ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus GmbHGöttingen, Germany10.5194/acp-15-1463-2015Intercomparing different devices for the investigation of ice nucleating
particles using Snomax® as test substanceWexH.wex@tropos.dehttps://orcid.org/0000-0003-2129-9323Augustin-BauditzS.BooseY.https://orcid.org/0000-0001-9495-2165BudkeC.CurtiusJ.https://orcid.org/0000-0003-3153-4630DiehlK.DreyerA.FrankF.https://orcid.org/0000-0002-1477-2920HartmannS.https://orcid.org/0000-0002-9556-2772HiranumaN.https://orcid.org/0000-0001-7790-4807JantschE.https://orcid.org/0000-0002-7292-2122KanjiZ. A.https://orcid.org/0000-0001-8610-3921KiselevA.https://orcid.org/0000-0003-0136-2428KoopT.https://orcid.org/0000-0002-7571-3684MöhlerO.NiedermeierD.https://orcid.org/0000-0002-8265-6235NilliusB.RöschM.RoseD.SchmidtC.SteinkeI.StratmannF.Experimental Aerosol and Cloud Microphysics, Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, GermanyInstitute for Atmospheric and Climate Science, ETH Zürich, Zürich, SwitzerlandFaculty of Chemistry, Bielefeld University, Bielefeld, GermanyInstitute for Atmospheric and Environmental Sciences, Goethe University of Frankfurt, Frankfurt am Main, GermanyInstitute of Atmospheric Physics, University of Mainz, Mainz, GermanyInstitute for Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, GermanyInstitute for Environmental Physics, University of Heidelberg, Heidelberg, Germanynow at: Institute Advanced Ceramics, Hamburg University of Technology (TUHH), Hamburg, Germanynow at: Michigan Technological University, Houghton, MI, USAnow at: Max Planck Institute for Chemistry, Multiphase Chemistry Department, Mainz, GermanyH. Wex (wex@tropos.de)10February20151531463148522August20141September201417December201420December2014This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://www.atmos-chem-phys.net/15/1463/2015/acp-15-1463-2015.htmlThe full text article is available as a PDF file from https://www.atmos-chem-phys.net/15/1463/2015/acp-15-1463-2015.pdf
Seven different instruments and measurement methods were used to examine the
immersion freezing of bacterial ice nuclei from
Snomax® (hereafter Snomax), a product
containing ice-active protein complexes from non-viable Pseudomonas syringae bacteria. The experimental conditions were kept as similar as
possible for the different measurements. Of the participating instruments,
some examined droplets which had been made from suspensions directly, and the
others examined droplets activated on previously generated Snomax particles,
with particle diameters of mostly a few hundred nanometers and up to a few
micrometers in some cases. Data were obtained in the temperature range from
-2 to -38 ∘C, and it was found that all ice-active protein
complexes were already activated above -12 ∘C. Droplets with
different Snomax mass concentrations covering 10 orders of magnitude were
examined. Some instruments had very short ice nucleation times down to below
1 s, while others had comparably slow cooling rates around 1 K min-1.
Displaying data from the different instruments in terms of numbers of ice-active protein complexes per dry mass of Snomax, nm, showed
that within their uncertainty, the data agree well with each other as well as
to previously reported literature results. Two parameterizations were taken
from literature for a direct comparison to our results, and these were a time-dependent approach based on a contact angle distribution (Niedermeier
et al., 2014) and a modification of the parameterization presented in
Hartmann et al. (2013) representing a time-independent approach. The
agreement between these and the measured data were good; i.e., they agreed
within a temperature range of 0.6 K or equivalently a range in
nm of a factor of 2. From the results presented herein, we
propose that Snomax, at least when carefully shared and prepared, is a
suitable material to test and compare different instruments for their
accuracy of measuring immersion freezing.
Introduction
In the Earth's atmosphere, different types
of clouds exist: warm
clouds contain only liquid droplets, cirrus clouds consist solely of
ice crystals, and mixed-phase clouds contain both liquid droplets and
ice crystals. Ice formation can occur by homogenous freezing of cloud
droplets at temperatures below about -38 ∘C, or by
heterogeneous ice nucleation processes. In the latter case, a particular aerosol particle, called an ice nucleating particle (INP), induces the ice
nucleation, which can occur at all temperatures below
0 ∘C. Immersion freezing is one of the heterogeneous
freezing processes, where an INP immersed in a supercooled cloud
droplet induces ice nucleation. For mixed-phase clouds, this
might be one of the most important freezing process, if not
the most important one, as suggested e.g., by and
. Below -38 ∘C, homogeneous
freezing can take place. Thus, mixed-phase clouds, which are most
important for the generation of precipitation outside the tropics,
tend to occur at T>-38∘C. Cirrus clouds found at
T<-38∘C are generally assumed to have formed by
homogeneous freezing; i.e., for cirrus clouds it is thought that
homogeneous freezing is the most important mechanism to nucleate
ice. However, it was recently suggested by that
heterogeneous freezing might be the dominant ice formation mechanism
for convective outflow and synoptically formed cirrus in the Northern
Hemisphere.
In general, the initiation of ice in clouds, i.e., the ice nucleation process, has to be investigated if we want to understand and describe
the formation of precipitation as well as cloud radiative properties,
e.g., in weather and climate models. It should also be mentioned that
ice multiplication processes e.g., might play an
important role for the overall ice content in clouds, too. But even
our understanding of ice nucleation in clouds is still
limited. showed, that a scatter of up to 2 orders
of magnitude in measured ice fractions was obtained for Saharan dust
samples, when results from different instruments which measured ice
nucleation were compared. Mineral dust is considered to contribute
a large fraction or even the majority of INPs worldwide
, and K-feldspar was recently reported by
to be the most ice nucleation effective mineral
dust compound found so far. However, these INPs can only explain ice
nucleation in the temperature range below about
-15 ∘C, while in atmospheric clouds ice is often
observed already at higher temperatures
e.g.,. The presence of biological particles
might contribute to the observed high temperatures for ice formation
in clouds , and recently
it was found that in soil dust, biological components on the dust
particles enhanced or even determined the particles' ability to
nucleate ice .
The ice nucleation ability of biological material has been found to
originate in ice nucleation active macromolecules (INM) such as some
polysaccharides for pollen and
proteinaceous INM for fungi and
bacteria e.g.,and references therein. Both
and were able to determine
the ice nucleation ability of single INM for birch pollen and Snomax,
respectively. While the discovery of INM active in pollen and fungi
was made recently or was only recently intensified again
respectively, it has long been
known that protein complexes are responsible for the ice activity in
bacteria. Much research has been done on the latter topic, and the
literature cited in the following paragraph is only a small selection
of what can be found.
Already and described that
several bacteria occurring in the atmosphere, among them
Pseudomonas syringae, can induce heterogeneous freezing at
comparatively high temperatures, with freezing sometimes setting in
already at about -2 ∘C.
described a gene which produces proteins located in the outer cell
membrane which are responsible for the ice nucleation. This gene is
highly homologous in all ice-active bacteria. A single ice-active
protein was estimated to have a mass of about 150 kDa and to induce
freezing at -12 to -13 ∘C. However, the ice-active proteins
show a tendency to aggregate, forming protein complexes
e.g.,. It was found for
P. syringae, that ice nucleation can be induced in the
temperature range from about -7 to
-10 ∘C. The respective type of protein complexes
active in this temperature region was called group III or class C, and
it was found that they occurred in about “1 of 300 cells” to “almost
all cells” of P. syringae cultures ( and
, respectively). Responsible for group III ice
nucleation behavior are protein complexes of at least two up to a few
single ice-active proteins with diameters of a few nanometers. Much
more rarely, bacterial cells are observed which induce freezing
already at temperatures around -2 to
-4.5 ∘C (group I or class A behavior) and around
-4.5 to -7 ∘C (group II or
class B behavior), where the characterizations in groups is given in
and the one in classes in ,
both giving slightly different temperature ranges. Different
publications give the fraction of cells on which these more ice-active
cells occur with 1 in 104 to 1 in 107, associated with much
larger protein complexes, containing at least 50 proteins
which corresponds to sizes of roughly
some 10 nanometers.
These early findings are in agreement with a recent study by
, who examined immersion freezing induced by
non-viable P. syringae present in Snomax. Examined droplets
contained single or at most a few of the small protein complexes
responsible for the observed group III freezing behavior. Freezing was
mostly induced at temperatures from -7 to
-10 ∘C, and below -12 ∘C no
additional freezing was observed. Snomax is a commercially available
material for artificial snow production and contains non-viable P. syringae bacteria and their fragments, i.e.,
cell constituents and fragments of the cell membrane with or without
attached ice-active protein complex, remnants of the nutrition medium
used for bacterial cultivation, and some other unknown byproducts. It
has been used in the past as surrogate for living bacteria
.
Within the research unit INUIT (Ice Nuclei research UnIT, FOR 1525),
which is funded by DFG (Deutsche Forschungsgemeinschaft), we did an intercomparison, comparing immersion freezing measured by a suite
of different techniques. We examined different test substances. In
order to minimize experimental biases in measured data, we shared the
same samples and the same particle/droplet production techniques as
far as possible while exploring a wide range of
experimental conditions concerning particle sizes, droplet
concentrations and temperatures. We included mineral dust samples and
a biological sample, namely Snomax, in the INUIT comparisons. Results
for the former will be presented in separate papers of the same
special issue, while the results from the respective comparison for
the biological sample will form the focus of this paper.
We present immersion freezing measurements for Snomax, made with seven
different instruments in the framework of INUIT. Different Snomax
concentrations in the examined droplets are covered, ranging from
6×10-12 to 1×10-2 mg per droplet. Also,
different ice nucleation times were employed, ranging from cooling
rates of 1 Kmin-1 to short residence times of below
1 s at a given ice nucleation temperature. Two basically
different types of measurement methods were included. Some studies
examined droplets which had been generated from Snomax suspensions
directly. Others generated dry aerosol particles from Snomax
suspensions to enable a size selection and then immersed each of these
particles in a droplet. These droplets were then examined with respect
to their freezing behavior. In the following, measurement methods and
the modeling approach chosen for the data evaluation are briefly
discussed, before the results are described in
Sect. .
