Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

doi:10.5194/gmd-9-111-2016

Title: Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

Journal Article · Tue Jan 19 00:00:00 EST 2016 · Geoscientific Model Development (Online)

DOI:https://doi.org/10.5194/gmd-9-111-2016· OSTI ID:1236098

Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Kohler theory to predict the effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. Furthermore, the model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.

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Research Organization:: North Carolina State University, Raleigh, NC (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0006633; SC0010470

OSTI ID:: 1236098

Alternate ID(s):: OSTI ID: 1268169

Journal Information:: Geoscientific Model Development (Online), Journal Name: Geoscientific Model Development (Online) Vol. 9 Journal Issue: 1; ISSN 1991-9603

Publisher:: Copernicus Publications, EGUCopyright Statement

Country of Publication:: Germany

Language:: English

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Cited by: 29 works

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54 ENVIRONMENTAL SCIENCES
single-parameter representation
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activity-coefficients
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Title: Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

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