Introduction
Aerosol particles are ubiquitous in the atmosphere, yet only a small
fraction of these particles, referred to as ice-nucleating particles (INPs),
are able to initiate the formation of ice at temperatures warmer than
homogeneous freezing temperatures. INPs may impact the frequencies,
lifetime, and optical properties of ice and mixed-phase clouds (Andreae
and Rosenfeld, 2008; Cziczo and Abbatt, 2001; Lohmann and Feichter, 2005).
It is now well established that mineral dust particles represent a large
fraction of INPs in the atmosphere (Hoose et
al., 2010). For example, laboratory studies have shown that mineral dust
particles are efficient at nucleating ice (Atkinson
et al., 2013; Boose et al., 2016a; Broadley et al., 2012; Eastwood et al.,
2008; Field et al., 2006; Hartmann et al., 2016; Hiranuma et al., 2015;
Kanji and Abbatt, 2010; Knopf and Koop, 2006; Murray et al., 2011; Wex et
al., 2014). Field measurements have shown that mineral dust is a main
component of INPs in different locations (Boose
et al., 2016b; DeMott et al., 2003; Klein et al., 2010; Prenni et al., 2009;
Worringen et al., 2015). Modelling studies have also suggested that mineral
dust particles are a major contributor to INP concentrations in many
locations around the globe (Hoose et al.,
2010; Vergara-Temprado et al., 2017).
Map showing the three sampling locations: Amphitrite Point (red
dot), Labrador Sea (green dot), and Lancaster Sound (yellow dot). Inserts
show the images of the sampling platform used at each location.
Recent studies also suggest that sea spray aerosols may be an important
source of INPs in some remote marine regions (Wilson et al., 2015). For
example, field and laboratory measurements have shown that seawater contains
particles that can nucleate ice (Alpert
et al., 2011a, b; Irish et al., 2017; Knopf et al., 2011; Schnell, 1977;
Schnell and Vali, 1976, 1975; Wilson et al., 2015), and these INPs in
seawater are thought to be emitted into the atmosphere by wave-breaking and
bubble-bursting mechanisms (DeMott
et al., 2016; Wang et al., 2015). Field measurements suggest that ambient
INPs collected in marine environments can come from marine origins (DeMott
et al., 2016; Rosinski et al., 1986, 1988; Schnell, 1982), and modelling
studies have shown that sea spray aerosols are a major source of INPs in some
remote marine environments (Burrows
et al., 2013; Vergara-Temprado et al., 2017; Wilson et al., 2015). Modelling
studies have also suggested that INPs from the ocean can significantly
modify the properties of mixed-phase clouds in the atmosphere, with
implications for radiative forcing predictions (Yun
and Penner, 2013). Despite the growing evidence indicating that sea spray
aerosols are an important type of INPs, our understanding of when and where
sea spray aerosols are an important component of the total INP population is
far from complete. Additional field measurements of INPs in marine
environments would help improve our understanding of this topic.
Here we report INP measurements in the immersion mode from three coastal
marine sites. Immersion freezing refers to freezing initiated by INPs
immersed in liquid droplets (Vali et al., 2015),
and this freezing mode is considered to be the most relevant for mixed-phase
clouds (Ansmann
et al., 2009; de Boer et al., 2011; Westbrook and Illingworth, 2011). The
three coastal marine sites investigated were Amphitrite Point, Labrador Sea,
and Lancaster Sound (Fig. 1). For two of these sites (Amphitrite Point and
Labrador Sea), the size distributions of INPs in the immersion mode have
been reported previously (Mason
et al., 2015a, 2016). In the following, we build on these previous
measurements by reporting the following for all three coastal marine sites:
(1) the size distribution of INPs, (2) the fraction of aerosol particles
acting as an INP as a function of size, and (3) the surface active site
density, ns, as a function of size. In addition, we compare the INP
measurements to predictions from a recently developed global model of INP
concentrations (Vergara-Temprado et
al., 2017). We use this combined information to help determine if sea spray
aerosols or mineral dust are the major sources of INPs at these three sites.
This type of information is needed to help constrain future modelling studies
of INPs and mixed-phase clouds.
Methods
Measurements of INP concentrations as a function of size
Concentrations of INPs as a function of size were measured with the
micro-orifice uniform deposit impactor-droplet freezing technique
(MOUDI-DFT; Mason et al., 2015b). This technique involves collecting size-fractionated
aerosol particles on hydrophobic glass slides with a micro-orifice uniform
deposit impactor (MOUDI; Marple et al., 1991) and determining the freezing properties of collected aerosol
particles with the droplet freezing technique (DFT). Details are given
below.
Aerosol particle sampling with a MOUDI
A MOUDI (model 110R or 120R; MSP Corp., Shoreview, MN, USA) was used to
collect size-fractionated aerosol particles. Aerosol particles were sampled
at a flow rate of 30 L min-1. The MOUDI has eleven stages, and each
stage consists of a nozzle plate and an impaction plate. Aerosol particles
were collected by inertial impaction onto hydrophobic glass slides (HR3-215;
Hampton Research, USA) positioned on top of each impaction plate. Custom
substrate holders were used to position the glass slides within the MOUDI.
