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  Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories

Schmale, J., Henning, S., Decesari, S., Henzing, B., Keskinen, H., Sellegri, K., et al. (2018). Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories. Atmospheric Chemistry and Physics, 18(4), 2853-2881. doi:10.5194/acp-18-2853-2018.

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Schmale, Julia1, Autor
Henning, Silvia1, Autor
Decesari, Stefano1, Autor
Henzing, Bas1, Autor
Keskinen, Helmi1, Autor
Sellegri, Karine1, Autor
Ovadnevaite, Jurgita1, Autor
Pöhlker, Mira L.2, Autor           
Brito, Joel1, Autor
Bougiatioti, Aikaterini1, Autor
Kristensson, Adam1, Autor
Kalivitis, Nikos1, Autor
Stavroulas, Iasonas1, Autor
Carbone, Samara1, Autor
Jefferson, Anne1, Autor
Park, Minsu1, Autor
Schlag, Patrick1, Autor
Iwamoto, Yoko1, Autor
Aalto, Pasi1, Autor
Aijala, Mikko1, Autor
Bukowiecki, Nicolas1, AutorEhn, Mikael1, AutorFrank, Goran1, AutorFrohlich, Roman1, AutorFrumau, Arnoud1, AutorHerrmann, Erik1, AutorHerrmann, Hartmut1, AutorHolzinger, Rupert1, AutorKos, Gerard1, AutorKulmala, Markku1, AutorMihalopoulos, Nikolaos1, AutorNenes, Athanasios1, AutorO'Dowd, Colin1, AutorPetaja, Tuukka1, AutorPicard, David1, AutorPöhlker, Christopher2, Autor           Pöschl, Ulrich2, Autor           Poulain, Laurent1, AutorPrevot, Andre Stephan Henry1, AutorSwietlicki, Erik1, AutorAndreae, Meinrat O.3, Autor           Artaxo, Paulo1, AutorWiedensohler, Alfred1, AutorOgren, John1, AutorMatsuki, Atsushi1, AutorYum, Seong Soo1, AutorStratmann, Frank1, AutorBaltensperger, Urs1, AutorGysel, Martin1, Autor mehr..
Affiliations:
1external, ou_persistent22              
2Multiphase Chemistry, Max Planck Institute for Chemistry, Max Planck Society, ou_1826290              
3Biogeochemistry, Max Planck Institute for Chemistry, Max Planck Society, ou_1826286              

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 Zusammenfassung: Aerosol–cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Here we present a data set – ready to be used for model validation – of long-term observations of CCN number concentrations, particle number size distributions and chemical composition from 12 sites on 3 continents. Studied environments include coastal background, rural background, alpine sites, remote forests and an urban surrounding. Expectedly, CCN characteristics are highly variable across site categories. However, they also vary within them, most strongly in the coastal background group, where CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behaviour, most continental stations exhibit very similar activation ratios (relative to particles >20nm) across the range of 0.1 to 1.0% supersaturation. At the coastal sites the transition from particles being CCN inactive to becoming CCN active occurs over a wider range of the supersaturation spectrum. Several stations show strong seasonal cycles of CCN number concentrations and particle number size distributions, e.g. at Barrow (Arctic haze in spring), at the alpine stations (stronger influence of polluted boundary layer air masses in summer), the rain forest (wet and dry season) or Finokalia (wildfire influence in autumn). The rural background and urban sites exhibit relatively little variability throughout the year, while short-term variability can be high especially at the urban site. The average hygroscopicity parameter, κ, calculated from the chemical composition of submicron particles was highest at the coastal site of Mace Head (0.6) and lowest at the rain forest station ATTO (0.2–0.3). We performed closure studies based on κ–Köhler theory to predict CCN number concentrations. The ratio of predicted to measured CCN concentrations is between 0.87 and 1.4 for five different types of κ. The temporal variability is also well captured, with Pearson correlation coefficients exceeding 0.87. Information on CCN number concentrations at many locations is important to better characterise ACI and their radiative forcing. But long-term comprehensive aerosol particle characterisations are labour intensive and costly. Hence, we recommend operating "migrating-CCNCs" to conduct collocated CCN number concentration and particle number size distribution measurements at individual locations throughout one year at least to derive a seasonally resolved hygroscopicity parameter. This way, CCN number concentrations can only be calculated based on continued particle number size distribution information and greater spatial coverage of long-term measurements can be achieved.

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 Datum: 2018
 Publikationsstatus: Erschienen
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 Identifikatoren: ISI: 000426312200002
DOI: 10.5194/acp-18-2853-2018
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Titel: Atmospheric Chemistry and Physics
  Kurztitel : ACP
Genre der Quelle: Zeitschrift
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Affiliations:
Ort, Verlag, Ausgabe: Göttingen : Copernicus Publications
Seiten: - Band / Heft: 18 (4) Artikelnummer: - Start- / Endseite: 2853 - 2881 Identifikator: ISSN: 1680-7316
CoNE: https://pure.mpg.de/cone/journals/resource/111030403014016