WRF modeling of PM 2.5 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 journalArticle

6 Citations (Scopus)

Abstract

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 PM 2.5 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. PM 2.5 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 × 10 5 m 3 /s and 3.80 × 10 5 m 3 /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 6 th Ring Road of the city, 11.2% and 14.6% of PM 2.5 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
Volume626
DOIs
StatePublished - Jun 1 2018

Fingerprint

Remediation
airflow
Cleaning
remediation
weather
atmospheric pollution
Air
modeling
simulation
Air pollution
atmosphere
potential temperature
solar system
buoyancy
Flow rate
solar radiation
mitigation
tracer
Solar system
road

Keywords

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

PubMed: MeSH publication types

  • Journal Article

Cite this

WRF modeling of PM 2.5 remediation by SALSCS and its clean air flow over Beijing terrain . / Cao, Qingfeng; Shen, Lian; Chen, Sheng Chieh; Pui, David Y.

In: Science of the Total Environment, Vol. 626, 01.06.2018, p. 134-146.

Research output: Contribution to journalArticle

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abstract = "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 PM 2.5 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. PM 2.5 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 × 10 5 m 3 /s and 3.80 × 10 5 m 3 /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 6 th Ring Road of the city, 11.2{\%} and 14.6{\%} of PM 2.5 concentrations were reduced under the two flow-rate simulation conditions, respectively.",
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