Introduction
Aerosols are an important component of the atmospheric system through their
various impacts on climate. Depending on the type (Satheesh and Moorthy,
2005), aerosols directly scatter and/or absorb radiation, thereby affecting
the atmospheric energy budget (Boucher et al., 2013). Notably, the largest
uncertainty of the energy budget (i.e., radiative forcing estimate) is the
aerosol indirect effect. As cloud condensation nuclei (CCN) and ice
nucleating particles (INPs), aerosols influence atmospheric radiation through
modulation of the microphysics of cloud droplets and ice crystals.
Aerosol-induced microphysical modifications influence cloud lifetime and
albedo, as well as the production of more or less precipitation (Albrecht,
1989; Twomey, 1977). However, constraining aerosol–cloud impacts in climate
models, specifically when parameterizing INPs in mixed phase cloud (MPC)
systems, remains a significant challenge due to limited observations (Cziczo
et al., 2017; Coluzza et al., 2017; DeMott et al., 2010; Kanji et al., 2017;
Korolev et al., 2017).
The efficacy of an aerosol to serve as an INP largely depends on its
composition (i.e., chemical, mineral, or biological makeup), morphology, and
size, and thus, its source. INPs nucleate ice through pathways dependent upon
temperature, saturation with respect to ice, and the INP size and composition
(Hoose and Möhler, 2012). Immersion freezing is the most relevant to MPC
formation and requires that INPs initially serve as CCN (Hande and Hoose,
2017). Aerosols such as mineral dust, soil dust, sea salt, volcanic ash,
black carbon from wildfires, and primary biological aerosol particles (PBAPs)
have been shown to serve as INPs (Murray et al., 2012; Hoose and Möhler,
2012; Coluzza et al., 2017; Petters et al., 2009; DeMott et al., 1999;
McCluskey et al., 2014; Conen et al., 2011). Among these, dust and PBAPs are
the most adroit INPs found in the atmosphere (Murray et al., 2012; Coluzza et
al., 2017). PBAPs originating from certain bacteria and vegetative detritus
are the most efficient INPs known, capable of initiating freezing near
-1 ∘C, while most PBAPs (e.g., pollen, fungal spores, algae, and
diatoms) tend to nucleate ice at temperatures similar to those of mineral
dust but warmer than sea salt or volcanic ash (Despres et al., 2012; Murray
et al., 2012; Hoose and Möhler, 2012; Tobo et al., 2014; Hader et al.,
2014; O'Sullivan et al., 2014; Creamean et al., 2013, 2014;
Hill et al., 2016; Tesson et al., 2016; Alpert et al., 2011; Knopf et al.,
2010; Umo et al., 2015; Durant et al., 2008; Fröhlich-Nowoisky et al.,
2015; McCluskey et al., 2014). However, dusts can serve as atmospheric
shuttles for small microbes, enabling these particle mixtures to behave more
efficiently as INPs compared to the dust alone (Conen et al., 2011; Creamean
et al., 2013; O'Sullivan et al., 2014). Consequently, PBAPs have the
potential to play a crucial role in cloud ice formation (Creamean et al.,
2013, 2014; Pratt et al., 2009) and precipitation enhancement (Morris et al.,
2004, 2014, 2017; Bergeron, 1935; Christner et al., 2008; Stopelli et al.,
2014), particularly in the presence of supercooled water or large cloud
droplets. PBAPs have been a key focus of recent ice nucleation studies, yet
estimating their global impact remains a challenge due to
a dearth of observations in time and space and
a poor understanding
of sources, flux, and abundance of PBAPs in the Earth–atmosphere system
(Hoose et al., 2010a).
Little is known about marine emissions of biological INPs – most studies of
such aerosols to date have examined terrestrial sources (Burrows et al.,
2013; Murray et al., 2012). Recent laboratory, field, and modeling studies
have evaluated the mechanical emission processes, ice nucleation efficiency,
and concentrations of INPs generated from marine environments (Knopf et al.,
2010; Mason et al., 2016; McCluskey et al., 2017). Results from these studies
imply that PBAPs are most relevant to ice formation at MPC temperatures
(i.e., > -10 ∘C), whereas sea salt aerosols nucleate
ice in both deposition and immersion modes at temperatures relevant for
cirrus clouds (i.e., < -38 ∘C) (Schill and Tolbert,
2014). Conclusions on the role of PBAPs in ice nucleation and precipitation
are equivocally based on results from climate modeling, with some studies
implying they are insignificant on a global scale (Hoose et al., 2010a, b;
Sesartic et al., 2012), while others have found them to be potentially
important (Phillips et al., 2008, 2009; Vergara-Temprado et al., 2017). An
inherent limitation of these pioneering studies is that results were
validated by a handful of terrestrial-based observations of biological INPs.
