, which correspond to the two main pathways of virus transmission: airborne transmission and surface contamination. Our simulations were conducted in some practical settings and agreement to the measurement was reached.
- Cao, Q., Shen, L., Chen, S. & Pui, D. (2018), “WRF modeling of PM2.5 remediation by SALSCS and its clean air flow over Beijing Terrain,” Science of the Total Environment, Vol. 626, pp.134-146.
- Cao, Q., Huang, M., Kuehn, T.H., Shen, L., Tao, W.-Q., Cao, J. & Pui, D.Y.H. (2018), “Urban-scale SALSCS, Part II: A parametric study of system performance,” Aerosol and Air Quality Research, Vol. 18, 2879-2894.
- Cao, Q., Kuehn, T.H., Shen, L., Chen, S.-C., Zhang, N., Huang, Y., Cao, J. & Pui, D.Y.H. (2018), “Urban-scale SALSCS, Part I: Experimental evaluation and numerical modeling of a demonstration unit,” Aerosol and Air Quality Research, Vol. 18, 2865-2878.