Introduction
Clouds and aerosols continue to cause the largest uncertainty in the
current assessment of global climate change (e.g., Boucher et al.,
2013). Despite their importance in the Earth's system, fundamental
knowledge on cloud formation and evolution is still missing. Clouds
containing ice can have a positive or negative effect on the Earth's
radiative budget, depending on their micro- and macrophysical
properties (Lohmann et al., 2016). Cloud microphysical processes are
highly variable depending on the available amount of water vapor and
the presence of supercooled cloud droplets and ice crystals. In
addition, cloud microphysical processes can change during the
development of a cloud, and the first formation of ice in clouds is
still not completely understood.
Different processes leading to ice formation from the vapor or liquid phase
are possible. In the absence of ice-nucleating particles (INPs) (Pruppacher
and Klett, 1997; Lohmann et al., 2016) freezing of supercooled droplets
occurs homogeneously, which is relevant in pristine atmospheric environments.
It requires temperatures T<235 K and a relative humidity (RH)
with respect to ice (RHi)>140 % where the
nucleation rate is high enough to outcompete heterogeneous nucleation. In the
presence of INPs, heterogeneous ice nucleation is favored, since the
particles can lower the energy barrier of the phase change. This freezing
pathway is dominant in the mixed-phase cloud regime at T>235 K,
where ice and supercooled water can co-exist and homogeneous freezing rates
are negligible. Currently, four different heterogeneous freezing mechanisms
are distinguished: deposition nucleation, contact freezing, immersion
freezing and condensation freezing (for a detailed description see Vali
et al., 2015). Deposition nucleation is relevant for the formation of cirrus
clouds as inferred by Cziczo et al. (2013) but is typically not relevant for
the formation of mixed-phase clouds, as lidar observations show that the
liquid phase is present before ice crystals form (Ansmann et al., 2008). The
two most likely freezing modes in mixed-phase clouds are immersion and
condensation freezing, where the INP initiates the freezing from within
a supercooled droplet. At present it is questioned whether there is
a physical difference between immersion and condensation freezing (Welti
et al., 2014; Wex et al., 2014; Burkert-Kohn et al., 2017) but, as the ice
germ should form from the liquid phase in both cases, it is not expected so.
In addition to different possible ice formation pathways, the
identification of ambient INPs remains challenging, since only a small
fraction of aerosol particles (∼1 out of 105) nucleates ice
(Rogers et al., 1998; DeMott et al., 2010), and the exact properties
rendering them ice active are not known. INPs can be solid and
water insoluble or soluble and crystalline (Kanji et al., 2017),
and their ice nucleation ability has been linked to a crystal lattice
match to ice, surface defects which increase the density of adsorbed
water molecules locally or functional groups which increase the
chemical affinity to ice via hydrogen bonds (Pruppacher and Klett,
1997). From the large variety of ambient aerosol classes (Kanji
et al., 2017), mineral dust particles were observed to nucleate ice
efficiently (Hoose and Möhler, 2012, and references therein), and
it has been found that K-feldspars are the most efficient INPs out of
many tested minerals (Atkinson et al., 2013b; Yakobi-Hancock et al.,
2013; Zolles et al., 2015; Harrison et al., 2016; Kaufmann et al.,
2016). Furthermore, due to its abundance in the lower free troposphere
(FT), it is thought that mineral dust plays a key role in atmospheric
ice nucleation (e.g., DeMott et al., 2003a; Kamphus et al.,
2010). Particles of biological origin, like certain bacteria, fungal
spores and pollen, were found to be efficient INPs at T>263 K (Hoose and Möhler, 2012); however, the
atmospheric concentration from whole and intact biological particles
which are ice active is temporally and spatially variable, and their
influence on ice formation is therefore rather seasonal and local in
nature (Després et al., 2012). Nanometer scaled fragments from
biological particles are present in much higher concentrations and
might have atmospheric implications (Pummer et al., 2012; Augustin
et al., 2013; O'Sullivan et al., 2015; Fröhlich-Nowoisky et al.,
2015; Wilson et al., 2015). Additionally, bacteria have been found in
Saharan (Meola et al., 2015) and soil dust (Conen et al.,
2011) aerosols, possibly influencing their ice nucleation activity.
The role of marine aerosol as a source of INPs has been reported for
the first time more than five decades ago (Brier and Kline, 1959;
Cziczo and Froyd, 2014) and has been reemphasized recently and
observed in various field and laboratory studies (Cziczo et al., 2013;
Knopf et al., 2014; Wilson et al., 2015; DeMott et al., 2016). Recent
field studies or studies of field samples in the laboratory (Cziczo
et al., 2013; Knopf et al., 2014; Wilson et al., 2015; Ladino et al.,
2016; DeMott et al., 2016) have shown that particles and organic
matter sampled or emitted from the sea surface can be a source of
INPs. Marine aerosols are produced via a bubble-bursting mechanism
(e.g., de Leeuw et al., 2011; Gantt and Meskhidze, 2013; Aller et al.,
2005; Cunliffe et al., 2013) when entrained air bubbles rise through
the sea surface microlayer and burst upon contact with the
atmosphere. The sea surface microlayer is usually enriched in biogenic
material leading to the emission of these in the atmosphere as aerosol
particles. A source of these marine particles can be microorganisms
like phytoplankton and bacteria, exopolymer secretion, colloidal
aggregates, glassy organic aerosols, crystalline hydrated sodium
chloride particles and frost flowers (summarized in Burrows et al.,
2013). Cells or cell fragments and exudates of phytoplankton species
were found to be ice active (Knopf et al., 2011; Alpert et al., 2011;
Wilson et al., 2015), and biological material during phytoplankton
blooms might also play an important role for ice nucleation (Prather
et al., 2013; DeMott et al., 2016). These marine aerosols can be
submicrometer in size (e.g., 0.02–0.2 µm, Wilson
et al., 2015; 0.25–1 µm, DeLeon-Rodriguez et al.,
2013), a size range which is transported to higher altitudes. Burrows
et al. (2013) state that marine biogenic particles are an important
source of INPs in remote marine areas in the absence of other
efficient INPs such as mineral dust. During airborne measurements,
Cziczo et al. (2013) found sea salt in ice residuals from tropical
tropopause cirrus clouds, especially over the open ocean but also in
reduced concentrations over land.
