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作为雨强函数的多分散细模态气溶胶云下清除的参数化。

Parameterization of below-cloud scavenging for polydisperse fine mode aerosols as a function of rain intensity.

机构信息

Department of Health Management, Kyungin Women's University, Incheon 21041, Korea.

Department of Environmental Science and Engineering, Ewha Woman's University, Seoul, Korea.

出版信息

J Environ Sci (China). 2023 Oct;132:43-55. doi: 10.1016/j.jes.2022.07.031. Epub 2022 Jul 28.

Abstract

The below-cloud aerosol scavenging process by precipitation is one of the most important mechanisms to remove aerosols from the atmosphere. Due to its complexity and dependence on both aerosol and raindrop sizes, wet scavenging process has been poorly treated, especially during the removal of fine particles. This makes the numerical simulation of below-cloud scavenging in large-scale aerosol models unrealistic. To consider the slip effects of submicron particles, a simplified expression for the diffusion scavenging was developed by approximating the Cunningham slip correction factor. The derived analytic solution was parameterized as a simple power function of rain intensity under the assumption of the lognormal size distribution of particles. The resultant approximated expression was compared to the observed data and the results of previous studies including a 3D atmospheric chemical transport model simulation. Compared with the default GEOS-Chem coefficient of 0.00106R and the observation-based coefficient of 0.0144R, the coefficient of a and b in Λ = aR spread in the range of 0.0002- 0.1959 for a and 0.3261- 0.525 for b over a size distribution of GSD of 1.3-2.5 and a geometric mean diameter of 0.01- 2.5 µm. Overall, this study showed that the scavenging coefficient varies widely by orders of magnitude according to the size distribution of particles and rain intensity. This study also demonstrated that the obtained simplified expression could consider the theoretical approach of aerosol polydispersity. Our proposed analytic approach showed that results can be effectively applied for reduced computational burden in atmospheric modeling.

摘要

云下气溶胶通过降水的清除过程是将气溶胶从大气中去除的最重要机制之一。由于其复杂性以及对气溶胶和雨滴大小的依赖性,湿清除过程一直处理得很差,尤其是在去除细颗粒物时。这使得在大规模气溶胶模型中对云下清除过程进行数值模拟变得不切实际。为了考虑亚微米颗粒的滑移效应,通过近似坎宁安滑移修正因子,推导出了一种用于扩散清除的简化表达式。在假定颗粒对数正态尺寸分布的情况下,将推导出的解析解参数化为雨强的简单幂函数。将所得的近似表达式与观测数据和先前研究的结果(包括三维大气化学输送模型模拟)进行了比较。与默认的 GEOS-Chem 系数 0.00106R 和基于观测的系数 0.0144R 相比,Λ=aR 中的 a 和 b 系数在 0.0002-0.1959 范围内变化,而在 0.3261-0.525 范围内变化,颗粒大小分布的 GSD 为 1.3-2.5,几何平均直径为 0.01-2.5μm。总的来说,这项研究表明,清除系数根据颗粒的大小分布和雨强的变化范围很大,变化幅度可达数量级。这项研究还表明,所获得的简化表达式可以考虑气溶胶多分散性的理论方法。我们提出的解析方法表明,结果可以有效地应用于大气模拟中降低计算负担。

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