Analysis of isothermal and cooling-rate-dependent immersion freezing by a unifying stochastic ice nucleation model

Abstract. Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature, T, and relative humidity, RH, at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling-rate-dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nucleating particles (INPs) all have the same INP surface area (ISA); however, the validity of this assumption or the impact it may have on analysis and interpretation of the experimental data is rarely questioned. Descriptions of ice active sites and variability of contact angles have been successfully formulated to describe ice nucleation experimental data in previous research; however, we consider the ability of a stochastic freezing model founded on classical nucleation theory to reproduce previous results and to explain experimental uncertainties and data scatter. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses parameters including the total number of droplets, Ntot, and the heterogeneous ice nucleation rate coefficient, Jhet(T). This model is applied to address if (i) a time and ISA-dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous-flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time-dependent isothermal frozen fractions exhibiting non-exponential behavior can be readily explained by this model considering varying ISA. An apparent cooling-rate dependence of Jhet is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling-rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. The model simulations allow for a quantitative experimental uncertainty analysis for parameters Ntot, T, RH, and the ISA variability. The implications of our results for experimental analysis and interpretation of the immersion freezing process are discussed.

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Analysis of isothermal and cooling rate dependent immersion freezing by a unifying stochastic ice nucleation model

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-15-13109-2015 ◽

2015 ◽

Vol 15 (9) ◽

pp. 13109-13166

Author(s):

P. A. Alpert ◽

D. A. Knopf

Keyword(s):

Cooling Rate ◽

Surface Area ◽

Ice Nucleation ◽

Rate Dependence ◽

Nucleation Theory ◽

Freezing Process ◽

Nucleation Kinetics ◽

Rate Dependent ◽

Immersion Freezing ◽

The Impact

Abstract. Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature (T) and relative humidity (RH) at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling rate dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nuclei (IN) all have the same IN surface area (ISA), however the validity of this assumption or the impact it may have on analysis and interpretation of the experimental data is rarely questioned. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses physically observable parameters including the total number of droplets (Ntot) and the heterogeneous ice nucleation rate coefficient, Jhet(T). This model is applied to address if (i) a time and ISA dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time dependent isothermal frozen fractions exhibiting non-exponential behavior with time can be readily explained by this model considering varying ISA. An apparent cooling rate dependence ofJhet is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. The model simulations allow for a quantitative experimental uncertainty analysis for parameters Ntot, T, RH, and the ISA variability. In an idealized cloud parcel model applying variability in ISAs for each droplet, the model predicts enhanced immersion freezing temperatures and greater ice crystal production compared to a case when ISAs are uniform in each droplet. The implications of our results for experimental analysis and interpretation of the immersion freezing process are discussed.

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Nucleation Behavior of a Single Al-20Si Particle Rapidly Solidified in a Fast Scanning Calorimeter

Materials ◽

10.3390/ma14112920 ◽

2021 ◽

Vol 14 (11) ◽

pp. 2920

Author(s):

Qin Peng ◽

Bin Yang ◽

Benjamin Milkereit ◽

Dongmei Liu ◽

Armin Springer ◽

...

Keyword(s):

Cooling Rate ◽

Rapid Solidification ◽

Heterogeneous Nucleation ◽

Nucleation Theory ◽

Classical Nucleation Theory ◽

Solidification Behavior ◽

Nucleation Kinetics ◽

Nucleation Behavior ◽

Nucleation Undercooling ◽

Primary Si

Understanding the rapid solidification behavior characteristics, nucleation undercooling, and nucleation mechanism is important for modifying the microstructures and properties of metal alloys. In order to investigate the rapid solidification behavior in-situ, accurate measurements of nucleation undercooling and cooling rate are required in most rapid solidification processes, e.g., in additive manufacturing (AM). In this study, differential fast scanning calorimetry (DFSC) was applied to investigate the nucleation kinetics in a single micro-sized Al-20Si (mass%) particle under a controlled cooling rate of 5000 K/s. The nucleation rates of primary Si and secondary α-Al phases were calculated by a statistical analysis of 300 identical melting/solidification experiments. Applying a model based on the classical nucleation theory (CNT) together with available thermodynamic data, two different heterogeneous nucleation mechanisms of primary Si and secondary α-Al were proposed, i.e., surface heterogeneous nucleation for primary Si and interface heterogenous nucleation for secondary α-Al. The present study introduces a practical method for a detailed investigation of rapid solidification behavior of metal particles to distinguish surface and interface nucleation.

