Modelling studies suggest that the climate and the
hydrological cycle are sensitive to the concentrations of ice-nucleating
particles (INPs). However, the concentrations, composition, and sources of
INPs in the atmosphere remain uncertain. Here, we report daily concentrations
of INPs in the immersion freezing mode and tracers of mineral dust (Al, Fe,
Ti, and Mn), sea spray aerosol (Na+ and Cl-), and anthropogenic
aerosol (Zn, Pb, NO3-, NH4+, and non-sea-salt
SO42-) at Alert, Canada, during a 3-week campaign in March 2016.
In total, 16 daily measurements of INPs are reported. The average INP
concentrations measured in the immersion freezing mode were
0.005±0.002, 0.020±0.004, and 0.186±0.040 L-1 at -15,
-20, and -25∘C, respectively. These concentrations are within
the range of concentrations measured previously in the Arctic at ground
level or sea level. Mineral dust tracers all correlated with INPs at
-25∘C (correlation coefficient, R, ranged from 0.70 to 0.76),
suggesting that mineral dust was a major contributor to the INP population
at -25∘C. Particle dispersion modelling suggests that the
source of the mineral dust may have been long-range transport from the Gobi
Desert. Sea spray tracers were anti-correlated with INPs at -25∘C
(R=-0.56). In addition, INP concentrations at -25∘C divided by
mass concentrations of aluminum were anti-correlated with sea spray
tracers (R=-0.51 and -0.55 for Na+
and Cl-, respectively), suggesting that the components of sea spray
aerosol suppressed the ice-nucleating ability of mineral dust in the
immersion freezing mode. Correlations between INPs and anthropogenic aerosol
tracers were not statistically significant. These results will improve our
understanding of INPs in the Arctic during spring.
Introduction
The formation of ice in clouds can be initiated by homogeneous or
heterogeneous nucleation. Heterogeneous nucleation of ice in clouds occurs
on only a small subset of atmospheric particles, referred to as
ice-nucleating particles (INPs) (Vali et al.,
2015). A variety of aerosol particle types have been identified as possible
INPs, including, but not limited to, mineral dust, sea spray aerosol
containing biological material, and primary biological particles from
terrestrial sources (Coluzza
et al., 2017; Cziczo et al., 2017; Hoose and Möhler, 2012; Kanji et al.,
2017; Murray et al., 2012). INPs can change the frequency and properties of
clouds in the atmosphere and influence climate and precipitation (Andreae
and Rosenfeld, 2008; Curry, 1995; DeMott et al., 2010; Du et al., 2011;
Lohmann and Feichter, 2005; Prenni et al., 2007; Xie et al., 2013). As a
result, to predict precipitation and Earth's climate, an understanding of
the concentrations, composition, and sources of INPs in the atmosphere is required.
INPs have been measured in the Arctic since as early as the 1970s (Bigg,
1996; Bigg and Leck, 2001; Borys, 1989; Conen et al., 2016; Creamean et al.,
2018; DeMott et al., 2016; Flyger et al., 1973, 1976; Flyger and Heidam,
1978; Fountain and Ohtake, 1985; Mason et al., 2016; McFarquhar et al.,
2011; Prenni et al., 2007, 2009; Radke et al., 1976; Rogers et al., 2001).
Nevertheless, our understanding of the concentrations, composition, and
sources of INPs in this region is incomplete. In the following, we focus on
INPs in the Arctic during the spring. In the Arctic winter–spring, land is
mostly covered by snow, and hence local emissions of mineral dust and primary
terrestrial biological particles are expected to be small. In addition, a
large fraction of the Arctic Ocean is covered by ice, limiting emissions of
sea spray aerosol. On the other hand, during the winter–spring, long-range
transport of particles from midlatitudes is important, and removal
processes of aerosols are reduced, leading to elevated aerosol particle
concentrations in the region, referred to as Arctic haze (Barrie,
1986; Barrie et al., 1981; Norman et al., 1999; Pacyna, 1995; Quinn et al.,
2007; Shaw, 1995).
There have only been a small number of measurements of INPs in the Arctic
during the spring (Borys,
1989; Creamean et al., 2018; Fountain and Ohtake, 1985; Mason et al., 2016;
McFarquhar et al., 2011; Radke et al., 1976; Rogers et al., 2001). Of note,
Borys (1989) measured INP concentrations in April 1986 and
found that low concentrations of INPs were associated with tracers of
pollution, while high concentrations of INPs were associated with a tracer
of mineral dust. Fountain and Ohtake (1985) measured
surface INP concentrations in Alaska from August 1978 to March 1979 and
observed that high INP concentrations in March were correlated with air
masses transported from Eurasia. Rogers et al. (2001)
measured concentrations and the chemical composition of INPs during aircraft
studies in May 1998. Chemical analysis of the INPs indicated that a
significant fraction of the INPs (approximately 37 %) contained mineral
dust. Mason et al. (2016) carried out size-resolved measurements of INPs from the end of
March to late July 2014. They found that a large fraction (>60 % at -20∘C)
of the INPs were larger than 1 µm,
indicating that supermicron particles such as mineral dust or sea spray aerosol
containing biological material contributed to a majority of the INPs.
The locations of previous ground-based and ship-based INP studies in
the Arctic. For Bigg (1996) and Bigg and Leck (2001), samples were collected
along the ship track, but only one location for each study is shown in this map.
The red diamond represents the location of current study.
In the following, we investigate the composition and sources of INPs at
Alert, Nunavut in the Canadian High Arctic from 11 to 29 March 2016. This
study was carried out as part of the Network on Climate and Aerosols:
Addressing Key Uncertainties in Remote Canadian Environments (NETCARE).
Specifically, we measured the concentrations of INPs daily in the immersion
freezing mode, and concentrations of tracers of mineral dust (Al, Fe, Ti,
and Mn), sea spray aerosol (Na+ and Cl-), and anthropogenic
aerosol (Zn, Pb, NO3-, NH4+, and non-sea-salt
SO42-). These data were used to determine if mineral dust, sea
spray aerosol, and anthropogenic aerosol are a major contributor to the INP
population at -15, -20, and -25∘C in the Canadian High
Arctic during spring. Studies as a function of temperature are necessary
since different types of aerosols are ice active at different temperatures.
Although a few studies have identified mineral dust particles as an
important contributor to the INP population in the Arctic during spring,
additional studies are needed to determine how often mineral dust is an
important contributor. The measurements reported here together with particle
dispersion modelling were also used to assess the source of the INPs at a
freezing temperature of -25∘C.
MethodsSampling location
Sampling was conducted at the Dr. Neil Trivett Global Atmosphere Watch
Observatory (82.5∘ N, 62.5∘ W) at Alert,
Nunavut (Fig. 1), a research laboratory operated by Environment and Climate
Change Canada. The research laboratory is on a plateau that is approximately
185 m a.s.l. (above sea level) and is powered by electricity generated by the
Canadian Forces Station Alert, which is 6 km to the north of the research
laboratory. The population at Alert is about 75 on a regular basis. The
closest community is Grise Fiord (population 129) located approximately 800 km
to the south of Alert.
INP measurements
Concentrations of INPs were determined by first collecting particles on
hydrophobic glass slides with an inertia impactor followed by determining
the freezing temperatures of the collected aerosol particles with the
droplet freezing technique (DeMott et al., 2016; Irish et al., 2019). Details
are given below.
Inertia impactor
The inertia impactor (model 100–180nm–10lpm; MSP Corp., Shoreview, MN, USA)
consisted of two impactor stages. The first impactor stage collected
particles with aerodynamic diameters > 10 µm, and the
second impactor stage collected particles with aerodynamic diameters between
0.18 and 10 µm. For each collection period, three circular
hydrophobic glass slides (HR3-277; Hampton Research, USA) were placed on the
second impactor stage simultaneously to collect particles for INP analysis.
As a result, each collected sample consisted of three hydrophobic glass
slides. Due to the design of the impactor, the collected particles were
concentrated into spots on the hydrophobic glass slides. Particles collected
on the first stage were not analyzed. The hydrophobic glass slides were
cleaned with Millipore water and dried with ultrapure nitrogen gas before
being sent to the field for particle collection. After collection, all
slides were placed in petri dishes, wrapped in aluminum foil, and stored at
4 ∘C before analysis. The inertia impactor was operated at
a flow rate of 10 L min-1, and the average collection time for INP
samples was approximately 2 h.
The inertia impactor was located within the Dr. Neil Trivett Global
Atmosphere Watch Observatory. Aerosol particles were first sampled through a
louvered total suspended particulate (TSP) inlet (Mesa Labs Inc., Butler,
NJ, USA) that was approximately 10 m a.g.l. (above ground level). Next, the aerosol
particles were passed through a humidifier (model FC125-240; Perma Pure LLC,
Lakewood, NJ, USA) to condition the aerosol particles to an average relative
humidity (RH) of 84 % at room temperature. Finally, the aerosol particles
were passed through the inertia impactor to collect the particles on the
hydrophobic glass slides for INP analysis. In total, 16 daily measurements
of INPs are reported in this study.