See Mason et al. (2015b) for details on the substrate holders. Stages 2 through 8 of the
MOUDI were analyzed for this study (seven stages in total), corresponding to
aerodynamic diameters of 5.6–10, 3.2–5.6, 1.8–3.2,
1.0–1.8, 0.56–1.0, 0.32–0.56, and
0.18–0.32 µm, respectively, where the bounds are 50 % cut-off
efficiencies (Marple et al., 1991).
Particle rebound from the substrate is an issue when sampling particles with
an inertial impactor. 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).
Rebound can alter the number concentration and size distribution of the INPs
determined with the MOUDI-DFT. Previous work has shown that particle rebound
can be reduced when the relative humidity (RH) is above 70 % (Bateman
et al., 2014; Chen et al., 2011; Fang et al., 1991). In addition, good
agreement between INP concentrations measured by the MOUDI-DFT and INP
concentrations measured by a continuous flow diffusion chamber (a technique
that is not susceptible to rebound) has been observed in previous field
campaigns when the RH of the sampled aerosol stream was as low as 40–45 % (DeMott
et al., 2017; Mason et al., 2015b).
Droplet freezing experiments
The freezing properties of the collected aerosol particles were determined
using the DFT (Iannone
et al., 2011; Mason et al., 2015b; Wheeler et al., 2015). Briefly, the
hydrophobic glass slides with the collected particles were placed in a
temperature- and humidity-controlled flow cell coupled to an optical
microscope (Axiolab; Zeiss, Oberkochen, Germany). The temperature was
decreased to approximately 0 ∘C, and the relative humidity
was increased to above water saturation using a humidified flow of He
(99.999 %, Praxair), resulting in the condensation and growth of water
droplets on the collected particles. On average, approximately 40 droplets
were analyzed in each experiment. The final droplet size was approximately
50–150 µm in diameter, and the spacing between droplets was roughly
100 µm, on average. After the formation of 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.
During this process, most freezing events occurred by immersion freezing,
while approximately 10 % occurred by contact freezing, which refers to
the freezing of liquid droplets caused by contact with neighbouring frozen
droplets. When calculating INP concentrations, the contact freezing was
accounted for in two ways: (i) an upper limit to the fraction frozen by
immersion freezing was calculated by assuming all the contact freezing
droplets froze by immersion freezing, and (ii) a lower limit to the fraction
frozen by immersion freezing was calculated by assuming all the contact
freezing droplets remained liquid until the homogeneous freezing temperature
was reached. The freezing temperature for each droplet was determined using
the recorded images. From the freezing temperatures, the number of INPs
active at a given temperature, #INPs(T), in each freezing experiment was
calculated using the following equation:
#INPs(T)=-lnNuTN0N0fnu,0.25-0.1mm,
where NuT is the number of unfrozen droplets at
temperature T, N0 is the total number of droplets analyzed within
an experiment, and fnu,0.25-0.1mm is a correction factor for the
non-uniformity of particle concentrations across the sample deposit at a
scale of 0.25–0.1 mm (see Mason et al., 2015b for details). Equation (1) accounts for the possibility of multiple
INPs in one droplet (Vali, 1971).
The number concentration of INPs in the atmosphere, [INPs(T)], was then
determined using the following equation:
INPsT=#INPs(T)AdepositADFTVfnu,1mm,
where Adeposit is the total area of the sample deposit on each MOUDI
impaction plate, ADFT is the area analyzed in the droplet freezing
experiment, V is the total volume of air sampled by the MOUDI, and fnu,1mm is a correction factor for the non-uniformity of particle
concentrations across the sample deposit at a scale of 1 mm (see Mason et al., 2015b for details). The values of fnu,1mm
and fnu,0.25-0.1mm are given in Table S1 in the Supplement.
Measurements of aerosol particle number and surface-area size
distributions
The combination of an aerodynamic particle sizer (APS) and a scanning
mobility particle sizer (SMPS) was used to measure the aerosol number and
surface area as a function of size. The APS (model 3321, TSI, Shoreview, MN,
USA) measures diameters using the time-of-flight technique (Baron, 1986). At all three
sites, the APS was operated with a sample flow of 1 L min-1 and a
sheath flow of 4 L min-1. The aerodynamic diameter range measured by
the APS was 0.54–20 µm. Due to possible drop-off in the sampling
efficiency of the APS at sizes below 0.7 µm (Beddows et al., 2010), only APS data at sizes above
0.7 µm are used here, as done previously (Maguhn et al., 2003). The SMPS
measures diameters based on the mobility of a particle in an electric field (Asbach et al., 2009;
Hoppel, 1978). The SMPS was equipped with an inertial impactor at the inlet that
removed large particles outside the measurement range. At Amphitrite Point,
the SMPS (model 3936, TSI) was operated at a 0.57 L min-1 sample flow
with a 2 L min-1 sheath flow and was used to measure particles with
mobility diameters from 18.4 to 930.6 nm. At Labrador Sea and Lancaster
Sound, the SMPS (model 3034, TSI) was operated at a 1 L min-1 sample flow
rate with a 4 L min-1 sheath flow and was used to measure particles with
mobility diameters from 10 to 487 nm. The sampling condition and strategy
are discussed below for each site.
The three sampling locations used in this study and conditions
during sampling including ambient temperature (T) and relative humidity
(RH). Included are the mean values and standard deviations. For Labrador Sea
and Lancaster Sound, the coordinates are the locations at the midpoints of
the sampling periods.