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Immersion freezing of water and aqueous ammonium sulfate droplets initiated by humic-like substances as a function of water activity

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-6603-2013 ◽

2013 ◽

Vol 13 (13) ◽

pp. 6603-6622 ◽

Cited By ~ 22

Author(s):

Y. J. Rigg ◽

P. A. Alpert ◽

D. A. Knopf

Keyword(s):

Water Activity ◽

Active Sites ◽

Melting Curve ◽

Contact Angles ◽

Ice Nucleation ◽

Nucleation Theory ◽

Classical Nucleation Theory ◽

Surface Areas ◽

Immersion Freezing ◽

Freezing Temperatures

Abstract. Immersion freezing of water and aqueous (NH4)2SO4 droplets containing leonardite (LEO) and Pahokee peat (PP) serving as surrogates for humic-like substances (HULIS) has been investigated. Organic aerosol containing HULIS are ubiquitous in the atmosphere; however, their potential for ice cloud formation is uncertain. Immersion freezing has been studied for temperatures as low as 215 K and solution water activity, aw, from 0.85 to 1.0. The freezing temperatures of water and aqueous solution droplets containing LEO and PP are 5–15 K warmer than homogeneous ice nucleation temperatures. Heterogeneous freezing temperatures can be represented by a horizontal shift of the ice melting curve as a function of solution aw by Δaw = 0.2703 and 0.2466, respectively. Corresponding hetrogeneous ice nucleation rate coefficients, Jhet, are (9.6 ± 2.5)×104 and (5.4 ± 1.4)×104 cm−2 s−1 for LEO and PP containing droplets, respectively, and remain constant along freezing curves characterized by Δaw. Consequently predictions of freezing temperatures and kinetics can be made without knowledge of the solute type when relative humidity and ice nuclei (IN) surface areas are known. The acquired ice nucleation data are applied to evaluate different approaches to fit and reproduce experimentally derived frozen fractions. In addition, we apply a basic formulation of classical nucleation theory (α(T)-model) to calculate contact angles and frozen fractions. Contact angles calculated for each ice nucleus as a function of temperature, α(T)-model, reproduce exactly experimentally derived frozen fractions without involving free-fit parameters. However, assigning the IN a single contact angle for the entire population (single-α model) is not suited to represent the frozen fractions. Application of α-PDF, active sites, and deterministic model approaches to measured frozen fractions yield similar good representations. Furthermore, when using a single parameterization of α-PDF or active sites distribution to fit all individual aw immersion freezing data simultaneously, frozen fraction curves are not reproduced. This implies that these fitting formulations cannot be applied to immersion freezing of aqueous solutions, and suggests that derived fit parameters do not represent independent particle properties. Thus, from fitting frozen fractions only, the underlying ice nucleation mechanism and nature of the ice nucleating sites cannot be inferred. In contrast to using fitted functions obtained to represent experimental conditions only, we suggest to use experimentally derived Jhet as a function of temperature and aw that can be applied to conditions outside of those probed in laboratory. This is because Jhet(T) is independent of time and IN surface areas in contrast to the fit parameters obtained by representation of experimentally derived frozen fractions.

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A New Ice Nucleation Active Site Parameterization for Desert Dust and Soot

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-16-0074.1 ◽

2017 ◽

Vol 74 (3) ◽

pp. 699-717 ◽

Cited By ~ 64

Author(s):

Romy Ullrich ◽

Corinna Hoose ◽

Ottmar Möhler ◽

Monika Niemand ◽

Robert Wagner ◽

...