When sampling aerosol particles with an inertia impactor, a possible issue
is particle rebound from the collection substrate. Rebound occurs when the
kinetic energy of the particles striking the impactor substrate exceeds the
adhesion and dissipation energies at impact (Bateman et al., 2014). If
rebound is a factor, the measured INP concentrations will be lower than the
actual INP concentrations in the atmosphere. Previous work has shown that
particle rebound can be reduced when RH is above 70 % (Bateman
et al., 2014; Chen et al., 2011; Fang et al., 1991), although this will
depend on the chemical composition of the particles. In addition, field
measurements of INP concentrations using a similar inertia impactor have
shown good agreement with INP concentrations measured by a continuous flow
diffusion chamber (a technique that is not susceptible to rebound) when the
RH of the sampled aerosol stream was as low as 40 % (DeMott
et al., 2017; Mason et al., 2015). In our experiments, the RH was increased
to an average value of 84 % at room temperature with a humidifier to
reduce rebound. However, rebound cannot be completely ruled out.
Droplet freezing technique
The INP number concentrations in the immersion freezing mode were determined
with the droplet freezing technique (Iannone
et al., 2011; Mason et al., 2015; Wheeler et al., 2015). Briefly, the
hydrophobic glass slides used to collect aerosol particles with the inertia
impactor were placed in a temperature- and humidity-controlled flow cell
coupled to an optical microscope (Axiolab; Zeiss, Oberkochen, Germany) with
a CCD camera. Typically between 15 and 25 spots of particles (out of 300 spots
generated by the inertia impactor) were visible in the microscopic field of
view. The diameter of each spot was approximately 110 µm. After
locating the hydrophobic glass slides in the flow cell, the temperature in
the flow cell was decreased to approximately 0 ∘C and a
humidified flow of helium with a dew point of approximately 3 ∘C
was passed over the hydrophobic glass slide, resulting
in water droplets with diameters of approximately 100–500 µm
condensing on the spots of particles as well as other areas on the glass
slides. Droplets that condensed on the spots of particles are referred to as
spot droplets, while droplets that condensed on other areas of the slide are
referred to as non-spot droplets. After condensation of the water droplets,
the flow cell was cooled down to -40∘C at a rate of
-10∘C min-1 while images of the droplets were recorded. A
small flow of dry helium (∼0.2 L min-1) was passed
through the flow cell during the cooling process to prevent further
condensation of water vapour. The freezing temperature of each droplet was
then determined from the images. The droplets that overlapped with spots of
particles were also identified from these images. The number of INPs, #INPs, within
the microscopic field of view was calculated as a function of temperature
using the following equation:
#INPs(T)=-lnNus(T)NsNs,
where Nus(T) is the number of unfrozen spot droplets at
temperature T, and Ns is the total number of spots analyzed in the
microscopic field of view. Equation (1) represents the cumulative nucleus
spectrum or the number of INPs active at all temperatures ≥T.
The use of Eq. (1) to quantify the number of INPs active at all
temperatures ≥T from droplet freezing experiments has been justified
using Poisson's law and Monte Carlo simulations (Vali, 1971).
Equation (1) assumes that each droplet covered only one spot. However,
sometimes more than one droplet formed on one spot. In these cases, the
first droplet to freeze was considered in Eq. (1), which should give the
equivalent result to one droplet condensing on one spot. Another situation
is when one droplet covered two spots (this occurred for less than 5 % of
the total analyzed spot droplets). For these cases, an upper limit of the
number of INPs was calculated by assuming two droplets covered the two spots
and both droplets froze at the observed freezing temperature. A lower limit
was calculated by assuming two droplets covered the two spots with one
droplet freezing at the observed freezing temperature and the other
freezing at -37∘C (approximately the homogeneous freezing
temperature of the droplets). A similar approach was applied to cases where
one droplet covered three or more spots.
Freezing of non-spot droplets was less frequent than freezing of spot
droplets at temperatures ≥-25∘C. For example, the
ratio of frozen non-spot droplets to frozen spot droplets was 0.2 at
-25∘C. Freezing of non-spot droplets may have been due to
INPs < 0.18 µm in diameter not focused into the spots or a small
fraction of INPs ≥ 0.18 µm not concentrated into the spots due
to rebound from the hydrophobic glass slides. To take into account the INPs
in the non-spot droplets, we assumed each frozen non-spot droplet contained
one INP, and the number of frozen non-spot droplets, Nns, was added to
Eq. (1), resulting in the following equation:
#INPs(T)=-lnNus(T)NsNs+Nns.
During the freezing experiments, most freezing events occurred by immersion
freezing, while some occurred by contact freezing, which refers to the
freezing of liquid droplets coming into contact with neighbouring frozen
droplets. Contact freezing only accounted for approximately 2 % of the
total freezing events, and droplets that froze by contact freezing were not
considered when determining the INP concentrations.
The INP concentration as a function of temperature in the atmosphere,
[INPs(T)], was calculated using the following equation:
[INPs(T)]=#INPs(T)300NsVfne,
where 300 is the number of nozzles in the nozzle plate of the impactor, and
consequently, the number of spots of particles generated on the second stage
of the impactor, V is the total volume of air sampled by the impactor, and
fne represents the uncertainty associated with the limited number of
nucleation events detected and is based on nucleation statistics
(Koop et al., 1997). In Eq. (3), the ratio of
300/Ns accounts for the fact that only a fraction of total spots was
analyzed with the droplet freezing technique. The overall uncertainty in the
concentrations of INPs reported here includes the uncertainty from the
limited number of nucleation events, as well as the other uncertainties discussed above.
Droplet freezing experiments were also performed on glass slides that were
not exposed to any particles. These slides are referred to as blanks. One
field blank was collected by treating the slides in the same manner as the
sample hydrophobic slides including locating the hydrophobic slides in the
impactor, except that the pump was not turned on. Lab blanks refer to slides
cleaned in the same manner as the ones used for sampling in the field but
not sent to the field. For the blanks, we assumed the number of INPs was equal
to the number of observed freezing events since multiple INPs within the
same droplet were unlikely at temperatures ≥-25∘C.
[INPs(T)] was then calculated using Eq. (3) with
the assumptions that Ns is 21 (average number of spots analyzed in one
experiment) and V is 1208 L (average air volume sampled).
Meteorological parameters
Local ground-level meteorological conditions were monitored at the site by
Environment and Climate Change Canada. The March 2016 data were retrieved
from http://climate.weather.gc.ca/ (last access: 28 August 2018) (climate IDs 2400305 and 2400306). The ambient
temperature, ambient RH, wind speed, and wind direction were measured
hourly. The sum of the total rainfall and the water equivalent of the total
snowfall in millimetres was measured daily as total precipitation.
Tracers of mineral dust, sea spray, and anthropogenic aerosol
The elements Al, Fe, Ti, and Mn were used as tracers of mineral dust, as
done previously (Balasubramanian et al., 2003; Barrie and Barrie, 1990;
Formenti et al., 2003; Malm et al.,
1994; Quinn et al., 2004). These elements are components of the Earth's
crust (Usher et al., 2003; Wedepohl, 1995). The species Na+ and Cl-, which are the major
inorganic components of seawater (Holland, 1978), were used as
tracers of sea spray, as done previously (Balasubramanian et al., 2003; Malm et al., 1994; Quinn et al., 2002, 2004). For tracers of
anthropogenic aerosol, we used Zn, Pb, NO3-, NH4+, and
non-sea-salt SO42- (nss-SO42-). Pb and Zn are almost
exclusively from anthropogenic sources (Macdonald
et al., 2000; Nriagu and Pacyna, 1988; Pacyna, 1995). The major
anthropogenic sources for Pb are gasoline combustion and, to a lesser
extent, non-ferrous metal industry and fossil fuel combustion, and the major
anthropogenic sources for Zn are non-ferrous metal industry followed by
fossil fuel combustion (Barrie et al., 1992;
Nriagu and Pacyna, 1988; Pacyna, 1995). NO3-, NH4+, and
nss-SO42- can come from both anthropogenic and natural sources,
but mostly from anthropogenic sources. NO3- is mainly formed from
NOx, which is emitted from combustion processes (Seinfeld
and Pandis, 2006). NH4+ originates mainly from agricultural
activities (Follett and Hatfield, 2001). The main anthropogenic
source of nss-SO42- is fossil fuel combustion (Schwikowski et al.,
1999; Ward, 2009).
To determine the concentrations of the tracers discussed above, aerosol
particulate samples were collected on 20×25 cm Whatman-41 quartz filters
daily using a high-volume sampler (Barrie
et al., 1981, 1989), which was located approximately 500 m away from the
laboratory on the ground. The face velocity of sampling (50 cm s-1) and
typical filter loadings ensured collection efficiencies better than 95 %
(Watts et al., 1987). The average sampling time was
23.5 h except for the first sample, which was collected over 2 days due to
a storm making it difficult to change the filter. Hence, collection times
for tracer measurements (∼24 h) were different than the
collection times for INP measurements (∼2 h). The implications
of the different collection times are discussed in Sect. 3.3. For the filter
samples, the average total air volume sampled was roughly 2300 m3 at
standard conditions of 1 atm pressure and 0 ∘C. The
precision of volume sampled was estimated to be ±5 % (Sirois and Barrie, 1999). The
quartz filter samples were stored at room temperature before analysis.
The concentrations of Al, Fe, Ti, Mn, Zn, and Pb were determined using
inductively coupled plasma atomic emission spectroscopy (ICP-AES). These
experiments were carried out at Chester LabNet, Oregon, USA. Punches from
the quartz filters were submerged in a solution containing ultrapure
HNO3 and HCl. The solution was then heated and sonicated, and then
further diluted and filtered before being nebulized and analyzed by the
ICP-AES (Perkin-Elmer Optima 8300). Sample duplicates were also analyzed to
estimate the method precision. The accuracy and precision of the technique
were estimated to be ±10 %.