In addition to laboratory studies, which aim to understand the
physical processes of ice nucleation and determine key aspects of
aerosols acting as INPs, it is crucial to quantify the total number
concentration of ambient INPs in an environment relevant for clouds
containing ice and to address the question of their variability in
space and time. Several studies exist from airborne platforms
(e.g., Bigg, 1967; Rogers et al., 1998; Prenni et al., 2009; DeMott
et al., 2010; Avramov et al., 2011; Schrod et al., 2017) and
ground-based observations (e.g., DeMott et al., 2003b; Chou et al.,
2011; Ardon-Dryer and Levin, 2014; Mason et al., 2016; Boose et al.,
2016a, b) quantifying the number concentration of INPs and identifying
their potential sources. Typically, filter sampling with subsequent
offline freezing methods, and online measurements with
continuous-flow-diffusion chambers (CFDCs) are used as INP measurement
techniques. For filter sampling, aerosols are collected for a certain
time and known air volume, after which the collected particulate is
cooled and exposed to controlled temperature and RH conditions
(e.g., Bigg, 1967; Santachiara et al., 2010; Conen et al., 2011;
Bingemer et al., 2012; Ardon-Dryer and Levin, 2014; Knopf et al.,
2014; Mason et al., 2015). Filter techniques observe the onset
freezing temperature of a sample with a very large number of particles
resulting in a very sensitive detection limit. However, this comes at
the cost of a low temporal resolution since the sampling times of the
filters often are on the order of a few hours or longer. CFDCs measure
INP concentrations in real time with a higher temporal resolution, on
the order of a few to tens of minutes (e.g., Rogers, 1988; Rogers
et al., 2001; Chou et al., 2011), but their total sampling volume is
lower, and their sensitivity to detect INPs is limited at low
concentrations (Boose et al., 2016a). This in particular is
challenging at low supercooling or in areas where INP concentrations
are lower than 0.1–1 per standard liter (stdL-1;
normalized to standard T of 273 K and pressure, p, of 1013 hPa).
Measurements of INP concentrations are rare during different seasons in an
environment which is relevant for the formation of mixed-phase clouds. Conen et al. (2015) collected filters at different
elevations in the (partly) FT, namely at Mt. Chaumont and at the
Jungfraujoch (JFJ) in Switzerland (1171 and 3580 m,
respectively) and at the Izaña observatory on Tenerife, Canary
Islands (2373 m). They sampled for 1 year with one sample
representing 24 h, and INP measurements were reported for the
temperature range of 265 to 269 K. At the JFJ, and for the same
temperature range, they found a seasonal cycle with INP concentrations
ranging from 0.001 to 0.01 stdL-1, with a maximum in
summer and a minimum in winter. This variation is attributed to
previous INP activation and subsequent fallout from advected air
masses prior to reaching the JFJ, leaving an air mass which is
depleted in INPs upon arrival to the JFJ during wintertime (Conen
et al., 2015; Stopelli et al., 2015). Also at the JFJ, INP
measurements were performed at T=241 K during
winters 2012, 2013 and 2014 with the CFDC Portable Ice Nucleation
Chamber (PINC; Boose et al., 2016a). INP concentrations were sampled
in the deposition nucleation mode in winters 2012–2014 and also in the condensation freezing mode in winter
2014. Median INP concentrations
below (above) water saturation were in the range of ≤ 0.05–0.1
(4.2) stdL-1. To extend these measurements and to
establish a longer time series of measurements at the JFJ, INP
concentrations are measured since summer 2014 at the same temperature
and RH conditions, with the newly built Horizontal Ice Nucleation
Chamber (HINC) based on the design of Kanji and Abbatt (2009). In this
study, the new chamber is characterized to be used as a field
instrument. To complement the validation and verification experiments
performed in the laboratory, two field campaigns in winters 2015 and
2016 were performed, and results are compared to previous winter
measurements from the same location discussed in Boose
et al. (2016a). In addition, two events of anomalously high INP
concentrations from the winter 2015 campaign are discussed to
investigate the origin of these INPs.
Ice nucleation measurements
Technical description
HINC is a CFDC, based on the design of the UT-CFDC (Kanji and Abbatt, 2009).
A schematic of HINC is shown in Fig. 1, including the outer dimensions of the
chamber. Inner dimensions and more detailed design aspects can be found in
Kanji and Abbatt (2009). HINC consists of two horizontally oriented copper
plates which are cooled by an external recirculating ethanol cooler (LAUDA,
RP 890 C). Self-adhering glass fiber filter papers (PALL 66217) mounted on
the inner walls of the chamber are wetted prior to an experiment to create an
ice layer upon cooling the walls. For the wetting procedure, the walls are
kept at room temperature and the chamber is tilted to an angle of
45∘, and approximately 100 mL of double-deionized water is
used to wet the filter papers via four water ports, which are in contact with
the filter papers of the upper and lower walls. The chamber is kept in this
position for 30 min to drain excess water via the outlet port downstream of
the chamber. After draining, the chamber is brought back into a horizontal
position and the outlet port is dried to ensure no residual water drops are
retained. Following the wetting procedure, an optical particle counter (OPC;
MetOne, GT-526S) is attached to the outlet port, and the walls are cooled
down to the desired set point temperature <273 K. To establish
a RHi and RHw>100 %,
a temperature gradient ΔT is applied between the two ice coated
walls (both walls below 273 K), with the upper wall set to the warmer
temperature. The horizontal orientation of the chamber ensures no internal
convection. For an experiment where the RH should be increased, which is
typical to determine the onset RH of INPs, the ΔT is achieved by
a temperature increase and decrease of the respective walls at equal rates.
This ensures that the temperature in the center, where the air containing the
aerosols is injected, remains constant. Aerosol particles enter the chamber
via a movable injector and are released into the chamber via a slit in the
front of the injector. The cross section area of the slit is smaller than the
cross section of the inner diameter on the injector, which creates a small
overpressure at the particles exiting through the slit promoting an equal
distribution of the aerosols over the width of the slit. The outer diameter
of the injector is 6.35 mm (inner diameter 3.175 mm), which
ensures that at a flow rate of 2.8 stdLmin-1, and at
242 K the turbulence regime is not encountered by air flowing over
the aerosol injector (Reynolds number 880, well below the threshold of 2000
for turbulent flow). Furthermore, given the chamber dimensions, before and
after the injector, the Reynolds number is 66, well below the critical
number. It is expected that the minor disturbances in the flow by the
injector will not result in transitioning from the laminar to turbulent
regime. The center flow containing the aerosols (aerosol flow) is layered in
between a dry particle-free sheath nitrogen (purity 5.0, 99.999 %,
H2O ≤ 3 ppm) flow, with a sheath-to-aerosol flow
ratio of typically 12 : 1, which ensures the aerosol flow remains laminar
and is exposed to the constant center temperature and RH conditions in the
chamber. The sheath air is controlled by a mass flow controller (MFC; MKS,
MF1, full scale flow of 5 stdLmin-1). The position of the
injector thereby determines the residence time of the aerosols in the
chamber. Within this residence time ice crystals may nucleate on aerosol
particles and grow to larger sizes, allowing for discrimination by size with
the OPC. For the field measurements reported here, particles detected by the
OPC in size bin > 5 µm in diameter are classified as ice (see
Sect. 2.2.3). Counts in smaller size channels could be contaminated by
unactivated aerosol particles and, at water-saturated conditions, the size
bins up to 3–4 µm could be contaminated by droplets. For
measurements reported here, HINC was kept at sufficiently low RH to ensure
that water droplets did not contaminate the signal in the
> 5 µm channel. The OPC is calibrated for a total
flow of 2.8 stdLmin-1, which is set by an external pump. The
MFC is used to set the 92 % sheath air flow, so that the remaining
8 % is made up by the aerosol flow sampled (pulled) into the chamber.
