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

2018, Schmale, Julia, Henning, Silvia, Decesari, Stefano, Henzing, Bas, Keskinen, Helmi, Sellegri, Karine, Ovadnevaite, Jurgita, Pöhlker, Mira L., Brito, Joel, Bougiatioti, Aikaterini, Kristensson, Adam, Kalivitis, Nikos, Stavroulas, Iasonas, Carbone, Samara, Jefferson, Anne, Park, Minsu, Schlag, Patrick, Iwamoto, Yoko, Aalto, Pasi, Äijälä, Mikko, Bukowiecki, Nicolas, Ehn, Mikael, Frank, Göran, Fröhlich, Roman, Frumau, Arnoud, Herrmann, Erik, Herrmann, Hartmut, Holzinger, Rupert, Kos, Gerard, Kulmala, Markku, Mihalopoulos, Nikolaos, Nenes, Athanasios, O'Dowd, Colin, Petäjä, Tuukka, Picard, David, Pöhlker, Christopher, Pöschl, Ulrich, Poulain, Laurent, Prévôt, André Stephan Henry, Swietlicki, Erik, Andreae, Meinrat O., Artaxo, Paulo, Wiedensohler, Alfred, Ogren, John, Matsuki, Atsushi, Yum, Seong Soo, Stratmann, Frank, Baltensperger, Urs, Gysel, Martin

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, 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 -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 . 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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Immersionmode ice nucleationmeasurements with the new Portable Immersion Mode Cooling chAmber (PIMCA)

2016, Kohn, Monika, Lohmann, Ulrike, Welti, André, Kanji, Zamin A.

The new Portable Immersion Mode Cooling chAmber (PIMCA) has been developed for online immersion freezing of single-immersed aerosol particles. PIMCA is a vertical extension of the established Portable Ice Nucleation Chamber (PINC). PIMCA immerses aerosol particles into cloud droplets before they enter PINC. Immersion freezing experiments on cloud droplets with a radius of 5–7 μm at a prescribed supercooled temperature (T) and water saturation can be conducted, while other ice nucleation mechanisms (deposition, condensation, and contact mode) are excluded. Validation experiments on reference aerosol (kaolinite, ammonium sulfate, and ammonium nitrate) showed good agreement with theory and literature. The PIMCA-PINC setup was tested in the field during the Zurich AMBient Immersion freezing Study (ZAMBIS) in spring 2014 in Zurich, Switzerland. Significant concentrations of submicron ambient aerosol triggering immersion freezing at T > 236 K were rare. The mean frozen cloud droplet number concentration was estimated to be 7.22·105 L−1 for T < 238 K and determined from the measured frozen fraction and cloud condensation nuclei (CCN) concentrations predicted for the site at a typical supersaturation of SS = 0.3%. This value should be considered as an upper limit of cloud droplet freezing via immersion and homogeneous freezing processes. The predicted ice nucleating particle (INP) concentration based on measured total aerosol larger than 0.5 μm and the parameterization by DeMott et al. (2010) at T = 238 K is INPD10=54 ± 39 L−1. This is a lower limit as supermicron particles were not sampled with PIMCA-PINC during ZAMBIS.