A new multicomponent heterogeneous ice nucleation model and its application to Snomax bacterial particles and a Snomax–illite mineral particle mixture
Some biological particles, such as Snomax, are very active ice nucleating particles, inducing heterogeneous freezing in supercooled water at temperatures above −15 and up to −2 °C. Despite their exceptional freezing abilities, large uncertainties remain regarding the atmospheric abundance of bio...
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doaj-bc73be88db8f4d0ea38d5d05cefd7b342020-11-24T23:15:15ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242017-11-0117135451355710.5194/acp-17-13545-2017A new multicomponent heterogeneous ice nucleation model and its application to Snomax bacterial particles and a Snomax–illite mineral particle mixtureH. Beydoun0M. Polen1R. C. Sullivan2Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA, USACenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA, USACenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA, USASome biological particles, such as Snomax, are very active ice nucleating particles, inducing heterogeneous freezing in supercooled water at temperatures above −15 and up to −2 °C. Despite their exceptional freezing abilities, large uncertainties remain regarding the atmospheric abundance of biological ice nucleating particles, and their contribution to atmospheric ice nucleation. It has been suggested that small biological ice nucleating macromolecules or fragments can be carried on the surfaces of dust and other atmospheric particles. This could combine the atmospheric abundance of dust particles with the ice nucleating strength of biological material to create strongly enhanced and abundant ice nucleating surfaces in the atmosphere, with significant implications for the budget and distribution of atmospheric ice nucleating particles, and their consequent effects on cloud microphysics and mixed-phase clouds.<br><br> The new critical surface area <q><span style="text-decoration: overline;"><i>g</i></span></q> framework that was developed by Beydoun et al. (2016) is extended to produce a heterogeneous ice nucleation mixing model that can predict the freezing behavior of multicomponent particle surfaces immersed in droplets. The model successfully predicts the immersion freezing properties of droplets containing Snomax bacterial particles across a mass concentration range of 7 orders of magnitude, by treating Snomax as comprised of two distinct distributions of heterogeneous ice nucleating activity. Furthermore, the model successfully predicts the immersion freezing behavior of a low-concentration mixture of Snomax and illite mineral particles, a proxy for the biological material–dust (bio-dust) mixtures observed in atmospheric aerosols. It is shown that even at very low Snomax concentrations in the mixture, droplet freezing at higher temperatures is still determined solely by the second less active and more abundant distribution of heterogeneous ice nucleating activity of Snomax, while freezing at lower temperatures is determined solely by the heterogeneous ice nucleating activity of pure illite. This demonstrates that in this proxy system, biological ice nucleating particles do not compromise their ice nucleating activity upon mixing with dust and no new range of intermediary freezing temperatures associated with the mixture of ice nucleating particles of differing activities is produced. The study is the first to directly examine the freezing behavior of a mixture of Snomax and illite and presents the first multicomponent ice nucleation model experimentally evaluated using a wide range of ice nucleating particle concentration mixtures in droplets.https://www.atmos-chem-phys.net/17/13545/2017/acp-17-13545-2017.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
H. Beydoun M. Polen R. C. Sullivan |
spellingShingle |
H. Beydoun M. Polen R. C. Sullivan A new multicomponent heterogeneous ice nucleation model and its application to Snomax bacterial particles and a Snomax–illite mineral particle mixture Atmospheric Chemistry and Physics |
author_facet |
H. Beydoun M. Polen R. C. Sullivan |
author_sort |
H. Beydoun |
title |
A new multicomponent heterogeneous ice nucleation model and its application to Snomax bacterial particles and a Snomax–illite mineral particle mixture |
title_short |
A new multicomponent heterogeneous ice nucleation model and its application to Snomax bacterial particles and a Snomax–illite mineral particle mixture |
title_full |
A new multicomponent heterogeneous ice nucleation model and its application to Snomax bacterial particles and a Snomax–illite mineral particle mixture |
title_fullStr |
A new multicomponent heterogeneous ice nucleation model and its application to Snomax bacterial particles and a Snomax–illite mineral particle mixture |
title_full_unstemmed |
A new multicomponent heterogeneous ice nucleation model and its application to Snomax bacterial particles and a Snomax–illite mineral particle mixture |
title_sort |
new multicomponent heterogeneous ice nucleation model and its application to snomax bacterial particles and a snomax–illite mineral particle mixture |
publisher |
Copernicus Publications |
series |
Atmospheric Chemistry and Physics |
issn |
1680-7316 1680-7324 |
publishDate |
2017-11-01 |
description |
Some biological particles, such as Snomax, are very active ice nucleating
particles, inducing heterogeneous freezing in supercooled water at
temperatures above −15 and up to −2 °C. Despite
their exceptional freezing abilities, large uncertainties remain regarding
the atmospheric abundance of biological ice nucleating particles, and their
contribution to atmospheric ice nucleation. It has been suggested that small
biological ice nucleating macromolecules or fragments can be carried on the
surfaces of dust and other atmospheric particles. This could combine the
atmospheric abundance of dust particles with the ice nucleating strength of
biological material to create strongly enhanced and abundant ice nucleating
surfaces in the atmosphere, with significant implications for the budget and
distribution of atmospheric ice nucleating particles, and their consequent
effects on cloud microphysics and mixed-phase clouds.<br><br>
The new critical surface area <q><span style="text-decoration: overline;"><i>g</i></span></q> framework that was developed
by Beydoun et al. (2016) is extended to produce a heterogeneous ice
nucleation mixing model that can predict the freezing behavior of
multicomponent particle surfaces immersed in droplets. The model
successfully predicts the immersion freezing properties of droplets
containing Snomax bacterial particles across a mass concentration range of 7
orders of magnitude, by treating Snomax as comprised of two distinct
distributions of heterogeneous ice nucleating activity. Furthermore, the
model successfully predicts the immersion freezing behavior of a
low-concentration mixture of Snomax and illite mineral particles, a proxy for
the biological material–dust (bio-dust) mixtures observed in atmospheric
aerosols. It is shown that even at very low Snomax concentrations in the
mixture, droplet freezing at higher temperatures is still determined solely
by the second less active and more abundant distribution of heterogeneous ice
nucleating activity of Snomax, while freezing at lower temperatures is
determined solely by the heterogeneous ice nucleating activity of pure
illite. This demonstrates that in this proxy system, biological ice
nucleating particles do not compromise their ice nucleating activity upon
mixing with dust and no new range of intermediary freezing temperatures
associated with the mixture of ice nucleating particles of differing
activities is produced. The study is the first to directly examine the
freezing behavior of a mixture of Snomax and illite and presents the first
multicomponent ice nucleation model experimentally evaluated using a wide
range of ice nucleating particle concentration mixtures in droplets. |
url |
https://www.atmos-chem-phys.net/17/13545/2017/acp-17-13545-2017.pdf |
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