This, coupled with the fact that 70 % of the Earth's surface is covered by
ocean, implies that studies using global climate simulations have ignored a
potentially significant global source of INPs.
Previous work by Leck and Bigg in the High Arctic were among the first to
elucidate the potentially paramount role of the ocean as a source of
efficient INPs (Leck and Bigg, 2005; Bigg and Leck, 2001, 2008; Bigg, 1996),
suggesting bacteria and fragments of marine organisms were responsible for
the ice nucleating contribution to their samples. Schnell (1975) concluded
that zones of profuse marine phytoplankton growth may release large numbers
of INPs into the atmosphere based on measurements conducted on
laboratory-cultured marine phytoplankton. However, new studies that provide
information on key sources of INPs and their impacts on Arctic MPCs
are necessary to assess the direct contribution from the marine environment.
Irish et al. (2017) and Wilson et al. (2015) report enhanced ice nucleation
activity of particulate matter in the surface microlayer and bulk seawater
from the Arctic Ocean. Both studies concluded that the enhanced INP
concentrations measured were attributed to heat-labile biological material
and organic material associated with phytoplankton cell exudates,
respectively. In addition, sources of INPs at Arctic coastal locations have
been measured during the summer by Fountain and Ohtake (1985), Mason et
al. (2016), and Conen et al. (2016) in Alaska, Canada, and Norway,
respectively. Fountain and Ohtake (1985) did not comment on exact sources of
INPs they measured at Utqiaġvik (formally Barrow), but determined INPs
during episodic increases in concentration to be either from the Alaskan
interior or transported long range from Eurasia. Mason et al. (2016) did not
comment on the sources of their size-resolved INPs at Alert between March and
July but determined fewer local sources of aerosols as compared to their
midlatitude coastal locations. Conen et al. (2016) attributed a fraction of
their observed warm-temperature INPs (i.e., INP concentrations at
-8 ∘C) from May to September were fungal spores and that most INPs were
aerosolized locally by the impact of raindrops on plant, litter, and soil
surfaces. Their measurement site was 219 m above mean sea level
(m a.m.s.l.) and 20 km from the actual coast, and thus, could be the reason
terrestrial sources were more influential at their site. To date, only a
handful of studies have evaluated Arctic INPs in coastal or marine
environments.
The Arctic is a remarkable region with regard to many atmospheric processes,
but especially with regard to ice nucleation because
the Arctic is mostly ocean, which may be the most prolific regional source of
biological INPs;
interruption of ocean–atmospheric exchange by sea ice
cover likely affects seasonally dependent patterns in the emission of
PBAPs and INPs; and
aerosol–cloud interactions could have implications
important to understanding declining trends in sea ice and snow coverage.
Overall, limited information on aerosol–cloud processes (Lubin and Vogelmann,
2006; Garrett and Zhao, 2006), contradictory modeling results with regard to
the importance of biological INPs (Szyrmer and Zawadzki, 1997), and a
critical need to understand the role of aerosol particles in determining
cloud phase (Bergeron, 1935; Wegener, 1911; Findeisen, 1938) motivate the
need for additional observations to constrain the abundance and
ice-nucleating properties of aerosols in the Arctic (Murray et al., 2012).
Here, we present a 3-month record of continuous time- and size-resolved INP
concentrations at Oliktok Point, a coastal site in Alaska situated within the
North Slope of Alaska (Prudhoe Bay) oilfields, which have been shown to be
strong and localized sources of pollutants. Recent studies have indicated
that sources of aerosol in this region include carbonaceous combustion and
aged sea spray aerosol measured during the winter and summer (Gunsch et al.,
2017; Kirpes et al., 2018) and newly formed particles from Prudhoe Bay
gaseous emissions (Creamean et al., 2018a; Maahn et al., 2017; Kolesar et
al., 2017), in which the anthropogenic pollutant aerosol has been linked to
increased local cloud droplet concentrations over the Beaufort Sea (Hobbs and
Rangno, 1998). Although anthropogenic aerosol may be the dominant type in
this region, Gunsch et al. (2017) and Kirpes et al. (2018) also observed a
significant fraction of supermicron aerosol to be fresh sea spray aerosol.