Location
Coordinates
Sampling dates
Sampling
Ambient
Ambient
Wind speed
time (h)
T (∘C)
RH (%)
(m s-1)
Amphitrite Point,
48.92∘ N, 125.54∘ W
6–27 August 2013
7.8±1.3
13.9±1.0
97±4
4.0±2.3
BC, Canada
Labrador Sea,
54.59∘ N, 55.61∘ W
11 July 2014
6.2
10.9±0.8
70±5
5.4±2.1
NL, Canada
Lancaster Sound,
74.26∘ N, 91.46∘ W
20 July 2014
5.3
2.8±0.6
95±1
4.6±0.9
NU, Canada
Locations of sampling
Sampling occurred at three coastal marine sites: Amphitrite Point
(48.92∘ N, 125.54∘ W) on Vancouver Island in British
Columbia, Canada; Labrador Sea (54.59∘ N, 55.61∘ W) off the
coast of Newfoundland and Labrador, Canada; and Lancaster Sound
(74.26∘ N, 91.46∘ W) between Devon Island and Somerset
Island in Nunavut, Canada (Fig. 1 and Table 1). All measurements were
conducted as part of the Network on Climate and Aerosols: Addressing Key
Uncertainties in Remote Canadian Environments (NETCARE). Data from NETCARE are available
on the Government of Canada Open Government Portal (Si et al., 2018). The
sampling dates, ambient RH values, ambient temperatures, and wind speeds
during sampling are summarized in Table 1. Additional details about the three
coastal marine sites are given below.
Amphitrite Point
Measurements at Amphitrite Point were carried out at a marine boundary layer
site operated by Environment and Climate Change Canada, the BC Ministry of the
Environment, and Metro Vancouver. This site, which is frequently influenced
by marine background air (McKendry
et al., 2014), is located on the western coast of Vancouver Island, British
Columbia, Canada, and is approximately 2.3 km south of the town of Ucluelet
(population 1627), with the Pacific Ocean to its west and south, and Barkley
Sound to its southeast and east.
MOUDI samples were collected from 6 to 27 August 2013 (18 day samples, 16
night samples) as part of a larger campaign that focused on cloud
condensation nuclei and INPs at a marine coastal environment (Ladino
et al., 2016; Mason et al., 2015a, b; Yakobi-Hancock et al., 2014). The
average INP concentrations as a function of size for the entire campaign
have been reported previously as well as the INP concentrations for each
sample (Mason et al.,
2015a). In the following, we focus on a subset of these measurements (12 day
samples, 11 night samples) corresponding to the time period when MOUDI-DFT,
APS, and SMPS data are all available.
The MOUDI, APS, and SMPS were located within a mobile trailer (herein
referred to as the NETCARE trailer) that was approximately 100 m from the
rocky shoreline of the Pacific Ocean, separated by a narrow row of trees and
shrubs approximately 2–10 m in height (Mason et al., 2015a).
Aerosol particles were sampled through louvred total suspended particulate
(TSP) inlets (Mesa Labs Inc., Butler, NJ, USA) that were approximately 25 m a.s.l. The MOUDI and APS sampled directly from ambient air without
drying, whereas the SMPS sampled ambient air through diffusion dryers. After
MOUDI samples were collected, they were stored in petri dishes at room
temperature and analyzed for INP concentrations within 24 h of collection.
Meteorological parameters were measured at a lighthouse that was
approximately halfway between the NETCARE trailer and the Pacific Ocean. The
ambient temperature and RH were measured with an HMP45C probe (Campbell
Scientific, Logan, UT, USA). Wind speed was determined by a model 05305L
Wind Monitor (R. M. Young, Traverse City, Michigan, USA). The temperature
and RH within the NETCARE trailer were monitored using a temperature and RH
sensor probe (Acurite 00891W3). The average temperature inside the NETCARE
trailer during INP sampling period was 25 ∘C, compared to
an average ambient temperature of 14 ∘C. As a result, the
average RH of the air sampled by the MOUDI and APS inside the trailer was
lower than ambient RH. Based on the average ambient temperature and RH and
average temperature within the trailer, the average RH in the sampling line
for the MOUDI and APS was approximately 50 %. Three successive diffusion
dryers were used prior to sampling with the SMPS, and the silica was
exchanged and dried in an oven every 24 h. Although not measured on site in
this campaign, this technique has been found to always reduce the RH to less
than 20 %, usually to less than 2 % (Ladino
et al., 2014; Yakobi-Hancock et al., 2014). For typical atmospheric
conditions, the equilibration timescale for gas–particle partitioning of
semivolatile organic species is on the order of minutes to tens of minutes (Saleh et al., 2013). In contrast, the
residence time in the dryers during sampling in the current study was
approximately 10 s. Therefore, the removal of semi-volatile organic species during
drying may not have been a large issue but cannot be completely ruled out.
Labrador Sea and Lancaster Sound
Measurements at Labrador Sea and Lancaster Sound were carried out onboard
the Canadian Coast Guard Service (CCGS) vessel Amundsen. Amundsen serves as
both an icebreaker for shipping lanes and a research vessel. The APS and
MOUDI were located next to each other on top of the bridge of this vessel.