The concentrations of Cl-, Na+, NO3-, SO42-,
and NH4+ were determined using ion chromatography (IC) (Macdonald et al., 2017;
Toom-Sauntry and Barrie, 2002). These experiments were carried out at
Environment and Climate Change Canada in Ontario, Canada. To quantify
water-soluble cations and anions, punches taken from each quartz filter were
extracted in deionized water, and the extraction solution was passed through
an IC (Dionex IC: DX600). The concentration of nss-SO42-
was calculated using the following equation based on the assumption that
the chemical composition of sea salt particles is the same as that of
seawater (Millero, 1974):
nss-SO42-=SO42--0.14Cl-.
To determine whether the calculated concentrations of nss-SO42-
were sensitive to depletion of Cl- in the particles, we also calculated
nss-SO42- using Na+ rather than Cl- (Balasubramanian, 2003). The
difference between the concentrations of nss-SO42- based on
Cl- and the concentrations based on Na+ was less than 5 %.
The INP concentrations from each sample plotted as a function of
temperature. Black represents lab blanks. Red represents the field blank. Blue represents samples, and the legend gives the
collection date of each sample in mm/dd/yy format.
Particle dispersion modelling
The source regions of measured air masses were investigated using the
Lagrangian FLEXible PARTicle dispersion model (FLEXPART) (Stohl et al., 2005), which was driven
using operational meteorological analyses from the European Centre for
Medium-Range Weather Forecasts (ECMWF). FLEXPART was run at hourly intervals
in the backward mode for each sample collected for INP analysis. In each
run, 40 000 particles were released over 1 min in a 0.1∘× 0.1∘
area. The particles were followed backward for 20 days with output generated
at 1 h intervals. In backward mode, FLEXPART provides potential emission
sensitivities as output. This is the response function of a source–receptor
matrix (Seibert and Frank, 2004) and corresponds
directly to the residence time of the released particles in a given volume
of air. For each run, the hourly output was integrated over the 20 days to
produce a potential emission sensitivity (PES) plot. For a given INP sample,
the mean PES plot was generated by averaging all hourly PES plots. Since the
focus of this study is INP sources close to the surface, near-surface PES
plots (from the surface up to 100 m) were plotted as footprint PES plots.
Statistical analysis
To compute a correlation coefficient (R), Pearson correlation analysis was
applied between INPs and the variables measured in this study. The P values were
also calculated using a t test for Student's t distribution to determine if
the correlations were statistically significant at the 95 % confidence level (P<0.05).
Measurements of the concentrations of INPs at ground level or sea
level in the Arctic. Included is the information on the sampling platform
(ground vs. ship based), location, and dates.
StudyPlatformLocationDatesRadke et al. (1976)GroundUtqiaġvik, Alaska, USAMar 1970Flyger and Heidam (1978)GroundNorth GreenlandJun–Aug 1974Fountain and Ohtake (1985)GroundUtqiaġvik, Alaska, USAAug 1978–Apr 1979Bigg (1996)ShipCentral Arctic OceanAug–Oct 1991Bigg and Leck (2001)ShipArctic OceanJul–Sep 1996DeMott et al. (2016)ShipCanadian ArcticJul 2014Mason et al. (2016)GroundAlert, Nunavut, CanadaMar–Jul 2014Conen et al. (2016)GroundNorthern NorwayJul 2015Creamean et al. (2018)GroundAlaska oilfields, USAMar–May 2017Current studyGroundAlert, Nunavut, CanadaMar 2016
INP concentrations measured at ground level or sea level in the Arctic.
Black represents previous ground-based and ship-based studies, and red represents
the current study. The error bars on current study data points represent the
standard error of the mean.
Results and discussionConcentrations of INPs
Concentrations of INPs in the immersion mode are plotted as a function of
temperature in Fig. 2. Concentrations of INPs measured were higher than
concentrations of the blanks. In addition, all of the samples have warmer
onset temperatures than the blanks, with onset temperatures of the samples
varying from approximately -11 to -22∘C. For the remainder
of this document, we focus on INP concentrations at -15, -20, and
-25∘C. INP concentrations at temperatures warmer than
-15∘C are not discussed because freezing events at these
temperatures were rare. INP concentrations at temperatures below
-25∘C are not discussed since freezing of the blanks became
significant at these temperatures. Since freezing was rarely observed at
≥-25∘C in the blank experiments, the INP
concentrations determined in the blank experiments were not subtracted from
the INP concentrations reported in this study.
The time series of INP concentrations at -15, -20, and
-25∘C. INP samples were not collected on 25 March due to time
constraints. On several days, INP concentrations are shown at -25∘C,
but not at -15∘C and some cases not at -20∘C. In these
cases, INP concentration was below the detection limit and hence not shown in
this figure. The uncertainties in INP concentrations were calculated as
described in Sect. 2.2.2.
In the current study, the mean number concentration of INPs was
0.005±0.002 L-1 at -15∘C, 0.020±0.004 L-1
at -20∘C, and 0.186±0.040 L-1 at -25∘C
(Fig. 3). These concentrations are within the range of
INP concentrations measured in previous studies at ground level or sea level
in the Arctic (Fig. 3). The sampling platform, location, and dates of
previous Arctic INP studies at ground level or sea level that are shown in
Fig. 3 are summarized in Table 1 and Fig. 1 for comparison purposes.
The time series of INP concentrations measured in the current study at -15,
-20, and -25∘C is plotted in Fig. 4. The difference
between the highest INP concentration at -25∘C (measured
on 28 March) and the lowest INP concentration at -25∘C
(measured on 17 March) was roughly a factor of 50.
The correlation coefficient (R) matrix between each of the measured
aerosol constituents. Strong correlations
(R≥0.7) that are statistically significant at the
95 % confidence level (P<0.05) are highlighted in bold.
The time series of meteorological parameters, including total
precipitation, ambient temperature, ambient relative humidity (RH), wind speed,
and wind direction. The meteorological data were retrieved from
http://climate.weather.gc.ca/ (last access: 28 August 2018). For wind direction, a value of zero denotes
a calm wind, and a value of 360 denotes a wind blowing from the geographic North Pole.
Meteorological parameters and correlations with INPs
Shown in Fig. 5 is the time series of meteorological parameters measured at
Alert during the field campaign. Precipitation was rare throughout the
campaign, and the average ambient temperature was approximately
-30∘C. The RH was above 70 % for most of the time. The wind
speed was below 10 km h-1 except for two storm events during the first
part of the campaign. During the field campaign, the wind came mainly from
the SW (more than half of the time) with some contribution from the SE and NW.
In the current study, INP concentrations at freezing temperatures of -15,
-20, and -25∘C were not correlated with any meteorological
parameters (Table S1 in the Supplement). This result is consistent with the results from
Fountain and Ohtake (1985), who also did not find any
correlations between meteorological variables (including air temperature,
precipitation, fog, and wind direction, etc.) and INP concentrations
measured in Utqiaġvik (formerly Barrow), Alaska, from August 1978 to April 1979. In contrast,
measurements by Radke et al. (1976) in Utqiaġvik, Alaska, during March found that
the INP concentrations were affected by local weather conditions.
The time series of mineral dust tracers (Al, Fe, Ti, and Mn).
Tracers of mineral dust: concentrations, correlations with INPs, and sources
The time series of concentrations of mineral dust tracers (Al, Fe, Ti, and
Mn) is plotted in Fig. 6. Figure 6 shows that concentrations of different
tracers of mineral dust are correlated with each other. Shown in Table 2 is
a correlation coefficient matrix between each of the tracers based on a
Pearson correlation analysis. Correlations that are both strong (R≥0.7)
and statistically significant (P<0.05) are highlighted in bold. The correlation coefficients show that the mineral dust tracers are
strongly correlated with each other (R≥0.85), which is expected since
these elements are almost exclusively from the mineral dust sources.
In Fig. 7a, we compared the mean mass concentration of aluminum we
measured at the site during the campaign with the concentrations reported in
Sirois and Barrie (1999) for
the same site and for the time period from 1980 to 1995. The mean mass
concentration of aluminum measured during the current study was lower than
the previous concentrations measured in March at Alert, indicating that the
concentration of mineral dust during the current campaign was lower than
many of the previous measurements at Alert during March.
Results of Pearson correlation analysis between the INP number
concentrations (at freezing temperatures of -15, -20, and -25∘C)
and tracers of aerosol components measured in this study. R is the correlation
coefficient, P is the probability value (two tailed), and the sample number
is 16. Correlations that are statistically significant at the 95 % confidence
interval (P<0.05) are highlighted in bold.
Comparison between the mean mass concentrations of each of the aerosol
tracers measured at the Alert site during the current study and the
concentrations reported from a 15-year (1980–1995) study at the same site
(Sirois and Barrie, 1999). The x axis represents the months. The black dots
represent the weekly concentrations measured by Sirois and Barrie (1999), and
the black line represents the estimated seasonal variations. The red symbols
represent the mean mass concentrations measured in this study with standard
deviation as y-error bars. The x-error bars represent the time period of
this study. The mass concentrations of Fe, Ti, and Mn were not available from
the 15-year study.