Additional sources of aerosol observed at higher altitudes over Prudhoe Bay
include regional wildfires and long-range transported pollution, although,
these were measured during the summer (Creamean et al., 2018a). However, INPs
and their sources have yet to be evaluated in this region. Here, we employ a
comprehensive combination of size-resolved INP measurements, single-particle
chemistry, bulk aerosol chemistry, local meteorology, regional scale
transport, and sea ice and land cover conditions to assess INP sources in
Prudhoe Bay. Unique observations of an increase in what were likely marine-
and terrestrial-sourced INPs are discussed. This is the first time INP
measurements have been conducted in an Arctic oilfield, and we demonstrate
how efficient, mineral- and marine-sourced INPs are likely important in such a
relatively polluted Arctic location.
Methods
Study location and dates
INPOP (Ice Nucleating Particles at Oliktok Point) was conducted at the Third
Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF-3) operated by
the United States Department of Energy (DOE) in Oliktok Point, Alaska
(70.51∘ N, 149.86∘ W, 2 m a.m.s.l.) (Creamean, 2017).
Oliktok Point is located in Prudhoe Bay (Fig. 1), the third largest oilfield
in North America (US Energy Information Administration, 2015). The study time
period was 1 March–31 May 2017. Data from INPOP and the rest of the AMF-3
data record (2013–present) are available on the ARM data archive
(https://www.archive.arm.gov/discovery/, last access: 11 November 2018)
(Creamean, 2017).
Map of the North Slope of Alaska highlighting Oliktok Point and oil
wells that are active in Prudhoe Bay (data obtained from
http://doa.alaska.gov/ogc/publicdb.html, last access: March 2017). The
approximate areas of Prudhoe Bay and the Brooks Mountain range are shown.
The inset shows the inside of the DRUM case, with stage A exposed (i.e., cover
removed) and major components labeled.
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Dates and start times of sample collection during INPOP (2017) for
samples analyzed for INPs. Samples correspond to 1 full day (24 h from the
start time). The “INPs” column corresponds to the stages that were analyzed
via the DFCP per daily sample. A = 2.96–> 12 µm,
B = 1.21–2.96 µm, C = 0.34–1.21 µm, and
D = 0.15–0.34 µm.
Date
Start (UTC)
INPs
11 Mar
21:00
A, C
18 Mar
20:00
A, C
25 Mar
20:00
A, C
1 Apr
20:00
A, C
17 Apr
16:00
A, B, C, D
24 Apr
16:00
A, B, C, D
2 May
16:00
A, B, C, D
9 May
16:00
A, B, C, D
16 May
16:30
A, B, C, D
22 May
16:30
A, B, C, D
23 May
16:30
A, B, C, D
24 May
16:30
A, B, C, D
25 May
16:30
A, B, C, D
26 May
16:30
A, B, C, D
27 May
16:30
A, B, C, D
28 May
16:30
A, B, C, D
29 May
16:30
A, B, C, D
Sample collection
For offline ice nucleation analyses, daily aerosol samples were collected
11 March–31 May 2017 (Table 1) using a 4-stage time- and size-resolved Davis
Rotating-drum Universal-size-cut Monitoring (DRUM) single-jet impactor
(DA400, DRUMAir, LLC.) (Cahill et al., 1987) housed in a
47 cm × 35.7 cm × 17.6 cm
Pelican™ case (inset in Fig. 1). The DRUM
impactor collected aerosol particles at four size ranges (0.15–0.34, 0.34–1.20,
1.20–2.96, and 2.96–> 12 µm in Stokes' equivalent
diameter) and sampled at 26.7 L min-1, equalling 38 428 total liters of
air per day (i.e., per sample). Such size ranges cover a wide array of
aerosols, particularly those that serve as INPs (DeMott et al., 2010;
Fridlind et al., 2012; Mason et al., 2016). Simultaneously, the large volume
of air collected promotes collection of rarer warm-temperature biological
INPs, which may represent a lower fraction of overall INP concentrations
(Mossop and Thorndike, 1966). Samples were deposited onto 20 × 190 mm strips of petrolatum-coated (100 %,
Vaseline®)
Mylar™ (0.02 mm thick;
DuPont®) substrate secured onto the rotating
drums (20 mm thick, 60 mm in diameter) in each of the four stages at the
rate of 7 mm day-1 (5 mm of sample streaked onto the Mylar followed
by 2 mm of blank).
