2020, Laj, Paolo, Bigi, Alessandro, Rose, Clémence, Andrews, Elisabeth, Lund Myhre, Cathrine, Collaud Coen, Martine, Lin, Yong, Wiedensohler, Alfred, Schulz, Michael, Ogren, John A., Fiebig, Markus, Prenni, Anthony, Reisen, Fabienne, Romano, Salvatore, Sellegri, Karine, Sharma, Sangeeta, Schauer, Gerhard, Sheridan, Patrick, Sherman, James Patrick, Schütze, Maik, Schwerin, Andreas, Tuch, Thomas, Sohmer, Ralf, Sorribas, Mar, Steinbacher, Martin, Sun, Junying, Titos, Gloria, Toczko, Barbara, Tulet, Pierre, Tunved, Peter, Vakkari, Ville, Velarde, Fernando, Velasquez, Patricio, Villani, Paolo, Vratolis, Sterios, Wang, Sheng-Hsiang, Weinhold, Kay, Gliß, Jonas, Weller, Rolf, Yela, Margarita, Yus-Diez, Jesus, Zdimal, Vladimir, Zieger, Paul, Zikova, Nadezda, Mortier, Augustin, Pandolfi, Marco, Petäja, Tuukka, Kim, Sang-Woo, Aas, Wenche, Putaud, Jean-Philippe, Mayol-Bracero, Olga, Keywood, Melita, Labrador, Lorenzo, Aalto, Pasi, Ahlberg, Erik, Alados Arboledas, Lucas, Alastuey, Andrés, Andrade, Marcos, Artíñano, Begoña, Ausmeel, Stina, Arsov, Todor, Asmi, Eija, Backman, John, Baltensperger, Urs, Bastian, Susanne, Bath, Olaf, Beukes, Johan Paul, Brem, Benjamin T., Bukowiecki, Nicolas, Conil, Sébastien, Couret, Cedric, Day, Derek, Dayantolis, Wan, Degorska, Anna, Eleftheriadis, Konstantinos, Fetfatzis, Prodromos, Favez, Olivier, Flentje, Harald, Gini, Maria I., Gregorič, Asta, Gysel-Beer, Martin, Hallar, A. Gannet, Hand, Jenny, Hoffer, Andras, Hueglin, Christoph, Hooda, Rakesh K., Hyvärinen, Antti, Kalapov, Ivo, Kalivitis, Nikos, Kasper-Giebl, Anne, Kim, Jeong Eun, Kouvarakis, Giorgos, Kranjc, Irena, Krejci, Radovan, Kulmala, Markku, Labuschagne, Casper, Lee, Hae-Jung, Lihavainen, Heikki, Lin, Neng-Huei, Löschau, Gunter, Luoma, Krista, Marinoni, Angela, Martins Dos Santos, Sebastiao, Meinhardt, Frank, Merkel, Maik, Metzger, Jean-Marc, Mihalopoulos, Nikolaos, Nguyen, Nhat Anh, Ondracek, Jakub, Pérez, Noemi, Perrone, Maria Rita, Petit, Jean-Eudes, Picard, David, Pichon, Jean-Marc, Pont, Veronique, Prats, Natalia

Aerosol particles are essential constituents of the Earth's atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence times, resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in situ near-surface segment of the atmospheric observation system. This paper will provide the widest effort so far to document variability of climate-relevant in situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High-quality data from almost 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single-scattering albedo, and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information, including data provision procedures, quality control and analysis, data policy, and usage of the ground-based aerosol measurement network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.

2016, Swietlicki, Erik, Zhou, Jingchuan, Covert, David S., Hämeri, Kaarle, Busch, Bernhard, Väkeva, Minna, Dusek, Ulrike, Berg, Olle H., Wiedensohler, Alfred, Aalto, Pasi, Mäkelä, Jyrki, Martinsson, Bengt G., Papaspiropoulos, Giorgos, Mentes, Besim, Frank, Göran, Stratmann, Frank

