Preprints
https://doi.org/10.5194/egusphere-2025-5300
https://doi.org/10.5194/egusphere-2025-5300
04 Jan 2026
 | 04 Jan 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

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

Jie Zhang, Wanzhi Li, Ning Huang, and Binbin Pei

Abstract. Wet deposition by snowfall refers to the scavenging of atmospheric dust by snow particles. Existing models only consider vertical scavenging in quiescent atmosphere, neglecting the complex vertical and horizontal motion of snowfall particles induced by turbulence in the actual atmosphere boundary layer, affecting the accurate estimation of wet deposition flux. However, precise quantitative analysis of dust collection mechanism during snow particle setting remains lacking under turbulence. Therefore, we employ the Euler-Lagrange numerical method to simulate and analyze snow particles dynamic characteristics and dust collection in turbulent boundary layers. It is shown that increasing friction velocity (u*) alters the dominant factors controlling the relative motion between snow particles and air. The transition occurs at a critical 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). When αd>0.2, the vertical relative motion dominates, and its dominance strengthens with increasing αd; when αd<0.2, the horizontal relative motion becomes predominant. This change in dynamic characteristics significantly enhances total dust collection capacity and shifts the dominant collection mechanism from vertical to horizontal: for αd≥1, vertical collection accounts for over 75% of the total, while under horizontal dominance, its contribution exceed 50%. The results show that neglecting horizontal collection underestimates wet deposition flux. Thus, we establish a quantitative wet deposition model, providing a theoretical basis for snowfall particle collection mechanisms under turbulent, with significant applications for predicting atmospheric dust wet deposition and artificial dust removal.

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Jie Zhang, Wanzhi Li, Ning Huang, and Binbin Pei

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Jie Zhang, Wanzhi Li, Ning Huang, and Binbin Pei
Jie Zhang, Wanzhi Li, Ning Huang, and Binbin Pei

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Short summary
Snow cleans air as falling snow captures dust. We studied how wind turbulence affects this process. Our computer simulations reveal that turbulence makes snow particles move horizontally, greatly increasing their dust collection. Current models ignore this horizontal motion and thus underestimate cleaning. Our new model captures this effect, offering a better tool for predicting air pollution removal and guiding environmental cleanup efforts.
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