The DRUM impactor was secured inside the AMF-3 container, with an approximately 7 m
long sampling line (6.4 mm inner diameter static-dissipative polyurethane
tubing; McMaster-Carr®) leading to outside of
the container and connected to a plastic funnel inlet, covered with loose
mosquito netting to prevent rimed ice build-up or blowing snow from clogging
the inlet. Aerosol collection was conducted at ambient relative humidity,
which may affect particle size. The purpose of not drying the aerosol was to
collect at sizes relevant to the particles in true environmental conditions.
Daily rotation checks were conducted by disconnecting the DRUM impactor from its pump
and removing the stage caps to ensure the drums were rotating at the correct
rate and sample substrates remained secured to each drum. Weekly checks of
the inlet flow and pressure measured at each stage were conducted to ensure
the orifices to each stage were not clogged and the DRUM pump was operating
correctly.
The drums rotated for 24 to 26 days before sample substrates were changed
(i.e., one full rotation of the drums), equalling three drum changes during
INPOP. Sampled substrates were kept on the drums and stored frozen in a
standard freezer until transport to Boulder, Colorado, and stored frozen in a
chest freezer for 5 to 7 months before offline INP analyses (see following
section). This is the first time a DRUM impactor has been used for offline INP
analyses, but as we demonstrate, it is a useful sample collection method for
long-term studies.
For offline single-particle analysis, daily samples were collected at
16.1 L min-1 using a 3-stage DRUM impactor with particle size ranges
0.10–0.34, 0.34–1.15, and > 1.15 µm on transmission
electron microscopy (TEM) grids (Formvar carbon Type-B copper grids, Ted
Pella, Inc.) attached to each of the three drums. The rotation was set at
3 mm day-1, such that particles were deposited over the width of one
TEM grid per 24 h sampling period. Drums were changed once over the course
of the INPOP study. Sampled substrates were kept on the drums and stored in
the dark at ambient temperature until analysis (∼ 3 months) (Laskina et
al., 2015). Select daily samples corresponding to interesting case studies
were analyzed for discussion in the current paper. A third DRUM sampler
collecting particles in eight size bins (0.09–0.26, 0.26–0.34, 0.34–0.56,
0.56–0.75, 0.75–1.15, 1.15–2.5, 2.5–5.0, and
5.0–> 12 µm) on Mylar™
for 12 h per sample was co-located for bulk inorganic analysis
(∼ 2 months after collection). The flow rate was maintained at
9.6 L min-1 with a drum rotation rate of 0.5 mm day-1. Only one
set of drums for this sampler was needed for the duration of INPOP. Samples
were stored in the DRUM chambers during shipment and storage until analysis.
The same sampling line setups and routine checks as the 4-stage DRUM
impactor were applied to the 3-stage and 8-stage DRUM impactors.
Drop freezing assays (DFAs) for immersion mode INPs
In total, 216 daily samples were collected between the four different stages
(herein, stages A, B, C, and D correspond to 2.96–12, 1.20–2.96,
0.34–1.20, and 0.15–0.34 µm particles, respectively. Due to
contamination issues, stages B and D were not analyzed from the first set of
daily samples (see Table 1). Other missing data (i.e., samples not analyzed)
are due to occasional power outages at the AMF-3. Due to the large volume of
samples, initially, one daily sample per week was analyzed to assess a
broader picture of INPs over the course of the spring months. Daily samples
were analyzed 22–29 May 2017 due to interesting aerosol events and source
influences (as evidenced in the following sections) observed during this time
period as described herein. Immediately prior to analysis, sample strips were
cut into their daily segments and stored frozen in 29 mL sterile
Whirl-pak® bags for up to 1 week.
