prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods
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2016
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Abstract
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 Köhler 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. 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.
| Reference Key |
petters2016geoscientificprediction
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|---|---|
| Authors | ;M. D. Petters;S. M. Kreidenweis;P. J. Ziemann |
| Journal | international journal of quantum chemistry |
| Year | 2016 |
| DOI |
10.5194/gmd-9-111-2016
|
| URL | |
| Keywords |
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