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| Titel |
Cloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China – Part 1: Size-resolved measurements and implications for the modeling of aerosol particle hygroscopicity and CCN activity |
| VerfasserIn |
D. Rose, A. Nowak, P. Achtert, A. Wiedensohler, M. Hu, M. Shao, Y. Zhang, M. O. Andreae, U. Pöschl |
| 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. 7 ; Nr. 10, no. 7 (2010-04-09), S.3365-3383 |
| Datensatznummer |
250008336
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| Publikation (Nr.) |
 copernicus.org/acp-10-3365-2010.pdf |
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| Zusammenfassung |
Atmospheric aerosol particles serving as Cloud Condensation Nuclei (CCN) are
key elements of the hydrological cycle and climate. We measured and
characterized CCN in polluted air and biomass burning smoke during the
PRIDE-PRD2006 campaign from 1–30 July 2006 at a rural site ~60 km
northwest of the mega-city Guangzhou in southeastern China.
CCN efficiency spectra (activated fraction vs. dry particle diameter;
20–290 nm) were recorded at water vapor supersaturations (S) in the range
of 0.068% to 1.27%. The corresponding effective hygroscopicity parameters
describing the influence of particle composition on CCN activity were in the
range of κ≈0.1–0.5. The campaign average value of
κ=0.3 equals the average value of κ for other continental
locations. During a strong local biomass burning event, the average value of
κ dropped to 0.2, which can be considered as characteristic for
freshly emitted smoke from the burning of agricultural waste. At low S
(≤0.27%), the maximum activated fraction remained generally well below
one, indicating substantial portions of externally mixed CCN-inactive
particles with much lower hygroscopicity – most likely soot particles (up to
~60% at ~250 nm).
The mean CCN number concentrations (NCCN,S) ranged from
1000 cm−3 at S=0.068% to 16 000 cm−3 at S=1.27%, which is
about two orders of magnitude higher than in pristine air.
Nevertheless, the ratios between CCN concentration and total aerosol particle
concentration (integral CCN efficiencies) were similar to the ratios observed
in pristine continental air (~6% to ~85% at S=0.068% to
1.27%). Based on the measurement data, we have tested different model
approaches for the approximation/prediction of NCCN,S. Depending on
S and on the model approach, the relative deviations between observed and
predicted NCCN,S ranged from a few percent to several hundred
percent. The largest deviations occurred at low S with a simple power law.
With a Köhler model using variable κ values obtained from individual
CCN efficiency spectra, the relative deviations were on average less than
~10% and hardly exceeded 20%, confirming the applicability of the
κ-Köhler model approach for efficient description of the CCN
activity of atmospheric aerosols. Note, however, that different types of
κ-parameters must be distinguished for external mixtures of CCN-active
and -inactive aerosol particles (κa, κt,
κcut). Using a constant average hygroscopicity parameter
(κ=0.3) and variable size distributions as measured, the deviations
between observed and predicted CCN concentrations were on average less than
20%. In contrast, model calculations using variable hygroscopicity
parameters as measured and constant size distributions led to much higher
deviations: ~70% for the campaign average size distribution,
~80% for a generic rural size distribution, and ~140% for a
generic urban size distribution. These findings confirm earlier studies
suggesting that aerosol particle number and size are the major
predictors for the variability of the CCN concentration in continental
boundary layer air, followed by particle composition and hygroscopicity as
relatively minor modulators. Depending on the required and applicable level
of detail, the information and parameterizations presented in this study
should enable efficient description of the CCN activity of atmospheric
aerosols in detailed process models as well as in large-scale atmospheric and
climate models. |
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