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Intercomparison of 15 aerodynamic particle size spectrometers (APS 3321): Uncertainties in particle sizing and number size distribution
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.
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.