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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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Modelling winter organic aerosol at the European scale with CAMx: Evaluation and source apportionment with a VBS parameterization based on novel wood burning smog chamber experiments

2017, Ciarelli, Giancarlo, Aksoyoglu, Sebnem, El Haddad, Imad, Bruns, Emily A., Crippa, Monica, Poulain, Laurent, Äijälä, Mikko, Carbone, Samara, Freney, Evelyn, O'Dowd, Colin, Baltensperger, Urs, Prévôt, André S. H.

We evaluated a modified VBS (volatility basis set) scheme to treat biomass-burning-like organic aerosol (BBOA) implemented in CAMx (Comprehensive Air Quality Model with extensions). The updated scheme was parameterized with novel wood combustion smog chamber experiments using a hybrid VBS framework which accounts for a mixture of wood burning organic aerosol precursors and their further functionalization and fragmentation in the atmosphere. The new scheme was evaluated for one of the winter EMEP intensive campaigns (February-March 2009) against aerosol mass spectrometer (AMS) measurements performed at 11 sites in Europe. We found a considerable improvement for the modelled organic aerosol (OA) mass compared to our previous model application with the mean fractional bias (MFB) reduced from -61 to -29 %. We performed model-based source apportionment studies and compared results against positive matrix factorization (PMF) analysis performed on OA AMS data. Both model and observations suggest that OA was mainly of secondary origin at almost all sites. Modelled secondary organic aerosol (SOA) contributions to total OA varied from 32 to 88% (with an average contribution of 62 %) and absolute concentrations were generally under-predicted. Modelled primary hydrocarbon-like organic aerosol (HOA) and primary biomass-burning-like aerosol (BBPOA) fractions contributed to a lesser extent (HOA from 3 to 30 %, and BBPOA from 1 to 39 %) with average contributions of 13 and 25 %, respectively. Modelled BBPOA fractions were found to represent 12 to 64% of the total residential-heating-related OA, with increasing contributions at stations located in the northern part of the domain. Source apportionment studies were performed to assess the contribution of residential and non-residential combustion precursors to the total SOA. Non-residential combustion and road transportation sector contributed about 30-40% to SOA formation (with increasing contributions at urban and near industrialized sites), whereas residential combustion (mainly related to wood burning) contributed to a larger extent, around 60-70 %. Contributions to OA from residential combustion precursors in different volatility ranges were also assessed: our results indicate that residential combustion gas-phase precursors in the semivolatile range (SVOC) contributed from 6 to 30 %, with higher contributions predicted at stations located in the southern part of the domain. On the other hand, the oxidation products of higher-volatility precursors (the sum of intermediate-volatility compounds (IVOCs) and volatile organic compounds (VOCs)) contribute from 15 to 38% with no specific gradient among the stations. Although the new parameterization leads to a better agreement between model results and observations, it still underpredicts the SOA fraction, suggesting that uncertainties in the new scheme and other sources and/or formation mechanisms remain to be elucidated. Moreover, a more detailed characterization of the semivolatile components of the emissions is needed.

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Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition

2017, Schmale, Julia, Henning, Silvia, Henzing, Bas, Keskinen, Helmi, Sellegri, Karine, Ovadnevaite, Jurgita, Bougiatioti, Aikaterini, Kalivitis, Nikos, Stavroulas, Iasonas, Jefferson, Anne, Park, Minsu, Schlag, Patrick, Kristensson, Adam, Iwamoto, Yoko, Pringle, Kirsty, Reddington, Carly, Aalto, Pasi, Äijälä, Mikko, Baltensperger, Urs, Bialek, Jakub, Birmili, Wolfram, Bukowiecki, Nicolas, Ehn, Mikael, Fjæraa, Ann Mari, Fiebig, Markus, Frank, Göran, Fröhlich, Roman, Frumau, Arnoud, Furuya, Masaki, Hammer, Emanuel, Heikkinen, Liine, Herrmann, Erik, Holzinger, Rupert, Hyono, Hiroyuki, Kanakidou, Maria, Kiendler-Scharr, Astrid, Kinouchi, Kento, Kos, Gerard, Kulmala, Markku, Mihalopoulos, Nikolaos, Motos, Ghislain, Nenes, Athanasios, O’Dowd, Colin, Paramonov, Mikhail, Petäjä, Tuukka, Picard, David, Poulain, Laurent, Prévôt, André Stephan Henry, Slowik, Jay, Sonntag, Andre, Swietlicki, Erik, Svenningsson, Birgitta, Tsurumaru, Hiroshi, Wiedensohler, Alfred, Wittbom, Cerina, Ogren, John A., Matsuki, Atsushi, Yum, Seong Soo, Myhre, Cathrine Lund, Carslaw, Ken, Stratmann, Frank, Gysel, Martin

Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.