Keyword(s):

Active Surface ◽

Ice Nucleation ◽

Nucleation Theory ◽

Classical Nucleation Theory ◽

Negative Slope ◽

Organic Carbon Content ◽

Desert Dust ◽

Soot Aerosol ◽

Immersion Freezing ◽

Heterogeneous Ice Nucleation

Abstract Based on results of 11 yr of heterogeneous ice nucleation experiments at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) chamber in Karlsruhe, Germany, a new empirical parameterization framework for heterogeneous ice nucleation was developed. The framework currently includes desert dust and soot aerosol and quantifies the ice nucleation efficiency in terms of the ice nucleation active surface site (INAS) approach. The immersion freezing INAS densities nS of all desert dust experiments follow an exponential fit as a function of temperature, well in agreement with an earlier analysis of AIDA experiments. The deposition nucleation nS isolines for desert dust follow u-shaped curves in the ice saturation ratio–temperature (Si–T) diagram at temperatures below about 240 K. The negative slope of these isolines toward lower temperatures may be explained by classical nucleation theory (CNT), whereas the behavior toward higher temperatures may be caused by a pore condensation and freezing mechanism. The deposition nucleation measured for soot at temperatures below about 240 K also follows u-shaped isolines with a shift toward higher Si for soot with higher organic carbon content. For immersion freezing of soot aerosol, only upper limits for nS were determined and used to rescale an existing parameterization line. The new parameterization framework is compared to a CNT-based parameterization and an empirical framework as used in models. The comparison shows large differences in shape and magnitude of the nS isolines especially for deposition nucleation. For the application in models, implementation of this new framework is simple compared to that of other expressions.

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A comprehensive laboratory study on the immersion freezing behavior of illite NX particles: a comparison of 17 ice nucleation measurement techniques

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-2489-2015 ◽

2015 ◽

Vol 15 (5) ◽

pp. 2489-2518 ◽

Cited By ~ 123

Author(s):

N. Hiranuma ◽

S. Augustin-Bauditz ◽

H. Bingemer ◽

C. Budke ◽

J. Curtius ◽

...

Keyword(s):

Cooling Rate ◽

Surface Area ◽

Mineral Dust ◽

Measurement Techniques ◽

Ice Nucleation ◽

Measurement Methods ◽

Dust Particles ◽

Immersion Freezing ◽

Nucleation Activity ◽

Ice Nucleation Activity

Abstract. Immersion freezing is the most relevant heterogeneous ice nucleation mechanism through which ice crystals are formed in mixed-phase clouds. In recent years, an increasing number of laboratory experiments utilizing a variety of instruments have examined immersion freezing activity of atmospherically relevant ice-nucleating particles. However, an intercomparison of these laboratory results is a difficult task because investigators have used different ice nucleation (IN) measurement methods to produce these results. A remaining challenge is to explore the sensitivity and accuracy of these techniques and to understand how the IN results are potentially influenced or biased by experimental parameters associated with these techniques. Within the framework of INUIT (Ice Nuclei Research Unit), we distributed an illite-rich sample (illite NX) as a representative surrogate for atmospheric mineral dust particles to investigators to perform immersion freezing experiments using different IN measurement methods and to obtain IN data as a function of particle concentration, temperature (T), cooling rate and nucleation time. A total of 17 measurement methods were involved in the data intercomparison. Experiments with seven instruments started with the test sample pre-suspended in water before cooling, while 10 other instruments employed water vapor condensation onto dry-dispersed particles followed by immersion freezing. The resulting comprehensive immersion freezing data set was evaluated using the ice nucleation active surface-site density, ns, to develop a representative ns(T) spectrum that spans a wide temperature range (−37 °C < T < −11 °C) and covers 9 orders of magnitude in ns. In general, the 17 immersion freezing measurement techniques deviate, within a range of about 8 °C in terms of temperature, by 3 orders of magnitude with respect to ns. In addition, we show evidence that the immersion freezing efficiency expressed in ns of illite NX particles is relatively independent of droplet size, particle mass in suspension, particle size and cooling rate during freezing. A strong temperature dependence and weak time and size dependence of the immersion freezing efficiency of illite-rich clay mineral particles enabled the ns parameterization solely as a function of temperature. We also characterized the ns(T) spectra and identified a section with a steep slope between −20 and −27 °C, where a large fraction of active sites of our test dust may trigger immersion freezing. This slope was followed by a region with a gentler slope at temperatures below −27 °C. While the agreement between different instruments was reasonable below ~ −27 °C, there seemed to be a different trend in the temperature-dependent ice nucleation activity from the suspension and dry-dispersed particle measurements for this mineral dust, in particular at higher temperatures. For instance, the ice nucleation activity expressed in ns was smaller for the average of the wet suspended samples and higher for the average of the dry-dispersed aerosol samples between about −27 and −18 °C. Only instruments making measurements with wet suspended samples were able to measure ice nucleation above −18 °C. A possible explanation for the deviation between −27 and −18 °C is discussed. Multiple exponential distribution fits in both linear and log space for both specific surface area-based ns(T) and geometric surface area-based ns(T) are provided. These new fits, constrained by using identical reference samples, will help to compare IN measurement methods that are not included in the present study and IN data from future IN instruments.