Immersion mode freezing was tested using a drop freezing assay (DFA) cold
plate apparatus. This cold plate technique was based on previous but slightly
modified apparatuses (Hill et al., 2016; Tobo, 2016; Stopelli et al., 2014;
Wright and Petters, 2013) and is discussed in detail by Creamean et
al. (2018b). For brevity, we call this system the drop freezing cold plate
(DFCP). Before analyzing with the DFCP, 2 mL of ultrapure water (UPW;
Barnstead™
Smart2Pure™ 6 UV/UF) was added to the sterile
Whirl-pak® bags containing sample segments to
resuspend deposited particles. The bags were sealed and shaken at 500 rpm
for 2 h (Bowers et al., 2009). It is possible not all particles were removed
during the extraction process; however, previous control testing indicates
sufficient aerosol loading is resuspended (Creamean et al., 2018b). Yet, the
fraction of material resuspended may depend on the overall loading. Copper
discs (76 mm in diameter, 3.2 mm thick) were prepared by cleaning with
isopropanol (99.5 % ACS Grade; LabChem, Inc.), then coating with a thin
layer of petrolatum (Tobo, 2016; Bowers et al., 2009). Following sample
preparation, a sterile, single-use plastic syringe was used to draw 0.25 mL
of the suspension and 100 drops were pipetted onto the petrolatum-coated
copper disc, creating an array of ∼ 2.5 µL aliquots. Drops
were visually inspected for size; however, it is possible not all drops were
the same exact volume, which could lead to a small level of indeterminable
uncertainty (Alpert and Knopf, 2016). However, we have previously
demonstrated that drop size variability does not impact freezing results
(Creamean et al., 2018b). Previous studies have elucidated that drops need to
be orders of magnitude different in volume to significantly perturb the
freezing temperature from drop size, alone (Hader et al., 2014; Bigg, 1953;
Langham and Mason, 1958). The copper disc was then placed on a thermoelectric
cold plate (Aldrich®) and covered with a
transparent plastic dome. Small holes in the side of the dome and copper disc
permitted placement of up to four temperature probes using an
Omega™ thermometer/data logger
(RDXL4SD; 0.1 ∘C resolution and accuracy of ±
(0.4 % + 1 ∘C) for the K sensor types used). During the
test, the cold plate was cooled variably within a
1–10 ∘C min-1 range from room temperature until around
-30 ∘C. Control experiments with UPW at various cooling rates
within this range show no discernible dependency of drop freezing on cooling
rate (Creamean et al., 2018b), akin to previous works (Wright and Petters,
2013; Vali and Stansbury, 1966).
A +0.33 ∘C correction factor was added to any temperature herein,
and an uncertainty of 0.15 ∘C was added to the probe accuracy
uncertainty based on DFCP characterization testing presented in Creamean et
al. (2018b) to account for the temperature difference
between the measurement (i.e., in the plate center) and actual drop
temperature. Frozen drops were detected visually, but the freezing
temperature and cooling rate of each drop frozen were recorded through custom
software. The test continued until all 100 drops were frozen or when the
system reached approximately -30 ∘C. Each sample was tested three
times, with 100 new drops for each test. From each test, the fraction frozen
and percentage of detected frozen drops were calculated. For INPOP, 71 %–100 %
of the 100 drops were visually detected and recorded as frozen for
each test. The results from the triplicate tests were then binned every
0.5 ∘C to produce one spectrum per sample. Cumulative INP spectra were
calculated using the equation posed by Vali (1971) and adjusted to
account for the total volume of air per sample:
INPs(T)(L-1)=lnNo-lnNu(T)Vdrop×VsuspensionVair,
where No is the total number of drops, Nu(T) is the number of
unfrozen drops at each temperature, Vdrop is the average volume of each
drop, Vsuspension is the volume of the suspension (i.e., 0.75 mL total
for the three tests), and Vair is the volume of air per sample (38 428 L)
(Stopelli et al., 2014; Mason et al., 2016; Chen et al., 2018; Boose et al.,
2016a).
Single-particle and bulk aerosol composition
Particles collected on TEM grids using the 3-stage DRUM impactors were analyzed for
single-particle chemical composition and morphology using computer-controlled
scanning electron microscopy with energy dispersive X-ray spectroscopy
(CCSEM-EDX). Samples were analyzed using a FEI Quanta scanning electron
microscope with a field emission gun operating at 20 keV and equipped with a
high-angle annular dark field detector for particle size and morphology and
an energy dispersive X-ray spectrometer (EDAX, Inc.) and a Si(Li)
detector (10 mm2) for particle elemental composition of elements
including C, N, O, Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Fe, Ni, and Zn. An
average of 1000 particles were analyzed per substrate. Data were analyzed using
k-means cluster analysis of the single-particle EDX spectra (Ault et al.,
2012). Fifty clusters were combined into six classes of particle types,
including fresh sea spray aerosol, aged sea spray aerosol, dust, organic
aerosol, fly ash, and soot, based on similarity of elemental composition
(Kirpes et al., 2018; Gunsch et al., 2017; Weinbruch et al., 2012).
