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

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 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 ofmore » 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.« less

Authors:
; ;
Publication Date:
Research Org.:
North Carolina State Univ., Raleigh, NC (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1236098
Alternate Identifier(s):
OSTI ID: 1268169
Grant/Contract Number:  
SC0006633; SC0010470
Resource Type:
Published Article
Journal Name:
Geoscientific Model Development (Online)
Additional Journal Information:
Journal Name: Geoscientific Model Development (Online) Journal Volume: 9 Journal Issue: 1; Journal ID: ISSN 1991-9603
Publisher:
Copernicus Publications, EGU
Country of Publication:
Germany
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; single-parameter representation; soluble surfactant properties; aerosol-particles; hygroscopic growth; aqueous-solutions; ccn activation; part 2; activity-coefficients; chemical-composition; inorganic aerosols

Citation Formats

Petters, M. D., Kreidenweis, S. M., and Ziemann, P. J. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods. Germany: N. p., 2016. Web. doi:10.5194/gmd-9-111-2016.
Petters, M. D., Kreidenweis, S. M., & Ziemann, P. J. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods. Germany. https://doi.org/10.5194/gmd-9-111-2016
Petters, M. D., Kreidenweis, S. M., and Ziemann, P. J. Tue . "Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods". Germany. https://doi.org/10.5194/gmd-9-111-2016.
@article{osti_1236098,
title = {Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods},
author = {Petters, M. D. and Kreidenweis, S. M. and Ziemann, P. J.},
abstractNote = {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.},
doi = {10.5194/gmd-9-111-2016},
journal = {Geoscientific Model Development (Online)},
number = 1,
volume = 9,
place = {Germany},
year = {2016},
month = {1}
}

Journal Article:
Free Publicly Available Full Text
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https://doi.org/10.5194/gmd-9-111-2016

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Cited by: 13 works
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