Isolating and identifying atmospheric ice-nucleating aerosols: a new technique
ABSTRACT Laboratory studies examined two key aspects of the performance of a continuous-flow diffusion chamber (CFD) instrument that detects ice nuclei (IN) concentrations in air samples: separating IN from non-IN, and collecting IN aerosols to determine chemical composition. In the first study, submicron AgI IN particles were mixed in a sample stream with submicron non-IN salt particles, and the sample stream was processed in the CFD at −19°C and 23% supersaturation with respect to ice. Examination of the residual particles from crystals nucleated in the CFD confirmed that only AgI particles served as IN in the mixed stream. The second study applied this technique to separate and analyze IN and non-IN particles in a natural air sample. Energy-dispersive X-ray analyses (EDS) of the elemental composition of selected particles from the IN and non-IN fractions in ambient air showed chemical differences: Si and Ca were present in both, but S, Fe and K were also detected in the non-IN fraction.
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ABSTRACT: An overview is presented of airborne systems for in situ measurements of aerosol particles, clouds and radiation that are currently in use on research aircraft around the world. Description of the technology is at a level sufficient for introducing the basic principles of operation and an extensive list of references for further reading is given. A number of newer instruments that implement emerging technology are described and the review concludes with a description of some of the most important measurement challenges that remain. This overview is a synthesis of material from a reference book that is currently in preparation and that will be published in 2012 by Wiley.Atmospheric Research 01/2011; 102(2011):10-29. · 2.20 Impact Factor
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ABSTRACT: This paper presents airborne measurements of ice nuclei (IN) number concentration and elemental composition from the mixed-phase Arctic cloud experiment (M-PACE) in northern Alaska during October 2004. Although the project average IN concentration was low, less than 1 L−1 STP, there was significant spatial and temporal variability, with local maximum concentrations of nearly 60 L−1 STP. Immersion and/or condensation freezing appear to be the dominant freezing mechanisms, whereas mechanisms that occur below water saturation played a smaller role. The dominant particle types identified as IN were metal oxides/dust (39%), carbonaceous particles (35%) and mixtures of metal oxides/dust with either carbonaceous components or salts/sulphates (25%), although there was significant variability in elemental composition. Trajectory analysis suggests both local and remote sources, including biomass burning and volcanic ash. Seasonal variability of IN number concentrations based on this study and data from SHEBA/FIRE-ACE indicates that fall concentrations are depleted relative to spring by about a factor of five. Average IN number concentrations from both studies compare favorably with cloud ice number concentrations of cloud particles larger than 125 μm, for temperatures less than −10 °C. Cloud ice number concentrations also were enhanced in spring, by a factor of ∼2, but only over a limited temperature range.Tellus B 02/2009; 61(2):436 - 448. · 3.20 Impact Factor
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ABSTRACT: A new technique for the sampling of atmospheric ice nuclei is presented. Aerosols are electrostatically precipitated onto silicon discs, and are subsequently analyzed in a diffusion chamber. The method is compared to continuous flow chamber measurements and to membrane filter measurements of ice nuclei. Ice nucleus measurements obtained using this new method compare well to the continuous flow chamber measurements. In contrast, membrane filters were found to lead to serious underestimates of the ice nuclei number concentration when the filters were treated with a pore sealant and analyzed under vacuum. This confirms previous findings of other authors.The electrostatic aerosol collection device is lightweight and easy to handle.Atmospheric Research 01/2010; 96(2):218-224. · 2.20 Impact Factor