Measurement methods
In this study, we present a comparison between results obtained from
different measurement methods for immersion freezing induced by
Snomax. The following seven different instruments are included in the
comparison (given in alphabetical order): an acoustic levitator
(abbreviated AL herein), AIDA (Aerosol Interaction and Dynamics in the
Atmosphere) cloud simulation chamber, BINARY (Bielefeld Ice Nucleation
ARraY), FINCH (Fast Ice Nucleus CHamber), LACIS (Leipzig Aerosol Cloud
Interaction Simulator), the Mainz vertical wind tunnel (abbreviated WT
herein) and PINC (Portable Ice Nucleation Chamber). A more detailed
description of the instrumentation and measurement methods can be
found in Appendix , together with the respective
citations of the relevant literature.
Snomax from the same batch was used for all measurements unless
mentioned explicitly. It was obtained from SMI Snow Makers AG,
Switzerland and distributed to all participating groups. Care was
taken to keep the sample frozen at all times, besides short (hour
long) breaks during transport by mail from the company to Leipzig and
from Leipzig to the INUIT partners. For the latter the Snomax was sent
in cooled thermal boxes with thermal insulation.
The measurement methods used by the different instruments within this
study can be grouped in two subgroups. On the one hand, there are measurement devices that examined droplets generated directly from
suspensions, which are referred to as suspension methods in this
study. These include AL, BINARY and WL.
The second group consists of AIDA, FINCH, LACIS and PINC, which generally examined droplets
activated on size-selected Snomax particles, and in which also some AIDA
measurements using polydisperse Snomax aerosol were included.
This group of instruments will be referred to as particle methods
herein. Important parameters for each method are given in the
following two paragraphs and also in Table .
Droplets examined with the AL, BINARY and the WT had diameters of
2.0 mm (=4.2µL), 1.24 mm
(=1.0µL) and 0.76 mm (=0.23µL),
respectively. The suspensions from which the droplets were made
contained ultra-pure water and Snomax in defined
concentrations. Altogether, examined concentrations ranged from
10-8 to 10 mgmL-1, covering 9 orders of
magnitude. Figure shows the ranges of Snomax
mass per droplet which were used for measurements by the different
instruments, while the concentrations of Snomax in the suspensions
used to generate the droplet are shown in the legends of
Figs. and .
At each droplet concentration, a total droplet number of 100 droplets
was examined with the AL, and either 144 or 180 droplets were examined
in the case of BINARY, while 50 droplets were examined at each
concentration and at each temperature by the WT. For the AL, ice
nucleation time depended on temperature (see
Appendix ) and the maximum time the droplets spent in
the instrument was 10 to 20 s. BINARY was operated at
a cooling rate of 1 Kmin-1. Data reported for WT are
integrated ice fractions which were obtained 30 s after the
droplets were injected into the instrument, while the instrument
remained at a fixed temperature.
Experimental details for the different measurement
techniques/instruments.
Methods examining droplets made directly from suspensions: droplet diameternumber of dropletscooling rate or ice nucleation timeexamineda,bAL2.00 mm100atemperature dependent,see Appendix BINARY1.24 mm144 or 180a1 Kmin-1WT0.76 mm50b30 sMethods examining droplets activated on aerosol particles: particle diameternumber of dropletscooling rate or ice nucleation timeexamineda,bAIDA200 to 600 nm size-selected,∼1000 to 10 000b∼1 to 3 Kmin-1and polydispersecFINCH900 nm> 2400b∼1sLACIS500, 650 and 800 nm≥2000b≈0.2s at T<-12∘Cup to 1.6 s at colder TPINC500 nm500 to 3000b5 s
a Indicates per concentration, b per data point.
c Polydisperse experiments included also particles
< 200nm.
Snomax mass per droplet examined by the
different instruments. For AL, BINARY, and WT values follow directly from the
Snomax concentration in the suspensions used to produce the droplets, and
from the respective droplet size. For AIDA, FINCH, LACIS, and PINC masses
were derived using Eq. ().
For measurements with instruments belonging to the particle methods (AIDA, FINCH, LACIS and PINC), suspensions were used to generate dry
particles. These particles were mostly in the sub-micron size range
and generated by atomization and subsequent drying in a diffusion
dryer. For polydisperse AIDA measurements, particles in the size
range above 1 µm were also present, as the suspensions were
sprayed into the AIDA chamber directly. For sub-micron particles,
the particle production was similar to that described in detail in Hartmann et al. (2013).
All groups used the same atomizer (unless
explicitly mentioned), which was sent around within the INUIT
community. It was comparable to an atomizer available from TSI
(Constant Output Atomizer, Model 3076), but differed in that the
outlet for the droplets was at the location of the impaction plate,
opposite of the nozzle. In the atomizer, compressed air expands
through an orifice, forming a high velocity jet, which then draws
liquid into the region of the jet and atomizes it, i.e., forms droplets
(see the instruction manual for TSI Model 3076). The suspensions used
in the atomizer had a concentration of 5 gL-1 (unless
a differing value is given). The droplets generated by the atomizer
were dried in diffusion dryers. Subsequently, a DMA (Differential
Mobility Analyzer) was used to select a particle size, and
the size-selected dry particles were then fed into the instruments (i.e., into
AIDA, FINCH, LACIS and PINC). When needed, the particle flow was
diluted with dry, particle-free air to reduce the particle number
concentration. In all of these instruments particles are activated to
droplets which then can freeze upon further cooling.
As for the suspension methods, in the following we give the number of
droplets which were examined by the different particle methods,
together with the ice nucleation times or cooling rates. These values
are also summarized in Table . In AIDA,
roughly 1000 to 10 000 droplets were counted for each data point; i.e., this is the respective total number of droplets analyzed by the
WELAS WhitE-Light Aerosol Spectrometer during a 10 s
measurement period. In LACIS, for each separate measurement at each
temperature at least 2000 droplets (unfrozen or frozen) were counted;
for PINC there were roughly 500 to 3000, and there were at least 2400 in FINCH. In
AIDA, cooling rates used to obtain the data presented herein ranged
roughly from 1/50 to 1/20Ks-1 (i.e., approx. 1 to
3 Kmin-1). Ice nucleation times in the cooled sections in
FINCH, LACIS and PINC were ∼1s, < 1s
(temperature dependent) and 5 s, respectively.
Data analysis
For the presentation of the data in this study, a singular, time
independent description was chosen. derived
nucleation rates for the immersion freezing of group III protein
complexes in Snomax (thus for P. syringae), i.e., for those
protein complexes which become ice-active at roughly
-7 ∘C. Results in were found to
agree with other studies referenced therein, showing that nucleation
rates increase steeply over a narrow temperature range. This indicates
that the group III protein complexes responsible for inducing the
observed ice nucleation are all comparably similar in their ice
nucleation ability. Furthermore, it was recently shown that ice nucleation by
Snomax shows only a very small time dependence at cooling rates comparable to
the current intercomparison , and hence a time-independent
treatment of the freezing process seems justifiable. It was clearly shown in
, that the number of ice nucleation active
macromolecules (INM) (i.e., the protein complexes) scaled with the
volume of the examined particles, and therefore also with the mass of
Snomax present in a droplet. Therefore, in the study presented here, the ice nucleation ability will be expressed per unit mass of Snomax. For similar cases, the following
description for the frozen fractions fice (i.e., the number
of frozen droplets divided by the total number of examined droplets)
observed for immersion freezing of droplets containing biological
material was already introduced by and again
recommended in :
fice(T)=1-exp(-nm(T)⋅Cm⋅Vd)nm(T) is the number of INM per unit of dry Snomax mass,
Cm is the mass concentration of Snomax in the examined
droplets and Vd is the droplet volume and T the
temperature in ∘C. Equation () can be used
directly for the determination of nm for those
measurements, in which droplets of a known concentration are examined,
i.e., in our study the suspension methods AL, BINARY, and the
WT. For each suspension method, the examined droplets all had an identical size,
and during each individual experiment, all droplets had the same Snomax concentration
(and different concentrations in different experimental runs). Moreover, as immersion freezing can be assumed to be droplet-volume independent, it ultimately is only necessary to know how many
INM were present in a droplet initially. If, in one of the
suspension methods, a droplet were to change its size (and hence
concentration) due to evaporation or additional condensation, the
number of INM present in a droplet would not change. And therefore,
the ice nucleation behavior of a droplet would not be affected. This,
however, holds only as long as the droplet would not evaporate so much
that a freezing point depression due to increased solute concentration
started to influence the ice nucleation process
.
For the particle methods, neither the exact droplet size was known at
the time at which ice nucleation is induced, nor the Snomax
concentration in the droplet. But as particles used were either size-selected, or the particle size distribution was measured, the
diameter of the examined particles was known
(dp). Snomax particles were generated from
suspensions. In Sect. we will show that the
majority of cell fragments contained in the generated particles were
in a size range below 250 nm, together with soluble
material. Therefore, it can be assumed that the particles that were
examined in this study were spherical. Together with the Snomax
density (ρ, see also Sect. ), the mass of
Snomax per particle (and hence per droplet) is then obtained as
M=Cm⋅Vd=ρ⋅π6⋅dp3.
Now Eq. () can be written as
fice(T)=1-exp-nm(T)⋅ρ⋅π6⋅dp3.
It should be mentioned here that the relationship presented in
Eq. () was also used to obtain the mass of Snomax per
droplet for the particle methods (i.e., AIDA, FINCH, LACIS and PINC)
shown in Fig. . Please note that Eqs. () and () are valid
for size-selected particles, i.e., for cases where, during one experiment, particles of the same dp
are used, or for which, alternatively, a mass mean dp can be determined.
In experiments had been conducted such, that not
all of the examined droplets contained INM. It is obvious that this
occurs when the number of INM present in an ensemble of droplets is
smaller than the number of droplets. In general, when producing
particles or droplets from a suspension, all present INM are
distributed randomly over the produced particles/droplets, following
Poisson distribution for details see:
λ=-ln(1-fice∗).
