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

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

Research output: Contribution to journalArticle

11 Citations (Scopus)

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 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.

Original languageEnglish
Pages (from-to)2853-2881
Number of pages29
JournalAtmospheric Chemistry and Physics
Volume18
Issue number4
DOIs
Publication statusPublished - 2018 Feb 28

Fingerprint

cloud condensation nucleus
observatory
chemical composition
volcanic cloud
hygroscopicity
urban site
supersaturation
radiative forcing
particle
model validation
haze
wildfire
wet season
air mass
coastal zone
dry season
boundary layer
labor
autumn

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Cite this

Schmale, Julia ; Henning, Silvia ; Decesari, Stefano ; Henzing, Bas ; Keskinen, Helmi ; Sellegri, Karine ; Ovadnevaite, Jurgita ; Pöhlker, Mira ; 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 ; 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 ; Andreae, Meinrat ; Artaxo, Paulo ; Wiedensohler, Alfred ; Ogren, John ; Matsuki, Atsushi ; Soo Yum, Seong ; Stratmann, Frank ; Baltensperger, Urs ; Gysel, Martin. / Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories. In: Atmospheric Chemistry and Physics. 2018 ; Vol. 18, No. 4. pp. 2853-2881.
@article{b9476f11e9d94d3b840b75341abdcbe8,
title = "Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories",
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 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 -K{\"o}hler 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.",
author = "Julia Schmale and Silvia Henning and Stefano Decesari and Bas Henzing and Helmi Keskinen and Karine Sellegri and Jurgita Ovadnevaite and Mira P{\"o}hlker and Joel Brito and Aikaterini Bougiatioti and Adam Kristensson and Nikos Kalivitis and Iasonas Stavroulas and Samara Carbone and Anne Jefferson and Minsu Park and Patrick Schlag and Yoko Iwamoto and Pasi Aalto and Mikko {\"A}ij{\"a}l{\"a} and Nicolas Bukowiecki and Mikael Ehn and Roman Fr{\"o}hlich and Arnoud Frumau and Erik Herrmann and Hartmut Herrmann and Rupert Holzinger and Gerard Kos and Markku Kulmala and Nikolaos Mihalopoulos and Athanasios Nenes and Colin O'Dowd and Tuukka Pet{\"a}j{\"a} and David Picard and Christopher P{\"o}hlker and Ulrich P{\"o}schl and Laurent Poulain and Erik Swietlicki and Meinrat Andreae and Paulo Artaxo and Alfred Wiedensohler and John Ogren and Atsushi Matsuki and {Soo Yum}, Seong and Frank Stratmann and Urs Baltensperger and Martin Gysel",
year = "2018",
month = "2",
day = "28",
doi = "10.5194/acp-18-2853-2018",
language = "English",
volume = "18",
pages = "2853--2881",
journal = "Atmospheric Chemistry and Physics",
issn = "1680-7316",
publisher = "European Geosciences Union",
number = "4",

}

Schmale, J, Henning, S, Decesari, S, Henzing, B, Keskinen, H, Sellegri, K, Ovadnevaite, J, Pöhlker, M, Brito, J, Bougiatioti, A, Kristensson, A, Kalivitis, N, Stavroulas, I, Carbone, S, Jefferson, A, Park, M, Schlag, P, Iwamoto, Y, Aalto, P, Äijälä, M, Bukowiecki, N, Ehn, M, Fröhlich, R, Frumau, A, Herrmann, E, Herrmann, H, Holzinger, R, Kos, G, Kulmala, M, Mihalopoulos, N, Nenes, A, O'Dowd, C, Petäjä, T, Picard, D, Pöhlker, C, Pöschl, U, Poulain, L, Swietlicki, E, Andreae, M, Artaxo, P, Wiedensohler, A, Ogren, J, Matsuki, A, Soo Yum, S, Stratmann, F, Baltensperger, U & Gysel, M 2018, 'Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories', Atmospheric Chemistry and Physics, vol. 18, no. 4, pp. 2853-2881. https://doi.org/10.5194/acp-18-2853-2018

Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories. / Schmale, Julia; Henning, Silvia; Decesari, Stefano; Henzing, Bas; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Pöhlker, Mira; 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; 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; Andreae, Meinrat; Artaxo, Paulo; Wiedensohler, Alfred; Ogren, John; Matsuki, Atsushi; Soo Yum, Seong; Stratmann, Frank; Baltensperger, Urs; Gysel, Martin.

In: Atmospheric Chemistry and Physics, Vol. 18, No. 4, 28.02.2018, p. 2853-2881.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories

AU - Schmale, Julia

AU - Henning, Silvia

AU - Decesari, Stefano

AU - Henzing, Bas

AU - Keskinen, Helmi

AU - Sellegri, Karine

AU - Ovadnevaite, Jurgita

AU - Pöhlker, Mira

AU - Brito, Joel

AU - Bougiatioti, Aikaterini

AU - Kristensson, Adam

AU - Kalivitis, Nikos

AU - Stavroulas, Iasonas

AU - Carbone, Samara

AU - Jefferson, Anne

AU - Park, Minsu

AU - Schlag, Patrick

AU - Iwamoto, Yoko

AU - Aalto, Pasi

AU - Äijälä, Mikko

AU - Bukowiecki, Nicolas

AU - Ehn, Mikael

AU - Fröhlich, Roman

AU - Frumau, Arnoud

AU - Herrmann, Erik

AU - Herrmann, Hartmut

AU - Holzinger, Rupert

AU - Kos, Gerard

AU - Kulmala, Markku

AU - Mihalopoulos, Nikolaos

AU - Nenes, Athanasios

AU - O'Dowd, Colin

AU - Petäjä, Tuukka

AU - Picard, David

AU - Pöhlker, Christopher

AU - Pöschl, Ulrich

AU - Poulain, Laurent

AU - Swietlicki, Erik

AU - Andreae, Meinrat

AU - Artaxo, Paulo

AU - Wiedensohler, Alfred

AU - Ogren, John

AU - Matsuki, Atsushi

AU - Soo Yum, Seong

AU - Stratmann, Frank

AU - Baltensperger, Urs

AU - Gysel, Martin

PY - 2018/2/28

Y1 - 2018/2/28

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85042731217&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85042731217&partnerID=8YFLogxK

U2 - 10.5194/acp-18-2853-2018

DO - 10.5194/acp-18-2853-2018

M3 - Article

AN - SCOPUS:85042731217

VL - 18

SP - 2853

EP - 2881

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

SN - 1680-7316

IS - 4

ER -