Using depolarization to quantify ice nucleating particle concentrations: a new method

Zenker, J. Thomas; Collier, Kristen N.; Xu, Guanglang; Yang, Ping; Levin, Ezra J. T.; Suski, Kaitlyn J.; DeMott, Paul J.; Brooks, Sarah D.

doi:10.5194/amt-10-4639-2017

Cited by 13 publications

(8 citation statements)

References 70 publications

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“…The most common method used for phase discrimination in continuous flow chambers is to selectively shrink activated liquid droplets to accentuate ice crystals by their larger optical size. Some instruments use laser light depolarization for phase discrimination, but this is typically a suitable method only for higher signal-to-noise situations and ice active fractions that exceed several percent of particles (Nicolet et al, 2010;Garimella et al, 2016;Zenker et al, 2017). For these reasons, all such devices in FIN-02 include an "evaporation" section as a shorter column length below their growth sections, where the RH w is lowered toward ice saturation conditions by setting the two wall temperatures to be equivalent at either the warmest wall, coldest wall, or lamina temperature in the growth sections (see Supplement).…”

Section: Direct Sampling Systemsmentioning

confidence: 99%

The Fifth International Workshop on Ice Nucleation phase 2 (FIN-02): laboratory intercomparison of ice nucleation measurements

et al. 2018

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Abstract. The second phase of the Fifth International Ice Nucleation Workshop (FIN-02) involved the gathering of a large number of researchers at the Karlsruhe Institute of Technology's Aerosol Interactions and Dynamics of the Atmosphere (AIDA) facility to promote characterization and understanding of ice nucleation measurements made by a variety of methods used worldwide. Compared to the previous workshop in 2007, participation was doubled, reflecting a vibrant research area. Experimental methods involved sampling of aerosol particles by direct processing ice nucleation measuring systems from the same volume of air in separate experiments using different ice nucleating particle (INP) types, and collections of aerosol particle samples onto filters or into liquid for sharing amongst measurement techniques that post-process these samples. In this manner, any errors introduced by differences in generation methods when samples are shared across laboratories were mitigated. Furthermore, as much as possible, aerosol particle size distribution was controlled so that the size limitations of different methods were minimized. The results presented here use data from the workshop to assess the comparability of immersion freezing measurement methods activating INPs in bulk suspensions, methods that activate INPs in condensation and/or immersion freezing modes as single particles on a substrate, continuous flow diffusion chambers (CFDCs) directly sampling and processing particles well above water saturation to maximize immersion and subsequent freezing of aerosol particles, and expansion cloud chamber simulations in which liquid cloud droplets were first activated on aerosol particles prior to freezing. The AIDA expansion chamber measurements are expected to be the closest representation to INP activation in atmospheric cloud parcels in these comparisons, due to exposing particles freely to adiabatic cooling. The different particle types used as INPs included the minerals illite NX and potassium feldspar (K-feldspar), two natural soil dusts representative of arable sandy loam (Argentina) and highly erodible sandy dryland (Tunisia) soils, respectively, and a bacterial INP (Snomax®). Considered together, the agreement among post-processed immersion freezing measurements of the numbers and fractions of particles active at different temperatures following bulk collection of particles into liquid was excellent, with possible temperature uncertainties inferred to be a key factor in determining INP uncertainties. Collection onto filters for rinsing versus directly into liquid in impingers made little difference. For methods that activated collected single particles on a substrate at a controlled humidity