Samples collected on the 8-stage DRUM impactors were analyzed for elemental
concentrations using synchrotron-induced X-ray fluorescence spectrometry
(S-XRF) at the Lawrence Berkeley National Laboratory Advanced Light Source
facility (VanCuren et al., 2012; Perry et al., 2004). The 1.5 GeV polarized
X-ray beam provides very low background bremsstrahlung radiation and high
sensitivity of elements including Na, Mg, Al, Si, P, S, Cl, Ar, K, Ca, Sc,
Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Ge, As, Se, Br, Rb, Sr, Y, Zr, Nb, Mo,
and Pb. Spectra were acquired with a Vortex®-60EX silicon drift detector
(Hitachi High-Technologies, USA) and were post-processed using both WinAxil
(Canberra, Belgium) and PyMca (Sole et al., 2007) independently, for quality
assurance. Further data reduction into timestamped concentrations was
performed using custom software (R Foundation for Statistical Computing,
2017). For specific comparisons, non-soil K was calculated as
non-soilK = K-0.45×Fe (Lewis et
al., 1988) while soil K was calculated as soil K = K-non-soilK.
These estimations ignore any contribution from biomass burning, which was a
minor component of the observed single-particle designations.
Supporting observations and modeling
The AMF-3 at Oliktok Point includes the ARM Aerosol Observing System (AOS),
which provides a wide range of aerosol and meteorological measurements
(Jefferson, 2011). Data used here are publicly available in the ARM data
archive and include aerosol number and size and wind direction and speed.
Aerosol number concentrations were measured with a condensation particle
counter (CPCf; 10 nm–3 µm) and ultrafine CPC (CPCu;
3 nm–3 µm) (TSI, Inc., models 3010 and 3025, respectively).
Aerosol size distributions were measured with an ultrahigh-sensitivity
aerosol sizer (UHSAS, Droplet Measurement Technologies, Inc.) for particles
in the 60 nm–1 µm size range. The AOS Surface Meteorology
(AOSMET) data for atmospheric temperature, humidity, and wind speed and
direction were measured via a Vaisala, Inc. WXT520 Weather Transmitter
(Kyrouac, 2016). AOS data have a time resolution of 1 s. It is important to
note that the aerosol from the AOS is dried to 40 % relative humidity
(RH) while the DRUM impactor sampled aerosol at ambient relative humidity,
thus a possible small size disparity between the two inlets may exist. Daily
snow and ice cover data were obtained from the National Snow and Ice Data
Center. Snow cover data (http://nsidc.org/data/g02156#table3, last
access: 11 November 2018, version 1) were derived from the Ice Mapping System
(IMS) daily Northern Hemisphere snow analysis at a 1 km × 1 km
resolution and are derived from a variety of data products including
satellite imagery and in situ data (National Ice Center, 2008). Sea ice data
(https://nsidc.org/data/g10005, last access: 11 November 2018, version
1) were derived from the Multisensor Analyzed Sea Ice Extent Advanced
Microwave Scanning Radiometer 2 (MASAM2) daily 4 km sea ice concentration product that is a blend of two
other daily sea ice data products: ice coverage from the product at a 4 km
grid cell size and ice concentration from the AMSR2 at a 10 km grid cell
size (Fetterer et al., 2015). MASAM2 was used to meet a need for greater
accuracy and higher resolution in ice concentration fields. Air mass backward
trajectories (5-day) were calculated using the HYbrid Single-Particle
Lagrangian Integrated Trajectory (HYSPLIT) model with the SplitR package for
RStudio (https://github.com/rich-iannone/SplitR, last access: 11
November) (Draxler, 1999; Draxler and Rolph, 2011). Data from the Global Data
Assimilation System (GDAS; 1∘ latitude–longitude; 3-hourly) from
National Centers for Environmental Prediction (NCEP) were used as the
meteorological fields in HYSPLIT simulations. Trajectories were initiated at
5 m above ground level (a.g.l.) (i.e., the approximate height of the inlet)
every 3 h daily. Only hours within the sample day (i.e., starting at
16:00 UTC) were evaluated for each sample, such that 18:00 and 21:00 UTC on
the same day and 00:00, 03:00, 06:00 09:00, 12:00, and 15:00 UTC on the
following day were considered per sample. Trajectories were only simulated
for each day of May during sea ice melt off the Alaskan coast and during the
22–29 May case study.
