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    Chemical composition and droplet size distribution of cloud at the summit of Mount Tai, China
    (Katlenburg-Lindau : EGU, 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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    Impact of water uptake and mixing state on submicron particle deposition in the human respiratory tract (HRT) based on explicit hygroscopicity measurements at HRT-like conditions
    (Katlenburg-Lindau : EGU, 2022) Man, Ruiqi; Wu, Zhijun; Zong, Taomou; Voliotis, Aristeidis; Qiu, Yanting; Größ, Johannes; van Pinxteren, Dominik; Zeng, Limin; Herrmann, Hartmut; Wiedensohler, Alfred; Hu, Min
    Particle hygroscopicity plays a key role in determining the particle deposition in the human respiratory tract (HRT). In this study, the effects of hygroscopicity and mixing state on regional and total deposition doses on the basis of the particle number concentration for children, adults, and the elderly were quantified using the Multiple-Path Particle Dosimetry model, based on the size-resolved particle hygroscopicity measurements at HRT-like conditions (relative humidity = 98 %) performed in the North China Plain. The measured particle population with an external mixing state was dominated by hygroscopic particles (number fraction = (91.5 ± 5.7) %, mean ± standard deviation (SD); the same below). Particle hygroscopic growth in the HRT led to a reduction by around 24 % in the total doses of submicron particles for all age groups. Such a reduction was mainly caused by the growth of hygroscopic particles and was more pronounced in the pulmonary and tracheobronchial regions. Regardless of hygroscopicity, the elderly group of people had the highest total dose among three age groups, while children received the maximum total deposition rate. With 270 nm in diameter as the boundary, the total deposition doses of particles smaller than this diameter were overestimated, and those of larger particles were underestimated, assuming no particle hygroscopic growth in the HRT. From the perspective of the daily variation, the deposition rates of hygroscopic particles with an average of (2.88 ± 0.81) × 109 particles h-1 during the daytime were larger than those at night ((2.32 ± 0.24) × 109 particles h-1). On the contrary, hydrophobic particles interpreted as freshly emitted soot and primary organic aerosols exhibited higher deposition rates at nighttime ((3.39 ± 1.34) × 108 particles h-1) than those in the day ((2.58 ± 0.76) × 108 particles h-1). The traffic emissions during the rush hours enhanced the deposition rate of hydrophobic particles. This work provides a more explicit assessment of the impact of hygroscopicity and mixing state on the deposition pattern of submicron particles in the HRT. Copyright:
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    Cloud water composition during HCCT-2010: Scavenging efficiencies, solute concentrations, and droplet size dependence of inorganic ions and dissolved organic carbon
    (München : European Geopyhsical Union, 2016) van Pinxteren, Dominik; Fomba, Khanneh Wadinga; Mertes, Stephan; Müller, Konrad; Spindler, Gerald; Schneider, Johannes; Lee, Taehyoung; Collett, Jeffrey L.; Herrmann, Hartmut
    Cloud water samples were taken in September/October 2010 at Mt. Schmücke in a rural, forested area in Germany during the Lagrange-type Hill Cap Cloud Thuringia 2010 (HCCT-2010) cloud experiment. Besides bulk collectors, a three-stage and a five-stage collector were applied and samples were analysed for inorganic ions (SO42−,NO3−, NH4+, Cl−, Na+, Mg2+, Ca2+, K+), H2O2 (aq), S(IV), and dissolved organic carbon (DOC). Campaign volume-weighted mean concentrations were 191, 142, and 39 µmol L−1 for ammonium, nitrate, and sulfate respectively, between 4 and 27 µmol L−1 for minor ions, 5.4 µmol L−1 for H2O2 (aq), 1.9 µmol L−1 for S(IV), and 3.9 mgC L−1 for DOC. The concentrations compare well to more recent European cloud water data from similar sites. On a mass basis, organic material (as DOC × 1.8) contributed 20–40 % (event means) to total solute concentrations and was found to have non-negligible impact on cloud water acidity. Relative standard deviations of major ions were 60–66 % for solute concentrations and 52–80 % for cloud water loadings (CWLs). The similar variability of solute concentrations and CWLs together with the results of back-trajectory analysis and principal component analysis, suggests that concentrations in incoming air masses (i.e. air mass history), rather than cloud liquid water content (LWC), were the main factor controlling bulk solute concentrations for the cloud studied. Droplet effective radius was