Numerical simulation of flow, H2SO4 cycle and new particle formation in the CERN CLOUD chamber

To study the effect of galactic cosmic rays on aerosols and clouds, the Cosmic Leaving OUtdoor Droplets (CLOUD) project was established. Experiments are carried out at a 26 m3 tank at CERN (Switzerland). In the experiments, the effect of ionising particle radiation on H2SO4 particle formation and growth is investigated. To evaluate the experimental configuration, the experiment was simulated using a coupled multidimensional CFD – particle model (CLOUD-FPM). In the model the coupled fields of gas/vapour species, temperature, flow velocity and particle properties were computed to investigate the tank's mixing state and mixing times. Simulation results show that the mixing state of the tank's contents largely depends on the characteristics of the mixing fans and a 1-fan configuration, as used in first experiments, may not be sufficient to ensure a homogeneously mixed chamber. To mix the tank properly, 2 fans are necessary. The 1/e response times for instantaneous changes of wall temperature and saturation ratio inside the chamber were found to be in the order of few minutes. Particle nucleation and growth was also simulated and particle number size distribution properties of the freshly nucleated particles (particle number, mean size, standard deviation of the assumed log-normal distribution) were found to be mixed over the tank's volume similar to the gas species

Numerical simulations of mixing conditions and aerosol dynamics in the CERN CLOUD chamber

To study the effect of galactic cosmic rays on aerosols and clouds, the Cosmics Leaving OUtdoor Droplets (CLOUD) project was established. Experiments are carried out at a 26.1 m3 tank at CERN (Switzerland). In the experiments, the effect of ionizing radiation on H2SO4 particle formation and growth is investigated. To evaluate the experimental configuration, the experiment was simulated using a coupled multidimensional computational fluid dynamics (CFD) – particle model. In the model the coupled fields of gas/vapor species, temperature, flow velocity and particle properties were computed to investigate mixing state and mixing times of the CLOUD tank's contents. Simulation results show that a 1-fan configuration, as used in first experiments, may not be sufficient to ensure a homogeneously mixed chamber. To mix the tank properly, two fans and sufficiently high fan speeds are necessary. The 1/e response times for instantaneous changes of wall temperature and saturation ratio were found to be in the order of few minutes. Particle nucleation and growth was also simulated and particle number size distribution properties of the freshly nucleated particles (particle number, mean size, standard deviation of the assumed log-normal distribution) were found to be distributed over the tank's volume similar to the gas species

Global Analysis of Fragmentation Functions for Eta Mesons

Fragmentation functions for eta mesons are extracted at next-to-leading order accuracy of QCD in a global analysis of data taken in electron-positron annihilation and proton-proton scattering experiments. The obtained parametrization is in good agreement with all data sets analyzed and can be utilized, for instance, in future studies of double-spin asymmetries for single-inclusive eta production. The Lagrange multiplier technique is used to estimate the uncertainties of the fragmentation functions and to assess the role of the different data sets in constraining them.Comment: 11 pages, 8 figures, updated reference

Understanding aerosol microphysical properties from 10 years of data collected at Cabo Verde based on an unsupervised machine learning classification

The Cape Verde Atmospheric Observatory (CVAO), which is influenced by both marine and desert dust air masses, has been used for long-term measurements of different properties of the atmospheric aerosol from 2008 to 2017. These properties include particle number size distributions (PNSD), light-absorbing carbon (LAC) and concentrations of cloud condensation nuclei (CCN) together with their hygroscopicity. Here we summarize the results obtained for these properties and use an unsupervised machine learning algorithm for the classification of aerosol types. Five types of aerosols, i.e., marine, freshly formed, mixture, moderate dust and heavy dust, were classified. Air masses during marine periods are from the Atlantic Ocean and during dust periods are from the Sahara Desert. Heavy dust was more frequently present during wintertime, whereas the clean marine periods were more frequently present during springtime. It was observed that during the dust periods CCN number concentrations at a supersaturation of 0.30g% were roughly 2.5 times higher than during marine periods, but the hygroscopicity (κ) of particles in the size range from g1/4g30 to g1/4g175gnm during marine and dust periods were comparable. The long-term data presented here, together with the aerosol classification, can be used as a basis to improve our understanding of annual cycles of the atmospheric aerosol in the eastern tropical Atlantic Ocean and on aerosol-cloud interactions and it can be used as a basis for driving, evaluating and constraining atmospheric model simulations

Characterization and first results from LACIS-T : a moist-air wind tunnel to study aerosol–cloud–turbulence interactions

