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A moment model for simulating raindrop scavenging of aerosols
- A moment model for simulating raindrop scavenging of aerosols
- Jung C.H.; Kim Y.P.; Lee K.W.
- Ewha Authors
- SCOPUS Author ID
- Issue Date
- Journal Title
- Journal of Aerosol Science
- vol. 34, no. 9, pp. 1217 - 1233
- SCI; SCIE; SCOPUS
- The dynamics of a polydispersed aerosol size distribution, scavenged by precipitation, are numerically studied. The collision efficiency formula proposed by Slinn (Precipitation Scavenging in Atmospheric Sciences and Power Production - 1979, Division of Biomedical Environmental Research, US Department of Energy, Washington, DC, USA, 1983, Chapter 11) and the moment method were introduced to represent the particle removal mechanism by raindrops and the aerosol size distribution, respectively. Consequently, the dynamics of the particle size distribution were reduced to a set of ordinary differential equations using the moment approach. A generalized raindrop distribution, including two widely used distributions; the Marshall-Palmer (MP) and Krigian-Mazin (KM) raindrop distributions, was adopted. Our model results have shown that raindrops with smaller diameters, and narrower distributions, collect aerosols more efficiently. Further, it was shown, in the small particle size region that the geometric mean diameter increases, while in the large particle region it decreases. For the two size ranges, the geometric standard deviations decrease with time, and a scavenging gap, the minimum particle removal efficiency region, exists between these particle size ranges. The dynamics of the particle size distributions, the MP and KM raindrop distributions, in the small particle range, show that the effects of the overestimation in the MP distribution were not as great as expected. Also, this study ascertained that the conventional parameterization of the constant collision efficiency introduces significant errors for estimating the particle size distribution dynamics by wet scavenging. © 2003 Elsevier Ltd. All rights reserved.
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