A numerical simulation study of particulate collection by vegetative barriers

Shuli Ma, Ronaldo Maghirang, Dongsen Zhao, Xiaolin Liu, Chun Wang, Li Guo

Research output: Contribution to journalArticle

Abstract

Previous research has shown that particulate matter (PM) in the air can be captured by vegetative barriers (VB) serving as shelter against the wind; however, there is only limited research of factors affecting their efficiency. This study used computational fluid dynamics to predict particle collection efficiency (CE) of VBs, as affected by hedge geometry (i.e., the size expressed in terms of height, depth, and leaf surface area density [LSAD]) and the number of hedgerows. The experimental data of Tiwary et al. (Journal of Aerosol Science, 2005) were used for model parametrisation. The area of wind speed reduction, protection area and mean collection efficiency were defined and calculated to evaluate the effectiveness of VBs on sheltering function and particle collection. Simulation results predicted that compared with original size, increasing the height and LSAD of the hedge resulted in a greater decrease of wind speed. Increasing the depth of the hedge had the greatest effect on particle collection with 42.4% for dp = 15 μm, more effective than increasing the height or LSAD. Adding another row of hedge also increased the capability of the hedge in wind speed reduction and particle collection, while row spacing did not show great effect. The increasing rate of mean CE by adding a hedgerow was less than that by increasing hedge size, which more than double the CE of particles with diameter greater than 4.25 μm. Field measurements and additional simulation tests need to be conducted under different conditions for model validation.

Original languageEnglish (US)
Pages (from-to)182-194
Number of pages13
JournalBiosystems Engineering
Volume186
DOIs
StatePublished - Oct 2019
Externally publishedYes

Keywords

  • Collection efficiency
  • Computational fluid dynamics
  • Particulate matter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Food Science
  • Animal Science and Zoology
  • Agronomy and Crop Science
  • Soil Science

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