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The Leipzig Cloud Interaction Simulator (LACIS): operating principle and theoretical studies concerning homogeneous and heterogeneous ice nucleation

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-10-25577-2010 ◽

2010 ◽

Vol 10 (11) ◽

pp. 25577-25617

Author(s):

S. Hartmann ◽

D. Niedermeier ◽

J. Voigtländer ◽

T. Clauss ◽

R. A. Shaw ◽

...

Keyword(s):

Experimental Data ◽

Numerical Model ◽

Nucleation Rate ◽

Rate Coefficient ◽

Ice Nucleation ◽

Freezing Behavior ◽

Nucleation Theory ◽

Dust Particles ◽

Immersion Freezing ◽

Heterogeneous Ice Nucleation

Abstract. At the Leipzig Cloud Interaction Simulator (LACIS) experiments investigating homogeneous and heterogeneous nucleation of ice (particularly immersion freezing in the latter case) have been carried out. Here both the physical LACIS setup and the numerical model developed to design experiments at LACIS and interpret their results are presented in detail. Combining results from the numerical model with experimental data, it was found that for the experimental parameter space considered, classical homogeneous ice nucleation theory is able to predict the freezing behavior of highly diluted ammonium sulfate solution droplets, while classical heterogeneous ice nucleation theory, together with the assumption of a constant contact angle, fails to predict the immersion freezing behavior of surrogate mineral dust particles (Arizona Test Dust, ATD). The main reason for this failure is the compared to experimental data apparently overly strong temperature dependence of the nucleation rate coefficient. Assuming, in the numerical model, Classical Nucleation Theory (CNT) for homogeneous ice nucleation and a CNT-based parameterization for the nucleation rate coefficient in the immersion freezing mode, recently published by our group, it was found that even for a relatively effective ice nucleating agent such as pure ATD, there is a temperature range where homogeneous ice nucleation is dominant. The main explanation is the apparently different temperature dependencies of the two freezing mechanisms. Finally, reviewing the assumptions made during the derivation of the parameterization, it was found that the assumption of constant temperature during ice nucleation and the chosen nucleation time were highly justified, underlining the applicability of both the method to determine the fitting coefficients in the parameterization equation, and the validity of the parameterization concept itself.

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Classical nucleation theory of immersion freezing: sensitivity of contact angle schemes to thermodynamic and kinetic parameters

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-1713-2017 ◽

2017 ◽

Vol 17 (3) ◽

pp. 1713-1739 ◽

Cited By ~ 12

Author(s):

Luisa Ickes ◽

André Welti ◽

Ulrike Lohmann

Keyword(s):

