Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories
(2018) In Atmospheric Chemistry and Physics 18(4). p.2853-2881- 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... (More)
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.
(Less)
- author
- Schmale, Julia
; Henning, Silvia
; Decesari, Stefano
; Henzing, Bas
; Keskinen, Helmi
; Sellegri, Karine
; Ovadnevaite, Jurgita
; Pöhlker, Mira
; Brito, Joel
; Bougiatioti, Aikaterini
; Kristensson, Adam
LU
; Kalivitis, Nikos
; Stavroulas, Iasonas
; Carbone, Samara
; Jefferson, Anne
; Park, Minsu
; Schlag, Patrick
; Iwamoto, Yoko
; Aalto, Pasi
; Äijälä, Mikko
; Bukowiecki, Nicolas
; Ehn, Mikael
; 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
; Swietlicki, Erik
LU
; Andreae, Meinrat
; Artaxo, Paulo
; Wiedensohler, Alfred
; Ogren, John
; Matsuki, Atsushi
; Soo Yum, Seong
; Stratmann, Frank
; Baltensperger, Urs
; Gysel, Martin
and Frank, Göran
LU
(Less) - organization
- publishing date
- 2018-02-28
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Atmospheric Chemistry and Physics
- volume
- 18
- issue
- 4
- pages
- 29 pages
- publisher
- Copernicus GmbH
- external identifiers
-
- scopus:85042731217
- ISSN
- 1680-7316
- DOI
- 10.5194/acp-18-2853-2018
- language
- English
- LU publication?
- yes
- id
- 660dbf77-ff3b-4315-a041-58ceae3ae89c
- date added to LUP
- 2018-03-16 15:41:35
- date last changed
- 2022-06-05 23:34:41
@article{660dbf77-ff3b-4315-a041-58ceae3ae89c,
abstract = {{<p>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.</p>}},
author = {{Schmale, Julia and Henning, Silvia and Decesari, Stefano and Henzing, Bas and Keskinen, Helmi and Sellegri, Karine and Ovadnevaite, Jurgita and Pöhlker, Mira and Brito, Joel and Bougiatioti, Aikaterini and Kristensson, Adam and Kalivitis, Nikos and Stavroulas, Iasonas and Carbone, Samara and Jefferson, Anne and Park, Minsu and Schlag, Patrick and Iwamoto, Yoko and Aalto, Pasi and Äijälä, Mikko and Bukowiecki, Nicolas and Ehn, Mikael and Fröhlich, Roman and Frumau, Arnoud and Herrmann, Erik and Herrmann, Hartmut and Holzinger, Rupert and Kos, Gerard and Kulmala, Markku and Mihalopoulos, Nikolaos and Nenes, Athanasios and O'Dowd, Colin and Petäjä, Tuukka and Picard, David and Pöhlker, Christopher and Pöschl, Ulrich and Poulain, Laurent and Swietlicki, Erik and Andreae, Meinrat and Artaxo, Paulo and Wiedensohler, Alfred and Ogren, John and Matsuki, Atsushi and Soo Yum, Seong and Stratmann, Frank and Baltensperger, Urs and Gysel, Martin and Frank, Göran}},
issn = {{1680-7316}},
language = {{eng}},
month = {{02}},
number = {{4}},
pages = {{2853--2881}},
publisher = {{Copernicus GmbH}},
series = {{Atmospheric Chemistry and Physics}},
title = {{Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories}},
url = {{http://dx.doi.org/10.5194/acp-18-2853-2018}},
doi = {{10.5194/acp-18-2853-2018}},
volume = {{18}},
year = {{2018}},
}