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Cloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China – Part 2: Size-resolved aerosol chemical composition, diurnal cycles, and externally mixed weakly CCN-active soot particles
2011, Rose, D., Gunthe, S.S., Su, H., Garland, R.M., Yang, H., Berghof, M., Cheng, Y.F., Wehner, B., Achtert, P., Nowak, A., Wiedensohler, A., Takegawa, N., Kondo, Y., Hu, M., Zhang, Y., Andreae, M.O., Pöschl, U.
Size-resolved chemical composition, mixing state, and cloud condensation nucleus (CCN) activity of aerosol particles in polluted mega-city air and biomass burning smoke were measured during the PRIDE-PRD2006 campaign near Guangzhou, China, using an aerosol mass spectrometer (AMS), a volatility tandem differential mobility analyzer (VTDMA), and a continuous-flow CCN counter (DMT-CCNC). The size-dependence and temporal variations of the effective average hygroscopicity parameter for CCN-active particles (κa) could be parameterized as a function of organic and inorganic mass fractions (forg, finorg) determined by the AMS: κa,p=κorg·forg + κinorg·finorg. The characteristic κ values of organic and inorganic components were similar to those observed in other continental regions of the world: κorg≈0.1 and κinorg≈0.6. The campaign average κa values increased with particle size from ~0.25 at ~50 nm to ~0.4 at ~200 nm, while forg decreased with particle size. At ~50 nm, forg was on average 60% and increased to almost 100% during a biomass burning event. The VTDMA results and complementary aerosol optical data suggest that the large fractions of CCN-inactive particles observed at low supersaturations (up to 60% at S≤0.27%) were externally mixed weakly CCN-active soot particles with low volatility (diameter reduction <5% at 300 °C) and effective hygroscopicity parameters around κLV≈0.01. A proxy for the effective average hygroscopicity of the total ensemble of CCN-active particles including weakly CCN-active particles (κt) could be parameterized as a function of κa,p and the number fraction of low volatility particles determined by VTDMA (φLV): κt,p=κa,p−φLV·(κa,p−κLV). Based on κ values derived from AMS and VTDMA data, the observed CCN number concentrations (NCCN,S≈102–104 cm−3 at S = 0.068–0.47%) could be efficiently predicted from the measured particle number size distribution. The mean relative deviations between observed and predicted CCN concentrations were ~10% when using κt,p, and they increased to ~20% when using only κa,p. The mean relative deviations were not higher (~20%) when using an approximate continental average value of κ≈0.3, although the constant κ value cannot account for the observed temporal variations in particle composition and mixing state (diurnal cycles and biomass burning events). Overall, the results confirm that on a global and climate modeling scale an average value of κ≈0.3 can be used for approximate predictions of CCN number concentrations in continental boundary layer air when aerosol size distribution data are available without information about chemical composition. Bulk or size-resolved data on aerosol chemical composition enable improved CCN predictions resolving regional and temporal variations, but the composition data need to be highly accurate and complemented by information about particle mixing state to achieve high precision (relative deviations <20%).
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.