Pearson regression analysis was also done between INP concentrations at -15,
-20 and -25∘C, and tracers of mineral dust. The
correlation coefficients and P values are summarized in Table 3. The linear
regression plots between INP concentrations at -25∘C and
mineral dust tracers are shown in Fig. 8. When calculating the correlation
coefficients, a value of zero was used when tracer concentrations and INP
concentrations were below the detection limits. It is important to keep in
mind that the collection time was different for INPs (∼2 h)
and the aerosol tracers (∼24 h), and that the analysis
presented here is based on the assumption that the average concentrations of
the aerosol tracers during the INP sampling time were the same as the
average concentrations determined from the quartz filters. If this
assumption is not correct, correlation coefficients between INPs and aerosol
tracers will be smaller than expected. Shown in Fig. S1 in the Supplement are air mass back
trajectories initiated every 2 h during each 24 h quartz filter sampling
period. The back trajectories suggest that, for a large fraction of the
samples, the source of the air masses during INP sampling was similar to the
source of the air masses measured during quartz filter sampling.
Correlation plots between INP concentrations at -25∘C and
mineral dust tracers (Al, Fe, Ti, and Mn). Included in each panel are the
correlation coefficient (R) and the probability value (P).
As shown in Table 3, at -15∘C, the correlations between
INP concentrations and tracers of mineral dust were not statistically
significant (P>0.05). At -20∘C, the
correlations between INPs and Ti and Mn were not statistically significant.
Al and Fe were moderately correlated with INPs at -20∘C
(R=0.53 and 0.60, respectively), and the correlations were statistically
significant (P<0.05). At -25∘C, all four tracers
were strongly correlated with INPs (R ranged from 0.70 to 0.76), and the
correlations were statistically significant. This suggests that mineral dust
was a component of the sampled INPs at a freezing temperature of
-25∘C. This is consistent with previous field measurements
that have identified mineral dust as a major component of the INP population
at different locations (Boose
et al., 2016; Cziczo et al., 2013; DeMott et al., 2003; Klein et al., 2010;
Pratt et al., 2009; Prenni et al., 2009). A previous study of ice nucleation
of Arctic aerosol found that the elements of crustal or natural dust were
associated with high concentrations of INPs at -15 and
-25∘C (Borys, 1989). Chemical analysis of the
INPs during aircraft studies in the Arctic indicated that a significant
fraction of the INPs (approximately 37 %) contained mineral dust
(Rogers et al., 2001). Another study of snow crystals
during summer on the Greenland ice cap also suggested that the natural snow
crystals mainly formed on clay mineral particles by heterogeneous nucleation
(Kumai and Francis, 1962).
Mineral dust at Alert can come from both local sources and long-range
transport, but during the spring local sources are not likely important
since land is covered with snow during this time of the year. To investigate
the origins of mineral dust measured in this study, the FLEXPART model was
used to generate the footprint PES plots, which show the residence time of
aerosol particles in the layer from 0 to 100 m in altitude during the
20 days prior to sampling. Results are shown in Fig. 9. Figure 9a shows the
surface coverage type on the first day of sampling (12 March). The sampling
location at Alert was surrounded by ice and snow during the campaign.
Figure 9b shows the average footprint PES plot for all samples, and Fig. 9c
shows the average footprint PES plot for the four samples with the highest
mineral dust concentrations, which were collected on 21, 22, 27, and
28 March. Note that since average footprint PES plots are shown in Fig. 9b and c,
Fig. 9c is not a subset of Fig. 9b. Shown in Fig. 9d is a ratio plot
of the sum of footprint PES plots of the four samples with the highest
mineral dust concentrations to the sum of footprint PES plots of all
samples. These types of ratio plots are often used as a sensitive method to
identify the source regions of a component under investigation
(Hirdman et al., 2010). In these
types of plots, a value close to 1 indicates a more likely source region.
Figure 9d suggests that the north Pacific Ocean, Alaska, and the Gobi
Desert were possible source regions of the mineral dust sampled. Alaska was
covered in snow during the sampling period, so this was not likely the
source of the mineral dust, although mineral dust resuspended from blowing
snow cannot be ruled out. Mineral dust from shorelines also cannot be ruled
out. The north Pacific Ocean is not likely the source of mineral dust either
since the Pacific Ocean is not considered as a traditional source of mineral
dust. Based on the surface coverage types (Fig. 9a) and the ratio plot
(Fig. 9d), a possible source of the mineral dust was long-range transport
of dust from the Gobi Desert. This conclusion is consistent with previous
studies that have shown that a substantial fraction of the dust reaching
Alert in spring months comes from long-range transport of Asian dust (Drab
et al., 2002; Franzén et al., 1994; Pacyna and Ottar, 1989; Sirois and
Barrie, 1999; Welch et al., 1991).
Panel (a) shows the surface coverage types on the first day of
sampling (12 March 2016). White represents snow, light blue represents ice,
dark blue represents ocean, light brown represents land, and dark brown
represents desert (data from National Snow and Ice Data Center,
https://doi.org/10.7265/N52R3PMC, last access: 20 March 2018); panel (b) is the average
footprint PES plot from a 20-day FLEXPART analysis for all samples; panel (c) is
the average footprint PES plot for the four samples with the highest mineral
dust concentrations, which were collected on 21, 22, 27, and 28 March;
panel (d) shows the ratio of the sum of footprint PES plots of the four
samples with the highest mineral dust concentrations to the sum of footprint
PES plots of all samples. The red star indicates the sampling location.
Tracers of sea spray aerosol: concentrations and correlations with INPs
The time series of sea spray aerosol tracers (Na+ and Cl-) is
shown in Fig. 10, and the results of the Pearson correlation analysis
between these tracers are listed in Table 2. The correlation coefficients
show that sea spray tracers are strongly correlated with each other (R=0.95),
which is expected since these species are almost exclusively from sea spray.
The time series of sea spray tracers (Cl- and Na+).
A comparison between the mean mass concentrations of Na+ and
Cl- measured in the current study and the values measured by Sirois and Barrie (1999)
from 1980 to 1995 is shown in Fig. 7b and c. Figure 7b and c illustrate that the
concentrations of Na+ and Cl- measured in the current study were
consistent with many of previous measurements at Alert during March.
The correlation coefficients between INP concentrations at -15, -20, and
-25∘C, and tracers of sea spray aerosol are listed in Table 3.
The linear regression plots between INP concentrations at -25∘C
and the sea spray tracers are shown in Fig. 11. At -15 and -20∘C, the correlations between
INP concentrations and tracers of sea spray aerosol were not statistically
significant (P>0.05). At -25∘C, the sea spray
tracers were negatively correlated with INPs with moderate correlation
coefficients (R=-0.56) and statistical significance (P<0.05).
Previous field studies and modelling studies have suggested sea spray
aerosol as an important source of ambient INPs in marine environments when
other sources of INPs, such as mineral dust, are low (Burrows
et al., 2013; DeMott et al., 2016; Rosinski et al., 1986, 1988; Schnell,
1982; Vergara-Temprado et al., 2017; Wilson et al., 2015). Our results
suggest that mineral dust is a more important source of INPs at
-25∘C than sea spray aerosol for the time and location studied.
Correlation plots between INP concentrations at -25∘C and
sea spray tracers (Cl- and Na+). Included in each panel are
the correlation coefficient (R) and the probability value (P).
Due to the method of particle collection and the method of forming liquid
droplets in the freezing experiments, soluble material, such as salts
including NaCl, was mixed with mineral dust particles within the same
droplets during the freezing experiments. Salts decrease the freezing
temperature of droplets by decreasing the water activity in the solution.
However, the decrease in freezing temperature by this mechanism is not
expected to be important in our experiments since the concentration of salts
within a droplet is small. For example, the maximum concentration of NaCl in
the water droplets formed during the droplet freezing experiments was
estimated to be ∼0.03 M based on the mass concentrations of
Na+ and Cl- sampled. This concentration of NaCl in the droplets
would only cause a freezing point depression of ∼0.1∘C,
which is within the uncertainty of the measured
freezing temperatures and is too small to explain the negative correlation
between INP concentrations and tracers of sea spray aerosol shown in Fig. 11.
On the other hand, other studies have illustrated that trace amounts of NaCl
can lower the freezing temperature of mineral dust by surface-specific
interactions between NaCl and the mineral dust surface, and the decrease in
freezing temperature by this mechanism is more than expected based on the
traditional freezing point depression mechanism (Reischel and Vali, 1975; Whale et al., 2018). For
example, Reischel and Vali (1975) studied the effects
of 0.01, 0.1, and 1 M solutions of NaCl on the nucleating ability of kaolin
and found that the presence of NaCl led to lower freezing temperatures, by
as much as 4 ∘C, for kaolin. A recent study by
Whale et al. (2018) also found that a 0.015 M NaCl
solution caused a decrease in freezing temperature of approximately 2 to
4 ∘C for BCS376 microcline, Eifel sanidine, quartz, and
Arizona test dust, but had no effect on silica. To investigate the influence
of NaCl on the ice-nucleating ability of mineral dust at -25∘C
in the current study, INP concentrations at a freezing
temperature of -25∘C ([INPs]-25∘C) were divided by
the mass concentration of aluminum ([Al]), and this ratio was then plotted
as a function of Cl- and Na+ (Fig. 12). The variable
[INPs]-25∘C/[Al] is used as an estimation of the ice-nucleating
ability of mineral dust, and it was negatively correlated with Cl- and
Na+ with moderate correlation coefficients (R=-0.51 and -0.55,
respectively) and statistical significance (P<0.05), which suggests
that NaCl suppressed the ice-nucleating ability of mineral dust in the
current study. This result is consistent with the two previous laboratory
studies mentioned above and is the first field study that we are aware of
that suggests that NaCl can suppress the ice-nucleating ability of mineral
dust particles in the immersion freezing mode even in dilute solution droplets.
