A comprehensive characterization of ice nucleation by three different types of cellulose particles immersed in water

We present the laboratory results of immersion freezing efficiencies of cellulose particles at supercooled temperature (T) conditions. Three types of chemically homogeneous cellulose samples are used as surrogates that represent supermicron and submicron ice-nucleating plant structural polymers. These samples include microcrystalline cellulose (MCC), fibrous cellulose (FC) and nanocrystalline cellulose (NCC). Our immersion freezing dataset includes data from various ice nucleation measurement techniques available at 17 different institutions, including nine dry dispersion and 11 aqueous suspension techniques. With a total of 20 methods, we performed systematic accuracy and precision analysis of measurements from all 20 measurement techniques by evaluating T-binned (1 ∘C) data over a wide T range (−36 ∘C <T<-4 ∘C). Specifically, we intercompared the geometric surface area-based ice nucleation active surface site (INAS) density data derived from our measurements as a function of T, ns,geo(T). Additionally, we also compared the ns,geo(T) values and the freezing spectral slope parameter (Δlog(ns,geo)/ΔT) from our measurements to previous literature results. Results show all three cellulose materials are reasonably ice active. The freezing efficiencies of NCC samples agree reasonably well, whereas the diversity for the other two samples spans ≈ 10 ∘C. Despite given uncertainties within each instrument technique, the overall trend of the ns,geo(T) spectrum traced by the T-binned average of measurements suggests that predominantly supermicron-sized cellulose particles (MCC and FC) generally act as more efficient ice-nucleating particles (INPs) than NCC with about 1 order of magnitude higher ns,geo(T).

The WeIzmann Supercooled Droplets Observation on a Microarray (WISDOM) and application for ambient dust

The WeIzmann Supercooled Droplets Observation on Microarray (WISDOM) is a new setup for studying ice nucleation in an array of monodisperse droplets for atmospheric implications. WISDOM combines microfluidics techniques for droplets production and a cryo-optic stage for observation and characterization of freezing events of individual droplets. This setup is designed to explore heterogeneous ice nucleation in the immersion freezing mode, down to the homogeneous freezing of water (235 K) in various cooling rates (typically 0.1–10 K min−1). It can also be used for studying homogeneous freezing of aqueous solutions in colder temperatures. Frozen fraction, ice nucleation active surface site densities and freezing kinetics can be obtained from WISDOM measurements for hundreds of individual droplets in a single freezing experiment. Calibration experiments using eutectic solutions and previously studied materials are described. WISDOM also allows repeatable cycles of cooling and heating for the same array of droplets. This paper describes the WISDOM setup, its temperature calibration, validation experiments and measurement uncertainties. Finally, application of WISDOM to study the ice nucleating particle (INP) properties of size-selected ambient Saharan dust particles is presented.

The WeIzmann Supercooled Droplets Observation (WISDOM) on a Microarray and application for ambient dust

The WeIzmann Supercooled Droplets Observation on Microarray (WISDOM) is a new setup for studying ice nucleation in an array of monodisperse droplets for atmospheric implications. WISDOM combines microfluidics techniques for droplets production and a cryo-optic stage for observation and characterization of freezing events of individual droplets. This setup is designed to explore heterogeneous ice nucleation in the immersion freezing mode, down to the homogenous freezing of water (235 K) in various cooling rates (typically 0.1-10 K min−1). It can also be used for studying homogenous freezing of aqueous solutions in colder temperatures. Frozen fraction, ice nucleation active surface site (INAS) densities and freezing kinetics can be obtained from WISDOM measurements with excellent statistics of hundreds of individual droplets in a single freezing experiment. Droplets are surrounded by a mineral oil phase which assures the isolation of the droplets and prevents mutual seeding, mass transfer or evaporation, and hence increases the reliability and reproducibility of the measurement. WISDOM also allows repeatable cycles of cooling and heating for the same array of droplets. This paper describes the WISDOM setup, its temperature calibration, validation experiments and measurement uncertainties. Finally, application of WISDOM to study the INP properties of size-selected ambient Saharan dust particles is presented.

Investigating the discrepancy between wet-suspension- and dry-dispersion-derived ice nucleation efficiency of mineral particles

Cloud chamber investigations into ice nucleation by mineral particles were compared with results from cold-stage droplet freezing experiments. Kaolinite, NX-illite, and K-feldspar were examined, and K-feldspar was revealed to be the most ice-active mineral particle sample, in agreement with recent cold-stage studies. The ice nucleation efficiencies, as quantified using the ice-active surface site density method, were found to be in agreement with previous studies for the lower temperatures; however, at higher temperatures the efficiency was between a factor of 10 and 1000 higher than those inferred from cold-stage experiments. Numerical process modelling of cloud formation during the experiments, using the cold-stage-derived parameterisations to initiate the ice phase, revealed the cold-stage-derived parameterisations to consistently underpredict the number of ice crystals relative to that observed. We suggest the reason for the underestimation of ice in the model is that the slope of the cold-stage-derived ice-active surface site density vs. temperature curves are too steep, which results in an underestimation of the number of ice crystals at higher temperatures during the expansion. These ice crystals suppress further freezing due to the Bergeron–Findeison process. A coagulation model was used to investigate the idea that the mineral particles coagulate in suspension. This model suggests that coagulation during the experiments may be sufficient to significantly remove the particles for the suspension by sedimentation or reduce the total particle surface area available for ice nucleation to take place. Aggregation was confirmed to take place in mineral suspensions using dynamic light-scattering measurements. However, it is not proven that aggregation of the mineral particles is able to reduce the surface area available for ice nucleation. The implication is that the mineral particles may be more important at nucleating ice at high temperatures than previously thought.