LabVIEW® is used to control the recirculating
cooler temperature and resulting RH in the chamber by regulating the
cold and warm wall temperatures. Integrated into the
LabVIEW® control panel are the flow rate of the
sheath flow through the MFC and a motorised valve to direct the
aerosol flow through a HEPA filter to quantify the noise for the
signal-to-noise ratio (see Sect. 2.3). Additionally, the counts in all
size bins of the OPC are read out, and all set and output parameters
are logged into a single file which is later used for data analysis.
Schematic and outer dimensions of HINC (main chamber).
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HINC validation and verification
Here we present laboratory measurements, using a variety of aerosol
particles, to verify the accuracy in T and RH for the
newly built INP counter. We define the operational range, where it
reliably measures INPs in the water-saturated regime. To confirm these
operation settings in the field, additional tests with ambient
particles at the JFJ were performed.
Sample preparation
To validate the temperature and RH conditions in HINC, hygroscopic
growth upon deliquescence, cloud droplet activation and homogeneous
freezing experiments with size-selected ammonium sulfate
((NH4)2SO4), sodium chloride (NaCl) and sulfuric acid
(H2SO4) particles were conducted, as well as experiments with
polydisperse ambient particles in the field. Except for the latter,
particles were generated as aqueous solutions (0.05625 % w/w for
(NH4)2SO4, 5 % w/w for NaCl, 60 % w/w for
H2SO4), atomized and dried by diffusion to
RHw<2 %, before they were size selected by
a differential mobility analyzer (DMA; TSI, 3081). For the
deliquescence and cloud droplet activation experiments, 200 nm
particles were used, and for homogeneous freezing experiments
100 nmH2SO4 particles were used. Results from these experiments are
presented for different size channels, which show the growth of the
particles at different RHs to various sizes. For example, for the homogeneous
freezing experiments at 233 K, ice particles are observed in
size channels >0.5 µm at RHw>97.5 %, while in the experiments at 242/243 K and at
RHw=100–107 % cloud droplets are measured in
size channels <5 µm, but not in the size channel >5 µm, which is thus used to detect ice crystals. The
activated fraction (AF), which is the ratio of aerosol particles
activated into cloud droplets or nucleated ice crystals to the number
of total particles, counted by a condensation particle counter (CPC;
TSI 3772) in parallel, is reported.
Accuracy of temperature and RH in HINC
At T<235 K, homogeneous freezing experiments
were conducted to compare the onset of freezing observed in HINC to
values reported and modeled in the literature (Koop et al., 2000a). In
the respective experiments the RHw conditions in
HINC were increased at an approximate rate of 0.5 %min-1, so
that an increase in RHw of ∼ 10 % was
achieved over a total time of 20 min, which implies that during the
8 s aerosol residence time in HINC the particles experienced
constant RH conditions. Experiments with 100 nmH2SO4
particles at 233 K (Fig. 2) revealed that the onset of
freezing in HINC occurs within RHw±1.5 % of the expected RHw required to freeze
solution droplets of the same initial dry size of the solute particles
(Koop et al., 2000a), based on a fixed nucleation rate coefficient of
1010 cm-3s-1 (Koop et al., 2000a), which is
RHw=98.6 % as shown by the dashed line in
Fig. 2. The reported RHw on the x axis in the
figure represents the nominal conditions at the centerline of the
chamber, which is the center of the aerosol layer. Due to the width of
the aerosol layer, the particles are exposed to a variation in
RHw±1 % and to an uncertainty in
RHw±1 % due to the temperature
uncertainty. The grey shading in Fig. 2 represents this total
calculated uncertainty of RHw±2 %, for
a prescribed RHw=98.6 %. When the chamber
is set to RHw=98.6 %, the aerosols can be
exposed to the RHw range of
96.6–100.6 %. Our experiments reveal an increase in the AF of
particles between 2 and 8 µm, starting at 97.5 % and
reaching a plateau value at 99.5 %, which is in agreement to the
expected range of freezing within the aerosol layer. According to
theoretical calculations (Koop et al., 2000a) at 233 K and
RHw=98.6 % (99 %) and using a nucleation
rate of 1010 cm-3s-1, we expect for initial
100 nmH2SO4 particles at a residence time of 8 s an AF of
0.001 (0.005), which is an order of magnitude below the AFs observed in
Fig. 2. However, this AF is within the uncertainty range given that in
this region where the AF is a steep function of RH, an uncertainty of
RHw of 1 % can result in a change in AF by
a factor of 10–100.
Above homogeneous freezing temperatures (T>235 K), we
expect cloud droplet activation for 200 nm
(NH4)2SO4 and H2SO4 particles at
RHw=100 %. We thereby report the onset of
cloud droplet formation, which is the first observed increase in the
AF at a given size in the OPC channels. This is observed in the
smaller OPC channels (0.5–2 µm) as an increase in the AF
when the conditions in the chamber approach RHw=99–100 % as observed for H2SO4 (Fig. 3) and for ambient
particles (Fig. 4). The grey shaded area in Figs. 3, 4 and 5 also
includes the calculated variation and uncertainty in
RHw for the given temperatures of 242 and
243 K, respectively. As discussed above, the exposure of the
aerosol particles to this variable RH leads to droplet activation not
only at RH=100 % but in a range of RH pertaining to the
variation and uncertainty in HINC. Such aerosol particles grow
within the residence time of 8 s to different sizes, which is
depicted by the difference in the OPC size channels. In addition, this
is also the reason why at RHw=101 % for
example (Fig. 3), the AF is still observed to be increasing because
some particles in the aerosol layer are still exposed to
RHw=99–100 %, explaining why droplet
activation is observed up to a RHw of 102 %. We note that an
increase in the AF of initial 200 nmH2SO4 is observed
prior to RHw=100 % in the 0.5 and
1 µm channels (Fig. 3), which is to be expected due to
hygroscopic growth of the H2SO4 particles. Therefore, the
increase in size for RHw<100 % is only
observed in the smaller size channels occurring prior to droplet
activation at RHw<100 %, while an increase
at RHw=100 % in the >2 µm
channel is observed due to cloud droplet activation. In contrast, the ambient particles show droplet activation in the >0.5 µm, >1 µm and >2 µm
channels at RHw=101.5 % (Fig. 4). This is
likely due to the lower hygroscopicity of the ambient particles
compared to H2SO4 and due to a larger fraction of the sampled
ambient particles being ≪ 100 nm, requiring higher RH for
the droplets to activate and grow to detectable cloud droplet sizes at
this temperature. In addition, the experiments could also be
influenced by RH uncertainties (see Sect. 2.3).
