A 3D map of a town in the North-East of Singapore was used to simulate air pollution caused by nearby vehicular traffic.

© 2019 A*STAR Institute of High Performance Computing

Simulations shed light on air filter deployment

24 May 2019

Using computational tools, A*STAR researchers are learning how best to deploy air treatment systems across large urban areas.

High concentrations of particulate matter (PM) in the air, especially those with diameters less than 2.5 micrometers, have been linked to health problems and reduced economic productivity. Although technologies such as PM filters are currently available to purify the air, the question of how best to deploy these filters on a massive scale remains unanswered.

“One could assess the performance of these filters by carrying out wind or water tunnel experiments, or by directly installing large filter systems in cities and performing air pollution measurements. The former needs experimental facilities and the latter is very expensive,” said Venkata B.L. Boppana, a scientist with A*STAR’s Institute of High Performance Computing (IHPC), who is collaborating with Corning Singapore Holdings to simulate the deployment of filters across large urban areas.

Seeking to clear the air on the judicious use of PM filters in urban areas, the researchers first selected a 3D map of a typical town in the North-East of Singapore for their simulations. The area of interest is intersected by two roads, and vehicular traffic on those roads generate PM.

The team then developed a computational fluid dynamics (CFD) model that accounts for a wide range of parameters such as road conditions, the height of surrounding buildings and the volumetric air flow rate of large filter units (called Corning Air Treatment Systems).

Using this model, the team was able to simulate the distribution and concentration of PM in the area. “With the current model and configuration, we found that the clean air zone extending from the center of an air treatment unit is up to a few tens of meters, and that the addition of flanking noise barriers—ten-meter walls on either side of roads—can almost double the maximum reduction in PM levels,” Boppana explained.

Given the complex interplay among the various parameters used in the simulation and assumptions used in the computational model, Boppana cautioned against generalizing the findings of this study across other geographical settings. Nonetheless, having demonstrated that CFD tools can help to optimize the deployment and efficacy of air treatment units in urban settings, the researchers intend to include even more parameters in their model to increase the accuracy of simulations.

“Factors like vegetation, thermal stratification, turbulence from moving vehicles, air treatment system configurations and wind direction all play a role in the spread of pollutants. Quantifying the performance of these air treatment systems by incorporating all these variables is quite complex but worth pursuing in order to clean up polluted cities,” Boppana said.

The A*STAR-affiliated researchers contributing to this research are from the Institute of High Performance Computing (IHPC). The research was performed in collaboration with Corning Singapore Holdings.

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Boppana, V. B. L., Wise, D. J., Ooi, C. C., Zhmayev, E. & Poh, H. J. CFD assessment on particulate matter filters performance in urban areas. Sustainable Cities and Society 46, 101376 (2019). | article

About the Researcher

Bharathi Boppana


Institute of High Performance Computing
Bharathi Boppana obtained her PhD in 2007 from the University of Manchester where she investigated flow instabilities using numerical methods. Thereafter, she completed her postdoctoral research at the University of Southampton, gaining insights on applications of computational fluid dynamics to urban flows. Boppana joined the Institute of High Performance Computing (IHPC), A*STAR, in 2014 as a scientist. Her research interests revolve around addressing environmental flow problems using computational methods and tools.

This article was made for A*STAR Research by Wildtype Media Group