Sampling occurred through louvred TSP inlets that were approximately 15 m a.s.l. The SMPS was positioned
behind the bridge, approximately 20 m away from the APS and MOUDI, and aerosol particles were sampled through a 3/8”
outside diameter stainless steel tube with an inverted U-shaped inlet that
was approximately 15 m a.s.l. Meteorological parameters were
measured with sensors on a tower deployed on the foredeck of the Amundsen.
Wind speed and direction were monitored at a height of 16 m above sea
surface using a conventional propeller anemometer (RM Young Co. model
15106MA). Temperature and RH were measured using an RH/Temperature probe
(Vaisala model HMP45C212) housed in a vented sun shield.
One MOUDI sample was collected on 11 July 2014 in the Labrador Sea off
the coast of Newfoundland and Labrador. Results of this sample have been
reported in Mason
et al. (2016). A second MOUDI sample was collected on 20 July 2014 in
the Lancaster Sound between Devon Island and Somerset Island. During both
sample collection periods, the Amundsen was in transit, and the change of
the coordinates was less than 0.5∘ in longitude and less than 1∘ in latitude. When the two MOUDI samples were collected, the apparent
wind direction was ±90∘ of the bow, and the wind speed
was >9.3 km h-1, suggesting that ship emissions did not
influence the samples (Johnson et al.,
2008). After collection, the samples were vacuum-sealed
and stored in a 4 ∘C fridge for 45–46 days prior to analysis. In contrast,
the samples collected at Amphitrite Point were stored at room temperature
and relative humidity for less than 24 h prior to INP analysis, as mentioned
above. Studies are needed to determine the effect of sample storage
conditions on measured INP concentrations.
Conversion of mobility diameter to aerodynamic diameter and corrections
for hygroscopic growth
At Labrador Sea and Lancaster Sound, a dryer was not used prior to sampling
with the MOUDI, APS, and SMPS. Hence, for these two sites, all data
correspond to the RH and temperatures during the sampling. The sizes
measured by the MOUDI and the APS were aerodynamic diameters, while the
SMPS measured mobility diameter. To allow for comparison between the INP data,
APS data, and SMPS data at these two sites, all the SMPS data have been
converted to aerodynamic diameters (see Sect. S1 for details).
At Amphitrite Point, a dryer was also not used when sampling with the MOUDI
and APS. On the other hand, dryers were used prior to sampling with the
SMPS. To allow for comparison between the INP data, APS data, and SMPS data at
this site, a free parameter was used to convert the SMPS data under dry
conditions to aerodynamic diameters at the RH and temperature during the
sampling. The free parameter was determined from the optimal overlap between
the SMPS and APS data. This type of approach has been used successfully in
the past to merge SMPS and APS data (Beddows et
al., 2010; Khlystov et al., 2004; see Sect. S2 for details).
Back trajectory analysis
For each MOUDI sample collected for INP analysis, a 3-day back trajectory
was calculated using the HYSPLIT4 (Hybrid Single-Particle Lagrangian
Integrated Trajectory) model of the NOAA Air Resources Laboratory (Stein et al., 2015). The GDAS (Global Data
Assimilation System) 1∘ meteorological data were used as input. Back
trajectories were initiated at the beginning of each MOUDI sampling period
and at every hour until the end of the sampling period. The initiating
height was the same as the height of the MOUDI sampling inlets as mentioned
in Sect. 2.3. Back trajectories were also initiated at heights of 50 m and
150 m a.g.l. for each location to determine if the trajectories were
sensitive to the height of initiation.
Global model of INP concentrations
A global model of INP concentrations relevant for mixed-phase clouds was used
to predict concentrations of INPs at the three sampling sites
(Vergara-Temprado et al., 2017). The model considers ice nucleation by
K-feldspar, associated with desert dust, and marine organics, associated with
sea spray aerosols, as INPs. In this model (GLOMAP-mode), aerosol number and
mass concentration of several aerosol species are simulated in seven
lognormal modes (three insoluble and four soluble). The model has a
horizontal resolution of 2.8×2.8∘ with 31 vertical levels,
and it is run for the year 2001 with meteorological fields from the European
Centre for Medium-Range Weather Forecasts (ECMWF). Model output for the year
2001 was used, since this model output was available from previous studies.
The model includes a parameterization of boundary-layer turbulence (Holtslag
and Boville, 1993). The aerosol components are emitted, internally mixed with the species of their mode, and
several aerosol microphysical processes, including new particle formation,
particle growth, dry deposition, and wet scavenging are represented (Mann et
al., 2014). The INP concentrations are determined using a laboratory-based
temperature-dependent density of active sites (active sites per unit surface
area) for K-feldspar (Atkinson et al., 2013) and a parameterization for
marine organics based on the INP content of microlayer samples (expressed as
active sites per unit mass of organic carbon; Wilson et al., 2015) following
the method shown in Vergara-Temprado et al. (2017) in Appendix 2.
To predict INP concentrations at the three coastal marine sites, we used the
output of the model for the grid cells that overlapped with the measurement
locations. Since the measurements were carried out at the surface, output
from the lowest level of the model was used. We calculated the mean
concentrations of INPs from K-feldspar and marine organics for the months
when measurements were made. For the simulations at Amphitrite Point,
Labrador Sea, and Lancaster Sound, the months of August, July, and July were
used, respectively.
