Utilising the Leipzig Aerosol Cloud Interaction Simulator (LACIS), the immersion freezing behaviour of droplet ensembles containing monodisperse particles, generated from a Snomax™ solution/suspension, was investigated. Thereto ice fractions were measured in the temperature range between −5 °C to −38 °C. Snomax™ is an industrial product applied for artificial snow production and contains Pseudomonas syringae} bacteria which have long been used as model organism for atmospheric relevant ice nucleation active (INA) bacteria. The ice nucleation activity of such bacteria is controlled by INA protein complexes in their outer membrane.

In our experiments, ice fractions increased steeply in the temperature range from about −6 °C to about −10 °C and then levelled off at ice fractions smaller than one. The plateau implies that not all examined droplets contained an INA protein complex. Assuming the INA protein complexes to be Poisson distributed over the investigated droplet populations, we developed the CHESS model (stoCHastic modEl of similar and poiSSon distributed ice nuclei) which allows for the calculation of ice fractions as function of temperature and time for a given nucleation rate. Matching calculated and measured ice fractions, we determined and parameterised the nucleation rate of INA protein complexes exhibiting class III ice nucleation behaviour. Utilising the CHESS model, together with the determined nucleation rate, we compared predictions from the model to experimental data from the literature and found good agreement.

We found that (a) the heterogeneous ice nucleation rate expression quantifying the ice nucleation behaviour of the INA protein complex is capable of describing the ice nucleation behaviour observed in various experiments for both, Snomax™ and P. syringae bacteria, (b) the ice nucleation rate, and its temperature dependence, seem to be very similar regardless of whether the INA protein complexes inducing ice nucleation are attached to the outer membrane of intact bacteria or membrane fragments, (c) the temperature range in which heterogeneous droplet freezing occurs, and the fraction of droplets being able to freeze, both depend on the actual number of INA protein complexes present in the droplet ensemble, and (d) possible artifacts suspected to occur in connection with the drop freezing method, i.e., the method frequently used by biologist for quantifying ice nucleation behaviour, are of minor importance, at least for substances such as P. syringae, which induce freezing at comparably high temperatures. The last statement implies that for single ice nucleation entities such as INA protein complexes, it is the number of entities present in the droplet population, and the entities' nucleation rate, which control the freezing behaviour of the droplet population. Quantities such as ice active surface site density are not suitable in this context.

The results obtained in this study allow a different perspective on the quantification of the immersi...

Abstract. Birch pollen grains are known to be ice nucleating active biological particles. The ice nucleating activity has previously been tracked down to biological macromolecules that can be easily extracted from the pollen grains in water. In the present study, we investigated the immersion freezing behavior of these ice nucleating active (INA) macromolecules. Therefore we measured the frozen fractions of particles generated from birch pollen washing water as a function of temperature at the Leipzig Aerosol Cloud Interaction Simulator (LACIS). Two different birch pollen samples were considered, with one originating from Sweden and one from the Czech Republic. For the Czech and Swedish birch pollen samples, freezing was observed to start at −19 and −17 • C, respectively. The fraction of frozen droplets increased for both samples down to −24 • C. Further cooling did not increase the frozen fractions any more. Instead, a plateau formed at frozen fractions below 1. This fact could be used to determine the amount of INA macromolecules in the droplets examined here, which in turn allowed for the determination of nucleation rates for single INA macromolecules. The main differences between the Swedish birch pollen and the Czech birch pollen were obvious in the temperature range between −17 and −24 • C. In this range, a second plateau region could be seen for Swedish birch pollen. As we assume INA macromolecules to be the reason for the ice nucleation, we concluded that birch pollen is able to produce at least two different types of INA macromolecules. We were able to derive parameterizations for the heterogeneous nucleation rates for both INA macromolecule types, using two different methods: a simple exponential fit and the Soccer ball model. With these parameterization methods we were able to describe the ice nucleation behavior of single INA macromolecules from both the Czech and the Swedish birch pollen.