Measurements of the hygroscopic properties of sub-micrometer atmospheric aerosol particles were performed with hygroscopic tandem differential mobility analysers (H-TDMA) at 5 sites in the subtropical north-eastern Atlantic during the second Aerosol Characterization Experiment (ACE-2) from 16 June to 25 July 1997. Four of the sites were in the marine boundary layer and one was, at least occasionally, in the lower free troposphere. The hygroscopic diameter growth factors of individual aerosol particles in the dry particle diameter range 10−440 nm were generally measured for changes in relative humidity (RH) from <10% to 90%. In the marine boundary layer, growth factors at 90% RH were dependent on location, air mass type and particle size. The data was dominated by a unimodal growth distribution of more-hygroscopic particles, although a bimodal growth distribution including less-hygroscopic particles was observed at times, most often in the more polluted air masses. In clean marine air masses the more-hygroscopic growth factors ranged from about 1.6 to 1.8 with a consistent increase in growth factor with increasing particle size. There was also a tendency toward higher growth factors as sodium to sulphate molar ratio increased with increasing sea-salt contribution at higher wind speeds. During outbreaks of European pollution in the ACE-2 region, the growth factors of the largest particles were reduced, but only slightly. Growth factors at all sizes in both clean and polluted air masses were markedly lower at the Sagres, Portugal site due to more proximate continental influences. The frequency of occurrence of less-hygroscopic particles with a growth factor of ca. 1.15 was greatest during polluted conditions at Sagres. The free tropospheric 50 nm particles were predominately less-hygroscopic, with an intermediate growth factor of 1.4, but more-hygroscopic particles with growth factors of about 1.6 were also frequent. While these particles probably originate from within the marine boundary layer, the less-hygroscopic particles are probably more characteristic of lower free tropospheric air masses. For those occasions when measurements were made at 90% and an intermediate 60% or 70% RH, the growth factor G(RH) of the more-hygroscopic particles could be modelled empirically by a power law expression. For the ubiquitous more-hygroscopic particles, the expressions G(RH)=(1-RH/100)-0.210 for 50 nm Aitken mode particles and G(RH)=(1-RH/100)-0.233 for 166 nm accumulation mode particles are recommended for clean marine air masses in the north-eastern Atlantic within the range 0

2016, Pfeifer, Sascha, Müller, Thomas, Weinhold, Kay, Zikova, Nadezda, dos Santos, Sebastiao Martins, Marinoni, Angela, Bischof, Oliver F., Kykal, Carsten, Ries, Ludwig, Meinhardt, Frank, Aalto, Pasi, Mihalopoulos, Nikolaos, Wiedensohler, Alfred

Aerodynamic particle size spectrometers are a well-established method to measure number size distributions of coarse mode particles in the atmosphere. Quality assurance is essential for atmospheric observational aerosol networks to obtain comparable results with known uncertainties. In a laboratory study within the framework of ACTRIS (Aerosols, Clouds, and Trace gases Research Infrastructure Network), 15 aerodynamic particle size spectrometers (APS model 3321, TSI Inc., St. Paul, MN, USA) were compared with a focus on flow rates, particle sizing, and the unit-to-unit variability of the particle number size distribution. Flow rate deviations were relatively small (within a few percent), while the sizing accuracy was found to be within 10 % compared to polystyrene latex (PSL) reference particles. The unit-to-unit variability in terms of the particle number size distribution during this study was within 10 % to 20 % for particles in the range of 0.9 up to 3 µm, which is acceptable for atmospheric measurements. For particles smaller than that, the variability increased up to 60 %, probably caused by differences in the counting efficiencies of individual units. Number size distribution data for particles smaller than 0.9 µm in aerodynamic diameter should only be used with caution. For particles larger than 3 µm, the unit-to-unit variability increased as well. A possible reason is an insufficient sizing accuracy in combination with a steeply sloping particle number size distribution and the increasing uncertainty due to decreasing counting. Particularly this uncertainty of the particle number size distribution must be considered if higher moments of the size distribution such as the particle volume or mass are calculated, which require the conversion of the aerodynamic diameter measured to a volume equivalent diameter. In order to perform a quantitative quality assurance, a traceable reference method for the particle number concentration in the size range 0.5–3 µm is needed.

2017, Wiedensohler, Alfred, Covert, David S., Swietlicki, Erik, Aalto, Pasi, Heintzenberg, Jost, Leck, Caroline

The International Arctic Ocean Expedition 1991 (IAOE-91) provided a platform to study the occurrence and size distributions of ultrafine particles in the marine boundary layer (MBL) during Arctic summer and autumn. Measurements of both aerosol physics, and gas/particulate chemistry were taken aboard the Swedish icebreaker Oden. Three separate submicron aerosol modes were found: an ultrafine mode (Dp < 20 nm), the Aitken mode (20 < Dp < 100 nm), and the accumulation mode (Dp > 100 nm). We evaluated correlations between ultrafine particle number concentrations and mean diameter with the entire measured physical, chemical, and meteorological data set. Multivariate statistical methods were then used to make these comparisons. A principal component (PC) analysis indicated that the observed variation in the data could be explained by the influence from several types of air masses. These were characterised by contributions from the open sea or sources from the surrounding continents and islands. A partial least square (PLS) regression of the ultrafine particle concentration was also used. These results implied that the ultrafine particles were produced above or in upper layers of the MBL and mixed downwards. There were also indications that the open sea acted as a source of the precursors for ultrafine particle production. No anti-correlation was found between the ultrafine and accumulation particle number concentrations, thus indicating that the sources were in separate air masses.

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.