At lower RHw, hygroscopic growth due to
deliquescence was also observed as an increase in particle
concentrations in the smallest OPC channels of 0.3 and
1 µm, which occurred for 200 nm NaCl in the range
of RHw=79.5–81 % (Fig. 5). The observed
increase in the particle fraction due to deliquescence and hygroscopic
growth compares well to literature results reported to be
RHw=77±2.5 % (Koop et al., 2000b). We
observe a first strong increase in the particle fraction >0.3 and
>1 µm at 80–81 %, followed by a gradual increase in
the particle fraction to unity (within uncertainties) at
RHw≈94 % for the >0.3 µm trace. Deliquescence is a phase change and not
a growth process, and a delay as compared to the literature value
(dashed line Fig. 5) is expected, since the deliquesced particles need
to grow to a size >0.3 µm to be detected in the OPC. In
theory we would expect all particles to grow to sizes larger than
0.3 µm at RHw≥80 % since
the deliquescence and growth threshold has been reached. However, we
note that due to an uncertainty in sizing of up to 3.5 % in the
DMA, particles between 193 and 207 nm for a nominal size of
200 nm will be sampled. In reality, we expect an even broader
size distribution because dried NaCl particles are aspherical and
result in larger sizing errors (Ardon-Dryer et al., 2015). Due to the
size selection method with the DMA, a non-negligible fraction of
larger particles (10 %) between 320 and 440 nm (from double
and triple charged particles) will also be sampled by HINC. This
breadth in size distribution may explain the initial increase in
particle fraction at RHw=80 % arising from
the multiply charged particles followed by a progressive increase in
the particle fraction up to RHw=94 % where
all the particles grow to sizes >0.3 µm. The same can
be said for the >1 µm trace. Note that complete
activation in this trace occurs at RHw>100 %, which is expected from the variation in RH in the aerosol
layer. Finally, we note that the goal of this experiment is to
demonstrate that HINC can achieve prescribed RH conditions with
reasonable accuracy by controlling the wall temperature as is seen by
the onset in growth at RHw=80 % in
Fig. 5. Additionally, we acknowledge that the fraction of particles >0.3 µm reaches a maximum at higher
RHw than theoretically expected, which can also
be attributed to the sizing and counting uncertainty of the OPC, which
is most pronounced at these small particle sizes, when the wavelength
of the laser (780 nm) is similar to the diameter of detectable
particles. Due to the generation method of NaCl at T>273 K
and immediate exposure of the NaCl to the respective temperature and
humidity when the aerosol particles are injected in HINC, we believe
that we deliquesce NaCl anhydrate and not NaCl dihydrate (Bode
et al., 2015). For 200 nm (NH4)2SO4 particles,
deliquescence and hygroscopic growth was also observed at
RHw=82–85 %, consistent with the
(NH4)2SO4 deliquescence at a RHw=82–84 % (Cziczo and Abbatt, 1999). All validation experiments to
verify the RH and temperature accuracy in HINC are summarized in
Fig. 6.
Homogeneous freezing curve of 100 nm dry diameter
H2SO4 particles. AF as a function of
RHw at 233 K in the OPC size channels
0.5–2 µm (dark grey) and 2–8 µm (light
grey). The dashed line (RHw=98.6 %)
represents the expected RHw for homogeneous
freezing of dilute solution drops of an initial dry diameter of
100 nm (Koop et al., 2000a), and the shaded region indicates
the calculated range of RHw and uncertainty to
which the particles in the aerosol layer in HINC are exposed.
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Water droplet (or ice crystal for >5 µm)
activation fraction and subsequent growth as function of
RHw at 243 K for 200 nm dry
diameter H2SO4 particles, shown for all size channels >0.5 µm in the OPC. Vertical dashed line represents
expected onset for cloud droplet formation; grey area refers to the
calculated variation and uncertainty of RH in the aerosol layer.
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Water droplet activation fraction and subsequent growth as
function of RHw at 242 K for ambient
polydisperse particles sampled at the JFJ, shown for all size
channels in the OPC. Vertical dashed line represents expected onset
for cloud droplet formation; grey area refers to the calculated
variation and uncertainty of RH in the aerosol layer.
![]()
Particle fraction due to hygroscopic growth after
deliquescence as function of RHw at
238 K for 200 nm NaCl particles. Vertical dashed
lines represent deliquescence RHw of NaCl at
RHw=77 % and onset of cloud droplet
formation at RHw=100 %; green shaded area
refers to observed uncertainty in deliquescence by Koop
et al. (2000b); grey area refers to the calculated variation and
uncertainty of RH in HINC in the aerosol layer.
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Upper RH limit for ice crystal detection: water drop
survival (WDS)
The upper RH achievable to reliably detect ice crystals is limited by the
possible activation and subsequent diffusional growth of water drops, since
only the optical size is used to discriminate between ice crystals (larger)
and water droplets (smaller) at the same temperature and RH conditions. To
identify the maximum operation RH, experiments are conducted with
200 nm (NH4)2SO4 and H2SO4 particles at T>235 K where homogeneous freezing is insignificant. For these
experiments the RH is increased until activated water droplets grow to
a diameter which is detected in the OPC size channel used to detect ice
crystals. This is referred to as the WDS point. Based on diffusional growth
calculations (Rogers and Yau, 1989) activated cloud droplets of an initial
diameter of 200 nm can grow to a size of 4 µm in HINC at
242 K, with RHw=104 % for a residence time of
8 s (conditions used for field experiments reported here), giving us
confidence that droplets are not detected in the > 5 µm channel.
