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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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Regional modelling of polycyclic aromatic hydrocarbons: WRF-Chem-PAH model development and East Asia case studies

2017, Mu, Qing, Lammel, Gerhard, Gencarelli, Christian N., Hedgecock, Ian M., Chen, Ying, Přibylová, Petra, Teich, Monique, Zhang, Yuxuan, Zheng, Guangjie, van Pinxteren, Dominik, Zhang, Qiang, Herrmann, Hartmut, Shiraiwa, Manabu, Spichtinger, Peter, Su, Hang, Pöschl, Ulrich, Cheng, Yafang

Polycyclic aromatic hydrocarbons (PAHs) are hazardous pollutants, with increasing emissions in pace with economic development in East Asia, but their distribution and fate in the atmosphere are not yet well understood. We extended the regional atmospheric chemistry model WRF-Chem (Weather Research Forecast model with Chemistry module) to comprehensively study the atmospheric distribution and the fate of low-concentration, slowly degrading semivolatile compounds. The WRF-Chem-PAH model reflects the state-of-the-art understanding of current PAHs studies with several new or updated features. It was applied for PAHs covering a wide range of volatility and hydrophobicity, i.e. phenanthrene, chrysene and benzo[a]pyrene, in East Asia. Temporally highly resolved PAH concentrations and particulate mass fractions were evaluated against observations. The WRF-Chem-PAH model is able to reasonably well simulate the concentration levels and particulate mass fractions of PAHs near the sources and at a remote outflow region of East Asia, in high spatial and temporal resolutions. Sensitivity study shows that the heterogeneous reaction with ozone and the homogeneous reaction with the nitrate radical significantly influence the fate and distributions of PAHs. The methods to implement new species and to correct the transport problems can be applied to other newly implemented species in WRF-Chem.

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Perspectives on the future of ice nucleation research: Research needs and Unanswered questions identified from two international workshops

2017, Coluzza, Ivan, Creamean, Jessie, Rossi, Michel J., Wex, Heike, Alpert, Peter Aaron, Bianco, Valentino, Boose, Yvonne, Dellago, Christoph, Felgitsch, Laura, Fröhlich-Nowoisky, Janine, Herrmann, Hartmut, Jungblut, Swetlana, Kanji, Zamin A., Menzl, Georg, Moffett, Bruce, Moritz, Clemens, Mutzel, Anke, Pöschl, Ulrich, Schauperl, Michael, Scheel, Jan, Stopelli, Emiliano, Stratmann, Frank, Grothe, Hinrich, Schmale, David G.

There has been increasing interest in ice nucleation research in the last decade. To identify important gaps in our knowledge of ice nucleation processes and their impacts, two international workshops on ice nucleation were held in Vienna, Austria in 2015 and 2016. Experts from these workshops identified the following research needs: (1) uncovering the molecular identity of active sites for ice nucleation; (2) the importance of modeling for the understanding of heterogeneous ice nucleation; (3) identifying and quantifying contributions of biological ice nuclei from natural and managed environments; (4) examining the role of aging in ice nuclei; (5) conducting targeted sampling campaigns in clouds; and (6) designing lab and field experiments to increase our understanding of the role of ice-nucleating particles in the atmosphere. Interdisciplinary teams of scientists should work together to establish and maintain a common, unified language for ice nucleation research. A number of commercial applications benefit from ice nucleation research, including the production of artificial snow, the freezing and preservation of water-containing food products, and the potential modulation of weather. Additional work is needed to increase our understanding of ice nucleation processes and potential impacts on precipitation, water availability, climate change, crop health, and feedback cycles.