While λ represents the average number of INM per particle/droplet, fice∗ denotes
the fraction of particles/droplets which contain at least one of the INM. For λ=4.7,
1 % of all particles/droplets do not contain any INM
(fice∗=0.99). At λ=2,
fice∗ is only
86 %. fice∗< 1 shows up in the measurements
when fice(T) levels off in a plateau for temperatures
below about -12 ∘C, where in the plateau region
fice(T)=fice∗. For the present study, it
was possible for most instruments to run experiments such that
a plateau with fice∗< 1 could be observed for at
least one data set. This occurs when there are droplets that contain no INM,
which can occur for suspensions with correspondingly low concentrations or for
particles of respective sizes which might consist of biological material without
containing an INM. In , λ was
parameterized as a function of dp3, i.e., proportional
to particle volume, and data obtained in this study will be compared
to this parameterization (see Sect. ).
Different methods examine different numbers of droplets. Depending on
the number of droplets examined in a particular experiment, an
additional uncertainty in the measurements appears for those
experiments where fice∗< 1, based on the fact that
a comparably small number of INM is Poisson distributed to all
particles/droplets. This is shown exemplarily for four different
values of fice∗< 1 and a range of droplet numbers in
Fig. , where the standard deviations represent theoretically
predicted uncertainties which are due to the examination of only a limited number of droplets.
For calculation of these values,
1 million
droplets were evaluated in all cases. (To give an example,
for a case when the simulation was done for 100 droplets, it was done
10 000 times, and the standard deviation was taken from the results of
these 10 000 calculations.) At e.g., λ=0.5, when 50 or 100
droplets are examined, the relative standard deviation is
17 and 12 %, respectively, while it decreases to
3 % when 2000 droplets are examined. This clearly shows that
the measurement uncertainty decreases with an increase in the number
of droplets examined as an ensemble. This was examined here to acquire
a measure for the uncertainty that can be expected for the different
data sets presented in the following.
Measurements and resultsDetermination of the Snomax density and of the size of bacterial fragments
As demonstrated in Sect. , the density of Snomax
particles is needed for the data evaluation. The effective density of
these particles (ρeff) was determined by using
a combination of mobility and aerodynamic measurements. For the
measurements, particles were produced using the same atomizer
described above, and a DMA was used to select particles sizes of
either 320 or 550 nm. Behind the DMA, the mass distribution of
the Snomax particles preselected with the DMA was measured with the
Aerosol Particle Mass Analyzer (APM-II KANOMAX, Model
3601). ρeff was obtained from the combined measurements
of particle electrical mobility dp and mass M:
ρeff=6M‾πdp‾3,
where dp‾ and M‾ are the average
mobility diameter and average mass of the singly charged Snomax
particles. The measurements were done at 10 differently concentrated
Snomax suspensions (from 0.1 to
5 gL-1). Figure shows the values of
ρeff plotted as a function of concentration. Note that
ρeff is an apparent density and may include the effect
of porosity and particle shape
see. A variation in ρeff is
seen for the different examined particle sizes and also for the
differently concentrated Snomax suspensions, but it is very pronounced
only for concentrations which were much lower than those used in our
study. The examination of only two different particle sizes is not
sufficient to derive a trend for ρeff with size, and
hence it was decided for this study to use the average value of
1.35 gcm-3 for the data evaluation.
Furthermore, as mentioned above, it was assumed that spherical
particles result when sub-micron Snomax particles are produced from
suspensions followed by drying. Snomax consists not only of non-viable
bacteria, but also of nutrient remnants of the culture medium and of
material from the interior of broken bacteria, all of which is present
in a Snomax suspension. It is known that P. syringae bacteria
themselves are rod shaped with a diameter and length roughly below
1 and 2 µm, respectively
. and
both found, when using a particle generation method similar to the one
used here, that a slightly elevated amount of Snomax particles was
produced at sizes of roughly 800 nm (interpreted as whole
bacterial cells), while a large amount of particles was produced at
sizes down to below 100 nm. We will discuss in the following
paragraphs that these smaller particles also contain ice nucleation
active protein complexes originating from P. syringae
bacteria, together with other substances contained in Snomax.
Average fice∗ and
the respective standard deviation for different numbers of examined droplets
and for different values of λ, obtained by theoretical
considerations.
The effective density of Snomax measured for
particles generated from differently concentrated suspensions for two
different dry particle sizes.
For the production of Snomax, the P. syringae bacteria are
freeze-dried and irradiated to make them non-viable, and during the
process the bacteria might already be damaged. Particle generation
with an atomizer might damage them further, due to forces appearing in
the jet region of the atomizer, where the suspension fed into the
atomizer is torn into droplets. However, the protein complexes
responsible for the ice nucleation activity are rather small, on the
order of some nanometers for group III and some 10 nanometers for the
more ice-active groups I and II (see Introduction for details).
These complexes retain their ice nucleation activity as long as they
are still embedded in a fragment of the cell membrane, shown e.g., by
the fact that Snomax particles much smaller than the original bacteria
were found to be still ice-active .
We used a dynamic light scattering (DLS) method to determine the size
of intact bacteria and of bacterial fragments present in the examined
Snomax particles. For that, measurements were done with a StabiSizer
(Microtrac Europe GmbH, PMX 200CS). A detailed description of the
instruments and its applications can be found in
. In short, the diameter of the fragments was
determined from measurements of scattered light at an angle of
180∘. The light source was a laser with a wavelength of
750 nm.
At first, the size distribution of bacteria and fragments in a Snomax
suspension was examined using the DLS method directly after suspending
Snomax in water. The Snomax concentration was the same used to
generate dry particles in an atomizer with subsequent drying for the
AIDA, FINCH, LACIS, and PINC experiments,
i.e., 5 gL-1. Additionally, particles were produced from
these suspensions using two different particle generators, either
a nozzle spray disperser or the atomizer used for this
study. Dispersion of the suspensions was followed in both cases by
diffusion drying, and the resulting particles were fed into
a ventilated stainless steel vessel chamber (volume ∼4m3, temperature ∼20∘C, pressure
∼1000 mbar). Particles were then collected on a filter
(47 mm Nuclepore® substrates,
Whatman filter 111 106, 0.2 µm pore size) and subsequently
washed off to produce suspensions for further examination with the DLS
method.
Size distributions of the particulate matter
present in Snomax suspensions as measured with DLS. The blue curve represents
the size distribution seen in a freshly produced Snomax suspension, the black
and red curve show size distributions as present in particles after
dispersion with a nozzle spray disperser or an atomizer, respectively.
In the following paragraph, the term “particulates” is used to
denote particulate matter present in the examined suspensions, e.g.,
bacterial cells or fragments thereof. Results from the DLS
measurements are presented in Fig. . The diameter
(dDLS) of the particulate matter present in a freshly made
Snomax suspension ranged predominantly between 600 and
2000 nm. The distribution maximum is at 1000 nm. When
suspensions had been sprayed with the nozzle spray disperser, DLS
detected a larger amount of particulates in the range
> 400nm, some small particulates between 50 and
400 nm and a lower amount of particulates with larger
sizes. The maximum shifted slightly to 700 nm. The suspended
particulate matter consists presumably of whole bacterial cells and
maybe some larger fragments or crumpled cells. When the atomizer had
been used, the majority of fragments appeared in the diameter range
from 50 to 250 nm (with only a few fragments of the
size observed before remaining). This shows that particle generation
by the atomizer (even when no impaction plate was installed)
disintegrated the bacterial cells to smaller pieces. While this
enables particles down to a few hundred nanometers to also carry INM,
it does not change the number of INM per mass of dry Snomax, as long
as the protein complexes are not destroyed. This is in line with
a finding presented later in this study (Sect. );
namely that the distribution of INM occurs linearly with the Snomax
mass over a wide range and covering both methods examining droplets
made from suspensions directly and methods examining droplets
activated on dry Snomax particles.
Frozen fractions as a function of
temperature (fice) as measured by BINARY for 14 differently
concentrated Snomax suspensions for droplets with diameters of
1240 µm (i.e., 1 µL).
BINARY data
Figure shows fice as obtained from
BINARY for 14 different Snomax concentrations in the suspensions. The
concentrations ranged from 10-8 to 10 mgmL-1 (see legend
in Fig. ). For each of the concentrations, four
or five runs including 36 droplets each were made; i.e., a total of 144
or 180 droplets was examined. For cooling rate and size of the
examined droplets see Table . Data were
recorded with a resolution of 0.1 K in the range between
-40 and 0 ∘C. Data are only shown
in the temperature range down to -20 ∘C, as already
pure water had been observed to freeze at lower temperatures. This
could be attributed to ice nucleation induced by components in the
water or by the contact of the droplets to the walls of the BINARY. It
should be mentioned here that this is irrelevant for the present study
as the INM in Snomax are ice-active well above
-12 ∘C.
For the highly concentrated droplets, a sharp increase in
fice is seen at temperatures as high as
-3 ∘C, and after the sharp increase all droplets are
frozen. The temperature at which the increase occurs decreases with
Snomax concentration. For concentrations above 4×10-6mgmL-1, the maximum value obtained for
fice reaches 1 at temperatures above
-10 ∘C. For lower concentrations, a plateau for
fice< 1 is observed in the temperature range below roughly
-12 ∘C; i.e., for these concentrations not all
droplets freeze. This is similar to the plateau observed in
(see Sect. ). It shows that in
this concentration range only a comparably small number of INM is
distributed to the generated droplets, following a Poisson
distribution, such that some droplets contain no INM at all. The
plateau value fice∗ lowers with lowering
concentration, as the number of droplets containing no INM
increases. For the two lowest concentrations, the number of INM
containing droplets was so low that only a few single droplets froze,
making these two data sets very scarce.
Acoustic levitator and Mainz vertical wind tunnel
Figure shows fice as measured with
AL and WT for different Snomax concentrations in the droplets (see
legend). For ice nucleation times, sizes and numbers of examined
droplets see Table . Data were recorded with
a resolution of 1 K. Measurements are presented for six and
two different Snomax concentrations for the AL and the WT,
respectively. For the three highest concentrations used for
experiments with the AL and the highest one used for the WT, less than
five data points exist. This is due to the steepness of the increase in
fice and the comparably coarse temperature resolution.
Frozen fractions as a function of temperature
measured with AL and WT for differently concentrated Snomax suspensions. Data
for the one data set which showed a plateau value below 1 are displayed with
closed symbols. When the same symbols were used, the mass of Snomax per
droplet was similar.
