Numerical study of dry deposition of dust-PM10 on leaves of coniferous forest

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The present study aims to investigate the effect of forests on PM distribution following dust events in a region prone to frequent dust storms (Northern Negev, Israel). 3D numerical modeling of the particulate flow using a discrete phase model, based on the Eulerian-Lagrangian approach, has been performed to investigate the dust deposition to the vegetation element. The modeling considered several deposition mechanisms, namely, the drag force, buoyancy force, Brownian force, and Saffman's lift force. The vegetation element is considered as a prolate ellipsoid approximating in shape to a leaf of Aleppo pine (Pinus halepensis), the dominant tree species in Lahav Forest. Based on CFD modeling, the novel parameterization of the average collection rate is suggested. The validity of the model prediction is evaluated by comparison with experimental data available in the literature. It is shown that using a correlation based on dimensionless mass transfer parameters leads to an overestimation of the dust concentration at the leeward side of the forest by 23% compared to the measurement data. By contrast, the model supplemented with CFD-based average collection rate parameterization yields an overestimation of only 8%. It was also found that both models estimate the dust concentration with a difference of less than 5% in a location inside the forest in the area adjacent to the windward side of the forest. The influences of other essential factors, such as particle size and wind velocity, on deposition efficiency and the deposition velocity of dust particles on the vegetation element, are also analyzed and discussed.

Original languageAmerican English
Article number101859
JournalAtmospheric Pollution Research
Issue number9
StatePublished - 1 Sep 2023


  • Dust particles
  • Eulerian-Lagrangian approach
  • Semi-arid
  • Vegetation element
  • dry deposition

All Science Journal Classification (ASJC) codes

  • Waste Management and Disposal
  • Pollution
  • Atmospheric Science


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