Only at a RHw of 107 % can cloud droplets grow to >5 µm, and therefore by conducting our experiments at
RHw=104 % we only detect ice crystals in the
5 µm OPC channel. As a confirmation, no counts in the size
channel >5 µm were observed for H2SO4 particles
(Fig. 3) even up to a RHw of 107 %. With sampling
ambient particles an increase in AF for particles >5 µm at
RHw=104–105 % is observed (see Fig. 4), which can
be caused by ice crystals forming heterogeneously, since water droplets
cannot grow to this size at the respective conditions in HINC. These
calculations also reveal that the diffusional growth of the activated cloud
droplets and hence the final size of the cloud droplets of interest, which
is 5 µm for the discussed field experiments, are insensitive to
the initial dry diameter of the aerosol particles, since the final droplet
size at 242 K, RHw=104 % and a residence
time of 8 s of an initial 50, 200 and 800 nm is 4.035, 4.038 and
4.08 µm, respectively. Also, effects of the particle chemistry are
assumed to be negligible for the droplet activation, since we conduct our
experiments at RHw ≥ 104 %, where a variety
of aerosol chemical compositions should activate into droplets. Thus water
droplets contaminating the 5 µm channel should not occur even
with varying hygroscopicities and sizes of aerosol populations. Note that the
AF even at low RH is non-zero, which is caused by either unactivated sample
particles (particularly in the smallest size channels) or internal
background counts (see Sect. 2.3). These experiments give us confidence that
by operating at T=242 K and
an RHw ≤ 104 %, the OPC size channel >5 µm is suited to reliably detect ice crystals for field
measurements. Diffusional growth of ice crystals for the respective
conditions in HINC reveals that ice crystals can be lost to settling within
7 s. Still, residence time experiments with 400 nm microcline
particles at 242 K and RHw=104 % show that
the AF is at a maximum value at 8 s (Fig. A1, Appendix), which informed the
8 s residence time in the field experiments. This discrepancy with the
theoretical calculation of 7 s is expected due to assumptions in the
diffusional growth calculations, such as immediate activation upon entering
the chamber and assuming spherical ice crystals. The residence time of 8 s
therefore should include consideration for the equilibration time of the
particles to the center supersaturation (∼ 0.2 s), the growth time of
ice crystals to >5 µm (2 s) and time dependence for
nucleation (up to ∼6 s). Thus the residence time of 8 s should also
minimize the number of ice crystals < 5 µm, since ice
crystals only need 2 s to grow by diffusion to sizes >5 µm at
this high RHi=140 % (RHw=104 %). We believe that undercounting INPs due to ice crystals <5 µm should not significantly influence the INP concentrations
reported especially given the day-to-day variability in INP concentrations
found at the field site studied in this work.
Summary of characterization experiments and comparison to
literature and theoretical values of phase changes and growth
processes. Data from experiments reflect the first appearance of ice
(ice onset) when the AF increases above the chamber background
levels.
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Summary of validation and verification experiments
In Fig. 6, we show the results from all the validation experiments performed.
The observed phase changes are in the expected range of homogeneous freezing
of solution droplets (Koop et al., 2000a), cloud droplet formation (Lohmann
et al., 2016) and deliquescence of NaCl (Koop et al., 2000b) and
(NH4)2SO4 (Cziczo and Abbatt, 1999). The ice onset for
homogeneous freezing of H2SO4 was observed within a range of
RHw±1.5 % of the value reported in Koop
et al. (2000a). At colder temperatures, the onset of homogeneous freezing is
observed to shift to higher RHw but still remains well
within the range of uncertainty in RH (see Sect. 2.3) of HINC. Above
235 K, where freezing of dilute water droplets is not expected,
droplet formation for both H2SO4 and (NH4)2SO4 as well
as ambient particles was observed at RHw=100±1.5 %, where particles initially not detectable in the OPC size channel
>1 µm activate to droplets and grow large enough to be
detected. At lower RHw we observe hygroscopic growth
upon deliquescence of NaCl and (NH4)2SO4 particles as an
increase in the OPC size channel >0.3 µm. For NaCl such an
increase was observed at RHw=79–81 %, as compared
to a RHw=77±2.5 % (Koop et al., 2000b). For
(NH4)2SO4 particles a growth was observed at
RHw=81–85 % as compared to
RHw=82–84 % (Cziczo and Abbatt, 1999). Both the
phase change and cloud droplet formation experiments with H2SO4,
(NH4)2SO4, NaCl and ambient particles verify that HINC operates
reliably at the discussed settings of temperature and RH. As can be seen from
Fig. 6, some deviation (all within instrument uncertainty) of the data points
does occur. This is due to the fact that in the region of ice nucleation or
droplet activation the AF (nucleation rate) is a very steep function of RH
and a small change in water activity by, for example, 0.01 (∼ RH of
1 % at equilibrium) can change the nucleation rate by a factor of 10 or
15.
Uncertainties and limit of detection (LOD)
Uncertainties in temperature and RH to which the aerosol particles are
exposed to can arise from the set wall temperatures of HINC that are measured
by two thermocouples on each wall in the activation/growth section of the
chamber. The thermocouples have an uncertainty of ±0.1 K. This
translates into an uncertainty in RH at the center location of
RHw ± 1 %
(RHi = ± 1 %) at a center temperature of 242 K and at RHw=104 %. In addition to
this, the aerosol layer is only 1/13th of the total flow (for a typical
sheath-to-aerosol ratio of 12 : 1) and, since a linear temperature gradient
establishes between the warm and the cold wall, there is a temperature
variation of ±0.4 K across the aerosol layer for the
temperature conditions (242 K) used in the field measurements
presented here. The variation in temperature causes a variation in
RHw of ±1 %
(RHi ± 2 %). This translates into a calculated
total uncertainty of RHw ± 2 %
(RHi ± 3 %) at 242 K and
RHw=104 %. The validation experiments of
homogeneous freezing and cloud droplet activation reveal an uncertainty of
RHw ± 1.5 %, which is slightly lower than the
calculated uncertainty and shows that HINC is able to precisely establish
prescribed supersaturations. Thus we take the uncertainties to be
±0.4 K and RHw ± 1.5 %
(RHi ± 3 %), respectively.
The OPC, which is used to classify and count detected hydrometeors downstream
of HINC, has a relative counting accuracy of ±10 % and a relative
uncertainty in the sizing channels of ±10 %. The CPC, which was
used to measure the total particle concentration in parallel to the INP
measurements, has a relative counting accuracy of ±10 %, resulting
in a relative uncertainty in the AF of 14 %. The DMA, which was used to
size select the (NH4)2SO4 and H2SO4 particles, has
a relative sizing uncertainty of 3–3.5 %.