Comparable to what was found for BINARY, some of the most concentrated
droplets initiated freezing at high temperatures, even already at
-2 ∘C. Again, a decrease in Snomax concentration per
droplet corresponds to a shift of the freezing temperatures towards
lower values. For the lowest concentration used in the WT, a plateau
develops at fice∗< 1 in the temperature range
between -12 and -20 ∘C. In all
other cases fice∗ reaches 1; i.e., all droplets
froze at the lowest examined temperatures. In general, the curves are
somewhat more shallow than they are for BINARY. For the latter, curves
which go up to fice∗=1 reach that value at
a temperature of -9 ∘C or above. This is different
particularly for the AL. Data for the lowest, second lowest, and third
lowest concentration go up to fice∗=1, but reach
this final value only at -18,
-12, and -11 ∘C,
respectively. A direct comparison can be done using the data set
obtained for the second lowest concentration with the AL, which is
similar in mass per droplet to BINARY data with a concentration of
2.6×10-5mgmL-1. Data from the WT are similar
to those from the AL. For measurements with the WT, a similar mass of
Snomax in the droplets was used as in the AL (indicated by the use of
the same symbols in Fig. ). The strongest
difference between AL and WT is seen for the data sets with the lowest
concentration, where data for the AL increases up to 1, while
a plateau is observed at 0.87 for the WT.
LACIS, FINCH and PINC
Values of fice as measured by LACIS, FINCH and PINC are
shown in Fig. . Experimental details are again
summarized in Table . The three different
instruments all used dry particles produced from a Snomax
suspension. PINC data labeled with #1 in
Fig. were obtained during a stay of the
instrument at TROPOS, where PINC measured in parallel with
LACIS. During those measurements in Leipzig, a cyclone had been
installed in the particle generation setup to avoid multiply charged,
i.e., larger particles. PINC data labeled #2 and #3 were
measured at the ETH in Zürich, Switzerland, where particles were
generated by a different atomizer than otherwise used in this study,
and in one case also by a different batch of Snomax. Open symbols in
Fig. given for LACIS represent the data
published in , for which particles had also been
generated using a different atomizer and a different batch of
Snomax. LACIS and PINC data are given for particle diameters of
500 nm, and for LACIS additionally data for 650 and
800 nm are shown. FINCH data were measured at its home
laboratoy, the Goethe University in Frankfurt, Germany, for a particle
diameter of 900 nm. A pre-impactor was installed at the DMA to
avoid multiply charged particles.
Frozen fractions as a function of
temperature measured with FINCH, LACIS and PINC for different dry particle
sizes. Open symbols given for LACIS represent the data published in
. PINC data labeled with #1 were taken during
a campaign at LACIS, #2 and #3 denote data taken at ETH using the INUIT
snomax sample and a different Snomax sample, respectively. For more details
on the different data sets see Sect. .
For LACIS, error bars given in Fig.
correspond to standard deviations obtained from separate measurements,
while for FINCH and PINC they represent standard deviations obtained
from averaging several subsequently measured data points in one
run. The errors were found to compare well to the uncertainties shown
in Fig. , which had been obtained
theoretically.
As for BINARY, the AL and the WT, also here a steep increase in
fice is seen, however only for temperatures roughly above
-7 ∘C. All curves show a plateau with
fice∗< 1. This is all indicative of the fact that
the mass of Snomax included in the examined particles is much lower
than that included in most of the droplets examined with BINARY, the
AL and the WT, resulting in a lower λ. But in the LACIS data
set it can be seen already that fice∗ (and
λ) increase with increasing particle size.
A comparison of LACIS data obtained in the framework of this study
with older data obtained by reveals some
deviations (compare the data for 650 nm from the old and new
data set), but these are still within measurement uncertainty. The
new data set was obtained roughly 2 years after the old one, and the
two measurements differed in the Snomax sample that was used, in the
concentration of the Snomax suspension used to generate the particles
and in the atomizer itself used an atomizer following the TSI
design without modifications. Similarly, a comparison
can be done for PINC data obtained at two different locations (TROPOS
and ETH), which also means that different atomizers and different
concentrations in the Snomax suspension were used, together with two
different batches of Snomax (both done at ETH). In general, the
increase in fice observed by PINC occurs roughly
2 K below where it was observed for LACIS. But the PINC data
obtained for the different Snomax batches and different atomizers
agree well with each other. These results obtained from LACIS and PINC
can be interpreted such that likely neither the atomizer used to
generate the particles, nor the concentration in the suspension nor
the Snomax batch had a clearly noticeable influence on the results of
the measurements. It should, however, be pointed out that some
participants of this study reported that Snomax was observed to show
a decline in ice nucleation ability, particularly when it was stored
above 0 ∘C for some length of time (weeks), and less
so but still noticeable when it was stored frozen for several months
(data not shown in this study).
fice∗ for 500 nm particles examined with
LACIS and PINC agree well with each other for temperatures below about
-12 ∘C, while it was already mentioned above that
PINC observed the onset of ice nucleation at lower temperatures (by
roughly 2 K), compared to LACIS. This might originate in the
measurement principle of PINC (see Appendix ), where
supersaturation with respect to ice and water is generated by
a temperature gradient between two iced walls. For measurements at
high temperatures (roughly -10 ∘C and warmer), it is
not possible to generate high supersaturation with respect to water
any more, and residence times for supersaturated conditions become
very short. Hence PINC measurements in the temperature region above
-10 ∘C might be biased by instrumental limitations.
Frozen fractions as a function of temperature,
measured with AIDA during nine different experiments. Different dry particle
sizes or size distributions had been fed into the chamber. The diameter given
in the legend indicates the effective volume mean diameter and, in
parenthesis, the mobility diameter selected at the DMA is given in addition.
FINCH data were taken for a particle diameter of 900 nm, and
a plateau is observed close to that observed for 800 nm
particles with LACIS. Droplets examined in FINCH contain roughly the
same Snomax mass as droplets with the lowest concentrations examined
in the AL and the WT or droplets with Snomax concentrations between
2.7×10-7 and 1.0×10-6mgmL-1
examined in BINARY. The respective data sets from AL, BINARY, LACIS,
PINC and WT show a steep increase in fice only below
-7 ∘C, while fice measured by FINCH is
0.2 already at -6.5 ∘C. Unfortunately, no FINCH data
are available in the temperature range above -6 ∘C
for further comparisons.
AIDA
Figure shows data obtained with AIDA. Nine
separate runs were evaluated. For each run, the particle size spectrum
present in AIDA was different. While for some runs a polydisperse
particle size distribution was used, size-segregated particles were
fed in for others (see legend). In all cases the complete particle
size distribution from 10 to 17 000 nm was
measured and taken into account to calculate total particle number
concentrations and related parameters. A summary of cooling rates,
particle sizes, and numbers of examined droplets is again given in
Table .
For five of the runs presented here, expansions in the AIDA chamber
were started when the temperature in AIDA was above
-7 ∘C. For these cases, droplets were activated on
the particles before AIDA was cooled to the expected onset temperature
for the immersion freezing of the Snomax particles, and immersion
freezing could set in as soon as the expansion cooled the chamber
sufficiently. For any of these runs, a series of data points (2 up to
5), all averaged over 10 s, is presented in
Fig. . The calculation of fice was
limited to the early ice formation and growth period with ice crystals
well below the size limit of about 50 µm in diameter at
which settling losses may affect the measured ice crystal number
concentration. For four AIDA runs, the expansions were started at
a temperature of about -9 ∘C, so that
supersaturation with respect to water, and hence droplet activation,
was only reached below -9 ∘C. In these cases,
droplets were activated at temperatures where the Snomax particles, as
soon as they were suspended in the growing droplets, induced freezing at very
high rates. Therefore, the formation of droplets was followed by
a steep increase in the number of ice crystals, and for these runs,
only the maximum value of fice is depicted in
Fig. .
Not many data points exist in the temperature range in which the
plateau would be expected; i.e., there are no data below
-12 ∘C and four data points between
-10 and -12 ∘C. These four
points were obtained for differently sized particles and show a range
of values for fice. These differences are mainly caused by
a different Snomax mass contained in the droplets, i.e., by
a different aerosol particle size present during the different
runs. This will be addressed later. A steep increase of
fice in the temperature range between roughly
-7 and -10 ∘C is visible,
similar to what was observed for most other instruments.
ComparisonsComparing frozen fractions in the plateau region
Immersion freezing induced by P. syringae is known to set in
well above -12 ∘Cmostly even above
-10 ∘C, e.g.,, and as shown for the
separate instruments in Sect. , this was observed in
the current work as well. As discussed above, some measurements were
made for droplet ensembles for which not each droplet contained an
INM. In these cases, a plateau formed, and the respective frozen
fractions are denoted as fice∗ herein. These cases
are examined in more detail now. This is done following an approach
introduced in . For that, we used
Eq. () to calculate λ, based on
fice∗. For each instrument where the respective
data were available, and there for each particle size or Snomax
concentration in the droplets, an average fice∗ was
obtained for temperatures ≤-12 ∘C. For BINARY,
again only data ≥-20 ∘C were considered. AIDA
data were only taken at temperatures above -12 ∘C,
and the four data points sampled between -10.5
and -12 ∘C were also included.
Average number of INM per particle or droplet as
a function of the third power of particle diameter or mass per droplet,
respectively, for data sets that showed a clear plateau with
fice∗< 1. Grey symbols represent data published
in . The grey line is the corresponding fit function
derived in , which also describes the data collected in
the present study well. The black line represents a fit obtained for this
study (for details see text).
Figure shows the respective data, where λ is
plotted versus dp3. For data from BINARY and the WT,
Eq. () was used to convert the mass of Snomax
contained in the droplets to dp3, using
ρ=1.35gcm-3. The grey symbols in
Fig. represent data from , and
the grey line is the relation given therein between λ and
dp3; namely, λ=F⋅dp3 (with
F=9.995×10-10nm-3).
The uncertainties shown in Fig. are taken from the
measurement uncertainties of fice. These uncertainties are
similar to those which can be obtained based on the number of droplets
counted by the different instruments, besides for the two suspension
methods AL and BINARY. For these two, uncertainties which are based on
counting statistics are larger than the experimental uncertainties of
the measurements, likely due to the comparably low number of examined
droplets. Hence, for these two, also uncertainties taken from the
analysis presented in Fig. are shown in
Fig. , displayed with broader error bars.