found to be a somewhat better predictor for cloud water total ionic content (TIC) than LWC, even though no single explanatory variable can fully describe TIC (or solute concentration) variations in a simple functional relation due to the complex processes involved. Bulk concentrations typically agreed within a factor of 2 with co-located measurements of residual particle concentrations sampled by a counterflow virtual impactor (CVI) and analysed by an aerosol mass spectrometer (AMS), with the deviations being mainly caused by systematic differences and limitations of the approaches (such as outgassing of dissolved gases during residual particle sampling). Scavenging efficiencies (SEs) of aerosol constituents were 0.56–0.94, 0.79–0.99, 0.71–98, and 0.67–0.92 for SO42−, NO3−, NH4+, and DOC respectively when calculated as event means with in-cloud data only. SEs estimated using data from an upwind site were substantially different in many cases, revealing the impact of gas-phase uptake (for volatile constituents) and mass losses across Mt. Schmücke likely due to physical processes such as droplet scavenging by trees and/or entrainment. Drop size-resolved cloud water concentrations of major ions SO42−, NO3−, and NH4+ revealed two main profiles: decreasing concentrations with increasing droplet size and “U” shapes. In contrast, profiles of typical coarse particle mode minor ions were often increasing with increasing drop size, highlighting the importance of a species' particle concentration size distribution for the development of size-resolved solute concentration patterns. Concentration differences between droplet size classes were typically < 2 for major ions from the three-stage collector and somewhat more pronounced from the five-stage collector, while they were much larger for minor ions. Due to a better separation of droplet populations, the five-stage collector was capable of resolving some features of solute size dependencies not seen in the three-stage data, especially sharp concentration increases (up to a factor of 5–10) in the smallest droplets for many solutes.
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    The evolution of cloud and aerosol microphysics at the summit of Mt. Tai, China
    (Katlenburg-Lindau : EGU, 2020) Li, Jiarong; Zhu, Chao; Chen, Hui; Zhao, Defeng; Xue, Likun; Wang, Xinfeng; Li, Hongyong; Liu, Pengfei; Liu, Junfeng; Zhang, Chenglong; Mu, Yujing; Zhang, Wenjin; Zhang, Luming; Herrmann, Hartmut; Li, Kai; Liu, Min; Chen, Jianmin
    The influence of aerosols, both natural and anthropogenic, remains a major area of uncertainty when predicting the properties and the behaviours of clouds and their influence on climate. In an attempt to better understand the microphysical properties of cloud droplets, the simultaneous variations in aerosol microphysics and their potential interactions during cloud life cycles in the North China Plain, an intensive observation took place from 17 June to 30 July 2018 at the summit of Mt. Tai. Cloud microphysical parameters were monitored simultaneously with number concentrations of cloud condensation nuclei (NCCN) at different supersaturations, PM2:5 mass concentrations, particle size distributions and meteorological parameters. Number concentrations of cloud droplets (NC), liquid water content (LWC) and effective radius of cloud droplets (reff) show large variations among 40 cloud events observed during the campaign. The low values of reff and LWC observed at Mt. Tai are comparable with urban fog. Clouds on clean days are more susceptible to the change in concentrations of particle number (NP), while clouds formed on polluted days might be more sensitive to meteorological parameters, such as updraft velocity and cloud base height. Through studying the size distributions of aerosol particles and cloud droplets, we find that particles larger than 150 nm play important roles in forming cloud droplets with the size of 5-10 μm. In general, LWC consistently varies with reff. As NC increases, reff changes from a trimodal distribution to a unimodal distribution and shifts to smaller size mode. By assuming a constant cloud thickness and ignoring any lifetime effects, increase in NC and decrease in reff would increase cloud albedo, which may induce a cooling effect on the local climate system. Our results contribute valuable information to enhance the understanding of cloud and aerosol properties, along with their potential interactions on the North China plain. © Author(s) 2020.
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    Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories
    (Katlenburg-Lindau : EGU, 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.