Time series of hourly-averaged aerosol numbers and meteorological
variables from AOSMET during 1 March–31 May 2017, including aerosol number
concentrations measured by (a) the condensation particle
counter (CPCf) and an ultrafine CPC (CPCu) and (b) the
ultrahigh-sensitivity aerosol sizer (UHSAS). Average hourly mean particle
diameter (Dp) is also shown from the UHSAS in (b).
Meteorological data include (c) relative humidity and air
temperature. Light grey shading represents days where samples were analyzed
for INP concentrations. Dark grey shading represents times with missing
data.
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Results and discussion
Atmospheric conditions during INPOP
Shifts in the aerosol population and atmospheric conditions throughout the
course of INPOP were evident from the AOS measurements (Fig. 2). Particle
concentrations were high relative to what has been previously observed in the
surrounding areas on the North Slope (e.g., Creamean et al., 2018a; Quinn et
al., 2002), with the CPCu, CPCf, and UHSAS measuring average concentrations of
2065, 1603, and 1483 cm-3, respectively, over the entire study. These
elevated concentrations are likely the result of the local industrial
activities, which are prominent at Oliktok Point (Creamean et al., 2018a;
Maahn et al., 2017; Gunsch et al., 2017). Akin to previous work on the North
Slope during the Arctic haze, high particle concentrations were observed in
April (e.g., Quinn et al., 2007), with averages of 2091, 3286, and
1526 cm-3 for CPCu and 1702, 2736, and 907 cm-3 for CPCf measured
from March, April, and May, respectively. The monthly-averaged UHSAS
concentration was highest in March, at concentrations much higher than
measured in May (3063, 1658, and 975 cm-3 for March, April, and May,
respectively). Mean particle size from the UHSAS was fairly consistent
between the months (156.6 ± 7.6, 149.9 ± 9.9, and
143.6 ± 7.3 nm, respectively). However, data from March may not be
representative of the entire month due to a power outage in the first part of
that month (i.e., missing data in Fig. 2). As documented in previous studies
(Law and Stohl, 2007; Stohl, 2006; Garrett et al., 2010; Di Pierro et al.,
2013), changes in transport and precipitation patterns resulted in lower
particle concentrations around late May. However, one interesting feature is
the large variability in particle concentrations, particularly during late
May, when hourly-averaged concentrations ranged from 13–1486, 12–1111, and
35–1182 cm-3 for the CPCu, CPCf, and UHSAS, respectively. Ambient
temperature and relative humidity increased steadily over the course of the
study and reached values indicative of coastal marine conditions towards the
end of May (Cox et al., 2012).
Observation of a shift in springtime INP glaciation temperatures
and concentrations in Prudhoe Bay
INP concentrations from the Arctic are typically very low compared to other
regions (Kanji et al., 2017), and industrial regions are not thought to serve
as prolific INP sources (e.g., Chen et al., 2018). Figure 3 shows the
size-resolved INP concentrations from INPOP. A few key features are evident:
Larger particles were more efficient INPs, especially at warmer
temperatures.
Larger particles exhibited a larger spread in INP spectra.
Late May samples contained particularly high concentrations of warm-temperature (i.e., > -10 ∘C) INPs relative to March
and April.
INPOP INP concentrations were generally low, falling into the
lower end of ranges reported by Kanji et al. (2017) and Petters and
Wright (2015). Comparison of our results to previous ice nucleation studies
in the Arctic are discussed in Sect. 4.
Cumulative INP spectra for the four size-ranged samples of the DRUM
impactor from INPOP (a–d represent stages A–D, respectively). One
daily sample per week is shown from 11 March to 16 May and 17 April to 16 May
for stages A and C and stages B and D, respectively. Daily samples are shown from 22 to 29 May
for all stages. White diamond markers denote the blank Mylar sample in UPW
prepared in the same manner as the samples. This blank spectrum applies to
all size ranges.
