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| Titel |
CCN predictions using simplified assumptions of organic aerosol composition and mixing state: a synthesis from six different locations |
| VerfasserIn |
B. Ervens, M. J. Cubison, E. Andrews, G. Feingold, J. A. Ogren, J. L. Jimenez, P. K. Quinn, T. S. Bates, J. Wang, Q. Zhang, H. Coe, M. Flynn, J. D. Allan |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 10, no. 10 ; Nr. 10, no. 10 (2010-05-26), S.4795-4807 |
| Datensatznummer |
250008477
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| Publikation (Nr.) |
 copernicus.org/acp-10-4795-2010.pdf |
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| Zusammenfassung |
An accurate but simple quantification of the fraction of aerosol particles
that can act as cloud condensation nuclei (CCN) is needed for implementation
in large-scale models. Data on aerosol size distribution, chemical
composition, and CCN concentration from six different locations have been
analyzed to explore the extent to which simple assumptions of composition
and mixing state of the organic fraction can reproduce measured CCN number
concentrations.
Fresher pollution aerosol as encountered in Riverside, CA, and the ship
channel in Houston, TX, cannot be represented without knowledge of more
complex (size-resolved) composition. For aerosol that has experienced
processing (Mexico City, Holme Moss (UK), Point Reyes (CA), and Chebogue
Point (Canada)), CCN can be predicted within a factor of two assuming either
externally or internally mixed soluble organics although these simplified
compositions/mixing states might not represent the actual properties of
ambient aerosol populations, in agreement with many previous CCN studies in
the literature. Under typical conditions, a factor of two uncertainty in CCN
concentration due to composition assumptions translates to an uncertainty of
~15% in cloud drop concentration, which might be adequate for
large-scale models given the much larger uncertainty in cloudiness. |
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