Correlation plots between the ratio of INP number concentration at
-25∘C to aluminum mass concentration and sea spray tracers
(Cl- and Na+). Included in each panel are the correlation
coefficient (R) and the probability value (P).
Another possible explanation for the negative correlation between INP
concentrations at -25∘C and sea spray tracers is that the
air masses containing sea spray aerosol have relatively few mineral dust
particles. In this case, the sea spray aerosol does not influence the
ice-nucleating ability of mineral dust but rather appears as a negative
correlation by coincidence. However, Table 2 shows that the correlations
between tracers of mineral dust and tracers of sea spray aerosol are not
statistically significant, suggesting that this possible explanation is not
the major reason for the negative correlation between INP concentrations at
-25∘C and sea spray tracers.
Tracers of anthropogenic aerosol: concentrations and correlations with INPs
The time series of anthropogenic aerosol tracers (Zn, Pb, NO3-,
NH4+, and nss-SO42-) is plotted in Fig. 13. The results
of the Pearson correlation analysis between these different tracers are
listed in Table 2. Not all the anthropogenic aerosol tracers are correlated
with each other. This is not surprising since these tracers come from
different sources. However, there is a correlation between Zn and Pb, and
between nss-SO42- and NH4+. Zn and Pb are strongly
correlated with each other (R=0.84, P<0.01), and
nss-SO42- and NH4+ are strongly correlated with each
other (R=0.93, P<0.01).
The time series of anthropogenic aerosol tracers (Zn, Pb,
NH4+, nss-SO42-, and NO3-).
Correlation plots between the ratio of INP number concentration at
-25∘C to aluminum mass concentration and anthropogenic pollution
tracers (NH4+ and nss-SO42-) and
NH4+/ nss-SO42- mole ratio. Included in each panel are the
correlation coefficient (R) and the probability value (P).
The comparison between the mean mass concentrations of Zn, Pb,
NO3-, SO42-, and NH4+ measured in the
current study and the values measured by Sirois and Barrie (1999) from 1980
to 1995 is shown in Fig. 7d–h. The concentrations of Zn, Pb,
SO42-, and NH4+ were lower than previous concentrations
measured in March at Alert, which might be due to the reduced emissions from
Eurasia after the dissolution of the former USSR in 1991 (Christensen, 1997). The concentration
of NO3- was higher than previous concentrations measured in March.
An increasing trend of annual concentrations of NO3- has been
observed by others in the Arctic (Hole et al., 2006; Neftel et al., 1985).
The correlation coefficients between INP concentrations at -15, -20, and
-25∘C, and tracers of anthropogenic aerosol are listed in
Table 3. None of the correlations were statistically significant, consistent
with a recent study that showed no effect of atmospheric pollution on INP
concentrations in Beijing at freezing temperatures down to -25∘C
(Chen et al., 2018). In contrast, Borys (1989) found that pollution-derived Arctic haze
aerosol had lower INP concentrations than unpolluted troposphere aerosol.
There have been a few studies that investigated the effect of sulfate
coating on the ice-nucleating properties of mineral dust particles. Most
laboratory studies have shown decreased freezing abilities for
sulfate-coated mineral dust particles compared to uncoated particles (Chernoff
and Bertram, 2010; Eastwood et al., 2008; Gallavardin et al., 2008; Sullivan
et al., 2010). However, other studies have shown an increase in the freezing
temperature of droplets containing mineral dust particles in the presence of
ammonium sulfate (Reischel and Vali, 1975; Whale et
al., 2018). To investigate the effect of ammonium, sulfate, and the
ammonium-to-sulfate ratio on the ice-nucleating ability of mineral dust at
-25∘C, the parameter [INPs]-25∘C/[Al] was plotted
as a function of NH4+, nss-SO42-, and the
NH4+/ nss-SO42- ratio as shown in Fig. 14. The
NH4+/ nss-SO42- ratio was between 0 and 1. The
correlations between the ice-nucleating ability of mineral dust at
-25∘C and NH4+, nss-SO42-, and the
NH4+/ nss-SO42- ratio were not statistically significant.
Conclusions
The INP concentrations measured at Alert during March 2016 fell into the
range of previously reported INP concentrations measured in the Arctic at
ground level or sea level. At -25∘C, the INP concentrations were
strongly correlated with tracers of mineral dust (Al, Fe, Ti, and Mn),
anti-correlated with tracers of sea spray (Cl-, Na+), and not
correlated with tracers of anthropogenic aerosol (Zn, Pb, NO3-,
NH4+, and nss-SO42-) or meteorological variables. This
suggests that mineral dust was a major contributor to INP populations at
-25∘C at this site during the sampling period. The
ice-nucleating ability of mineral dust, represented as the ratio of INP
number concentration to the mass concentration of aluminum, was also
anti-correlated with the tracers of sea spray at -25∘C,
which suggests that NaCl suppressed the ice-nucleating ability of mineral
dust particles in the immersion freezing mode. This is the first field study
that we are aware of that showed the suppression effect of NaCl on the
ice-nucleating ability of mineral dust. Due to the way particles were
collected and droplets were formed in our experiments, soluble material,
such as NaCl, was internally mixed with mineral dust within the same
droplets. However, in the atmosphere, the soluble material, such as NaCl,
may not be internally mixed with mineral dust. Studies of the mixing state
of soluble material with mineral dust at Alert during the same time of the
year are needed.
The particle dispersion model analysis suggests that a likely source of
mineral dust that caused freezing at -25∘C was long-range
transport of dust from the Gobi Desert. Additional measurements of the
composition of individual INP or ice crystal residuals in the Arctic are
needed to confirm the conclusions reached in the current study.
Data availability
Data used in this study are available on the Government of
Canada Open Government Portal under NETCARE (https://open.canada.ca/,
last access: 13 February 2019; Si et al., 2019) and can also be obtained from the corresponding
author upon request.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-3007-2019-supplement.
Author contributions
MS and AKB designed the experiments. EE collected the
samples with help from KR, DV and AP. MS, JY, and YX carried out the droplet
freezing experiments. SH made the PES plots. AC carried out the ion chromatography
analysis. DK and PH provided FLEXPART results. SS and WRL gave constructive
advice. MS wrote the paper, with contributions from all co-authors.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “NETCARE (Network on
Aerosols and Climate: Addressing Key Uncertainties in Remote Canadian Environments)
(ACP/AMT/BG inter-journal SI)”. It is not associated with a conference.
Acknowledgements
The authors would like to thank Desiree Toom for assistance with ion
chromatography analysis. We want to acknowledge that the FLEXPART was downloaded
from https://www.flexpart.eu/ (last access: 20 March 2018) and the ECMWF data were retrieved from the
MARS server. We also would like to thank all the staff at the Alert site for
their assistance during the field study.
Edited by: Barbara Ervens
Reviewed by: two anonymous referees
ReferencesAndreae, M. O. and Rosenfeld, D.: Aerosol–cloud–precipitation interactions.
Part 1. The nature and sources of cloud-active aerosols, Earth-Sci. Rev., 89,
13–41, 10.1016/j.earscirev.2008.03.001, 2008.Balasubramanian, R., Qian, W.-B., Decesari, S., Facchini, M. C., and Fuzzi, S.:
Comprehensive characterization of PM2.5 aerosols in Singapore, J. Geophys.
Res., 108, 4523, 10.1029/2002JD002517, 2003.Barrie, L. A.: Arctic air pollution: An overview of current knowledge, Atmos.
Environ., 20, 643–663, 10.1016/0004-6981(86)90180-0, 1986.Barrie, L. A. and Barrie, M. J.: Chemical components of lower tropospheric
aerosols in the high arctic: Six years of observations, J. Atmos. Chem., 11,
211–226, 10.1007/BF00118349, 1990.Barrie, L. A., Hoff, R. M., and Daggupaty, S. M.: The influence of mid-latitudinal
pollution sources on haze in the Canadian arctic, Atmos. Environ., 15,
1407–1419, 10.1016/0004-6981(81)90347-4, 1981.Barrie, L. A., den Hartog, G., Bottenheim, J. W., and Landsberger, S.:
Anthropogenic aerosols and gases in the lower troposphere at Alert Canada in
April 1986, J. Atmos. Chem., 9, 101–127, 10.1007/BF00052827, 1989.Barrie, L. A., Gregor, D., Hargrave, B., Lake, R., Muir, D., Shearer, R.,
Tracey, B., and Bidleman, T.: Arctic contaminants: sources, occurrence and
pathways, Sci. Total Environ., 122, 1–74, 10.1016/0048-9697(92)90245-N, 1992.Bateman, A. P., Belassein, H., and Martin, S. T.: Impactor Apparatus for the
Study of Particle Rebound: Relative Humidity and Capillary Forces, Aerosol
Sci. Tech., 48, 42–52, 10.1080/02786826.2013.853866, 2014.Bigg, E. K.: Ice forming nuclei in the high Arctic, Tellus B, 48, 223–233,
10.1034/j.1600-0889.1996.t01-1-00007.x, 1996.Bigg, E. K. and Leck, C.: Cloud-active particles over the central Arctic Ocean,
J. Geophys. Res.-Atmos., 106, 32155–32166, 10.1029/1999JD901152, 2001.Boose, Y., Kanji, Z. A., Kohn, M., Sierau, B., Zipori, A., Crawford, I., Lloyd,
G., Bukowiecki, N., Herrmann, E., Kupiszewski, P., Steinbacher, M., and Lohmann,
U.: Ice Nucleating Particle Measurements at 241 K during Winter Months at
3580 m MSL in the Swiss Alps, J. Atmos. Sci., 73, 2203–2228, 10.1175/JAS-D-15-0236.1, 2016.Borys, R. D.: Studies of ice nucleation by Arctic aerosol on AGASP-II, J. Atmos.