Experimental Data ◽

Contact Angle ◽

Kinetic Parameters ◽

Aerosol Particles ◽

Nucleation Theory ◽

Classical Nucleation Theory ◽

Kinetic And Thermodynamic Parameters ◽

Immersion Freezing ◽

Thermodynamic And Kinetic Parameters ◽

Homogeneous Freezing

Abstract. Heterogeneous ice formation by immersion freezing in mixed-phase clouds can be parameterized in general circulation models (GCMs) by classical nucleation theory (CNT). CNT parameterization schemes describe immersion freezing as a stochastic process, including the properties of insoluble aerosol particles in the droplets. There are different ways to parameterize the properties of aerosol particles (i.e., contact angle schemes), which are compiled and tested in this paper. The goal of this study is to find a parameterization scheme for GCMs to describe immersion freezing with the ability to shift and adjust the slope of the freezing curve compared to homogeneous freezing to match experimental data. We showed in a previous publication that the resulting freezing curves from CNT are very sensitive to unconstrained kinetic and thermodynamic parameters in the case of homogeneous freezing. Here we investigate how sensitive the outcome of a parameter estimation for contact angle schemes from experimental data is to unconstrained kinetic and thermodynamic parameters. We demonstrate that the parameters describing the contact angle schemes can mask the uncertainty in thermodynamic and kinetic parameters. Different CNT formulations are fitted to an extensive immersion freezing dataset consisting of size-selected measurements as a function of temperature and time for different mineral dust types, namely kaolinite, illite, montmorillonite, microcline (K-feldspar), and Arizona test dust. We investigated how accurate different CNT formulations (with estimated fit parameters for different contact angle schemes) reproduce the measured freezing data, especially the time and particle size dependence of the freezing process. The results are compared to a simplified deterministic freezing scheme. In this context, we evaluated which CNT-based parameterization scheme able to represent particle properties is the best choice to describe immersion freezing in a GCM.

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Classical nucleation theory of immersion freezing: Sensitivity of contact angle schemes to thermodynamic and kinetic parameters

10.5194/acp-2015-969 ◽

2016 ◽

Cited By ~ 2

Author(s):

L. Ickes ◽

A. Welti ◽

U. Lohmann

Keyword(s):

Experimental Data ◽

Contact Angle ◽

Kinetic Parameters ◽

Aerosol Particles ◽

Nucleation Theory ◽

Classical Nucleation Theory ◽

Kinetic And Thermodynamic Parameters ◽

Immersion Freezing ◽

Thermodynamic And Kinetic Parameters ◽

Homogeneous Freezing

Abstract. Heterogeneous ice formation by immersion freezing in mixed-phase clouds can be parameterized in general circulation models (GCMs) by Classical Nucleation Theory (CNT). CNT parameterization schemes describe freezing as a stochastic process including the properties of insoluble aerosol particles, so called ice nuclei, in the droplets. There are different ways how to describe the properties of aerosol particles (i.e. contact angle schemes), which are compiled and tested in this paper. The goal of this study is to ﬁnd a parameterization scheme for GCMs to describe immersion freezing with the ability to shift and adjust the slope of the freezing curve compared to homogeneous freezing to match experimental data. The results of using CNT are very sensitive to unconstrained kinetic and thermodynamic parameters in the case of homogeneous freezing leading to uncertainties in calculated nucleation rates Jhom of several orders of magnitude. Here we investigate how sensitive the outcome of a parameter estimation for contact angle schemes from experimental data is to kinetic and thermodynamic parameters. We show that additional free parameter can mask the uncertainty of Jimm due to thermodynamic and kinetic parameters. Different CNT formulations are ﬁtted to an extensive immersion freezing dataset as a function of particle diameter (d), temperature T and time t for different mineral dust types, namely kaolinite, illite, montmorillonite, microcline (K-feldspar) and Arizona test dust. It is investigated how accurate different CNT formulations (with the estimated ﬁt parameters) reproduce the measured freezing curves, especially the time and particle size dependence of the freezing process. The results are compared to a simpliﬁed deterministic freezing scheme. It is evaluated in this context which CNT based parameterization scheme to represent particle properties is a good choice to describe immersion freezing in a GCM.

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Immersion freezing of water and aqueous ammonium sulphate droplets initiated by Humic Like Substances as a function of water activity

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-4917-2013 ◽

2013 ◽

Vol 13 (2) ◽

pp. 4917-4961

Author(s):

Y. J. Rigg ◽

P. A. Alpert ◽

D. A. Knopf

Keyword(s):