at or above water saturation, agreement with immersion freezing methods was good in most cases, but was biased low in a few others for reasons that have not been resolved, but could relate to water vapor competition effects. Amongst CFDC-style instruments, various factors requiring (variable) higher supersaturations to achieve equivalent immersion freezing activation dominate the uncertainty between these measurements, and for comparison with bulk immersion freezing methods. When operated above water saturation to include assessment of immersion freezing, CFDC measurements often measured at or above the upper bound of immersion freezing device measurements, but often underestimated INP concentration in comparison to an immersion freezing method that first activates all particles into liquid droplets prior to cooling (the PIMCA-PINC device, or Portable Immersion Mode Cooling chAmber–Portable Ice Nucleation Chamber), and typically slightly underestimated INP number concentrations in comparison to cloud parcel expansions in the AIDA chamber; this can be largely mitigated when it is possible to raise the relative humidity to sufficiently high values in the CFDCs, although this is not always possible operationally. Correspondence of measurements of INPs among direct sampling and post-processing systems varied depending on the INP type. Agreement was best for Snomax® particles in the temperature regime colder than −10 ∘C, where their ice nucleation activity is nearly maximized and changes very little with temperature. At temperatures warmer than −10 ∘C, Snomax® INP measurements (all via freezing of suspensions) demonstrated discrepancies consistent with previous reports of the instability of its protein aggregates that appear to make it less suitable as a calibration INP at these temperatures. For Argentinian soil dust particles, there was excellent agreement across all measurement methods; measures ranged within 1 order of magnitude for INP number concentrations, active fractions and calculated active site densities over a 25 to 30 ∘C range and 5 to 8 orders of corresponding magnitude change in number concentrations. This was also the case for all temperatures warmer than −25 ∘C in Tunisian dust experiments. In contrast, discrepancies in measurements of INP concentrations or active site densities that exceeded 2 orders of magnitude across a broad range of temperature measurements found at temperatures warmer than −25 ∘C in a previous study were replicated for illite NX. Discrepancies also exceeded 2 orders of magnitude at temperatures of −20 to −25 ∘C for potassium feldspar (K-feldspar), but these coincided with the range of temperatures at which INP concentrations increase rapidly at approximately an order of magnitude per 2 ∘C cooling for K-feldspar. These few discrepancies did not outweigh the overall positive outcomes of the workshop activity, nor the future utility of this data set or future similar efforts for resolving remaining measurement issues. Measurements of the same materials were repeatable over the time of the workshop and demonstrated strong consistency with prior studies, as reflected by agreement of data broadly with parameterizations of different specific or general (e.g., soil dust) aerosol types. The divergent measurements of the INP activity of illite NX by direct versus post-processing methods were not repeated for other particle types, and the Snomax® data demonstrated that, at least for a biological INP type, there is no expected measurement bias between bulk collection and direct immediately processed freezing methods to as warm as −10 ∘C. Since particle size ranges were limited for this workshop, it can be expected that for atmospheric populations of INPs, measurement discrepancies will appear due to the different capabilities of methods for sampling the full aerosol size distribution, or due to limitations on achieving sufficient water supersaturations to fully capture immersion freezing in direct processing instruments. Overall, this workshop presents an improved picture of present capabilities for measuring INPs than in past workshops, and provides direction toward addressing remaining measurement issues.