In the present study, the immersion freezing behavior of birch pollen, i.e. its ice nucleating active (INA) macromolecules, was investigated at the Leipzig Aerosol Cloud Interaction Simulator (LACIS). For that, washing water of two different birch pollen samples with different regional origin (Northern birch and Southern birch) were used. The immersion freezing of droplets generated from the pollen washing water was already observed at temperatures higher than −20 °C, for both samples. Main differences between the Northern birch pollen and the Southern birch pollen were obvious in a temperature range, between −18 °C and −24 °C, where the ice fraction increased with decreasing temperature. There, the Northern birch pollen washing water featured two different slopes, with one being steeper and one being similar to the slope of the Southern birch pollen washing water. As we assume single INA macromolecules being the reason for the ice nucleation, we concluded that the Northern birch pollen are able to produce at least two different types of INA macromolecules. We were able to determine the heterogeneous nucleation rates for both INA macromolecule types and so could explain the ice nucleation behavior of both, the Southern and the Northern birch pollen washing water

Abstract. We report on the development and test results of the new optical particle counter TOPS-Ice (Thermo-stabilized Optical Particle Spectrometer for the detection of Ice). The instrument uses measurements of the cross-polarized scattered light by single particles into the near-forward direction (42.5° ± 12.7°) to distinguish between spherical and non-spherical particles. This approach allows the differentiation between liquid water droplets (spherical) and ice particles (non-spherical) having similar volume-equivalent sizes and therefore can be used to determine the fraction of frozen droplets in a typical immersion freezing experiment. We show that the numerical simulation of the light scattered on non-spherical particles (spheroids in random orientation) considering the actual scattering geometry used in the instrument supports the validity of the approach, even though the cross-polarized component of the light scattered by spherical droplets does not vanish in this scattering angle. For the separation of the ice particle mode from the liquid droplet mode, we use the width of the pulse detected in the depolarization channel instead of the pulse height. Exploiting the intrinsic relationship between pulse height and pulse width for Gaussian pulses allows us to calculate the fraction of frozen droplets even if the liquid droplet mode dominates the particle ensemble. We present test results obtained with TOPS-Ice in the immersion freezing experiments at the laminar diffusion chamber LACIS (Leipzig Aerosol Cloud Interaction Simulator) and demonstrate the excellent agreement with the data obtained in similar experiments with a different optical instrument. Finally, the advantages of using the cross-polarized light measurements for the differentiation of liquid and frozen droplets in the realistic immersion freezing experiments are discussed.

Biological particles, e.g. bacteria and their Ice Nucleating Active (INA) protein complexes, might play an important role for the ice formation in atmospheric mixed-phase clouds. Therefore, the immersion freezing behavior of INA protein complexes generated from a Snomax^TM solution/suspension was investigated as function of temperature in a range of −5 &deg;C to −38 &deg;C at the Leipzig Aerosol Cloud Interaction Simulator (LACIS). The immersion freezing of droplets containing small numbers of INA protein complexes occurs in a temperature range of −7 &deg;C and −10 &deg;C. The experiments performed in the lower temperature range, where all droplets freeze which contain at least one INA protein complex, are used to determine the average number of INA protein complexes present, assuming that the INA protein complexes are Poisson distributed over the droplet ensemble. Knowing the average number of INA protein complexes, the heterogeneous ice nucleation rate and rate coefficient of a single INA protein complex is determined by using the newly-developed CHESS model (stoCHastic model of idEntical poiSSon distributed ice nuclei). Therefore, we assume the ice nucleation process to be of stochastic nature, and a parameterization of the INA protein complex's nucleation rate. Analyzing the results of immersion freezing experiments from literature (Snomax^TM and <i>Pseudomonas syringae</i> bacteria), to results gained in this study, demonstrates that first, a similar temperature dependence of the heterogeneous ice nucleation rate for a single INA protein complex was found in all experiments, second, the shift of the ice fraction curves to higher temperatures can be explained consistently by a higher average number of INA protein complexes being present in the droplet ensemble, and finally the heterogeneous ice nucleation rate of one single INA protein complex might be also applicable for intact <i>Pseudomonas syringae</i> bacteria cells. The results obtained in this study allow a new perspective on the interpretation of immersion freezing experiments considering INA protein complexes and the derived simple parameterization of the heterogeneous ice nucleation rate can be used in cloud resolving models for studying the effect of bacteria induced ice nucleation