WRF modeling of PM2.5 remediation by SALSCS and its clean air flow over Beijing terrain

Qingfeng Cao, Lian Shen, Sheng Chieh Chen, David Y Pui

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


Atmospheric simulations were carried out over the terrain of entire Beijing, China, to investigate the effectiveness of an air-pollution cleaning system named Solar-Assisted Large-Scale Cleaning System (SALSCS) for PM2.5 mitigation by using the Weather Research and Forecasting (WRF) model. SALSCS was proposed to utilize solar energy to generate airflow therefrom the airborne particulate pollution of atmosphere was separated by filtration elements. Our model used a derived tendency term in the potential temperature equation to simulate the buoyancy effect of SALSCS created with solar radiation on its nearby atmosphere. PM2.5 pollutant and SALSCS clean air were simulated in the model domain by passive tracer scalars. Simulation conditions with two system flow rates of 2.64 × 105 m3/s and 3.80 × 105 m3/s were tested for seven air pollution episodes of Beijing during the winters of 2015–2017. The numerical results showed that with eight SALSCSs installed along the 6th Ring Road of the city, 11.2% and 14.6% of PM2.5 concentrations were reduced under the two flow-rate simulation conditions, respectively.

Original languageEnglish (US)
Pages (from-to)134-146
Number of pages13
JournalScience of the Total Environment
StatePublished - Jun 1 2018


  • Air pollution reduction
  • Atmospheric simulation
  • Clean air
  • WRF


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