It can be seen that the data point for the largest λ from the
BINARY data set deviates from the linear relationship seen for most
data points in Fig. . At large λ values, small
deviations in fice cause a large uncertainty in λ,
due to the strong non-linearity of λ as function of
fice, particularly for fice> 0.95, i.e., for
λ> 3. Hence the data point from BINARY for the largest
λ is less well constrained than the others, and data for
λ> 3 can not be expected to follow a linear behavior as
otherwise displayed in Fig. . AIDA data included in
Fig. deviate towards lower values. However, because
of the fast ice crystal growth at temperatures around
-10 ∘C already mentioned above, in a single AIDA
expansion run it was not possible to measure the full transition of
fice from its steep increase below about
-10 ∘C to the plateau value. Only four data points
were obtained at temperatures between -10.5 and
-12 ∘C, were the plateau was not yet fully reached
according to most other data sets. This could explain the slight low
bias in λ seen for AIDA data.
Two new fits for data shown in Fig. were also done
for data points obtained in this study for T<-12∘C
and λ< 3. For that, data obtained in this study was used
together with data from in one case, while for
the other case data from was excluded. For these
two cases, values of F of 8.21×10-10nm-3
and 8.18×10-10nm-3 were obtained,
respectively. This is less than 20 % lower than the
respective value derived based on data from
alone. The resulting fits are very similar and are depicted together
as one black line in Fig. . Generally, it can be said
that data obtained in this study align well with those from
.
In general, the data presented in Fig. confirm that
the distribution of INM over the droplet population can be well
described using a Poisson distribution. When a sufficiently small
number of INM is distributed over a sufficiently large number of
droplets, so that not all of the generated droplets contain an INM,
a plateau at fice∗< 1 occurs below
-12 ∘C. Moreover, the presented analysis included
the determination of dp3 for BINARY and the WT based on
the mass and density of Snomax in the droplets. The fact that a good
comparison was found with data from FINCH, LACIS and PINC justifies
the value used for the density of Snomax, where, however, it should be
pointed out that values for ρeff between 1.2 and
1.5 gcm-3 would only lead to a deviation in the Snomax
mass per droplet of 10 % for the suspension methods, which
would result in error bars still being located within the respective
symbols depicted in Fig. .
Comparing active site densities per mass, nmBINARY
Here we first show and discuss values of nm (i.e., INM
per unit of dry Snomax mass) as derived from BINARY data, and then
compare and discuss the respective values derived from measurements of
all other instruments.
Figure shows nm derived from
measured fice using Eq. (). Although 9
orders of magnitude were spanned with respect to the Snomax
concentrations in the examined suspensions, data on nm
for all these different concentrations fall nicely together. After
a first increase in fice starting at roughly
-2 ∘C, a slight shoulder is visible in the data at
nm∼106mg-1 and
∼-6 ∘C. A second strong rise in nm
is seen in the temperature range from -7 to
-9 ∘C, leveling off at a value of
nm∼109mg-1.
BINARY data represented as number of INM per
dry Snomax mass, nm, as a function of temperature, for all data
shown in Fig. and using identical symbols.
Number of INM per dry Snomax mass as a function
of temperature, derived from measured fice of all instruments,
i.e., for all data shown in Figs. to
. BINARY data are solely displayed in red, but otherwise
the same symbols and color codes are used as in Figs.
to ; i.e., in all cases data from one instrument are
always displayed in a single color. The right panel is similar to the left,
zooming in on values for
5×106 mg-1<nm< 2.5×109mg-1 and on temperatures
>-21 ∘C.
The two clearly distinct rises show that the ice activity comes from
two clearly different types of INP (i.e., from two distinct types of
INM or more specific two different protein complexes (remember that we
are dealing with P. syringae)). In each of the two
temperature ranges, one type is ice-active, corresponding to different
groups or classes as described above (see Introduction). Group III
behavior is seen clearly in the temperature range below
-7 ∘C. All INM active above -7 ∘C
will be ranked as group I, as no further clear discrimination between
different types of INM can be seen in this temperature range. In both
temperature ranges, below and above -7 ∘C, a rise of
fice as well as of nm is distributed over
a certain temperature range, as even within one group of INM there are
small differences between the different protein complexes. As the
temperature lowers, more and more of the respective INM induce ice
formation. When a plateau is reached, all INM of one group which are
capable of inducing ice have done so. Therefore the plateau reveals
how many INM per mass of dry Snomax are present in the sample. As
mentioned above, this is ∼106mg-1 and
∼109mg-1 for the two groups of INM observed here.
For T>-6∘C, only droplets made from suspensions
with concentrations >10-5mgmL-1 froze. This is in
line with the fact that the more ice-active group I-INM occur roughly
3 orders of magnitude less frequent than the less ice-active
ones. For a concentration of 10-8mgmL-1, even the
more abundant group III-INM were hardly present in any of the droplets
(see Fig. ), and hence at concentrations
< 10-5mgmL-1, it can be expected that the more ice
active but less abundant group I-INM ceased to populate the droplets.
Overall comparison
In Figure , values for nm are shown for
all fice data presented in Sect. , where
Eqs. () or () were used to obtain
nm for those methods which examined droplets from
suspensions or size-segregated particles, respectively. The panel on
the left of Fig. gives an overview of all data,
while the panel on the right is an enlargement of a part of the
former.
Data of all different instruments are close to each other, with some
exceptions. As described above, also here a region can be seen in
which fice increases linearly for most data sets, in the
temperature range from roughly -7 to
-9 ∘C, and the plateau in nm is
visible roughly below -12 ∘C. Of all data down to
-12 ∘C, and for nm between 2×106mg-1 and 7×108mg-1,
72 % of all data points fall within a 1 K band and
78 % within 2 K band around the mean. In the region
where nm forms a plateau, all data are found in the
range from 7×108mg-1 to 2.1×109mg-1, i.e., less than a factor of 3 apart, with an
average value of 1.4×109mg-1. Hence, apart from
issues which will be discussed below, data from the instruments
included in this study agree quite well.
For the AL, all values for nm below
-8 ∘C are clearly lower than those from all other
instruments. A similar effect is also seen, albeit only weakly, for
data from the high concentrated droplets examined in the WT, which,
however, might be traced back to the temperature resolution of only
1 K of that data set. The observed lower nm
values for the AL are related to the fact that the respective curves
for fice did increase less steeply than those reported by
other instruments and only leveled off below -10 ∘C
(Sect. and Fig. ). Data
from the WT obtained for the low Snomax concentration increase almost
as steep as the bulk of the data in the temperature range below
-10 ∘C and form a plateau in nm with
values slightly above the bulk of the data. Here, the comparatively
low number of examined droplets corresponds to a comparably large
uncertainty in the data which causes these data to agree with the bulk
within measurement uncertainty (see Sect. together
with Figs. and ).
FINCH, as already discussed for fice, did not detect the
steep increase in nm between -7 and
-9 ∘C. Instead, nm measured at
-6.5 ∘C does not differ significantly from those
values measured between -8 and
-12 ∘C, while nm measured at
-13 ∘C is almost twice as large as values measured
at higher temperatures.
As discussed above, a somewhat delayed increase for the PINC data
compared to the bulk is visible. This might originate in the fact that
the instrumental limitations impede immersion freezing measurements at
temperatures above -10 ∘C and cause very short
residence times at these comparatively high temperatures. It should
also be mentioned that all of the PINC data for
T>-12∘C were done with a different
atomizer; however, this is likely not the reason for the deviation, as data for
T<-12∘C are in agreement, no matter which atomizer
was used. PINC data in the plateau region agree well with the bulk. It
should be mentioned that nm values for
T<-12∘C, i.e., in the plateau region, when derived
from PINC and also from LACIS data, show a scatter of roughly a factor
of up to 1.5 when these measurements were done repeatedly at the same
temperature. The observed scatter is larger in the temperature range
above -9 ∘C, particularly for LACIS data, which,
however, originates from the steep increase in fice and
nm at these temperatures.
Above -10 ∘C, nm derived from AIDA
measurements agree with the bulk of the data. In the range below
-10 ∘C, the two data points obtained from
measurements examining polydisperse particles are among the lowest
ones found at the respective temperatures, and they are are lower than
the two AIDA data points from monodisperse measurements done in this
temperature range by about roughly a factor of 2. A possible
explanation could be that polydisperse measurements in AIDA include
very small aerosol particles for which the distribution of INM might
not follow a Poisson distribution.
When the above explicitly mentioned data are excluded from the
examination, a much larger fraction of all data is included in the
1 and 2 K bands described above. A discussion
motivating the exclusion of these data is given in the section
following below. These data are BINARY data for
T<-20∘C, which generally had been excluded in the
analysis presented herein, data from the AL for T≤-9∘C, the two polydisperse measurements done with
AIDA at T<-10∘C, the FINCH data point at
-6.5 ∘C and PINC data for
T>-10∘C. When these data are excluded, of all data
down to -12 ∘C and for nm between
2×106mg-1 and 7×108mg-1,
86 % of all separate data points fall within a 1 K
band and 91 % within a 2 K band around the mean,
while, as before, all data in the plateau region are less than
a factor of 3 apart from each other.
Discussion
The comparison introduced in the study presented here taught us some
lessons. But before we discuss them, we want to mention that, unless
otherwise stated, the following remarks are generally valid also for
other suspension methods or other particle methods, not only for those
included in this study.
Based on the results from the current work, we propose that Snomax is
an appropriate material to be used as a test substance for future
studies, at least when carefully shared and prepared. The majority of
the data obtained for this study was collected using Snomax from the
same batch and using the same atomizer. However, data measured by
LACIS and PINC using different Snomax batches, atomizers and
suspension concentrations have also been included here. Given that
none of the variations in sample generation and preparation noticeably
influenced the measurement results, we suggest that Snomax could be
used as a standard reference aerosol for future comparisons. This can
also encourage others to compare respective results with those
published herein.
We also note that the examination of the complete temperature range
can yield additional information, compared to the examination of only
the temperature range in which a strong increase in fice
is observed. The range in which the strong increase is observed is
important when temperature accuracy is examined. However, also temperature
ranges were observed in which no additional ice nucleation was observed, i.e.,
in which nm was rather constant (around -6 ∘C and
below -12 ∘C). When fice measured in these temperature
ranges is below 1, then these measurements, made for Snomax or other substances,
can give information about the counting accuracy of the instrument or about
instrumental issues. To obtain the respective measurements with values of fice below 1,
either sufficiently low concentrated suspensions for suspension methods, or a respectively small
particle size for the particle methods has to be chosen, where, however, in our study all
particle sizes which could possibly be chosen with a DMA were sufficiently small.