The 3-day HYSPLIT back trajectories for Amphitrite Point (red
dot), Labrador Sea (green dot), and Lancaster Sound (yellow dot). The back
trajectories were calculated for every hour during the MOUDI sampling
period. The altitude is indicated with the colour scale. Global Data
Assimilation System (GDAS) meteorological data at 1∘×1∘ spatial resolution were used as input to calculate the
back trajectories using HYSPLIT.
As mentioned above and as done previously, the model output from the year
2001 was compared with measurements from different years. The inter-annual
variability of aerosol concentrations simulated in the model is expected to
be up to a factor of 2 due to differences in meteorological conditions (Marmer and Langmann, 2007). Model output for the year
2001 has been found to be able to reproduce the mass concentrations of
mineral dust and marine organic aerosols within an order of magnitude with
observations made in various years (Vergara-Temprado et al., 2017).
Furthermore, the model output for the year 2001 was able to reproduce 62 % of the INP concentrations measured from studies spanning from 1973 to
2016 within an order of magnitude, which is the uncertainty in the predicted
INP concentrations reported here (Fig. 8).
Results and discussion
Air mass sources from back trajectories
Figure 2 shows the 3-day back trajectories initiated for every hour during
the MOUDI sampling at the three sites. Back trajectories initiated at
heights of 50 m and 150 m a.g.l. (see Figs. S1–S2) showed
similar results. When considering all the back trajectories, at Amphitrite
Point, 94 % of the time was spent over the ocean, at Labrador Sea, 40 % of the time was spent over the ocean, and at Lancaster Sound, 63 %
of the time was spent over the ocean. The rest of the time was spent over
the land. At Amphitrite Point, although the air masses were predominantly
from the ocean based on the back trajectory analysis, the air masses did
pass over local vegetation including coastal western hemlock. This local
vegetation could potentially release enough INPs to overwhelm a small INP
source from the ocean. Therefore, it was not possible to determine if the
INPs are of marine or terrestrial origins based on the back trajectories
alone. INPs may even have been long-range transported from sources that were
not reached by the 3-day back trajectories (Vergara-Temprado et al., 2017).
INP concentrations as a function of size
In Fig. 3, the average INP number concentration is plotted as a function of
size for the freezing temperatures of -15, -20, and -25 ∘C. These three temperatures
were chosen because freezing events were rare at temperatures warmer than
-15 ∘C, and for some MOUDI stages, all the droplets were
frozen at temperatures lower than -25 ∘C, making
calculations of INP concentrations using Eqs. (1)–(2) not possible at
temperatures lower than -25 ∘C. Mason et al. (2015a)
previously reported the average INP number concentrations as a function of
size at Amphitrite Point for the time period of 6–27 August 2013. Here we
report the average INP number concentrations as a function of size at the
same site for a subset of the measurements (23 out of 34 samples) from Mason et al. (2015a)
when both APS and SMPS data were available. Not surprisingly, the results
shown here are very similar to the results shown by Mason et al. (2015a).
The result for Labrador Sea shown in Fig. 3 has also been reported
previously in Mason
et al. (2016), while the result for Lancaster Sound is new and represents
the first report of INP concentrations as a function of size in the Arctic
marine boundary layer. Lancaster Sound had the lowest INP concentrations
among the three sites, with average concentrations of INPs of 0,
0.16, and 0.67 L-1 for the freezing temperatures of -15, -20, and -25 ∘C,
respectively. These numbers are consistent with several previous
measurements reported in the Arctic. For example, Mason et al. (2016) reported the following mean concentrations at a surface site
in Alert, Nunavut: 0.05, 0.22, and 0.99 L-1 for
freezing temperatures of -15, -20, and -25 ∘C, respectively. Bigg (1996) reported mean INP
concentration of 0.01 L-1 at -15 ∘C on an icebreaker
in the Arctic. Fountain and Ohtake (1985) measured mean INP
concentrations of 0.17 L-1 at -20 ∘C at a surface site
in Barrow, Alaska.
Average INP number concentrations at freezing temperatures of -15, -20, and -25 ∘C as
a function of aerodynamic diameter (Dae) for the three sites studied.
The plotted x values represent the midpoints of the size bins from the
MOUDI. The x error bars represent the widths of the size bins from the
MOUDI. For the Amphitrite Point samples, standard error of the mean was used
to represent the uncertainty of INP concentrations during the month. At both
Labrador Sea and Lancaster Sound, only one MOUDI sample was collected, and
we assume the monthly INP concentrations have the same normal distribution
as the Amphitrite Point samples. Hence for the y error bars at these
locations, we assume that the relative standard deviations for supermicron and
submicron particles were the same as the relative standard deviation for
supermicron and submicron particles observed in the Amphitrite Point data.
Average concentrations of (a) aerosol number, N, and
(b) surface area, S, as a function of aerodynamic diameter,
Dae. The y error bars represent the standard error of the mean for each
size bin. In many cases, the error bars are smaller than the size of the
symbols. For cases where a gap existed between the SMPS data and the APS
data, a straight line was used to extrapolate the data.
At Amphitrite Point and Labrador Sea, the majority of INPs measured were
>1 µm in diameter at all the temperatures studied. At
Lancaster Sound, the majority of INPs were also >1 µm at
-25 ∘C. At -15 ∘C, the concentrations of
INPs were not above the detection limit at any of the sizes, while at -20 ∘C, freezing was only observed for sizes
between 0.56 and 1 µm.