Chem., 9, 169–185, 10.1007/BF00052831, 1989.Burrows, S. M., Hoose, C., Pöschl, U., and Lawrence, M. G.: Ice nuclei in
marine air: biogenic particles or dust?, Atmos. Chem. Phys., 13, 245–267,
10.5194/acp-13-245-2013, 2013.Chen, J., Wu, Z., Augustin-Bauditz, S., Grawe, S., Hartmann, M., Pei, X., Liu,
Z., Ji, D., and Wex, H.: Ice-nucleating particle concentrations unaffected by
urban air pollution in Beijing, China, Atmos. Chem. Phys., 18, 3523–3539,
10.5194/acp-18-3523-2018, 2018.Chen, S., Tsai, C., Chen, H., Huang, C., and Roam, G.: The Influence of Relative
Humidity on Nanoparticle Concentration and Particle Mass Distribution Measurements
by the MOUDI, Aerosol Sci. Tech., 45, 596–603, 10.1080/02786826.2010.551557, 2011.Chernoff, D. I. and Bertram, A. K.: Effects of sulfate coatings on the ice
nucleation properties of a biological ice nucleus and several types of minerals,
J. Geophys. Res., 115, D20205, 10.1029/2010JD014254, 2010.Christensen, J. H.: The Danish eulerian hemispheric model – a three-dimensional
air pollution model used for the arctic, Atmos. Environ., 31, 4169–4191,
10.1016/S1352-2310(97)00264-1, 1997.Coluzza, I., Creamean, J., Rossi, M., Wex, H., Alpert, P., Bianco, V., Boose,
Y., Dellago, C., Felgitsch, L., Fröhlich-Nowoisky, J., Herrmann, H.,
Jungblut, S., Kanji, Z., Menzl, G., Moffett, B., Moritz, C., Mutzel, A.,
Pöschl, U., Schauperl, M., Scheel, J., Stopelli, E., Stratmann, F., Grothe,
H., and Schmale, D.: Perspectives on the Future of Ice Nucleation Research:
Research Needs and Unanswered Questions Identified from Two International
Workshops, Atmosphere (Basel), 8, 138, 10.3390/atmos8080138, 2017.Conen, F., Stopelli, E., and Zimmermann, L.: Clues that decaying leaves enrich
Arctic air with ice nucleating particles, Atmos. Environ., 129, 91–94,
10.1016/j.atmosenv.2016.01.027, 2016.Creamean, J. M., Kirpes, R. M., Pratt, K. A., Spada, N. J., Maahn, M., de Boer,
G., Schnell, R. C., and China, S.: Marine and terrestrial influences on ice
nucleating particles during continuous springtime measurements in an Arctic
oilfield location, Atmos. Chem. Phys., 18, 18023–18042, 10.5194/acp-18-18023-2018, 2018.Curry, J. A.: Interactions among aerosols, clouds, and climate of the Arctic
Ocean, Sci. Total Environ., 160–161, 777–791, 10.1016/0048-9697(95)04411-S, 1995.Cziczo, D. J., Froyd, K. D., Hoose, C., Jensen, E. J., Diao, M., Zondlo, M. A.,
Smith, J. B., Twohy, C. H., and Murphy, D. M.: Clarifying the Dominant Sources
and Mechanisms of Cirrus Cloud Formation, Science, 1320, 1–8, 10.1126/science.1234145, 2013.Cziczo, D. J., Ladino, L., Boose, Y., Kanji, Z. A., Kupiszewski, P., Lance, S.,
Mertes, S., and Wex, H.: Measurements of Ice Nucleating Particles and Ice
Residuals, Meteorol. Monogr., 58, 8.1–8.13, 10.1175/AMSMONOGRAPHS-D-16-0008.1, 2017.DeMott, P. J., Sassen, K., Poellot, M. R., Baumgardner, D., Rogers, D. C.,
Brooks, S. D., Prenni, A. J., and Kreidenweis, S. M.: African dust aerosols
as atmospheric ice nuclei, Geophys. Res. Lett., 30, 26–29, 10.1029/2003GL017410, 2003.DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D.,
Twohy, C. H., Richardson, M. S., Eidhammer, T., and Rogers, D. C.: Predicting
global atmospheric ice nuclei distributions and their impacts on climate, P.
Natl. Acad. Sci. USA, 107, 11217–11222, 10.1073/pnas.0910818107, 2010.DeMott, P. J., Hill, T. C. J., McCluskey, C. S., Prather, K. A., Collins, D.
B., Sullivan, R. C., Ruppel, M. J., Mason, R. H., Irish, V. E., Lee, T., Hwang,
C. Y., Rhee, T. S., Snider, J. R., McMeeking, G. R., Dhaniyala, S., Lewis, E.
R., Wentzell, J. J. B., Abbatt, J., Lee, C., Sultana, C. M., Ault, A. P., Axson,
J. L., Diaz Martinez, M., Venero, I., Santos-Figueroa, G., Stokes, M. D., Deane,
G. B., Mayol-Bracero, O. L., Grassian, V. H., Bertram, T. H., Bertram, A. K.,
Moffett, B. F., and Franc, G. D.: Sea spray aerosol as a unique source of ice
nucleating particles, P. Natl. Acad. Sci. USA, 113, 5797–5803, 10.1073/pnas.1514034112, 2016.DeMott, P. J., Hill, T. C. J., Petters, M. D., Bertram, A. K., Tobo, Y., Mason,
R. H., Suski, K. J., McCluskey, C. S., Levin, E. J. T., Schill, G. P., Boose,
Y., Rauker, A. M., Miller, A. J., Zaragoza, J., Rocci, K., Rothfuss, N. E.,
Taylor, H. P., Hader, J. D., Chou, C., Huffman, J. A., Pöschl, U., Prenni,
A. J., and Kreidenweis, S. M.: Comparative measurements of ambient atmospheric
concentrations of ice nucleating particles using multiple immersion freezing
methods and a continuous flow diffusion chamber, Atmos. Chem. Phys., 17,
11227–11245, 10.5194/acp-17-11227-2017, 2017.Drab, E., Gaudichet, A., Jaffrezo, J. L., and Colin, J. L.: Mineral particles
content in recent snow at Summit (Greenland), Atmos. Environ., 36, 5365–5376,
10.1016/S1352-2310(02)00470-3, 2002.Du, P., Girard, E., Bertram, A. K., and Shupe, M. D.: Modeling of the cloud and
radiation processes observed during SHEBA, Atmos. Res., 101, 911–927,
10.1016/j.atmosres.2011.05.018, 2011.Eastwood, M. L., Cremel, S., Gehrke, C., Girard, E., and Bertram, A. K.: Ice
nucleation on mineral dust particles: Onset conditions, nucleation rates and
contact angles, J. Geophys. Res., 113, D22203, 10.1029/2008JD010639, 2008.Fang, C. P., McMurry, P. H., Marple, V. A., and Rubow, K. L.: Effect of
Flow-induced Relative Humidity Changes on Size Cuts for Sulfuric Acid Droplets
in the Microorifice Uniform Deposit Impactor (MOUDI), Aerosol Sci. Tech., 14,
266–277, 10.1080/02786829108959489, 1991.Flyger, H. and Heidam, N. Z.: Ground level measurements of the summer tropospheric
aerosol in Northern Greenland, J. Aerosol Sci., 9, 157–168, 10.1016/0021-8502(78)90075-7, 1978.Flyger, H., Hansen, K., Megaw, W. J., and Cox, L. C.: The Background Level of
the Summer Tropospheric Aerosol Over Greenland and the North Atlantic Ocean,
J. Appl. Meteorol., 12, 161–174, 10.1175/1520-0450(1973)012<0161:TBLOTS>2.0.CO;2, 1973.Flyger, H., Heidam, N., Hansen, K., Megaw, W., Walther, E., and Hogan, A.: The
background level of the summer tropospheric aerosol, sulphur dioxide and ozone
over Greenland and the North Atlantic Ocean, J. Aerosol Sci., 7, 103–140,
10.1016/0021-8502(76)90069-0, 1976.
Follett, R. F. and Hatfield, J. L.: Nitrogen in the Environment: Sources,
Problems, and Management, Elsevier, Amsterdam, the Netherlands, 2001.Formenti, P., Elbert, W., Maenhaut, W., Haywood, J., and Andreae, M. O.: Chemical
composition of mineral dust aerosol during the Saharan Dust Experiment (SHADE)
airborne campaign in the Cape Verde region, September 2000, J. Geophys. Res.,
108, 8576, 10.1029/2002JD002648, 2003.Fountain, A. G. and Ohtake, T.: Concentrations and Source Areas of Ice Nuclei
in the Alaskan Atmosphere, J. Clim. Appl. Meteorol., 2, 377–382,
10.1175/1520-0450(1985)024<0377:CASAOI>2.0.CO;2, 1985.Franzén, L. G., Hjelmroos, M., Kållberg, P., Brorström-Lunden, E.,
Juntto, S., and Savolainen, A. L.: The “yellow snowepisode” of northern
Fennoscandia, march 1991-A case study of long-distance transport of soil, pollen
and stable organic compounds, Atmos. Environ., 28, 3587–3604, 10.1016/1352-2310(94)00191-M, 1994.Gallavardin, S. J., Froyd, K. D., Lohmann, U., Moehler, O., Murphy, D. M., and
Cziczo, D. J.: Single Particle Laser Mass Spectrometry Applied to Differential
Ice Nucleation Experiments at the AIDA Chamber, Aerosol Sci. Tech., 42, 773–791,
10.1080/02786820802339538, 2008.Hirdman, D., Sodemann, H., Eckhardt, S., Burkhart, J. F., Jefferson, A.,
Mefford, T., Quinn, P. K., Sharma, S., Ström, J., and Stohl, A.: Source
identification of short-lived air pollutants in the Arctic using statistical
analysis of measurement data and particle dispersion model output, Atmos. Chem.