During an ice nucleation experiment, erroneous counts in the OPC ice
channel can arise from electrical noise in the OPC or from internal
ice sources such as frost falling off the warmer chamber wall giving
rise to particle counts that are falsely classified as ice. In order
to assess and to correct for the contribution of such false counts,
filter measurements are conducted regularly before and after each
sampling period to determine a background count in the following way:
the instrument is set to its target temperature and RH, and the
aerosol flow is sampled through a particle filter placed upstream of
the aerosol injector for 10 min before and after each
aerosol-sampling period of 20 min. It is observed that the background
counts do not change significantly over this time and follow a Poisson
distribution. The mean background (μ) and the standard deviation
(σ) are derived from the two 10 min filter periods. The
mean ambient INP counts (INP‾) are calculated from the
counts (ω) during a 20 min sampling by taking the
background into consideration, resulting in INP‾=ω-μ. The values of μ and σ are used to
assess whether the signal, i.e., INP‾, is significantly different
from the noise. Therefore, the instrument's LOD for ambient INP
following Poisson statistics is calculated as LOD=σ.
Comparing INP‾ to the LOD can result in one of
three scenarios:
INP‾>σ,
INP‾<0,
0<INP‾<σ.
Scenario 1 is considered as a quantifiable INP measurement with
significance because ω>μ+σ and therefore
above the LOD. In scenario 2, INP counts are considered to be
non-quantifiable for the volume of air sampled during the 20 min
period. In scenario 3, INP counts are below the LOD but above μ,
therefore quantifiable but not with significant confidence. INP
concentrations below the instrument LOD (scenarios 2 and 3) are
included in calculations of field campaign averages. We believe that
this is crucial since ambient INP concentrations are typically quite
low in the FT, and scenarios 2 and 3 occurring frequently actually
speaks to this low observed INP concentration. Complete ignorance of
values from scenarios 2 and 3 would lead to an artificially positive
bias in reporting INP concentrations (for detailed discussion see
Boose et al., 2016a). The concentrations below the LOD are taken into
account as their measured value (scenario 3). In the case of
scenario 2, instead of using a value of zero for calculating campaign
averages, a minimum quantifiable concentration for a 20 min period is
used. This is determined by taking the minimum count possible in the
OPC ice channel (1 count) and normalizing to the volume of ambient air
during a 20 min sampling period. By doing so we acknowledge that the
true concentration could be below this minimum value (shown in
Table 2). In addition, by accounting for the minimum quantifiable
concentration in the manner described above, we take into
consideration the increase in sampled volume of ambient aerosol flow
due to the use of an aerosol concentrator, applied in winters 2013 and
2014 (Boose et al., 2016a), which lowers the LOD by a certain
concentration factor. For transparency we show average INP
concentrations including and excluding the values below the
LOD. Finally, ambient INP counts and LODs are converted to
concentrations in stdL-1.
Field measurements
To further validate the chamber performance for field measurements,
INP measurements were conducted at the JFJ during the winters of 2015
and 2016 with HINC and are compared to earlier measurements conducted
at the same location and sampling conditions with PINC (Boose et al.,
2016a) during winters 2012, 2013 and 2014. The ice nucleation
measurements were performed in the deposition nucleation mode and,
since winter 2014, also in the condensation freezing mode. Detailed
measurement dates and sampling periods for the campaigns are given in
Table 1.
Field measurement period and respective total sampling time
of INP measurements and cloud water samples. Measurements were
performed with PINC (winter 2012–2014) and HINC (winter 2015 and
2016).
Measurements
Start
End
Breaks
Total sampling time (h)
PINC/HINC
Cloud water
T (K)
RHw 93/94 %
RHw-104 %
Winter 2012∗
12 Jan
27 Jan
–
241
62.3
–
Winter 2013∗
21 Jan
28 Feb
–
241
138.9
–
Winter 2014∗
23 Jan
16 Feb
–
241
54.6
28.5
67.8
Winter 2015
24 Jan
9 Feb
–
242
16
26
146
Winter 2016
13 Jan
6 Mar
1 Feb–26 Feb
242
17.1
99
42.5
∗ Boose et al. (2016a) measured with PINC
HINC was set up in the field as shown in the schematic in
Fig. 7. Particles were sampled from a total aerosol inlet, which is
described in detail by Weingartner et al. (1999). Ambient interstitial
and cloud-phase particles with diameters <40 µm at
wind velocities <20 ms-1 were sampled through an
inlet heated to 293 K to evaporate cloud droplets and ice
crystals. To exclude an additional humidity source from ambient air,
the aerosol flow was passed through a diffusion dryer
(RHw<2 %) and was then split into HINC
(0.22 stdLmin-1 aerosol flow,
2.83 stdLmin-1 total flow) and a CPC (TSI 3772,
1 stdLmin-1), counting the total particle concentration
in parallel.
The measurement conditions were set such that the aerosol flow
experienced a constant temperature of 242 K and
RHw=94±1 % (RHi=127±2 %), relevant for heterogeneous nucleation of ice
clouds, and at T=242 K and RHw=104±1.5 % (RHi=140±3 %) in
winters 2015 and 2016, relevant for the mixed-phase cloud regime. The
injector position was set to an optimal residence time (8 s) for the
aerosol particles, which takes into account prevention of ice crystal
losses due to gravitational settling in the chamber but also allows
for enough growth time to reach an optical diameter of ≥ 5 µm. Experiments with two OPCs, one in parallel and one
downstream of the ice chamber, were performed in order to obtain the
difference in concentrations due to aerosol particle losses. For this
test, HINC was set to its field campaign at T=242 K and well below water saturation to prevent any
activation of particles as droplets or ice crystals. The experiments
revealed a particle loss of 26 % for 1 µm particles,
44 % for 2 µm particles and 100 % for
particles >5 µm; therefore the OPC channel used to
detect ice should not be contaminated with large (>5 µm) unactivated ambient particles. As such the INP
measurements reported here are representative for ambient particles
below 2 µm. This size range is characteristic for ambient
aerosols at the JFJ, since particle concentrations >1 µm are naturally very low (e.g., Nyeki et al., 1998;
Baltensperger et al., 1998). In addition, calculations with the
Particle Loss Calculator (von der Weiden et al., 2009) revealed that
0.8 % of 1 µm particles, 2.6 % of
2 µm particles and 14–50 % of 5–10 µm
particles should be lost in the inlet and tubing upstream of HINC,
which we consider to be negligible in light of the low abundance of
particles >5 µm (on the order of
0.05 stdL-1).
For the field measurements, after the icing procedure (see Sect. 2.1)
the chamber walls were set to their target temperature, such that
a center aerosol temperature of 242 K and a
RHw of 94 % were achieved. While the chamber
cooled down to these conditions, it was flooded with filtered dry air
to prevent moist room air from contaminating the iced chamber
walls. When the target temperature and RH was reached, a 10 min
filter measurement, to quantify the background counts, was conducted,
followed by a 20 min aerosol measurement and another 10 min filter
measurement. Following this procedure, the RH was further increased to
104 %, and the background–sample–background measurement cycle was
repeated.
