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Volume 13, issue 11
Atmos. Chem. Phys., 13, 5751–5766, 2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Results from the ice nucleation research unit (INUIT) (ACP/AMT...

Atmos. Chem. Phys., 13, 5751–5766, 2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 14 Jun 2013

Research article | 14 Jun 2013

Immersion freezing of ice nucleation active protein complexes

S. Hartmann1, S. Augustin1, T. Clauss1, H. Wex1, T. Šantl-Temkiv2, J. Voigtländer1, D. Niedermeier1, and F. Stratmann1 S. Hartmann et al.
  • 1Leibniz Institute for Tropospheric Research, Permoserstr. 15, 04318 Leipzig, Germany
  • 2Aarhus University, Stellar Astrophysics Centre, Department of Physics and Astronomy, 120 Ny Munkegade, 8000 Aarhus, Denmark

Abstract. 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 immersion freezing behaviour of bacterial ice nucleation.

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