Dynamic characteristics of snowfall particles in atmospheric turbulent boundary layer and its effect on dust wet deposition

Abstract. Wet deposition by snowfall refers to the scavenging of atmospheric dust by snow particles. Existing models only consider vertical scavenging under still-air conditions, neglecting turbulence-induced complex vertical and horizontal motions of snowfall particles in the actual atmosphere boundary layer, which leads to inaccurate estimation of wet deposition flux. Currently, precise quantitative analysis of dust collection mechanism during snow particle setting remains lacking under turbulence. We employ the Euler-Lagrange numerical method, simplifying snow particles as spherical particles, to simulate and analyze snow particles dynamic characteristics and dust collection in turbulent boundary layer. The study introduces a dimensionless parameter αd=Vt/κu*= 0.2 (Vt is the terminal settling velocity of snow particles, and κ= 0.4 is the von Kármán constant) to characterize the dynamic behavior of snow particles in turbulence. This parameter reflects the relative strength between gravitational setting and turbulent diffusion. Results show that when αd> 0.2, the vertical relative motion dominates (with stronger dominances as αd increases); when αd< 0.2, horizontal relative motion becomes dominant. This shift in dynamic characteristics significantly enhances total dust collection capacity of snow particles and causes the dominant collection mechanism from vertical to horizontal: for αd≥ 1, vertical collection for over 75 % of the total; when horizontal dominance, horizontal collection contributes over 50 %. The study demonstrates that neglecting horizontal collection underestimates wet deposition flux. Thus, we establish a quantitative wet deposition model, providing a theoretical basis for predicting atmospheric dust wet deposition and artificial dust removal.

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Publication Details

Journal
Atmospheric chemistry and physics
Published
2026-05-22
DOI
https://doi.org/10.5194/acp-26-7013-2026
Primary Topic
Particle Dynamics in Fluid Flows
Type
article
Field-Weighted Citation Impact
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article

Dynamic characteristics of snowfall particles in atmospheric turbulent boundary layer and its effect on dust wet deposition

Binbin Pei, Wanzhi Li, Jie Zhang, Ning Huang
Atmospheric chemistry and physics
Particle Dynamics in Fluid Flows
article

Dynamic characteristics of snowfall particles in atmospheric turbulent boundary layer and its effect on dust wet deposition

Binbin Pei, Wanzhi Li, Jie Zhang, Ning Huang
article en

Abstract

Abstract. Wet deposition by snowfall refers to the scavenging of atmospheric dust by snow particles. Existing models only consider vertical scavenging under still-air conditions, neglecting turbulence-induced complex vertical and horizontal motions of snowfall particles in the actual atmosphere boundary layer, which leads to inaccurate estimation of wet deposition flux. Currently, precise quantitative analysis of dust collection mechanism during snow particle setting remains lacking under turbulence. We employ the Euler-Lagrange numerical method, simplifying snow particles as spherical particles, to simulate and analyze snow particles dynamic characteristics and dust collection in turbulent boundary layer. The study introduces a dimensionless parameter αd=Vt/κu*= 0.2 (Vt is the terminal settling velocity of snow particles, and κ= 0.4 is the von Kármán constant) to characterize the dynamic behavior of snow particles in turbulence. This parameter reflects the relative strength between gravitational setting and turbulent diffusion. Results show that when αd> 0.2, the vertical relative motion dominates (with stronger dominances as αd increases); when αd< 0.2, horizontal relative motion becomes dominant. This shift in dynamic characteristics significantly enhances total dust collection capacity of snow particles and causes the dominant collection mechanism from vertical to horizontal: for αd≥ 1, vertical collection for over 75 % of the total; when horizontal dominance, horizontal collection contributes over 50 %. The study demonstrates that neglecting horizontal collection underestimates wet deposition flux. Thus, we establish a quantitative wet deposition model, providing a theoretical basis for predicting atmospheric dust wet deposition and artificial dust removal.

Atmospheric chemistry and physicsVol. 26(10)
Lanzhou University (CN)
Lanzhou University, National Natural Science Foundation of China, Fundo para o Desenvolvimento das Ciências e da Tecnologia
Openalex Percentile: Top 6%
Particle Dynamics in Fluid Flows
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