The interactions between turbulence and cloud microphysical processes have been investigated primarily through numerical simulation and field measurements over the last 10 years. However, only in the laboratory we can be confident in our knowledge of initial and boundary conditions and are able to measure under statistically stationary and repeatable conditions. In the scope of this paper, we present a unique turbulent moist-air wind tunnel, called the Turbulent Leipzig Aerosol Cloud Interaction Simulator (LACIS-T) which has been developed at TROPOS in order to study cloud physical processes in general and interactions between turbulence and cloud microphysical processes in particular. The investigations take place under well-defined and reproducible turbulent and thermodynamic conditions covering the temperature range of warm, mixed-phase and cold clouds (25∘C>T>−40∘C ). The continuous-flow design of the facility allows for the investigation of processes occurring on small temporal (up to a few seconds) and spatial scales (micrometer to meter scale) and with a Lagrangian perspective. The here-presented experimental studies using LACIS-T are accompanied and complemented by computational fluid dynamics (CFD) simulations which help us to design experiments as well as to interpret experimental results. In this paper, we will present the fundamental operating principle of LACIS-T, the numerical model, and results concerning the thermodynamic and flow conditions prevailing inside the wind tunnel, combining both characterization measurements and numerical simulations. Finally, the first results are depicted from deliquescence and hygroscopic growth as well as droplet activation and growth experiments. We observe clear indications of the effect of turbulence on the investigated microphysical processes

Characterization and first results from LACIS-T: a moist-air wind tunnel to study aerosol-cloud-turbulence interactions

The interactions between turbulence and cloud microphysical processes have been investigated primarily through numerical simulation and field measurements over the last 10 years. However, only in the laboratory we can be confident in our knowledge of initial and boundary conditions and are able to measure under statistically stationary and repeatable conditions. In the scope of this paper, we present a unique turbulent moist-air wind tunnel, called the Turbulent Leipzig Aerosol Cloud Interaction Simulator (LACIS-T) which has been developed at TROPOS in order to study cloud physical processes in general and interactions between turbulence and cloud microphysical processes in particular. The investigations take place under well-defined and reproducible turbulent and thermodynamic conditions covering the temperature range of warm, mixed-phase and cold clouds (25 °C > T > −40 °C). The continuous-flow design of the facility allows for the investigation of processes occurring on small temporal (up to a few seconds) and spatial scales (micrometer to meter scale) and with a Lagrangian perspective. The here-presented experimental studies using LACIS-T are accompanied and complemented by computational fluid dynamics (CFD) simulations which help us to design experiments as well as to interpret experimental results. In this paper, we will present the fundamental operating principle of LACIS-T, the numerical model, and results concerning the thermodynamic and flow conditions prevailing inside the wind tunnel, combining both characterization measurements and numerical simulations. Finally, the first results are depicted from deliquescence and hygroscopic growth as well as droplet activation and growth experiments. We observe clear indications of the effect of turbulence on the investigated microphysical processes

Determination of highly polar compounds in atmospheric aerosol particles at ultra-trace levels using ion chromatography Orbitrap mass spectrometry

A method using ion chromatography coupled to high-resolution Orbitrap mass spectrometry was developed to quantify highly-polar organic compounds in aqueous filter extracts of atmospheric particles. In total, 43 compounds, including short-chain carboxylic acids, terpene-derived acids, organosulfates, and inorganic anions were separated within 33 min by a KOH gradient. Ionization by electrospray was maximized by adding 100 µL min−1 isopropanol as post-column solvent and optimizing the ion source settings. Detection limits (S/N ≥ 3) were in the range of 0.075–25 μg L−1 and better than previously reported for 22 compounds. Recoveries of extraction typically range from 85 to 117%. The developed method was applied to three ambient samples, including two arctic flight samples, and one sample from Melpitz, a continental backround research site. A total of 32 different compounds were identified for all samples. From the arctic flight samples, organic tracers could be quantified for the first time with concentrations ranging from 0.1 to 17.8 ng m−3. Due to the minimal sample preparation, the beneficial figures of merit, and the broad range of accessible compounds, including very polar ones, the new method offers advantages over existing ones and enables a detailed analysis of organic marker compounds in atmospheric aerosol particles

Ice Nucleating Particles in Northern Greenland: annual cycles, biological contribution and parameterizations

Ice nucleating particles (INPs) can initiate ice formation in clouds at temperatures above &minus;38 &deg;C through heterogeneous ice nucleation. As a result, INPs affect cloud microphysical and radiative properties, cloud life time and precipitation behavior and thereby ultimately the Earth&rsquo;s climate. Yet, little is known regarding the sources, abundance and properties of INPs especially in remote regions such as the Arctic. In this study, two-year-long INP measurements (from July 2018 to September 2020) at Villum 5 Research Station (VRS) in Northern Greenland are presented. A low-volume filter sampler was deployed to collect filter samples for off-line INP analysis. An annual cycle of INP concentration (NINP) was observed and the fraction of biogenic INPs was found to be higher in snow-free months and lower in months when the surface was snow-covered. Samples were categorized into three different types based only on the slope of their INP spectra, namely into summer, winter and mix type. For each of the types a temperature dependent INP parameterization was derived, clearly different depending on the time 10 of the year. Winter and summer type occurred only during their respective seasons and were seen 60 % of the time. The mixed type occurred in the remaining 40 % of the time throughout the year. April, May and November were found to be transition months. A case study comparing April 2019 and April 2020 was performed. The month of April was selected because a significant difference in NINP was observed during these two periods, with clearly higher NINP in April 2020. NINP in the case study period revealed no clear dependency on either meteorological parameters or different surface types which were passed 15 by the collected air masses. Overall, the results suggest that the coastal regions of Greenland were main sources of INPs in April 2019 and 2020, most likely including both local terrestrial and marine sources. In parallel to the observed differences in NINP, also a higher cloud ice fraction was observed in satellite data for April 2020, compared to April 2019.</p