Ice nucleation properties of fine ash particles from the Eyjafjallajökull eruption in April 2010

During the eruption of the Eyjafjallajökull volcano in the south of Iceland in April/May 2010, about 40 Tg of ash mass were emitted into the atmosphere. It was unclear whether volcanic ash particles with d < 10 μm facilitate the glaciation of clouds. Thus, ice nucleation properties of volcanic ash particles were investigated in AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber experiments simulating atmospherically relevant conditions. The ash sample that was used for our experiments had been collected at a distance of 58 km from the Eyjafjallajökull during the eruption period in April 2010. The temperature range covered by our ice nucleation experiments extended from 219 to 264 K, and both ice nucleation via immersion freezing and deposition nucleation could be observed. Immersion freezing was first observed at 252 K, whereas the deposition nucleation onset lay at 242 K and RHice =126%. About 0.1% of the volcanic ash particles were active as immersion freezing nuclei at a temperature of 249 K. For deposition nucleation, an ice fraction of 0.1% was observed at around 233 K and RHice =116%. Taking ice-active surface site densities as a measure for the ice nucleation efficiency, volcanic ash particles are similarly efficient ice nuclei in immersion freezing mode (ns,imm ~ 109 m−2 at 247 K) compared to certain mineral dusts. For deposition nucleation, the observed ice-active surface site densities ns,dep were found to be 1011 m−2 at 224 K and RHice =116%. Thus, volcanic ash particles initiate deposition nucleation more efficiently than Asian and Saharan dust but appear to be poorer ice nuclei than ATD particles. Based on the experimental data, we have derived ice-active surface site densities as a function of temperature for immersion freezing and of relative humidity over ice and temperature for deposition nucleation.

Ice nucleation properties of fine ash particles from the Eyjafjallajökull eruption in April 2010

During the eruption of the Eyjafjallajökull volcano in the south of Iceland in April/May 2010, about 40 Tg of ash mass were emitted into the atmosphere. However, it was unclear whether volcanic ash particles with d < 10 μm facilitate the glaciation of clouds. Thus, ice nucleation properties of volcanic ash particles were investigated in AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber experiments simulating atmospherically relevant conditions. The ash sample that was used for our experiments had been collected at a distance of 58 km from the Eyjafjallajökull during the eruption period in April 2010. The temperature range covered by our ice nucleation experiments extended from 219 to 264 K, and both ice nucleation via immersion freezing and deposition nucleation could be observed. Immersion freezing was first observed at 252 K, whereas the deposition nucleation onset lay at 242 K and RHice = 126 %. About 0.1 % of the volcanic ash particles were active as immersion freezing nuclei at a temperature of 249 K. For deposition nucleation, an ice fraction of 0.1 % was observed at around 233 K and RHice = 116 %. Taking ice-active surface site densities as a measure for the ice nucleation efficiency, volcanic ash particles are similarly efficient ice nuclei in immersion freezing mode (ns, imm ~ 109 m−2 at 247 K) compared to certain mineral dusts. For deposition nucleation, the observed ice-active surface site densities ns, dep were found to be 1011 m−2 at 224 K and RHice = 116 %. Thus, volcanic ash particles initiate deposition nucleation more efficiently than Asian and Saharan dust but appear to be poorer ice nuclei than ATD particles. Based on the experimental data, we have derived ice-active surface site densities as a function of temperature for immersion freezing and of relative humidity over ice and temperature for deposition nucleation.

Studies of heterogeneous freezing by three different desert dust samples

We present results of experiments at the aerosol interactions and dynamics in the atmosphere (AIDA) chamber facility looking at the freezing of water by three different types of mineral particles at temperatures between −12°C and −33°C. The three different dusts are Asia Dust-1 (AD1), Sahara Dust-2 (SD2) and Arizona test Dust (ATD). The dust samples used had particle concentrations of sizes that were log-normally distributed with mode diameters between 0.3 and 0.5 μm and standard deviations, σg, of 1.6–1.9. The results from the freezing experiments are consistent with the singular hypothesis of ice nucleation. The dusts showed different nucleation abilities, with ATD showing a rather sharp increase in ice-active surface site density at temperatures less than −24°C. AD1 was the next most efficient freezing nuclei and showed a more gradual increase in activity than the ATD sample. SD2 was the least active freezing nuclei. We used data taken with particle counting probes to derive the ice-active surface site density forming on the dust as a function of temperature for each of the three samples and polynomial curves are fitted to this data. The curve fits are then used independently within a bin microphysical model to simulate the ice formation rates from the experiments in order to test the validity of parameterising the data with smooth curves. Good agreement is found between the measurements and the model for AD1 and SD2; however, the curve for ATD does not yield results that agree well with the observations. The reason for this is that more experiments between −20 and −24°C are needed to quantify the rather sharp increase in ice-active surface site density on ATD in this temperature regime. The curves presented can be used as parameterisations in atmospheric cloud models where cooling rates of approximately 1°C min−1 or more are present to predict the concentration of ice crystals forming by the condensation-freezing mode of ice nucleation. Finally a polynomial is fitted to all three samples together in order to have a parameterisation describing the average ice-active surface site density vs. temperature for an equal mixture of the three dust samples.