Water Activity ◽

Active Sites ◽

Melting Curve ◽

Contact Angles ◽

Ice Nucleation ◽

Nucleation Theory ◽

Classical Nucleation Theory ◽

Surface Areas ◽

Immersion Freezing ◽

Freezing Temperatures

Abstract. Immersion freezing of water and aqueous (NH4)2SO4 droplets containing Leonardite (LEO) and Pahokee peat (PP) serving as surrogates for Humic Like Substances (HULIS) has been investigated. Organic aerosol containing HULIS are ubiquitous in the atmosphere, however, their potential for ice cloud formation is uncertain. Immersion freezing has been studied for temperatures as low as 215 K and solution water activity, aw, from 0.85–1.0. The freezing temperatures of water and aqueous solution droplets containing LEO and PP are 5–15 K warmer than homogeneous ice nucleation temperatures. Heterogeneous freezing temperatures can be represented by a horizontal shift of the ice melting curve as a function of solution aw, Δaw, by 0.2703 and 0.2466, respectively. Corresponding heterogeneous ice nucleation rate coefficients, Jhet, are (9.6 ± 2.5)×104 and (5.4 ± 1.4)×104 cm−2 s−1 for LEO and PP containing droplets, respectively, and remain constant along freezing curves characterized by Δaw. Consequently predictions of freezing temperatures and kinetics can be made without knowledge of the solute type when relative humidity and IN surface areas are known. The acquired ice nucleation data are applied to evaluate different approaches to fit and reproduce experimentally derived frozen fractions. In addition, we apply a basic formulation of classical nucleation theory (α(T)-model) to calculate contact angles and frozen fractions. Contact angles calculated for each ice nucleus as a function of temperature, α(T)-model, reproduce exactly experimentally derived frozen fractions without involving free fit parameters. However, assigning the IN a single contact angle for entire population (single-α model) is not suited to represent the frozen fractions. Application of α-PDF, active sites, and deterministic model approaches to measured frozen fractions yield similar good representations. Thus, from fitting frozen fractions only, the underlying ice nucleation mechanism and nature of the ice nucleating sites cannot be inferred. In contrast to using fitted functions obtained to represent experimental conditions only, we suggest to use experimentally derived Jhet as a function of temperature and aw that can be applied to conditions outside of those probed in laboratory. This is because Jhet(T) is independent of time and IN surface areas in contrast to the fit parameters obtained by representation of experimentally derived frozen fractions.

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Homogeneous and heterogeneous ice nucleation at LACIS: operating principle and theoretical studies

Atmospheric Chemistry and Physics ◽

10.5194/acp-11-1753-2011 ◽

2011 ◽

Vol 11 (4) ◽

pp. 1753-1767 ◽

Cited By ~ 54

Author(s):

S. Hartmann ◽

D. Niedermeier ◽

J. Voigtländer ◽

T. Clauss ◽

R. A. Shaw ◽

...

Keyword(s):

Experimental Data ◽

Numerical Model ◽

Nucleation Rate ◽

Rate Coefficient ◽

Ice Nucleation ◽

Freezing Behavior ◽

Nucleation Theory ◽

Dust Particles ◽

Immersion Freezing ◽

Heterogeneous Ice Nucleation

Abstract. At the Leipzig Aerosol Cloud Interaction Simulator (LACIS) experiments investigating homogeneous and heterogeneous nucleation of ice (particularly immersion freezing in the latter case) have been carried out. Here both the physical LACIS setup and the numerical model developed to design experiments at LACIS and interpret their results are presented in detail. Combining results from the numerical model with experimental data, it was found that for the experimental parameter space considered, classical homogeneous ice nucleation theory is able to predict the freezing behavior of highly diluted ammonium sulfate solution droplets, while classical heterogeneous ice nucleation theory, together with the assumption of a constant contact angle, fails to predict the immersion freezing behavior of surrogate mineral dust particles (Arizona Test Dust, ATD). The main reason for this failure is the compared to experimental data apparently overly strong temperature dependence of the nucleation rate coefficient. Assuming, in the numerical model, Classical Nucleation Theory (CNT) for homogeneous ice nucleation and a CNT-based parameterization for the nucleation rate coefficient in the immersion freezing mode, recently published by our group, it was found that even for a relatively effective ice nucleating agent such as pure ATD, there is a temperature range where homogeneous ice nucleation is dominant. The main explanation is the apparently different temperature dependencies of the two freezing mechanisms. Finally, reviewing the assumptions made during the derivation of the CNT-based parameterization for immersion freezing, it was found that the assumption of constant temperature during ice nucleation and the chosen ice nucleation time were justified, underlining the applicability of the method to determine the fitting coefficients in the parameterization equation.

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