To avoid depletion of the ice layers in HINC, sampling time was limited to
a maximum of 14 h, of which approximately 50 % was performed during
nighttime, namely from 19:00 to 07:00.
Schematic of aerosol flow and instrument setup during field
measurements at the JFJ research station.
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Location
Measurements were performed at the JFJ, located in the Bernese Alps
(3580 ma.s.l.; 46∘33′ N,
7∘59′ E). The research facility is a Global
Atmospheric Watch (GAW) monitoring station and part of the ACTRIS2
Infrastructure (European Research Infrastructure for the observation
of Aerosol, Clouds, and Trace gases), the Swiss National Air Pollution
Monitoring Network (NABEL) and the SwissMetNet meteorological
network. The station is located on an exposed mountain col, only
surrounded by firn ice and rocks, without noticeable influence from
local vegetation. Due to its elevation, the site is mostly located in
the FT and represents background aerosol concentrations (Baltensperger
et al., 1997). It can be influenced by local emissions due to daytime
tourist activities and boundary layer injections in the warmer season
(Lugauer et al., 1998; Zellweger et al., 2003; Collaud Coen et al.,
2011; Griffiths et al., 2013; Herrmann et al., 2015). In addition, the
station is regularly affected by Saharan dust events (SDEs) where
Saharan dust is transported within the FT to the JFJ (Collaud Coen
et al., 2004). Continuous measurements of aerosol physical properties
(e.g., Baltensperger et al., 1997; Bukowiecki et al., 2016), trace
gases (Steinbacher et al., 2016) and meteorological conditions
(Appenzeller et al., 2008) are conducted and give additional
information on aerosol properties and air mass origin to complement
the INP measurements conducted.
Aerosol particle measurements
A custom-built scanning mobility particle sizer (SMPS), consisting of a DMA
(TSI 3071) and a CPC (TSI, 3775), measured the aerosol size distributions
between 20 and 600 nm in diameter with a time resolution of
6 min (Herrmann et al., 2015). Larger-sized particles were measured
by an OPC (GRIMM Dust Monitor 1.108; size range 0.23–16.4 µm).
To merge the respective size distributions, the mobility and optical
diameters were converted to volume equivalent diameters, assuming a particle
density of 1565 kgm-3 (Sjogren et al., 2008) and a unity shape
factor. An integrating nephelometer (TSI, 3563) and an aethalometer (MAGEE
scientific, AE31) measured the total aerosol scattering coefficients (three
wavelengths) and the absorption coefficients (seven wavelengths),
respectively. From this the single scattering albedo (SSA) at 450, 550 and
700 nm is derived, as well as the SSA Ångström exponent, as
described by Collaud Coen et al. (2004). For the normal background aerosol,
the SSA increases with wavelength, resulting in a positive SSA
Ångström exponent, while for Saharan dust particles, due to their
larger size and different optical properties, the SSA decreases with
wavelength and its exponent becomes negative. A SDE is declared if the SSA
exponent is negative for more than 4 consecutive hours. The aethalometer also
measures the equivalent black carbon (eBC) mass concentration, derived from
the attenuation measurement by applying the factory standard mass attenuation
cross section of 16.6 m2g-1 at 880 nm.
Cloud water samples
Cloud water samples at the JFJ were collected to determine the air mass
origin and aerosol source regions by analyzing the samples for trace chemical
elements (e.g., Zipori et al., 2015) and as such were taken in parallel to
the ice nucleation measurements during cloudy periods (see Table 1 for
sampling times). Samples were collected on the terrace next to the
laboratories at the JFJ, with a home-built plexiglass plate (20×20×0.5 cm) which was attached vertically to the railing, facing
the windward side. Prior to the sampling, the plate was cleaned with a super
pure (65 %) nitric acid solution (0.1 % w/w) and double-deionized
water, and a blank sample with double-deionized water was taken by pouring it
over the sampler. The sampling method works only for supercooled cloud
droplets which freeze upon contact with the plate and not for ice crystals
and precipitation particles, since ice crystals are deflected, and snowflakes
are too heavy to stick to the sampler. The supercooled cloud droplets remain
as an ice layer on the sampler, which is melted into pre-rinsed plastic bags
and stored in Falcon® tubes. The samples
were sent to the clean room laboratory at the Hebrew University of Jerusalem,
where they were analyzed for 23 trace metals using inductively coupled plasma
mass spectrometer (ICP-MS, Agilent, 7500cx). Detailed information
regarding sample handling, analysis protocol and quality control can be found
in Zipori et al. (2012, 2015).
The interpretation of the analysis of elemental concentrations was
focused on sodium (Na), aluminium (Al), lead (Pb) and strontium
(Sr). Sodium chloride (NaCl) is a natural component of the ocean, and
the positive ion Na+ is found in an appreciable quantity in
sea spray aerosol. In addition, Na+ found in cloud samples is
always accompanied by Sr. The fraction of Sr coming from sea salt
(f(Sr)ss) is used as an indication for air masses
influence and is calculated using the following equation:
fSrss=SrNass×NaSrsamp,
where f(Sr)ss is the fraction of Sr contributed from sea
salt, [Sr / Na]ss is the Sr-to-Na ratio found
in sea salt and [Sr / Na]samp are the
concentrations of Na and Sr found in the samples (Herut et al., 1993).
Furthermore, elemental ratios such Na / Al,
Pb / Al and Pb / Na were used as
indications for marine / dust, anthropogenic / dust and anthropogenic / marine
influence in the samples, respectively.
In addition to the chemical analysis, Sr isotopic ratios were also measured
with a multi-collector inductively coupled plasma mass spectrometer
(MC-ICP-MS, NEPTUNE Plus). Sr separation was done with Sr-Spec resin flowing,
a method described by Stein et al. (1997). Since marine
87Sr / 86Sr is constant with a value of 0.70917
(Hodell et al., 1990) while basalt and volcanic rocks have a lower ratio and
Saharan dust has higher ratio (Capo et al., 1998, and references therein),
this parameter can be used to determine the prevailing aerosol type in the
sample due to scavenging.