Phys., 10, 669–693, 10.5194/acp-10-669-2010, 2010.
Hole, L. R., Christensen, J., Ginzburg, V. A., Makarov, V., Pershina, N. A.,
Polischuk, A. I., Ruoho-Airola, T., Svistov, P. P., and Vasilenko, V. N.: AMAP
Assessment 2006: Acidifying Pollutants, Arctic Haze, and Acidification in the
Arctic, Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway, 11–30, 2006.
Holland, H. D.: The Chemistry of the Atmosphere and Oceans, John Wiley, Hoboken, NJ, 1978.Hoose, C. and Möhler, O.: Heterogeneous ice nucleation on atmospheric
aerosols: a review of results from laboratory experiments, Atmos. Chem. Phys.,
12, 9817–9854, 10.5194/acp-12-9817-2012, 2012.Iannone, R., Chernoff, D. I., Pringle, A., Martin, S. T., and Bertram, A. K.:
The ice nucleation ability of one of the most abundant types of fungal spores
found in the atmosphere, Atmos. Chem. Phys., 11, 1191–1201, 10.5194/acp-11-1191-2011, 2011.Irish, V. E., Hanna, S. J., Willis, M. D., China, S., Thomas, J. L., Wentzell,
J. J. B., Cirisan, A., Si, M., Leaitch, W. R., Murphy, J. G., Abbatt, J. P. D.,
Laskin, A., Girard, E., and Bertram, A. K.: Ice nucleating particles in the
marine boundary layer in the Canadian Arctic during summer 2014, Atmos. Chem.
Phys., 19, 1027–1039, 10.5194/acp-19-1027-2019, 2019.Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo, D.
J., and Krämer, M.: Overview of Ice Nucleating Particles, Meteorol. Monogr.,
58, 1.1–1.33, 10.1175/AMSMONOGRAPHS-D-16-0006.1, 2017.Klein, H., Nickovic, S., Haunold, W., Bundke, U., Nillius, B., Ebert, M.,
Weinbruch, S., Schuetz, L., Levin, Z., Barrie, L. A., and Bingemer, H.: Saharan
dust and ice nuclei over Central Europe, Atmos. Chem. Phys., 10, 10211–10221,
10.5194/acp-10-10211-2010, 2010.Koop, T., Luo, B., Biermann, U. M., Crutzen, P. J., and Peter, T.: Freezing
of HNO3/H2SO4/H2O Solutions at Stratospheric
Temperatures: Nucleation Statistics and Experiments, J. Phys. Chem. A, 101,
1117–1133, 10.1021/jp9626531, 1997.Kumai, M. and Francis, K. E.: Nuclei in Snow and Ice Crystals on the Greenland
Ice Cap under Natural and Artificially Stimulated Conditions, J. Atmos. Sci.,
19, 474–481, 10.1175/1520-0469(1962)019<0474:NISAIC>2.0.CO;2, 1962.Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review, Atmos.
Chem. Phys., 5, 715–737, 10.5194/acp-5-715-2005, 2005.Macdonald, K. M., Sharma, S., Toom, D., Chivulescu, A., Hanna, S., Bertram, A.
K., Platt, A., Elsasser, M., Huang, L., Tarasick, D., Chellman, N., McConnell,
J. R., Bozem, H., Kunkel, D., Lei, Y. D., Evans, G. J., and Abbatt, J. P. D.:
Observations of atmospheric chemical deposition to high Arctic snow, Atmos.
Chem. Phys., 17, 5775–5788, 10.5194/acp-17-5775-2017, 2017.Macdonald, R. W., Barrie, L. A., Bidleman, T. F., Diamond, M. L., Gregor, D. J.,
Semkin, R. G., Strachan, W. M. J., Li, Y. F., Wania, F., Alaee, M., Alexeeva,
L. B., Backus, S. M., Bailey, R., Bewers, J. M., Gobeil, C., Halsall, C. J.,
Harner, T., Hoff, J. T., Jantunen, L. M. M., Lockhart, W. L., Mackay, D., Muir,
D. C. G., Pudykiewicz, J., Reimer, K. J., Smith, J. N., Stern, G., Schroeder,
W. H., Wagemann, R., and Yunker, M. B.: Contaminants in the Canadian Arctic:
5 years of progress in understanding sources, occurrence and pathways, Sci.
Total Environ., 254, 93–234, 10.1016/S0048-9697(00)00434-4, 2000.Malm, W. C., Sisler, J. F., Huffman, D., Eldred, R. A., and Cahill, T. A.:
Spatial and seasonal trends in particle concentration and optical extinction
in the United States, J. Geophys. Res., 99, 1347, 10.1029/93JD02916, 1994.Mason, R. H., Chou, C., McCluskey, C. S., Levin, E. J. T., Schiller, C. L.,
Hill, T. C. J., Huffman, J. A., DeMott, P. J., and Bertram, A. K.: The
micro-orifice uniform deposit impactor–droplet freezing technique (MOUDI-DFT)
for measuring concentrations of ice nucleating particles as a function of size:
improvements and initial validation, Atmos. Meas. Tech., 8, 2449–2462,
10.5194/amt-8-2449-2015, 2015.Mason, R. H., Si, M., Chou, C., Irish, V. E., Dickie, R., Elizondo, P., Wong,
R., Brintnell, M., Elsasser, M., Lassar, W. M., Pierce, K. M., Leaitch, W. R.,
MacDonald, A. M., Platt, A., Toom-Sauntry, D., Sarda-Estève, R., Schiller,
C. L., Suski, K. J., Hill, T. C. J., Abbatt, J. P. D., Huffman, J. A., DeMott,
P. J., and Bertram, A. K.: Size-resolved measurements of ice-nucleating particles
at six locations in North America and one in Europe, Atmos. Chem. Phys., 16,
1637–1651, 10.5194/acp-16-1637-2016, 2016.McFarquhar, G. M., Ghan, S., Verlinde, J., Korolev, A., Strapp, J. W., Schmid,
B., Tomlinson, J. M., Wolde, M., Brooks, S. D., Cziczo, D., Dubey, M. K., Fan,
J., Flynn, C., Gultepe, I., Hubbe, J., Gilles, M. K., Laskin, A., Lawson, P.,
Leaitch, W. R., Liu, P., Liu, X., Lubin, D., Mazzoleni, C., Macdonald, A.-M.,
Moffet, R. C., Morrison, H., Ovchinnikov, M., Shupe, M. D., Turner, D. D., Xie,
S., Zelenyuk, A., Bae, K., Freer, M., and Glen, A.: Indirect and Semi-direct
Aerosol Campaign, B. Am. Meteorol. Soc., 92, 183–201, 10.1175/2010BAMS2935.1, 2011.Millero, F. J.: The Physical Chemistry of Seawater, Annu. Rev. Earth Planet.
Sci., 2, 101–150, 10.1146/annurev.ea.02.050174.000533, 1974.Murray, B. J., O'Sullivan, D., Atkinson, J. D., and Webb, M. E.: Ice nucleation
by particles immersed in supercooled cloud droplets, Chem. Soc. Rev., 41, 6519,
10.1039/c2cs35200a, 2012.Neftel, A., Beer, J., Oeschger, H., Zürcher, F., and Finkel, R. C.: Sulphate
and nitrate concentrations in snow from South Greenland 1895–1978, Nature,
314, 611–613, 10.1038/314611a0, 1985.Norman, A. L., Barrie, L. A., Toom-Sauntry, D., Sirois, A., Krouse, H. R., Li,
S. M., and Sharma, S.: Sources of aerosol sulphate at Alert: Apportionment using
stable isotopes, J. Geophys. Res.-Atmos., 104, 11619–11631, 10.1029/1999JD900078, 1999.Nriagu, J. O. and Pacyna, J. M.: Quantitative assessment of worldwide
contamination of air, water and soils by trace metals, Nature, 333, 134–139,
10.1038/333134a0, 1988.Pacyna, J. M.: The origin of Arctic air pollutants: lessons learned and future
research, Sci. Total Environ., 160–161, 39–53, 10.1016/0048-9697(95)04343-Y, 1995.Pacyna, J. M. and Ottar, B.: Origin of natural constituents in the Arctic aerosol,
Atmos. Environ., 23, 809–815, 10.1016/0004-6981(89)90485-X, 1989.Pratt, K. A., DeMott, P. J., French, J. R., Wang, Z., Westphal, D. L.,
Heymsfield, A. J., Twohy, C. H., Prenni, A. J., and Prather, K. A.: In situ
detection of biological particles in cloud ice-crystals, Nat. Geosci., 2,
398–401, 10.1038/ngeo521, 2009.Prenni, A. J., Harrington, J. Y., Tjernström, M., DeMott, P. J., Avramov,
A., Long, C. N., Kreidenweis, S. M., Olsson, P. Q., and Verlinde, J.: Can
Ice-Nucleating Aerosols Affect Arctic Seasonal Climate?, B. Am. Meteorol. Soc.,
88, 541–550, 10.1175/BAMS-88-4-541, 2007.Prenni, A. J., DeMott, P. J., Rogers, D. C., Kreidenweis, S. M., Mcfarquhar, G.
