AAAR 33rd Annual Conference
October 20 - October 24, 2014
Rosen Shingle Creek
Orlando, Florida, USA
Abstract View
Understanding Cloud Condensation Nuclei Mixing States from Flow Tube Experiments
DIEP VU, Shaokai Gao, Jeffrey Pierce, Akua Asa-Awuku, University of California, Riverside
Abstract Number: 18 Working Group: Aerosols, Clouds, and Climate
Abstract Cloud condensation nuclei (CCN) data analysis of single component aerosols, such as ammonium sulfate, (NH$_(4))$_(2)SO$_(4), are well understood. The activation of a single known component yields a simple sigmoidal activation curve. However ambient aerosols generally exist as complex heterogeneous mixtures of organic and inorganic species. CCN data sets from ambient and chamber studies, which consist of these aerosol mixtures, may not show a single clean activation curve but instead can exhibit multiple activation curves not associated with doubly charged particles.
To characterize and modify mixing states, a new laminar flow tube apparatus has been developed to control the extent of mixing of organic and inorganic fractions. Increasing the residence time can increase the extent of internal mixing. Preliminary data suggests that aerosol water is a significant factor; under dry conditions, the aerosols were externally mixed and humid conditions promoted internal mixing. For example, (NH$_(4))$_(2)SO$_(4) and C$_(4)H$_(6)O$_(4) (succinic acid) when dry, maintain an external mixture, multiple activation curves are constant, and can be reproduced with Köhler theory. We have successfully recreated data sets yielding multiple activation curves by mixing multiple compounds that are representative of different anthropogenic and biogenic sources in the flow tube. The data agree well with Köhler Theory and single parameter (kappa) theory thermodynamic predictions of droplet activation. Data sets are also compared with a diffusion based coagulation particle model to predict mixing behavior. The method of analysis and the effect of mixing states of multiple components on the supersaturated hygroscopic properties of aerosols are presented. Results suggest that the aerosol morphology can be observed in CCN activation data and can be revisited in complex aerosol data sets to understand the extent of mixing.