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Chemical composition and droplet size distribution of cloud at the summit of Mount Tai, China

2017, Li, Jiarong, Wang, Xinfeng, Chen, Jianmin, Zhu, Chao, Li, Weijun, Li, Chengbao, Liu, Lu, Xu, Caihong, Wen, Liang, Xue, Likun, Wang, Wenxing, Ding, Aijun, Herrmann, Hartmut

The chemical composition of 39 cloud samples and droplet size distributions in 24 cloud events were investigated at the summit of Mt. Tai from July to October 2014. Inorganic ions, organic acids, metals, HCHO, H2O2, sulfur( IV), organic carbon, and elemental carbon as well as pH and electrical conductivity were analyzed. The acidity of the cloud water significantly decreased from a reported value of pH 3.86 during 2007-2008 (Guo et al., 2012) to pH 5.87 in the present study. The concentrations of nitrate and ammonium were both increased since 2007-2008, but the overcompensation of ammonium led to an increase in the mean pH value. The microphysical properties showed that cloud droplets were smaller than 26.0 μm and most were in the range of 6.0-9.0 μm at Mt. Tai. The maximum droplet number concentration (Nd) was associated with a droplet size of 7.0 μm. High liquid water content (LWC) values could facilitate the formation of larger cloud droplets and broadened the droplet size distribution. Cloud droplets exhibited a strong interaction with atmospheric aerosols. Higher PM2.5 levels resulted in higher concentrations of water-soluble ions and smaller sizes with increased numbers of cloud droplets. The lower pH values were likely to occur at higher PM2.5 concentrations. Clouds were an important sink for soluble materials in the atmosphere. The dilution effect of cloud water should be considered when estimating concentrations of soluble components in the cloud phase.

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Contributions of transported Prudhoe Bay oil field emissions to the aerosol population in Utqiaġvik, Alaska

2017, Gunsch, Matthew J., Kirpes, Rachel M., Kolesar, Katheryn R., Barrett, Tate E., China, Swarup, Sheesley, Rebecca J., Laskin, Alexander, Wiedensohler, Alfred, Tuch, Thomas, Pratt, Kerri A.

Loss of sea ice is opening the Arctic to increasing development involving oil and gas extraction and shipping. Given the significant impacts of absorbing aerosol and secondary aerosol precursors emitted within the rapidly warming Arctic region, it is necessary to characterize local anthropogenic aerosol sources and compare to natural conditions. From August to September 2015 in Utqiaġvik (Barrow), AK, the chemical composition of individual atmospheric particles was measured by computer-controlled scanning electron microscopy with energy-dispersive X-ray spectroscopy (0.13-4 μm projected area diameter) and real-time single-particle mass spectrometry (0.2-1.5 μm vacuum aerodynamic diameter). During periods influenced by the Arctic Ocean (70 % of the study), our results show that fresh sea spray aerosol contributed ∼ 20 %, by number, of particles between 0.13 and 0.4 μm, 40-70 % between 0.4 and 1 μm, and 80-100 % between 1 and 4 μm particles. In contrast, for periods influenced by emissions from Prudhoe Bay (10 % of the study), the third largest oil field in North America, there was a strong influence from submicron (0.13-1 μm) combustion-derived particles (20-50 % organic carbon, by number; 5-10 % soot by number). While sea spray aerosol still comprised a large fraction of particles (90 % by number from 1 to 4 μm) detected under Prudhoe Bay influence, these particles were internally mixed with sulfate and nitrate indicative of aging processes during transport. In addition, the overall mode of the particle size number distribution shifted from 76 nm during Arctic Ocean influence to 27 nm during Prudhoe Bay influence, with particle concentrations increasing from 130 to 920 cm-3 due to transported particle emissions from the oil fields. The increased contributions of carbonaceous combustion products and partially aged sea spray aerosol should be considered in future Arctic atmospheric composition and climate simulations.

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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.