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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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The evolution of cloud and aerosol microphysics at the summit of Mt. Tai, China

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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The acidity of atmospheric particles and clouds

2020, Pye, Havala O.T., Nenes, Athanasios, Alexander, Becky, Ault, Andrew P., Barth, Mary C., Clegg, Simon L., Collett Jr, Jeffrey L., Fahey, Kathleen M., Hennigan, Christopher J., Herrmann, Hartmut, Kanakidou, Maria, Kelly, James T., Ku, I-Ting, McNeill, V. Faye, Riemer, Nicole, Schaefer, Thomas, Shi, Guoliang, Tilgner, Andreas, Walker, John T., Wang, Tao, Weber, Rodney, Xing, Jia, Zaveri, Rahul A., Zuend, Andreas

Acidity, defined as pH, is a central component of aqueous chemistry. In the atmosphere, the acidity of condensed phases (aerosol particles, cloud water, and fog droplets) governs the phase partitioning of semivolatile gases such as HNO3, NH3, HCl, and organic acids and bases as well as chemical reaction rates. It has implications for the atmospheric lifetime of pollutants, deposition, and human health. Despite its fundamental role in atmospheric processes, only recently has this field seen a growth in the number of studies on particle acidity. Even with this growth, many fine-particle pH estimates must be based on thermodynamic model calculations since no operational techniques exist for direct measurements. Current information indicates acidic fine particles are ubiquitous, but observationally constrained pH estimates are limited in spatial and temporal coverage. Clouds and fogs are also generally acidic, but to a lesser degree than particles, and have a range of pH that is quite sensitive to anthropogenic emissions of sulfur and nitrogen oxides, as well as ambient ammonia. Historical measurements indicate that cloud and fog droplet pH has changed in recent decades in response to controls on anthropogenic emissions, while the limited trend data for aerosol particles indicate acidity may be relatively constant due to the semivolatile nature of the key acids and bases and buffering in particles. This paper reviews and synthesizes the current state of knowledge on the acidity of atmospheric condensed phases, specifically particles and cloud droplets. It includes recommendations for estimating acidity and pH, standard nomenclature, a synthesis of current pH estimates based on observations, and new model calculations on the local and global scale. © 2020 Author(s).

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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

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.