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

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, , 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 longterm
measurements can be achieved.