The immersion freezing behavior of ash particles from wood and brown coal burning

It is generally known that ash particles from coal combustion can trigger ice nucleation when they interact with water vapor and/or supercooled droplets. However, data on the ice nucleation of ash particles from different sources, including both anthropogenic and natural combustion processes, are still scarce. As fossil energy sources still fuel the largest proportion of electric power production worldwide, and biomass burning contributes significantly to the global aerosol loading, further data are needed to better assess the ice nucleating efficiency of ash particles. In the framework of this study, we found that ash particles from brown coal (i.e., lignite) burning are up to 2 orders of magnitude more ice active in the immersion mode below −32 °C than those from wood burning. Fly ash from a coal-fired power plant was shown to be the most efficient at nucleating ice. Furthermore, the influence of various particle generation methods on the freezing behavior was studied. For instance, particles were generated either by dispersion of dry sample material, or by atomization of ash–water suspensions, and then led into the Leipzig Aerosol Cloud Interaction Simulator (LACIS) where the immersion freezing behavior was examined. Whereas the immersion freezing behavior of ashes from wood burning was not affected by the particle generation method, it depended on the type of particle generation for ash from brown coal. It was also found that the common practice of treating prepared suspensions in an ultrasonic bath to avoid aggregation of particles led to an enhanced ice nucleation activity. The findings of this study suggest (a) that ash from brown coal burning may influence immersion freezing in clouds close to the source and (b) that the freezing behavior of ash particles may be altered by a change in sample preparation and/or particle generation

Optimizing the detection, ablation, and ion extraction efficiency of a single-particle laser ablation mass spectrometer for application in environments with low aerosol particle concentrations

The aim of this study is to show how a newly developed aerodynamic lens system (ALS), a delayed ion extraction (DIE), and better electric shielding improve the efficiency of the Aircraft-based Laser ABlation Aerosol MAss spectrometer (ALABAMA). These improvements are applicable to single-particle laser ablation mass spectrometers in general. To characterize the modifications, extensive sizeresolved measurements with spherical polystyrene latex particles (PSL; 150-6000 nm) and cubic sodium chloride particles (NaCl; 400-1700 nm) were performed. Measurements at a fixed ALS position show an improved detectable particle size range of the new ALS compared to the previously used Liu-type ALS, especially for supermicron particles. At a lens pressure of 2.4 hPa, the new ALS achieves a PSL particle size range from 230 to 3240 nm with 50% detection efficiency and between 350 and 2000 nm with 95% detection efficiency. The particle beam divergence was determined by measuring the detection efficiency at variable ALS positions along the laser cross sections and found to be minimal for PSL at about 800 nm. Compared to measurements by singleparticle mass spectrometry (SPMS) instruments using Liutype ALSs, the minimum particle beam divergence is shifted towards larger particle sizes. However, there are no disadvantages compared to the Liu-type lenses for particle sizes down to 200 nm. Improvements achieved by using the DIE and an additional electric shielding could be evaluated by size-resolved measurements of the hit rate, which is the ratio of laser pulses yielding a detectable amount of ions to the total number of emitted laser pulses. In particular, the hit rate for multiply charged particles smaller than 500 nm is significantly improved by preventing an undesired deflection of these particles in the ion extraction field. Moreover, it was found that by using the DIE the ion yield of the ablation, ionization, and ion extraction process could be increased, resulting in up to 7 times higher signal intensities of the cation spectra. The enhanced ion yield results in a larger effective width of the ablation laser beam, which in turn leads to a hit rate of almost 100% for PSL particles in the size range from 350 to 2000 nm. Regarding cubic NaCl particles the modifications of the ALABAMA result in an up to 2 times increased detection efficiency and an up to 5 times increased hit rate. The need for such instrument modifications arises in particular for measurements of particles that are present in low number concentrations such as ice-nucleating particles (INPs) in general, but also aerosol particles at high altitudes or in pristine environments. Especially for these low particle number concentrations, improved efficiencies help to overcome the statistical limitations of single-particle mass spectrometer measurements. As an example, laboratory INP measurements carried out in this study show that the appli- cation of the DIE alone increases the number of INP mass spectra per time unit by a factor of 2 to 3 for the sampled substances. Overall, the combination of instrument modifications presented here resulted in an increased measurement efficiency of the ALABAMA for different particle types and particles shape as well as for highly charged particles. © 2020 Copernicus GmbH. All rights reserved