Size distributions of ambient aerosols
As mentioned above, the average concentrations of aerosol number and surface
area as a function of size during sampling periods were determined from
measurements with an SMPS and an APS. The results are shown in Fig. 4. The
size distributions were consistent with the size distributions measured at a
mid-latitude North Atlantic marine boundary layer site by O'Dowd et al. (2001); see Fig. S3. The average total number concentrations
were 1487±512 cm-3, 3020±128 cm-3, and 946±254 cm-3 for Amphitrite Point, Labrador Sea, and Lancaster Sound,
respectively. The number concentration at the Arctic site Lancaster Sound
may have been influenced by new particle formation in the summer Arctic
marine boundary layer (Burkart
et al., 2017; Tunved et al., 2013). For the size range of measured INPs
(0.18–10 µm), on average, <3 % of the number
concentration was supermicron in diameter, and <47 % of the
surface-area concentration was supermicron in diameter.
Ice-nucleating ability on a per number basis
The ice-nucleating ability on a per number basis is represented as the
fraction of aerosol particles acting as an INP. Shown in Fig. 5 is the
fraction of aerosol particles acting as an INP as a function of size. To
generate Fig. 5, the aerosol number concentration (Fig. 4a) was first
binned using the same bin widths as the MOUDI, resulting in the total
aerosol number concentration in each size bin (Fig. S4a). Then the INP
concentration (Fig. 3) was divided by the aerosol number concentration (Fig. S4a). Figure 5 shows that the fraction of particles acting as an INP is
strongly dependent on the size. For Amphitrite Point and Labrador Sea, and
for diameters of around 0.2 µm, approximately 1 in 106 particles
acted as an INP at -25 ∘C. On the other hand, at the same
sites and for diameters of around 8 µm, approximately 1 in 10
particles acted as an INP at -25 ∘C. A similar trend may be
present at Lancaster Sound, but at the smaller sizes investigated, the
concentrations of INPs were below the detection limit. The results in Fig. 5
show that the large particles at the three sites studied are extremely
efficient at nucleating ice, and as a result, even though the number
concentration of large particles might be small in the atmosphere, they can
make an important contribution to the total INP number concentrations.
The fraction of aerosol particles acting as an INP
(INP/Naerosol) plotted as a function of aerodynamic diameter (Dae) at
-15, -20, and -25 ∘C, respectively, where Naerosol is the number of aerosol particles in a
given size bin. The plotted x values represent the midpoints of the size bins
from the MOUDI. The x error bars represent the widths of the size bins, and
the y error bars are the propagated uncertainties from INP concentrations as
a function of size (Fig. 3) and aerosol number concentrations as a function
of size (Fig. S4a). In some cases, the y error bars are smaller than the
size of the symbols.
The strong dependence on the size shown in Fig. 5 is consistent with the
small number of previous studies that investigated the fraction of aerosol
particles acting as an INP as a function of size. Berezinski et al. (1988) studied INPs collected at
100–500 m a.g.l. in the southern part of the European territory
of the former USSR. At a freezing temperature of -20 ∘C and
for a diameter of 0.1 µm, approximately 1 in 105 particles acted
as an INP, while for a diameter of 10 µm, approximately 1 in 100
particles acted as an INP. A study of residuals of mixed-phase clouds by Mertes et al. (2007) found
that 1 in 10 supermicron particles acted as an INP, while only 1 in 103
submicron particles acted as an INP. Huffman
et al. (2013) studied INPs collected at a semi-arid pine forest in Colorado,
USA. At a freezing temperature of -15 ∘C and for
a diameter of 2 µm, approximately 1 in 103 particles acted as an
INP, while at the same freezing temperature but for a diameter of 10 µm, more than 1 in 100 particles acted as an INP.
Surface active site density, ns, as a function of size
The surface active site density, ns, represents the number of ice
nucleation sites per surface area (Connolly
et al., 2009; Hoose and Möhler, 2012; Vali et al., 2015). This
parameterization assumes that freezing is independent of time and can be
scaled with surface area. Although these assumptions may not be accurate in
all cases (Beydoun
et al., 2016; Emersic et al., 2015; Hiranuma et al., 2015), ns is
commonly used to describe freezing data due, in part, to its simplicity.
Here we use the following equation to calculate ns as a function of size
from our experimental data:
nsT=INPs(T)Stot,
where INPs(T) is the INP concentration at temperature T
determined from Eq. (2) in a given size range, and Stot is the total
surface area of all aerosol particles in the same size range. Since this
equation considers the surface area of all aerosol particles, rather than
the surface area of just the INPs, the calculated ns values correspond
to the total atmospheric aerosols.
Shown in Fig. 6 are the measured ns values as a function of size
determined with Eq. (3). To generate Fig. 6, the aerosol surface-area
concentration (Fig. 4b) was first binned using the same bin widths as the MOUDI,
resulting in the total aerosol surface-area concentration in each size bin
(Fig. S4b). Following Eq. (3), the INP concentration (Fig. 3) was then
divided by the total aerosol surface-area concentration (Fig. S4b),
resulting in ns values as a function of size. Figure 6 shows that
ns is dependent on the size, with the larger particles being more
efficient at nucleating ice. For Amphitrite Point and Labrador Sea, at a
freezing temperature of -25 ∘C, ns was approximately
2 orders of magnitude higher for 8 µm particles compared to 0.2 µm particles.