In our study, measurements in the plateau region below -20 ∘C revealed a clear increase
in fice for the BINARY data sets obtained for the four lowest concentrations.
This increase occurred well above the homogeneous nucleation temperature of -38 ∘C,
where an increase is unavoidable. These BIANRY data were neither displayed here, nor were they included
in the analysis of the ice nucleation behavior of Snomax. The observed increase was either caused by
impurities in the water used for dilution or by the substrate surface itself, as evidenced by the
fact that the respective nm values did scale with the dilution factor, i.e., a reduction
of Snomax concentration by a factor of 10 resulted in an increase in the observed nm
values by a factor of about 10. A possible influence of the substrate is avoided in AL and
WT. But generally, for suspension methods the possibility of an
influence of impurities in the water increases with the size of the
examined droplets. Another disadvantage of the suspension methods is,
that usually only a smaller number of droplets can be examined,
compared to the particle methods. This number of droplets still
differs between different suspension methods; e.g., while BINARY
measurements are automated and examine 36 droplets in one run, in both
AL and WT single droplets are examined separately consecutively.
In Figure , it can be seen that data for the more ice-active group I-INM were only reported by the AL and BINARY, indicating
an advantage of the suspension methods. At the same time, a weakness
of the particle methods is apparent, which is due to reaching the
lower limits of detection. Suspension methods can vary the amount of
ice nucleating material over a wide range. Samples exist, in which
only a very small fraction of all particles carries an INM (or,
alternatively, an ice-active site on mineral dust particles), as is the case for group I-INM in Snomax, for example. In contrast, when particles
are generated for the particle methods, they are restricted in their
upper size (and mass) by the particle generation method. Additionally,
particles in the super-micron size range are lost, due to impaction
and/or sedimentation, in the particle generation and instrument
set-up, increasingly so with size. In order to generate a particle
population in which 50 % of the particles carry at least one
of the group I-INM observed in Snomax (i.e., have a λ of 0.5
for these), they would have to have a diameter of roughly 8 µm. As mentioned above, however, particles in this size range are
difficult to generate and sample. Hence particle methods are limited
in their ability to detect rarely occurring INM (or ice-active sites
on mineral dusts). Among these instruments, AIDA can detect the lowest
ice crystal concentrations. The largest particle size examined up to
date in FINCH is 900 and 1000 nm in LACIS and
PINC. This may not represent the absolute upper size limit detectable
in these instruments, but instrument and detector limitations make it
challenging to sample super-micron particles.
In the present study we used a time-independent approach to compare
data from the different instruments. Based on our results as presented
in Fig. , where data from the fastest (LACIS) and
slowest (BINARY) instrument agreed well, it can be argued that
a strong time dependence for Snomax is unlikely. This would also be
expected from the steep dependence of fice with
temperature.
However, this likely does not apply for all ice nucleating substances,
and examination of the time dependence can be informative. AIDA and
BINARY can vary their cooling rates, ranging from 1 to
3 Kmin-1 for AIDA and from 0.1 to 10 Kmin-1
for BINARY. The WT allows to record the time when the freezing
occurred; however, up to now only cumulative results after
30 s have been used. And examining a time dependence is not
possible or can be done covering only a smaller range for AL, FINCH,
LACIS and PINC.
In Section , it was discussed that some
nm data deviated noticeably from the bulk of the
data. This included BINARY data below -20 ∘C, as
discussed above in this section. Also concerned were data measured
with AL at temperatures of -9 ∘C and below, two data
points measured with AIDA for polydisperse aerosols, the FINCH data
point at -6.5 ∘C and data measured with PINC for
temperatures above -10 ∘C. In the following
paragraphs, we will discuss specific issues which might have been the
cause for these observed deviations.
Acoustic levitator. We first want to address the AL. Some of
the AL data agree well with the bulk of the data, but measurements
below -8 ∘C show noticeably lower values for
nm. These measurements were done for droplets with lower
concentrations of Snomax per droplet, which only freeze at
temperatures below about -7 ∘C. An explanation might
be the following: in the AL, the temperature is measured directly at
the surface of the droplets by an infra-red thermometer. The signal
which is taken to indicate first ice nucleation is the start of an
increase in the droplet temperature, resulting from the release of
latent heat during ice formation. The droplets examined in the AL are
rather large (2 mm in diameter), and nucleation most likely
takes place in the interior of the droplets. When the first ice
nucleation occurs, it will take some time until the related increase
in droplet temperature propagates to the droplet surface. Meanwhile
the droplet is continuously cooled down and hence the temperature at
which the increase in the droplet temperature is detected is somewhat
below that at which the first ice nucleation took place.
This effect might not be negligible in particular for Snomax
experiments where freezing takes place in a temperature range not far
below 0 ∘C. There the cooling rate of the droplets in
the AL is very fast; i.e., they cool down from 0 to
-10 ∘C within 10 s; i.e., the cooling rate
is 1 Ks-1 (see Fig. ). For droplets
in which ice is nucleated at temperatures at and above
-8 ∘C, freezing may proceed so very fast that this
effect does not play a noticeable role, but at lower temperatures it
might become apparent by a less steeper slope of fice and
nm.
Another reason for the observed deviations in the AL data to others
could be that the droplets, which are cooled down very fast during the
first 10 s, are still warmer in their bulk than at their
surface. Hence, by the time the interior reaches a temperature which
is sufficiently low for ice nucleation to take place, the droplet
surface is already colder.
These deviations will be examined in more detail in the future, and
likely a calibration of this effect, maybe even based on the herein
presented Snomax data set, seems feasible to account for the offset in
temperature in the respective temperature range.
AIDA. For AIDA, nm data obtained for
polydisperse measurements at T<-10∘C were at the
lower end of values observed at the respective temperatures. This was
discussed in Sect. , and we only repeat here that
the particles which were used in these experiments were the smallest
ones used in this study, and possibly it might not be valid to assume
that the distribution of INM to these particles still followed
a Poisson distribution. This could be checked in future experiments
with size-selected particles below 200 nm diameter.
FINCH. FINCH was the only instrument which did not detect the
steep increase in nm between -7 and
-9 ∘C, and also detected an increase in
nm by a factor of 2 between -12 and
-13 ∘C, at a temperature where no additional new ice
activity is expected from Snomax INM. All of the data presented in
this study were taken during one experimental run, for which
temperatures were scanned comparatively fast, which might have caused
problems. However, as it was not possible to obtain additional data
prior to the submission of this study, a more detailed discussion of
possible issues in FINCH is not possible.
PINC. At temperatures above roughly -10 ∘C,
nm determined from PINC measurements were clearly lower
than other values for nm obtained for this study. The
upper sampling temperature used in PINC for this study was
-8 ∘C. In order to achieve supersaturation at the
sample position at -8 ∘C, the warm wall needs to be
at temperatures warmer than -3 ∘C, which makes the
mass transfer for ice from warm to cold wall quite high, leading to
anomalous ice crystal counts from falling frost particles growing on
the cold wall. This results in the limit of detection being too high
to quantify ice formation at temperatures above
-8 ∘C. However, below -8 ∘C, data
contaminated by frost falling off the walls can be distinguished and
excluded. A further issue might originate in the measurement principle
of PINC (see Appendix ), where supersaturation with
respect to ice and water is generated by a temperature gradient
between two iced walls. For measurements at high temperatures (roughly
-10 ∘C and warmer), it is not possible to generate
high enough supersaturation with respect to water any more, and
residence times for supersaturated conditions become very short. Hence
PINC measurements in the temperature region above
-10 ∘C might be biased by instrumental limitations.
Comparison of nm averages with parameterizations from literature
In this section we compare two existing parameterizations from the
literature to those obtained in the current work. In a first step,
average nm values were derived from our data. Based on
the instrumental peculiarities discussed above, some data were
excluded from the averaging procedure, as described in
Sect. . The remaining data from each of the
instruments were averaged separately. All values for nm
were averaged in 1 K bins below -12.5 ∘C and
in 0.5 K bins above. The resulting seven data sets were then
averaged to yield overall nm values representative for
this study. The results are shown as black circles in both panels of
Fig. . According to the averaging procedure, each
instrument contributed to the average with an equal weight, and the
error bars depicted for nm reflect the deviation based
on averaging the seven data sets. The uncertainty shown for the
temperature represents ±0.6 K. All separate data points
that were included in the averaging are shown in light grey in the
background.
Two existing models are compared to the average data in
Fig. . The red line represents the following curve:
nm(T)=6Fπρ1-exp-t⋅AexpB⋅T=1.4×109mg-11-exp-2×10-10exp-2.34∘C-1⋅T
This was obtained by equalling the fractions of unfrozen droplets as
described with the CHESS-model in to those as
described in Eq. (), with T in ∘C,
ρ=1.35gcm-3 (see Sect. ) and
values taken from : F=9.995×10-10nm-3, A=9.99×10-10s-1,
B=-2.34∘C-1 and t=0.2s (the respective
nucleation time in LACIS, on which the determination of A and B
was based). (The resulting nm represents a time
independent parameter, while a time-dependence had been incorporated
in the CHESS-model originally.)
Average nm values (black circles)
overlying all separate data points which were included in the average (shown
as background in light grey), together with fits obtained from a
time-independent variant of the parameterization given in
(red curve, see Eq. ) and in
(blue curve).
The blue line was obtained as follows: a model based on classical
nucleation theory, the Soccer ball model (SBM) as described in
, was used to calculate fice for
a nucleation time of 10 s (which is roughly a mean value for
the methods used in this study). A slight time dependence of the ice
nucleation process for Snomax can be observed as discussed in
detail in. But as a change of the nucleation time of
a factor of 10 shifts the freezing curve by roughly only 0.3 K
(and a factor of 100 by 0.6 K etc.), we use the mean
nucleation time given above as being representative for the whole
study and otherwise neglect a time dependence. The contact angle
distribution used for Snomax was μ0=0.595rad
(34.1∘) and σ=0.04rad (2.3∘) for the
mean contact angle and the standard deviation
. fice as calculated by the SBM was
then converted to nm using
Eq. (). nm was derived for particles
of sizes with 500, 1000, 1500 and
2000 nm (i.e., for different λ values), and as to be
expected, the resulting nm showed to be independent of
the particle size. The result of these calculations is seen as a blue
line in Fig. .