M., Zhang, G., and Poellot, M. R.: Ice nuclei characteristics from M-PACE and
their relation to ice formation in clouds, Tellus B, 61, 436–448,
10.1111/j.1600-0889.2009.00415.x, 2009.Quinn, P. K., Miller, T. L., Bates, T. S., Ogren, J. A., Andrews, E., and
Shaw, G. E.: A 3-year record of simultaneously measured aerosol chemical and
optical properties at Barrow, Alaska, J. Geophys. Res.-Atmos., 107, AAC 8-1–AAC 8-15,
10.1029/2001JD001248, 2002.Quinn, P. K., Coffman, D. J., Bates, T. S., Welton, E. J., Covert, D. S.,
Miller, T. L., Johnson, J. E., Maria, S., Russell, L., Arimoto, R., Carrico, C.
M., Rood, M. J., and Anderson, J.: Aerosol optical properties measured on board
the Ronald H. Brown during ACE-Asia as a function of aerosol chemical composition
and source region, J. Geophys. Res., 109, D19S01, 10.1029/2003JD004010, 2004.Quinn, P. K., Shaw, G., Andrews, E., Dutton, E. G., Ruoho-Airola, T., and Gong,
S. L.: Arctic haze: Current trends and knowledge gaps, Tellus B, 59, 99–114,
10.1111/j.1600-0889.2006.00238.x, 2007.Radke, L. F., Hobbs, P. V., and Pinnons, J. E.: Observations of Cloud
Condensation Nuclei, Sodium-Containing Particles, Ice Nuclei and the
Light-Scattering Coefficient Near Barrow, Alaska, J. Appl. Meteorol., 15,
982–995, 10.1175/1520-0450(1976)015<0982:OOCCNS>2.0.CO;2, 1976.Reischel, M. T. and Vali, G.: Freezing nucleation in aqueous electrolytes,
Tellus, 27, 414–427, 10.3402/tellusa.v27i4.9989, 1975.Rogers, D. C., DeMott, P. J., and Kreidenweis, S. M.: Airborne measurements of
tropospheric ice-nucleating aerosol particles in the Arctic spring, J. Geophys.
Res.-Atmos., 106, 15053–15063, 10.1029/2000JD900790, 2001.Rosinski, J., Haagenson, P. L., Nagamoto, C. T., and Parungo, F.: Ice-forming
nuclei of maritime origin, J. Aerosol Sci., 17, 23–46, 10.1016/0021-8502(86)90004-2, 1986.Rosinski, J., Haagenson, P. L., Nagamoto, C. T., Quintana, B., Parungo, F.,
and Hoyt, S. D.: Ice-forming nuclei in air masses over the Gulf of Mexico, J.
Aerosol Sci., 19, 539–551, 10.1016/0021-8502(88)90206-6, 1988.Schnell, R. C.: Airborne ice nucleus measurements around the Hawaiian Islands,
J. Geophys. Res., 87, 8886–8890, 10.1029/JC087iC11p08886, 1982.Schwikowski, M., Döscher, A., Gäggeler, H. W., and Schotterer, U.:
Anthropogenic versus natural sources of atmospheric sulphate from an Alpine
ice core, Tellus B, 51, 938–951, 10.3402/tellusb.v51i5.16506, 1999.Seibert, P. and Frank, A.: Source-receptor matrix calculation with a Lagrangian
particle dispersion model in backward mode, Atmos. Chem. Phys., 4, 51–63,
10.5194/acp-4-51-2004, 2004.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From
Air Pollution to Climate Change, John Wiley & Sons, Inc., Hoboken, NJ, 2006.Shaw, G. E.: The Arctic Haze Phenomenon, B. Am. Meteorol. Soc., 76, 2403–2413,
10.1175/1520-0477(1995)076<2403:TAHP>2.0.CO;2, 1995.Si, M., Evoy, E., Yun, J., Xi, Y., Hanna, S., Chivulescu, A., Rawlings, K.,
Veber, D., Platt, A., Kunkel, D., Hoor, P., Sharma, S., Leaitch, W. R., and
Bertram, A. K.: Concentrations, composition, and sources of ice-nucleating
particles in the Canadian High Arctic during spring 2016 [Data set], Government
of Canada Open Government Portal, available at: https://open.canada.ca,
last access: 13 February 2019.Sirois, A. and Barrie, L. A.: Arctic lower tropospheric aerosol trends and
composition at Alert, Canada: 1980–1995, J. Geophys. Res.-Atmos., 104,
11599–11618, 10.1029/1999JD900077, 1999.Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical note:
The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem.
Phys., 5, 2461–2474, 10.5194/acp-5-2461-2005, 2005.Sullivan, R. C., Petters, M. D., DeMott, P. J., Kreidenweis, S. M., Wex, H.,
Niedermeier, D., Hartmann, S., Clauss, T., Stratmann, F., Reitz, P., Schneider,
J., and Sierau, B.: Irreversible loss of ice nucleation active sites in mineral
dust particles caused by sulphuric acid condensation, Atmos. Chem. Phys., 10,
11471–11487, 10.5194/acp-10-11471-2010, 2010.Toom-Sauntry, D. and Barrie, L. A.: Chemical composition of snowfall in the
high Arctic: 1990–1994, Atmos. Environ., 36, 2683–2693, 10.1016/S1352-2310(02)00115-2, 2002.Usher, C. R., Michel, A. E., and Grassian, V. H.: Reactions on Mineral Dust,
Chem. Rev., 103, 4883–4940, 10.1021/cr020657y, 2003.Vali, G.: Quantitative Evaluation of Experimental Results an the Heterogeneous
Freezing Nucleation of Supercooled Liquids, J. Atmos. Sci., 28, 402–409,
10.1175/1520-0469(1971)028<0402:QEOERA>2.0.CO;2, 1971.Vali, G., DeMott, P. J., Möhler, O., and Whale, T. F.: Technical Note: A
proposal for ice nucleation terminology, Atmos. Chem. Phys., 15, 10263–10270,
10.5194/acp-15-10263-2015, 2015.Vergara-Temprado, J., Murray, B. J., Wilson, T. W., O'Sullivan, D., Browse, J.,
Pringle, K. J., Ardon-Dryer, K., Bertram, A. K., Burrows, S. M., Ceburnis, D.,
DeMott, P. J., Mason, R. H., O'Dowd, C. D., Rinaldi, M., and Carslaw, K. S.:
Contribution of feldspar and marine organic aerosols to global ice nucleating
particle concentrations, Atmos. Chem. Phys., 17, 3637–3658, 10.5194/acp-17-3637-2017, 2017.Ward, P. L.: Sulfur dioxide initiates global climate change in four ways, Thin
Solid Films, 517, 3188–3203, 10.1016/j.tsf.2009.01.005, 2009.Watts, S. F., Yaaqub, R., and Davies, T.: The use of Whatman 41 filter papers
for high volume aerosol sampling, Atmos. Environ., 21, 2731–2732,
10.1016/0004-6981(87)90207-1, 1987.
Wedepohl, K. H.: The composition of the continental crust, Geochim. Cosmochim.
Ac., 59, 1217–1232, 10.1016/0016-7037(95)00038-2, 1995.Welch, H. E., Muir, D. C. G., Billeck, B. N., Lockhart, W. L., Brunskill, G. J.,
Kling, H. J., Olson, M. P., and Lemoine, R. M.: Brown snow: a long-range
transport event in the Canadian Arctic, Environ. Sci. Technol., 25, 280–286,
10.1021/es00014a010, 1991.Whale, T. F., Holden, M. A., Wilson, T. W., O'Sullivan, D., and Murray, B. J.:
The enhancement and suppression of immersion mode heterogeneous ice-nucleation
by solutes, Chem. Sci., 9, 4142–4151, 10.1039/C7SC05421A, 2018.Wheeler, M. J., Mason, R. H., Steunenberg, K., Wagstaff, M., Chou, C., and
Bertram, A. K.: Immersion Freezing of Supermicron Mineral Dust Particles:
Freezing Results, Testing Different Schemes for Describing Ice Nucleation, and
Ice Nucleation Active Site Densities, J. Phys. Chem. A, 119, 4358–4372,
10.1021/jp507875q, 2015.Wilson, T. W., Ladino, L. A., Alpert, P. A., Breckels, M. N., Brooks, I. M.,
Browse, J., Burrows, S. M., Carslaw, K. S., Huffman, J. A., Judd, C., Kilthau,
W. P., Mason, R. H., McFiggans, G., Miller, L. A., Nájera, J. J., Polishchuk,
E., Rae, S., Schiller, C. L., Si, M., Temprado, J. V., Whale, T. F., Wong, J.
P. S., Wurl, O., Yakobi-Hancock, J. D., Abbatt, J. P. D., Aller, J. Y., Bertram,
A. K., Knopf, D. A., and Murray, B. J.: A marine biogenic source of atmospheric
ice-nucleating particles, Nature, 525, 234–238, 10.1038/nature14986, 2015.Xie, S., Liu, X., Zhao, C., and Zhang, Y.: Sensitivity of CAM5-Simulated Arctic
Clouds and Radiation to Ice Nucleation Parameterization, J. Climate, 26,
5981–5999, 10.1175/JCLI-D-12-00517.1, 2013.