The dependence of ns on size can be qualitatively
explained by considering four different types of aerosol particles, each
having progressively larger geometric mean diameters and larger ns
values. For example, consider a mixture of (a) sulfate aerosols internally
mixed with black carbon with a small ns and a small geometric mean
diameter, (b) sea salt aerosols with a larger ns and a larger geometric mean
diameter, (c) clay particles with a larger ns and a larger geometric mean
diameter, and (d) biological particles from terrestrial sources with the
largest ns and largest geometric mean diameter. The assumption of a
small ns for black carbon internally mixed with sulfate aerosols is
consistent with previous measurements (e.g. Brooks
et al., 2014; Chen et al., 2018).
Surface active site density, ns, as a function of aerodynamic
diameter (Dae) at -15, -20, and -25 ∘C, respectively. The plotted x values represent the
midpoints of the size bins from the MOUDI. The x errors represent the widths
of the size bins, and the y errors are the propagated uncertainties from INP
concentrations as a function of size (Fig. 3) and aerosol surface-area
concentrations as a function of size (Fig. S4b). In some cases, the y error
bars are smaller than the size of the symbols.
To determine whether sea spray aerosols or mineral dust are the major sources
of INPs at the three sites, Amphitrite Point, Labrador Sea, and Lancaster Sound, the measured ns values were compared to
the ns values of sea spray aerosols and mineral dust
at -15, -20, and -25 ∘C, respectively (Fig. 7). The ns values of sea spray aerosols in Fig. 7 are from field studies
in the marine boundary layer and laboratory studies of sea spray aerosols as
reported in DeMott et al. (2016). Specifically, the data in Fig. 1a in DeMott et al. (2016) were replotted and fitted using linear regression (Fig. S5).
Since the reported ns values in DeMott et al. (2016) were based on dry, geometric diameters, they overestimate the
ns values based on wet, aerodynamic diameters at 95 % RH by a factor
of 6 (see Sect. S3). Figure 7 shows that the ns values
of sea spray aerosols are smaller than the measured ns values in the
supermicron range at all freezing temperatures at Amphitrite Point. This is
also the case for Labrador Sea at freezing temperatures of -20 and -25 ∘C. For
Lancaster Sound, the ns values of sea spray
aerosols are smaller than the measured ns values for sizes of 5.6–10 µm and a
freezing temperature of -25 ∘C. These
combined results suggest that sea spray aerosols were not the major
contributor to the supermicron INP population at Amphitrite Point and
Labrador Sea and were not a major contributor to the largest INPs (5.6–10 µm in size) observed at Lancaster Sound.
Comparison of measured ns values with previously reported
ns values of sea spray aerosols and mineral dust at -15, -20, and -25 ∘C, respectively. The
ns values of sea spray aerosols were taken from DeMott et al. (2016), and the ns values of
mineral dust were taken from Niemand et al. (2012). The horizontal lines represent the calculated ns values from
linear regression, and the coloured bands represent the 95 % prediction
bands (see Figs. S5–S6). Blue represents sea spray aerosols,
and light green represents mineral dust.
The ns values of mineral dust particles shown in Fig. 7 are based on
laboratory measurements with five different dust samples: Asian dust,
Saharan dust, Canary Island dust, Israeli dust, and Arizona test dust (Niemand et al., 2012). Specifically, the data
in Fig. 6 in Niemand et al. (2012) were replotted and fitted using linear
regression (Fig. S6). Since the reported ns values
in Niemand et al. (2012) were based on
geometric diameters, they overestimate the ns values based on
aerodynamic diameters by a factor of 2 (see Sect. S3).
Figure 7 shows that the ns values for mineral dust are greater than or
equal to the measured ns values at all three sites. These results
suggest that mineral dust could be a possible source of the supermicron INPs
at the three sites studied. However, these results do not confirm mineral
dust as a major contributor to supermicron INPs nor do they rule out other
types of particles as major contributors to supermicron INPs. Note that the
data from Niemand et al. (2012) correspond
to the ns values of mineral dust particles only, whereas the ns
values reported here correspond to the total aerosol particles, as mentioned
above. If we assume mineral dust particles are the only INPs in the
atmosphere, and they account for 50 % of the total aerosol surface area,
then the ns values of mineral dust shown in Fig. 7 divided by a factor
of 2 would correspond to the ns values of the total atmospheric aerosols.
Comparison between measured and simulated INP concentrations
Shown in Fig. 8 is a comparison between the measured total INP concentrations
(sum of the INP concentrations for all sizes measured) and the simulated INP
concentrations at the surface at the three sites using a global model of INP
concentrations based on the ice nucleation of K-feldspar and marine organics.
When considering only marine organics as INPs in the model, predicted INP
concentrations are less than measured INP concentrations in all cases except
for Amphitrite Point at a freezing temperature of -25 ∘C.