The maximum average value of nm of 1.4×109mg-1 coincides very well by both approaches presented
in Fig. . But both parameterizations were originally
made to describe the immersion freezing behavior of the more abundant
but less ice-active INM, so that the shoulder in nm at
roughly -6 ∘C is not represented
explicitly. A further deviation occurs in the region where the steep
increase in nm levels off into the plateau (roughly
around -10 ∘C), where the bend in the curve based on
Eq. () is slightly
sharper than that seen in the average values. Another small deviation
can be seen for the three lowest average nm values below
2×103mg-1, which are underestimated by the
SBM. However, with the exception of these three values, both
parameterizations describe the average data well over the whole course
within a temperature uncertainty of ±0.6 K (95 %
confidence range) in the entire range in which an increase of
nm is seen. When judging the deviation in relation to
nm, it is less than a factor of 2 at all temperatures at
which measurements were made, again besides for the SBM
parameterization above -5 ∘C. But the INM which are
ice-active at these high temperatures, i.e., belonging to group I, can
be expected to be of a minor if not negligible atmospheric relevance,
due to their scarce occurrence which was already noted e.g., by
. Therefore, a new parameterization taking this
second type of INM explicitly into account was omitted in this
study. Instead it can be concluded that most of the data measured in
the framework of this present study are in agreement with already
existing parameterizations, where the two parameterizations described
here represent a time-independent one (Eq. )
and one in which a time dependence of the freezing process technically
is accounted for (SBM).
Summary and conclusions
In this study, data obtained for immersion freezing from seven
different measurement methods and instruments were compared to each
other. These instruments included methods examining droplets which
were made from suspensions directly (suspension methods), which were
an acoustic levitator (AL), an optical freezing array (BINARY) and
a wind tunnel (WT). The remaining four instruments all examined INP
(particle methods) and included an expansion chamber (AIDA), a flow
tube (LACIS) and two ice nucleation counters (FINCH and PINC). The
comparison was done within the research unit INUIT (Ice Nucleation
research UnIT), and focused on the examination of ice nucleation up to
comparably high temperatures, where the highest temperatures probed
with the different instruments were in the range from
-2 to -8 ∘C. Due to its ability
to induce ice nucleation at these high temperatures, Snomax was used
as the test substance. This is a commercially available product
containing ice nucleation active protein complexes originating from
P. syringae bacteria. Care was taken to use similar droplet
and particle generation techniques and Snomax from the same batch as
far as possible.
To enable a comparison, all data were represented as number of ice-active entities per mass of examined (dry) substance
(nm), an approach taken from . In
general, the observed curve for nm is in agreement with
the vast body of literature existing for P. syringae and
Snomax, for which it is known that ice nucleation active protein
complexes (i.e., ice nucleation active macromolecules, INM) induce the
freezing, and that more and less ice-active types of INM exist, i.e.,
group I and group III protein complexes. A sharp increase in measured
frozen fractions and nm was seen starting at
temperatures below -2 ∘C, leveling off in a shoulder
at -6 ∘C, followed by a second steep increase from
-7 to -9 ∘C. The two increases
show the temperature ranges in which two differently sized (and
differently ice-active) INM types become ice-active. A plateau in
nm developing below -12 ∘C yielded
that the number of group III-INM in the examined Snomax sample was
1.4×109mg-1. The more ice-active group I-INM were 3 orders of magnitude less abundant, i.e., occurring in numbers of
∼1×106mg-1.
Data determined for this study mostly were found within a range of
1 K for temperatures above -12 ∘C
(86 % after exclusion of some outliers). For temperatures
below -12 ∘C, they were found in a range from
7×108mg-1 to 2.1×109mg-1,
i.e. less than a factor of 3 apart around the average value of
1.4×109mg-1. Pronounced differences were only
seen for some instruments in some temperature ranges, including the AL
below -9 ∘C, BINARY below -20 ∘C,
FINCH above -8 ∘C, PINC above
-10 ∘C and two AIDA expansions made for polydisperse
particles below -10 ∘C. Possible reasons for the
observed deviations are discussed in the text, together with general
advantages and disadvantages of suspension and particle methods.
In the present study, besides the above discussed deviations, data
agreed well over the whole temperature range in which measurements
were made. In the temperature range below -12 ∘C,
where data from five of the seven instruments could be included in the
comparison, values scattered by less than a factor of
3. Suspension methods and particle methods included in our study
yielded similar average numbers of INM per particle/droplet, as can
be seen by the fact that λ was found to be proportional to the
particle volume and by the fact that nm agreed well for
the different instruments over the whole temperature range. Here it
shows that it might have been advantageous, that the bacterial cells
were torn apart in the atomizer which we used to produce particles. If
we had dealt with whole bacterial cells, these cells could not have
been distributed into particles smaller than the cell size, and
λ would have dropped to 0 sharply for these small
particles. It also is of advantage that Snomax contains much soluble
material, as particles produced from solutions tend to be more
spherical than e.g., insoluble mineral dust particles. As we found
that the relation between suspension methods and particle methods
could be based on a simple relation of the mass of Snomax to the
volume of Snomax particles, particle shape can be assumed to have been
close to sphericity. This facilitates the comparison of results from
the different instruments. More difficulties might arise for less
spherical INP or for substances where the relation between mass (or
surface) of the INP and number of the ice-active entities is not as
simple. We propose that Snomax indeed is a substance which can be used
as a model sample when testing instrumentation with respect to
performance in immersion freezing, particularly in the temperature
range where the strong increase in measured ice fractions is seen, but
also at lower temperatures. For the latter, conditions of the
experiment should be chosen such that not all droplets carry an INM,
which can be reached by examining sub micron dry particles or
sufficiently diluted suspensions, because this enables to measure
frozen fractions below 1 and hence gain additional information about
the performance of the instrument.
Two parameterizations taken from literature
compared well with the data obtained
in this study, although in these parameterizations the more ice-active
INM had not been incorporated. Nevertheless, deviations over the whole
course (from -2 to -38 ∘C) are
small enough to argue that these parameterizations, and also the time-independent parameterization based on derived in
the present study (see Eq. ) are applicable
for describing immersion freezing induced by P. syringae
bacteria over the whole temperature range in which immersion freezing
occurs.
InstrumentationAcoustic levitator (AL)
The employed acoustic levitator is the type APOS BA 10 from the
company TEC5. A standing ultrasonic wave is produced by interference
between a radiator and a reflector. At the nodes drops can be
levitated without any wall or substrate contact and without electrical
charges . For heterogeneous experiments the
levitator is installed inside a walk-in cold chamber together with
a platinum-resistor thermometer Pt100 to measure the ambient
temperature. A digital video camera is used to record the freezing
process and the droplet sizes. With an infrared thermometer the
temperature of the freezing drops is measured directly and free of
contact. As this requires a circular spot of approximately
1 mm in diameter, the investigated drops had sizes of 2.0±0.1mm in diameter .
Because of their rather large volume and missing ventilated heat
transfer, the levitated drops cooled down rather slowly while
exchanging heat with the ambient air in the cold chamber which was
approximately -23 ∘C during the Snomax
experiments. This resulted in a non-linear cooling rate and the
temperature of pure water drops in the levitator developed as follows
(see also Fig. ):
Tdrop(t)=-21.83862+21.88997⋅exp-t15.3108.
Individual drops containing Snomax in various concentrations were
levitated one after another and cooled down according to
Eq. (). The transition from the liquid to the ice phase was
visible by a sudden increase of the droplet temperature (caused by the
release of latent heat) recorded by the infrared thermometer. For each
particle concentration, approximately 100 drops were observed until
they froze and the freezing temperatures, i.e., the lowest droplet
temperatures, were recorded with a measuring error of
±0.7 K. Afterwards, for temperature steps of 1 K
the fractions of frozen drops were counted.
AIDA
The AIDA (Aerosol Interaction and Dynamics in the Atmosphere)
controlled expansion cloud-simulation chamber was
used to measure the droplet-freezing activity of Snomax particles
during expansion cooling. The experimental procedure of AIDA immersion
mode freezing measurements is described in previous literature
and is only briefly discussed
here. The AIDA chamber consists of a thermally instated
84 m3 aluminum vessel and an industrial air pump to
simulate the adiabatic cooling of an updrafted air parcel by
mechanical cooling. Due to the continuous cooling, water vapor becomes
fully saturated inside the vessel, resulting in freezing of Snomax
particles immersed in water droplets. Consequently, AIDA enables
experiments with an abundant concentration of supercooled droplets (up
to several hundred droplets per cubic centimeter) and atmospherically
relevant supercooled droplet sizes (several micrometer in diameter)
within experimental uncertainties in temperature of ±0.3 K
and in relative humidity with respect to water of ±5 %.
Development of droplet temperature during
cooling in the AL.
The injection of Snomax particles into the AIDA chamber was carried
out by atomization of a Snomax suspension (5 g Snomax in 1 L
of 18.2 MΩcm ultrapure water). For consistency with other INUIT
project partners, the same atomizer type was used at AIDA for particle
generation. Accordingly, aerosolized Snomax particles were directed
into the ventilated AIDA vessel and characterized for number
concentration (Nae) and particle size distribution by
a Scanning Mobility Particle Sizer (SMPS, TSI, Model 3080 DMA and
Model 3010 condensation particle counter) and an Aerosol Particle
Sizer (APS, TSI, Model 3321) prior to each expansion experiment.
During the typical AIDA expansion experiments carried out for the present work,
a constant mechanical pumping created the chamber pressure drop from atmospheric
pressure to roughly 900 mbar, resulting in time-averaged cooling rates of about
1 to 3 Kmin-1. A total of nine expansions (three
polydisperse and six size-selected measurements) was performed and immersion freezing
activities of Snomax aerosols were recorded in the temperature range
from -7.5 to -11.5 ∘C. The number density
of activated ice, Nice,
was measured by the Welas optical particle counter PALAS, Sensor series
2300 and 2500, installed on the bottom of the vessel during
each expansion, and was later on used to evaluate the activated ice fraction
(fice=Nice/Nae). We note that four expansions
were carried starting roughly at -9 ∘C, in order to estimate
fice in the temperature region below -9 ∘C with
a minimum influence of ice losses by the settling of ice crystals.
