Search Results

Now showing 1 - 3 of 3
Loading...
Thumbnail Image
Item

The Ice Selective Inlet: A novel technique for exclusive extraction of pristine ice crystals in mixed-phase clouds

2015, Kupiszewski, P., Weingartner, E., Vochezer, P., Schnaiter, M., Bigi, A., Gysel, M., Rosati, B., Toprak, E., Mertes, S., Baltensperger, U.

Climate predictions are affected by high uncertainties partially due to an insufficient knowledge of aerosol–cloud interactions. One of the poorly understood processes is formation of mixed-phase clouds (MPCs) via heterogeneous ice nucleation. Field measurements of the atmospheric ice phase in MPCs are challenging due to the presence of much more numerous liquid droplets. The Ice Selective Inlet (ISI), presented in this paper, is a novel inlet designed to selectively sample pristine ice crystals in mixed-phase clouds and extract the ice residual particles contained within the crystals for physical and chemical characterization. Using a modular setup composed of a cyclone impactor, droplet evaporation unit and pumped counterflow virtual impactor (PCVI), the ISI segregates particles based on their inertia and phase, exclusively extracting small ice particles between 5 and 20 μm in diameter. The setup also includes optical particle spectrometers for analysis of the number size distribution and shape of the sampled hydrometeors. The novelty of the ISI is a droplet evaporation unit, which separates liquid droplets and ice crystals in the airborne state, thus avoiding physical impaction of the hydrometeors and limiting potential artefacts. The design and validation of the droplet evaporation unit is based on modelling studies of droplet evaporation rates and computational fluid dynamics simulations of gas and particle flows through the unit. Prior to deployment in the field, an inter-comparison of the optical particle size spectrometers and a characterization of the transmission efficiency of the PCVI was conducted in the laboratory. The ISI was subsequently deployed during the Cloud and Aerosol Characterization Experiment (CLACE) 2013 and 2014 – two extensive international field campaigns encompassing comprehensive measurements of cloud microphysics, as well as bulk aerosol, ice residual and ice nuclei properties. The campaigns provided an important opportunity for a proof of concept of the inlet design. In this work we present the setup of the ISI, including the modelling and laboratory characterization of its components, as well as field measurements demonstrating the ISI performance and validating the working principle of the inlet. Finally, measurements of biological aerosol during a Saharan dust event (SDE) are presented, showing a first indication of enrichment of bio-material in sub-2 μm ice residuals.

Loading...
Thumbnail Image
Item

On microphysical processes of noctilucent clouds (NLC): Observations and modeling of mean and width of the particle size-distribution

2010, Baumgarten, G., Fiedler, J., Rapp, M.

Noctilucent clouds (NLC) in the polar summer mesopause region have been observed in Norway (69° N, 16° E) between 1998 and 2009 by 3-color lidar technique. Assuming a mono-modal Gaussian size distribution we deduce mean and width of the particle sizes throughout the clouds. We observe a quasi linear relationship between distribution width and mean of the particle size at the top of the clouds and a deviation from this behavior for particle sizes larger than 40 nm, most often in the lower part of the layer. The vertically integrated particle properties show that 65% of the data follows the linear relationship with a slope of 0.42±0.02 for mean particle sizes up to 40 nm. For the vertically resolved particle properties (Δz = Combining double low line 0.15 km) the slope is comparable and about 0.39±0.03. For particles larger than 40 nm the distribution width becomes nearly independent of particle size and even decreases in the lower part of the layer. We compare our observations to microphysical modeling of noctilucent clouds and find that the distribution width depends on turbulence, the time that turbulence can act (cloud age), and the sampling volume/time (atmospheric variability). The model results nicely reproduce the measurements and show that the observed slope can be explained by eddy diffusion profiles as observed from rocket measurements. © 2010 Author(s).

Loading...
Thumbnail Image
Item

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.