Back trajectories and source sensitivities
To obtain information on the trajectories of the air masses arriving
at the JFJ, an ensemble of 10-day back trajectories was calculated
every 6 h with the LAGRANTO model (Wernli and Davies, 1997), based on
ECMWF Integrated Forecast System wind fields. Back trajectories at
five different locations, one ending at the JFJ and four displaced by
0.5∘ to the north and south, are started at four different
altitude levels of 654, 704, 604 and 754 hPa. In addition,
source sensitivities, which determine the potential contribution of
ground-based regions to be the source region of the particles arriving at the
JFJ, are derived from the Lagrangian particle dispersion model,
FLEXPART, products browser at EMPA
(http://lagrange.empa.ch/FLEXPART_browser/; Stohl et al., 2005;
Sturm et al., 2013; Pandey Deolal et al., 2014). The source
sensitivities thus give the possible origin of the particles as
a probability of the geographical regions from which the aerosol
particles were emitted. It simulates the release of 50 000 particles
every 3 h at the JFJ and traces the particles backwards driven by
ECMWF Integrated Forecast System wind fields.
Assessment of free-tropospheric conditions
Different proxies are used in this study to qualitatively assess the exposure
of the site to the FT. The ratio of total reactive nitrogen (NOy,
as the sum of nitrogen oxide, nitrogen dioxide and its atmospheric oxidation
products) to carbon dioxide (CO) is commonly used as an indicator for
boundary layer injections into the FT at elevated stations (Zellweger et al.,
2003; Zanis et al., 2007; Pandey Deolal et al., 2013; Griffiths et al., 2014;
Herrmann et al., 2015; Boose et al., 2016a). Both tracers are subject to
emissions from anthropogenic sources, however, the
NOy / CO ratio decreases with increasing transport
(aging) of the air mass as CO is inert within the timescale of interest
(days) while the concentration decay rate of NOy is higher. Thus,
a NOy / CO ratio of 0.0057 ppbppb-1 was
chosen to distinguish between FT conditions and boundary layer influence, in
accordance with the value reported for wintertime measurements at the JFJ by
Zellweger et al. (2003). NOy / CO ratios below 0.0057
indicate FT conditions while an influence of boundary layer is likely for
ratios above this value.
The concentration of particles >90 nm was also used to identify FT
conditions, since particles of this size are not formed in the FT but are
transported from the boundary layer, and therefore gives information on
boundary layer influence (Herrmann et al., 2015). A threshold of
100 cm-3 was chosen, below which the air mass is assumed to be
free tropospheric. It should be mentioned that the concentration of particles
>90 nm can be influenced by the occurrence of larger-sized dust
particles and should therefore be considered with care during SDEs which are
transported in the FT.
Conclusions
This is the first study in which an INP counter of HINC's design has been
used to quantify ambient INP concentrations at temperature and RH conditions
relevant for mixed-phase cloud formation, where both liquid and ice particles
can co-exist. We demonstrated that HINC, based on the design of the UT-CFDC
(Kanji and Abbatt, 2009), was successfully deployed to sample ambient INP
concentrations. The RH and temperature accuracy were determined for the
temperature range 223–263 K and at conditions of sub- and
supersaturation with respect to water by observing droplet activation of
sulfuric acid particles and deliquescence of sodium chloride and ammonium
sulfate particles. In addition, homogenous freezing of sulfuric acid aerosols
at temperatures <235 K also validated accurate conditions in HINC
for ice formation. The uncertainty in INP measurements in HINC arises from
the variation in temperature and RH to which the aerosols in the chamber are
exposed, which are T ± 0.4 K and
RHw ± 1.5 %
(RHi ± 3 %) for T>235 K. These variations can lead to uncertainties in AFs in the region of activation and nucleation where nucleation rates
are a steep function of RH. Conducting field measurements of INPs with
ambient aerosols at 242 K and RH 104 %, where we ensure all
particles are fully activated to droplets, reduces the associated
uncertainties in INP concentrations arising from the RH variation in the
chamber. HINC was characterized for an optimum residence time to maximize the
growth time of the ice crystals but avoid particle losses due to
gravitational settling in the horizontally oriented chamber. INP
concentration measurements with HINC from winters 2015 and 2016 at the JFJ
were presented at 242 K for RHw=94 and
104 %. Median INP concentrations, excluding specific events of high INP
concentrations, were on average ≤ 0.2 stdL-1 below water
saturation, and these low concentrations are within the range of the median
INP concentration of 0.1 stdL-1 measured at the same site
before, with PINC (Boose et al., 2016a),
during winters 2012–2014. Above water saturation, INP concentrations are in
general an order of magnitude higher, with a median concentration of
3.8 stdL-1 for winters 2015 and 2016 (HINC) and
2.2 stdL-1 during winter 2014 (Boose et al., 2016a).
Differences in INP concentrations from year to year are expected to occur due
to natural variability.
In winter 2015, an increase in INP concentrations above water saturation was
observed during the influence of an air mass of marine origin, with up to
72.1 stdL-1 and a median concentration of
16.3 stdL-1. The support of marine influence was based on
chemical analysis of cloud water samples with a high
f(Sr)ss and an increased Na / Al
ratio. Model calculations of back trajectories and air mass origin further
support our conclusion of a marine source but cannot exclude contributions
from anthropogenic or other sources due to entrained particles, which can
result in chemical ageing processes during transport to the JFJ. Another
marine event was identified in winter 2016, when INP concentrations increased
to values up to 176.8 stdL-1. During winter 2014, Boose
et al. (2016a) identified a marine influenced air mass arriving at the JFJ,
but the INP concentrations were within the campaign average. Our findings
suggest that the JFJ could regularly be affected by marine aerosols, which
can therefore contribute to bursts of increased INP populations in the FT.
An air mass with an increase of INPs was sampled during a SDE in winter 2015,
with median INP concentrations reaching 42.6 stdL-1 and a peak
INP concentration of 146.2 stdL-1. The identification of the
dust-laden air mass was supported by several independent measures of aerosol
physical and optical properties such as an increase in larger-sized particles
(0.4–0.8 and > 0.8 µm), a negative SSA Ångström
exponent, chemical analysis of cloud water samples and a decrease
in the Na / Al and Pb / Al ratios
due to an enrichment in Al. The dust source was further supported by air mass
back-trajectory and source sensitivity calculations, revealing the Sahara as a source region.
To extend measurements to warmer temperatures, a significantly
improved LOD must be achieved as INP are rarer. To quantify INP
concentrations in the range between 253 and 273 K, a technique
that is sensitive at warmer temperatures must be used, such as offline
techniques of drop freezing (e.g., Mason et al., 2015; Conen et al.,
2015). However, improving the LOD of online counters can also be
achieved by means of using an aerosol concentrator upstream of an INP
counter. This has been done in winters 2013 and 2014 (Boose et al.,
2016a), achieving a concentration factor of 3. Recently a more
efficient aerosol concentrator was implemented during a field campaign
at the JFJ (winter 2017) and will be the subject of a separate
study. The ability to conduct field measurements with HINC will aid
future measurements with increasing frequency at the JFJ to determine
diurnal and interannual variabilities in INP concentrations at this
location.