March 2, 2023
Journal Article

Cloud Condensation Nuclei Closure Study Using Airborne Measurements over the Southern Great Plains

Abstract

Airborne measurements of non-refractory bulk aerosol chemical composition, aerosol size distributions, and cloud condensation nuclei (CCN) were conducted onboard a research aircraft during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign in the spring and summer of 2016. A CCN closure study was performed where measured CCN concentrations at 0.24 and 0.46% supersaturation were compared with the predicted CCN concentrations calculated using ?-Köhler theory, three different assumptions of aerosol mixing state, and various assumptions about hygroscopicity, density, and the insoluble fraction of organic particles. The Closure Ratio (CR) calculated as the ratio of predicted to measured CCN concentrations was equal to one, under two different aerosol mixing state assumptions: (1) all particles are composed of 100% organic particles, and (2) particles are externally mixed and composed of pure sulfates, nitrates, and organic particles assuming hygroscopicity values for organic particles (?org) between 0.04 and 0.17. A modest CCN closure with an error ± 20% was achieved assuming ?org between 0.01 and 0.27. The internal mixing state assumption provided a modest closure but at very low ?org and at 0.46% supersaturation. The results show that the density and insolubility of organic particles play a minor role in CCN prediction. Further, our study may provide constraints on various aerosol mixing state assumptions and ?org to predict CCN concentrations at a remote continental site that is dominated by organic particles.

Published: March 2, 2023

Citation

Kulkarni G.R., F. Mei, J.E. Shilling, J. Wang, R. Pinto Reveggino, C.J. Flynn, and A. Zelenyuk-Imre, et al. 2023. Cloud Condensation Nuclei Closure Study Using Airborne Measurements over the Southern Great Plains. Journal of Geophysical Research: Atmospheres 128, no. 5:Art. No. e2022JD037964. PNNL-SA-178174. doi:10.1029/2022JD037964

Research topics