This suggests that sea spray aerosols are not the dominant source of INPs at
the three coastal marine sites studied for all three temperatures, which is
consistent with conclusions reached in Sect. 3.5. When considering only
K-feldspar, associated with desert dust, as INPs in the model, the predicted
INP concentrations at -25 ∘C are consistent with the measurements
at all three sites, but at -15 and -20 ∘C, the predicted INP
concentrations are less than measured. When considering both marine organics
and K-feldspar as INPs in the model, the predicted INP concentrations at
-25 ∘C are consistent with measurements, but at warmer
temperatures, the predicted INPs are still less than measured. The
underestimation of INP concentrations at warmer temperatures of the model
could be explained by a missing source of INPs that are active at
temperatures warmer than -25 ∘C, as hypothesized in
Vergara-Temprado et al. (2017) based on the comparison with measurements at
other sites. Possible sources missing in the model that could explain the
high-temperature INPs include bacteria, fungal material, agricultural dust,
or biological nanoscale fragments attached to mineral dust particles
(Fröhlich-Nowoisky et al., 2015; Garcia et al., 2012; Haga et al., 2013;
Mason et al., 2015a; Möhler et al., 2008; Morris et al., 2004, 2013;
O'Sullivan et al., 2014, 2015, 2016; Spracklen and Heald, 2014; Tobo et al.,
2013, 2014).
Recently Mason et al. (2015a) investigated the source of INPs at Amphitrite Point using
correlations between INP number concentrations, atmospheric particles, and
meteorological conditions. Correlations between INP number concentrations
and marine aerosols (sodium as a tracer) and marine biological activities
(methanesulfonic acid as a tracer) were not statistically significant. On
the other hand, a strong correlation was observed between INP concentrations
and fluorescent bio-particles, suggesting that biological particles from
terrestrial sources were likely a dominant source of INPs at this site.
These results are consistent and complementary to the studies presented
above.
As discussed in Sect. 2.1.1, particle rebound from the substrate can be an
issue when sampling particles with an inertia impactor. Good agreement
between INP concentrations measured by the MOUDI-DFT and INP concentrations
measured by a continuous flow diffusion chamber (a technique that is not
susceptible to rebound) has been observed in previous field campaigns when
the RH of the sampled aerosol stream was as low as 40–45 % (DeMott
et al., 2017; Mason et al., 2015b). Nevertheless, particle rebound cannot be
completely ruled out in the current study. If particle rebound was a factor
when collecting particles with the MOUDI in the current study, the measured
INP concentrations would be lower limits to the true INP concentrations, and
the differences between simulated INP concentrations and measured INP
concentrations shown in Fig. 8 would only be larger.
Comparison of measured INP concentrations and (a) simulated INP
concentrations from marine organics, (b) simulated INP concentrations from
K-feldspar, and (c) simulated INP concentrations from both. The solid lines
represent 1:1 ratio, the dashed and dotted lines represent 1 order and 1.5
orders of magnitude's difference, respectively. The temperature is shown using
a colour scale. The simulated INP concentrations for Amphitrite Point,
Labrador Sea, and Lancaster Sound correspond to mean concentrations for the
months of August, July, and July, respectively. The uncertainties in the
simulated concentrations are estimated to be around 1 order of magnitude,
based on the parameterization and model uncertainty (Harrison
et al., 2016; Wilson et al., 2015).
Summary and conclusions
The INP number concentrations in the immersion freezing mode as a function
of size were determined at three coastal marine sites in Canada: Amphitrite
Point (48.92∘ N, 125.54∘ W), Labrador Sea
(54.59∘ N, 55.61∘ W), and Lancaster Sound
(74.26∘ N, 91.46∘ W). For Amphitrite Point,
23 sets of samples were analyzed, and for Labrador Sea and Lancaster Sound,
one set of samples was analyzed for each location. The result for Lancaster
Sound is the first report of INP number concentrations as a function of size
in the Arctic marine boundary layer. The freezing ability of aerosol
particles as a function of size was investigated by combining the
size-resolved concentrations of INPs and the size distributions of aerosol
number and surface area. We found that the fraction of aerosol particles
acting as an INP is strongly dependent on the particle size. At -25 ∘C and for Amphitrite Point and Labrador Sea, approximately
1 in 106 particles acted as an INP at diameters around 0.2 µm,
while approximately 1 in 10 particles acted as an INP at diameters around 8 µm. We also
found that the surface active site density, ns, is
dependent on the particle size. At -25 ∘C and for
Amphitrite Point and Labrador Sea, ns was approximately 2 orders of
magnitude higher for 8 µm particles compared to 0.2 µm
particles. The size distribution of ns can be qualitatively explained by
considering four different types of aerosol particles, each having
progressively larger geometric mean diameters and ns values.
Sea spray aerosols and mineral dust were investigated as the possible sources
of INPs. Sea spray aerosols were not the major source of INPs based on the
comparison of the measurements with the ns values of sea spray aerosols
and the INP concentrations predicted by a global model. On the other hand,
the mineral dust may be a main source of INPs at the three sites and at a
freezing temperature of -25 ∘C, based on the comparison of
the measured INP concentrations with the predictions of a global model.
However, the under-prediction of the INP concentrations at -15 and -20 ∘C suggests the existence of
other possible sources of INPs such as biological particles from terrestrial
sources or agricultural dust. Since only one sample was analyzed for both
Labrador Sea and Lancaster Sound, additional samples should be collected and
analyzed at these locations to determine the general applicability of the
results presented here for these locations. In addition, since the results
presented here correspond to surface measurements, similar studies as a
function of altitude are needed to determine if these results are applicable
to higher altitudes and to the free troposphere. Comparison with predictions
of INPs from a high-resolution model would also be useful to assess the
importance of local INP sources. Studies of the chemical composition of the
INPs are also needed to test the conclusions reached in the current study.