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Cloud condensation nuclei activity and droplet formation of primary and secondary organic aerosol mixtures

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Version 2 2017-12-04, 18:01
Version 1 2017-10-17, 18:57
journal contribution
posted on 2017-12-04, 18:01 authored by E. A. Fofie, N. M. Donahue, A. Asa-Awuku

Understanding the mixing behavior of anthropogenic primary and biogenic secondary organic aerosol (POA and SOA) is important for characterizing their interactions with water vapor. The following work expands upon previous studies and investigates cloud condensation nuclei (CCN) activity and droplet kinetics of α-pinene SOA formed in an environmental chamber and mixed with diesel or motor oil-diesel fuel POA. The changes in the aerosol mixing are similar to previously published work but this study provides new CCN activity and droplet information. The CCN activity of the unmixed aerosol systems are measured separately; κ = 0.15, 0.11, 0.022 for α-pinene SOA, diesel POA and motor oil-diesel fuel POA, respectively. In the α-pinene SOA + diesel POA mixture, the CCN activity, characterized by κ-hygroscopicity, decreases from κ = 0.15 to 0.06 after an initial injection of the POA but increases to κ = 0.12. The increase in CCN activity occurs after particle collision (coagulation and wall-loss) rates dominate aerosol processes in the chamber. The α-pinene SOA + motor oil-fuel POA does not readily mix and the CCN activity of the complex system increases with time (from κ = 0.022 to 0.10). An empirical equation using unit mass resolution (UMR) AMS data of two different ion fragments reasonably predicts CCN activity of the POA and SOA mixtures. CCN measurement may be a promising tool to gain additional insight into the complex mixtures of organic aerosol and subsequent interactions with water vapor.

Copyright © 2018 American Association for Aerosol Research

Funding

The authors would like to thank the United States National Science Foundation (NSF) and the University of California Transportation Research Fellowship for their support in this work. Specifically, the publication of this work was supported by the NSF grant 1151893. Its contents are solely the responsibility of the grantees and do not necessarily represent the official views of the NSF or UCTC. Further, the NSF does not endorse the purchase of any commercial products or services mentioned in the publication. Additionally, AAA and NMD thank the Dreyfus Postdoctoral Fellowship for their support in data collection.

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