Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories
Authors: 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 
Published: February 2018

Abstract. 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 > 20 nm) 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.