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Section: Direct Sampling Systemsmentioning

confidence: 99%

The Fifth International Workshop on Ice Nucleation phase 2 (FIN-02): laboratory intercomparison of ice nucleation measurements

et al. 2018

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“…2c), will yield relatively large PTM values, whereas values for spheres and aspherical (non fiber-like) particles will be significantly lower, as their intensity patterns cover a larger pixel range. It should be noted that an asphericity factor as used by, for example, Hirst et al (2001) and Zhang et al (2016) cannot be calculated due to the linearity of the detector arrays in PPD-HS. Hirst et al (2001) calculate an asphericity factor (A f ), as a measure of variation in scattered light intensity detected by the pixels across their circular detector array.…”

Section: Phase Discrimination Indicatorsmentioning

confidence: 99%

A high-speed particle phase discriminator (PPD-HS) for the classification of airborne particles, as tested in a continuous flow diffusion chamber

et al. 2019

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A new instrument, the High-speed Particle Phase Discriminator (PPD-HS), developed at the University of Hertfordshire, for sizing individual cloud hydrometeors and determining their phase is described herein. PPD-HS performs an in situ analysis of the spatial intensity distribution of near-forward scattered light for individual hydrometeors yielding shape properties. Discrimination of spherical and aspherical particles is based on an analysis of the symmetry of the recorded scattering patterns. Scattering patterns are collected onto two linear detector arrays, reducing the complete 2-D scattering pattern to scattered light intensities captured onto two linear, one-dimensional strips of light sensitive pixels. Using this reduced scattering information, we calculate symmetry indicators that are used for particle shape and ultimately phase analysis. This reduction of information allows for detection rates of a few hundred particles per second.Here, we present a comprehensive analysis of instrument performance using both spherical and aspherical particles generated in a well-controlled laboratory setting using a vibrating orifice aerosol generator (VOAG) and covering a size range of approximately 3-32 µm. We use supervised machine learning to train a random forest model on the VOAG data sets that can be used to classify any particles detected by PPD-HS. Classification results show that the PPD-HS can successfully discriminate between spherical and aspherical particles, with misclassification below 5 % for diameters > 3 µm. This phase discrimination method is subsequently applied to classify simulated cloud particles produced in a continuous flow diffusion chamber setup. We report observations of small, near-spherical ice crystals at early stages of the ice nucleation experiments, where shape analysis fails to correctly determine the particle phase. Nevertheless, in the case of simultaneous presence of cloud droplets and ice crystals, the introduced particle shape indicators allow for a clear distinction between these two classes, independent of optical particle size. From our laboratory experiments we conclude that PPD-HS constitutes a powerful new instrument to size and discriminate the phase of cloud hydrometeors. The working principle of PPD-HS forms a basis for future instruments to study microphysical properties of atmospheric mixed-phase clouds that represent a major source of uncertainty in aerosol-indirect effect for future climate projections.

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“…A common way to determine hydrometeor phase in CFDC studies encompasses polarization analysis (e.g. Zenker et al, 2017;Nicolet et al, 2007), making use of the fact that aspherical particles change the polarization of incident light, whereas spherical 2 Atmos. Meas.…”

Section: And the Forward Scattering Spectrometermentioning

confidence: 99%

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2019

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A new instrument, the High Speed Particle Phase Discriminator (PPD-HS) developed at the University of Hertfordshire, for sizing individual cloud hydrometeors and determining their phase is described herein. PPD-HS performs an in-situ analysis of the spatial intensity distribution of near forward scattered light for individual hydrometeors yielding shape properties. Discrimination of spherical and aspherical particles is based on an analysis of the symmetry of the recorded scattering patterns. Scattering patterns are collected onto two linear detector arrays, reducing the complete 2D scattering pattern to scattered light intensities captured onto two linear, one dimensional strips of light sensitive pixels. Using this reduced scattering information, we calculate symmetry indicators that are used for particle shape and ultimately phase analysis. This reduction of information allows for detection rates of a few hundred particles per second. Here, we present a comprehensive analysis of instrument performance using both spherical and aspherical particles, generated in a well-controlled laboratory setting using a Vibrating Orifice Aerosol Generator (VOAG) and covering a size range of approximately 3 − 32 µm. We use supervised machine learning to train a random forest model on the VOAG data sets that can be used to classify any particles detected by PPD-HS. Classification results show that the PPD-HS can successfully discriminate between spherical and aspherical particles, with misclassification below 5 % for diameters > 3 µm. This phase discrimination method is subsequently applied to classify simulated cloud particles produced in a continuous flow diffusion chamber setup. We report observations of small, near-spherical ice crystals at early stages of the ice nucleation experiments, where shape analysis fails to correctly determine the particle phase. Nevertheless, in case of simultaneous presence of cloud droplets and ice crystals, the introduced particle shape indicators allow for a clear distinction between these two classes independent of optical particle size. We conclude that PPD-HS constitutes a powerful new instrument to size and discriminate phase of cloud hydrometeors and thus study microphysical properties of mixed-phase clouds, that represent a major source of uncertainty in aerosol indirect effect for future climate projections.

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Using depolarization to quantify ice nucleating particle concentrations: a new method

Cited by 13 publications

References 70 publications

The Fifth International Workshop on Ice Nucleation phase 2 (FIN-02): laboratory intercomparison of ice nucleation measurements

The Fifth International Workshop on Ice Nucleation phase 2 (FIN-02): laboratory intercomparison of ice nucleation measurements

A high-speed particle phase discriminator (PPD-HS) for the classification of airborne particles, as tested in a continuous flow diffusion chamber

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