BINARY
The BINARY (Bielefeld Ice Nucleation ARraY) setup consists of an array
of 36 microliter-sized droplets positioned on a thin hydrophobic glass
surface placed on a Peltier cooling stage . With
the Peltier stage connected to a sink bath at 5 ∘C,
the droplets can be cooled to -40 ∘C at cooling
rates between 0.1 and 10 ∘Cmin-1. Heterogeneous
ice nucleation at the glass surface is minimized due to the
hydrophobicity of the glass, and also by using freshly
double-distilled water. The droplets are separated from each other by
a polydimethylsiloxane (PDMS) spacer and the resulting compartments
are sealed at the top with another glass slide. The droplet separation
prevents a Wegener–Bergeron–Findeisen process, in which frozen
droplets grow at the expense of unfrozen, i.e., supercooled liquid,
droplets due to the vapor pressure difference between ice and
supercooled liquid water . During an experiment
the droplet array is monitored continuously with a CCD camera which
enables the automatic detection of nucleation
events. A LabVIEW™ virtual instrument is used to control
the temperature of the Peltier stage and to analyze in real time the
obtained digital images, typically recorded every
6 s. Freezing is determined optically based on the change in
brightness when the transparent liquid droplets become opaque upon
freezing. The mean gray value, gv, (ranging from gv=0 (black) to
gv=255 (white)) is determined for each compartment/droplet i in
every image j, i.e., at every temperature. The difference in gv
between successive images and, hence, temperatures
Δgvi,j=gvi,j-gvi,j-1 is then
used to determine freezing and melting events. Typical gray value
differences Δgvi,j upon freezing are larger than
∼10, while the maximum background noise value is well below
±1, which we set as the threshold value for freezing and melting,
respectively.
FINCH
FINCH (Fast Ice Nucleus CHamber) consists of an 80 cm long
flow tube (8.8 cm inner diameter), which can be cooled down to
-65 ∘C. Right before entering the tube on the top
the sample flow is cooled and mixed with particle-free, humidified, warm
air as well as with dry, cold air. The mixing of the different air
flows and the cooling of the tube results in a defined freezing
temperature and supersaturation inside the tube
. For the present study FINCH was operated at
150 % RHi (relative humidity with respect to
ice), which is well above water saturation for the used range of
freezing temperatures. Therefore, particles that are entering the flow
tube grow to droplets and subsequently freeze depending on the nature
of the immersed aerosol particle and the adjusted freezing
temperature. An optical detector similar to is
mounted at the outlet of the flow tube. It determines whether the
arriving hydrometeors are liquid droplets or frozen ice crystals from
which the frozen fraction fice can be calculated.
FINCH measurements were performed on size-segregated particles, which
were produced by atomizing a Snomax suspension (1 g Snomax in
1 L of deionized water, using the same atomizer as for AIDA, LACIS,
and PINC measurements). After spraying, the particles were dried in
a silica diffusion drier and size-selected by a DMA (Differential
Mobility Analyzer, TSI 3081, sheath flow of 3 L min-1). The
monodisperse aerosol flow (∼0.1 to 0.3 L min-1) was
mixed with ∼2.7 to 2.9 L min-1 of dry, particle-free
air to reduce the number of particles considerably. For the
measurements with FINCH a particle number concentration of less than
∼1500L-1 is aimed at to avoid particle coincidence
in the detector.
LACIS
LACIS (Leipzig Aerosol Cloud Interaction Simulator) was used in its
immersion freezing mode for the study presented
here. LACIS is a 7 m long flow tube, consisting of 1 m
sections which can be temperature controlled separately. Temperatures
can go down to -40 ∘C. Before entering the flow tube, the sheath air stream is hydrated such – by
use of a humidifier (PH-30T-24KS, Perma Pure) – that droplets form on the aerosol particles upon cooling, i.e.,
during the passage of the flow tube. These droplets
can subsequently freeze, depending on the nature of the immersed
aerosol particle and the adjusted temperature. At the LACIS outlet,
a self-built optical particle spectrometer
TOPS-Ice, determines if the arriving
hydrometeors are liquid droplets or frozen ice crystals, resulting in
the determination of a frozen fraction, fice.
LACIS measurements were performed on size-segregated particles which
were produced by atomizing a Snomax suspension (5 g Snomax in
1 L of 18.2 MΩcm ultrapure water, using exactly the same
atomizer as used for AIDA, FINCH and PINC measurements). After
spraying, the particles were dried and size-selected by a DMA
(Differential Mobility Analyzer, type Vienna Hauke medium, aerosol to
sheath air flow ratio of 1:5) and provided for further analysis.
For a more detailed description of the particle generation and
measurement procedure see , where similar
measurements were introduced, differing only in the use of a different
batch of Snomax, the use of a different atomizer, and the use of
a different concentration in the sprayed suspension
(1.6 gL-1), which, however, does not influence the
particle generation as the aerosol was dried after spraying.
Mainz vertical wind tunnel (WT)
In the Mainz vertical wind tunnel, drops are freely floated at their
terminal velocities in an air stream. Thus, ventilation and heat
transfer are similar to the situation in the real atmosphere. The
wind speed is uniformly distributed around the tunnel cross section
area up to the boundary layer at the tunnel walls. This ensures that
drops float in a stable fashion in the experimental section of the
tunnel . The droplet sizes were calculated from
the recorded wind speed in the tunnel as it must be equal to the
terminal velocity of the droplet to keep the droplet floating in the
experimental section. The droplet temperature was determined from the
ambient temperature in the wind tunnel and the dew point with an
estimated error of ±0.75 K.
The experiments were performed in a manner very similar to earlier
studies with pollen at constant
ambient temperatures; i.e., the wind tunnel was pre-cooled to certain
temperatures in steps of 1 K. The adaption time of the drops,
i.e., the time after which the droplet temperature was equal to the
ambient temperature, was calculated according to
(Chapt. 13) by considering ventilation and heat transfer of a droplet
floating in an air stream. The results indicate that drops of the
investigated sizes reached the ambient temperatures of -5 to
-18 ∘C in the wind tunnel after 3 to 4 s.
Individual drops of 760 µm diameter containing Snomax in
two different concentrations were observed for approximately 30 to
40 s. Per temperature interval and Snomax concentration around
50 drops were investigated. The fractions of frozen drops were counted
for a total observation time of 30 s.
PINC
The Portable Ice Nucleation Chamber (PINC) operation principle is
based on the Continuous Flow Diffusion Chamber (CFDC;
) with two flat parallel plates (568×300mm) whose inner walls
are iced before each experiment. Applying a temperature gradient
between the two iced walls leads to supersaturation with respect to
ice and water and allows ice crystals to form and grow on ice nuclei
in the sub-saturated (RH < 100 %) and supersaturated
(RH > 100 %) regimes. For conditions when ice nucleation
is observed at RHw< 100%, deposition mode ice
formation is inferred, whereas for any ice formation observed at
RHw> 100%, condensation/immersion freezing is
implied. Droplets evaporate in the evaporation section downstream of
the freezing chamber. Upstream of PINC, aerosol particles are counted
with a condensation particle counter (CPC) after flowing through an
impactor with a D50 cutoff at 0.91 µm aerodynamic diameter
. The ice crystals are counted with an optical
particle counter (OPC) at the exit of PINC and are distinguished from
the small unactivated aerosol particles by their size.
Further details on the PINC design are described in
and . The activated fraction
is calculated by taking the ratio of the ice crystal number
concentration to the total particle number concentration measured with
the CPC. For comparison with other ice nucleation counters measuring
in the immersion mode, only data taken by PINC at RHw≥100% and below the RHw at which droplets
survive past the evaporation section (RHw,ds), are
presented. For each temperature, RH was scanned continuously from
RHi=100% up to RHw,ds. At
T=-20∘C, RHw,ds is 104.5 %. However,
at T=-10∘C it decreases to 101.7 %.
Particle losses in the tubing and the impactor upstream of PINC were
accounted for by a particle loss curve which was found for kaolinite
particles with a mobility diameter between 500–950 nm or
measured before the experiment using Snomax (for measurements at
T>-12∘C).
Temperature uncertainties in PINC are on the order of
±0.1 K resulting in a relative uncertainty of
±2 % in relative humidity. The temperature uncertainty
results in a variation across the sample lamina of up to 0.8 K
(±0.4 K). The uncertainty in nm from the
optical particle counter is 10 %.
Measurements were made during three different occasions. Measurements
were done in Leipzig in parallel to LACIS measurements (data labeled
with #1), where particles were produced using the INUIT Snomax
batch and the atomizer used within the INUIT community. During these
measurements, PINC only measured at T<-14∘C, due to
instrumental issues during the campaign. Snomax from the INUIT batch
was then also used for measurements at ETH, and care had been taken to
store the sample frozen at all times (stored at
-18.2 ∘C). The respective data are labeled #2. At
ETH, also Snomax from a different batch was used, and the respective
data are marked by #3 (this Snomax sample was stored at
+5 ∘C). PINC measurements done at ETH, including all
measurements at T>-12∘C, were performed with Snomax
particles prepared by suspending 0.08 g or 0.4 g
Snomax in 80 mL of deionized distilled water (DDW, 18.2 MΩcm)
(#2 and #3, respectively). Particles were suspended using an
atomizer and size-selected at 500 nm with a DMA (TSI, 1:5
sample to sheath air ratio).
The results suggest a good agreement between LACIS and PINC data at
temperatures below -14 ∘C. At warmer temperatures,
a RHw of 100 to 101.7 % and the short residence time of
the aerosol particles in PINC of 5 s might not be sufficient
to guarantee droplet formation. Thus, it is possible that we do not
observe immersion freezing at these conditions, but rather deposition
or condensation nucleation of ice.
Acknowledgements
The present study was done within the DFG funded Ice Nucleation
research UnIT (INUIT, FOR 1525), including project BU 1432/4-1, DI
1539/1-1, KO 2944/2-1, MO 668/4-1, and WE 4722/1-1. Z. A. Kanji and
Y. Boose would like to acknowledge SNF for funding. The authors also thank the
two referees of this work, Russel Schnell and Gabor Vali, for their encouraging reviews.
Edited by: A. Bertram
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