论文标题
一个基于拉格朗日粒子的数值模型，用于宏观的表面活性剂液滴
A Lagrangian Particle-Based Numerical Model for Surfactant-Laden Droplets at Macroscales
论文作者
论文摘要
大气气溶胶可以由无机和有机物质组成，包括以显着浓度的表面活性剂。重要的是，后者可以减少液体蒸气表面的表面张力，由于其两亲性结构，它们优先吸附它们。结果，液滴合并，降水的发展和最终云寿命等过程可能取决于气溶胶中表面活性剂的存在。在这里，我们提出了一个用于云液滴形成的数值模型，该模型基于基于拉格朗日粒子的微物理学 - scheme-Super-Super-Droplet方法，并考虑了液滴中表面活性剂的存在。我们的结果表明，表面活性剂通过增加活化液滴的数量和大小来促进云形成，该液滴集中在云的底部，而最大的液滴集中在云的顶部。这表明液滴的循环涉及激活和从云底向顶部的生长过程的循环。此外，我们的结论独立于用于建模由于亚网格尺度湍流而导致的欧拉变量扩散的特定方法。我们预计，我们的结果将丰富我们对表面活性剂在大气气溶胶行为中的作用的理解，重要的是，在宏观尺度上具有表面活性剂的系统的数值建模为进一步的发展铺平了道路。
Atmospheric aerosols can consist of inorganic and organic substances, including surfactants at a significant concentration. Importantly, the latter can reduce the surface tension at the liquid-vapor surfaces, where they preferentially adsorb due to their amphiphilic structure. As a result, processes such as droplet coalescence, development of precipitation and ultimately cloud lifetime, may depend on the presence of surfactants in the aerosols. Here, we present a numerical model for cloud droplet formation, which is based on the Lagrangian particle-based microphysics-scheme super-droplet method and takes into account the presence of surfactant in the droplets. Our results show that surfactant facilitates cloud formation by increasing the number and size of activated droplets, which concentrate at the bottom of the cloud, while the largest droplets are concentrated at the top of the cloud. This indicates a circulation of droplets that involves activation and growth processes from the bottom of the cloud towards the top. Moreover, our conclusions are independent of the particular approach used for modeling the diffusion of Eulerian variables due to the subgrid-scale turbulence. We anticipate that our results will enrich our understanding of the role of surfactants in the behavior of atmospheric aerosols and, importantly, will pave the way for further developments in the numerical modeling of systems with surfactants at macroscopic scales.