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The first feature discussed above has been reported by other size-resolved
Arctic INP studies. Mason et al. (2016) report similar observations in Alert,
Canada, where 95 % and 70 % of INPs were found at sizes
> 1 and > 2.5 µm in diameter, respectively,
and a median diameter of approximately 3 µm for all INPs at
-15 ∘C. They also sampled at ambient RH, stating RH at 70 % or
greater can significantly reduce particle bounce via impaction sampling – RH
during INPOP was typically > 70 % (86 ± 14 % on
average, Fig. 2), indicating the DRUM impactor was minimally affected by particle
bounce. In general, observational studies in locations outside of the Arctic
also report a relationship between temperature and particle size, where
supermicron or coarse mode aerosols are the most proficient INPs at warmer
temperatures (Vali, 1966; references cited in Mason et al., 2016; Huffman et
al., 2013; Conen et al., 2017). However, modeling studies suggest the mode
of INPs can be as small as 500 nm (DeMott et al., 2010, 2015; Fridlind et
al., 2012), while observational work suggests that nanometer-sized INPs are
typically found attached to larger particles in the atmosphere (O'Sullivan et
al., 2015). The second feature (larger spread in INP concentrations between
samples with an increasing size) indicates a larger variation in different
aerosol sources or source strength (Seinfeld and Pandis, 2016; Mason et al.,
2016) versus the smallest INPs observed which have similar spectra,
indicating similar sources. Additionally, stage A of the DRUM impactor has a wider
size range (∼ 9 µm) versus the smaller stages (∼ 0.2 to
2 µm). The third reported feature was unexpected, given the
characteristically polluted atmosphere in the Prudhoe Bay area. The
22–29 May period featured INP concentrations up to
4 × 10-3 L-1 at -10 ∘C and
2 × 10-2 L-1 at -15 ∘C, with warm-temperature
INPs apparent especially for the largest sizes (i.e.,
2.96–> 12 µm (stage A) and 1.21–2.96 µm,
stage B). The onset temperatures (up to -5 ∘C) were also much
higher during this period for the two largest size cuts of the DRUM impactor (Fig. 4),
indicating a presence of biological INPs (Murray et al., 2012; Kanji et al.,
2017). The presence of biological INPs in Prudhoe Bay in the spring is
somewhat unexpected given the predominantly frozen surfaces. Despite this,
the sizes of the observed INPs indicate a more local or regional origin due
to reduced atmospheric lifetime (Jaenicke, 1980). The smallest sizes
(0.34–1.21 µm for stage C and 0.15–0.34 µm for stage D) did not
portray the same trend during late May. There, a higher fraction of particles
were active at much colder temperatures (i.e., INP-20 and INP-25) as
compared to INP-10 or INP-15, where temperatures are generally
relevant to less efficient biological INPs (i.e., spores) and mineral dust
(Murray et al., 2012; Haga et al., 2014; Boose et al., 2016b). A previous
study by Stone et al. (2007) demonstrated transport of Asian dust to
Utqiaġvik during the spring, thus introducing sources of colder
temperature INPs even though the surface is predominantly frozen.
Onset freezing temperatures and INP concentrations at -10, -15,
-20, and -25 ∘C for DRUM stages (a) A, (b) B,
(c) C, and (d) D for each sample collected during INPOP.
Dark grey shading represents missing data. Error bars for the onset
temperature represent the probe uncertainty and the plate correction and standard
deviation for the INP concentrations.
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Open Arctic waters and snow melt over tundra as sources of
observed transition in INP properties
Focusing on the month of May, it is clear that there are higher
concentrations of warm-temperature INPs, particularly for DRUM stages A and B
(Fig. 4). Stages C and D include, or are completely composed of, particles
that are thought to be less efficient INPs relative to particles with larger
diameters (DeMott et al., 2010, 2015; Fridlind et al., 2012), which is
consistent with the low INP activity from such particles during INPOP. Stage
A was especially unique, with the range of freezing temperatures becoming
smaller over time. Snow coverage decreased sharply within 700 km of Oliktok
Point on 8 May, while sea ice within 700 km dropped in fraction after 13 May
(Fig. 5e), which roughly aligns with the increase in onset freezing
temperatures for the largest particles in stage A and generally higher onset
freezing temperatures for stages B and C.
Time series of INP freezing temperatures colored by INP
concentrations (colored bands, left axis) for DRUM stages (a) A,
(b) B, (c) C, and (d) D. Note that the INP
concentrations are in log scale. Also shown are the (e) sea ice and
snow coverage within a 300 and 700 km radius from Oliktok Point. Data for
the month of May are shown at https://nsidc.org/data/g02156 (last
access: 11 November 2018).
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5-day air mass backward trajectories initiated every 3 h and land
cover (e.g., sea ice, snow, ocean, and open land) for some of the case days
in May with INP data. Each date contains the map and corresponding
time–height cross section of the 5-day trajectories (shown below each map).
The x and y axes for the maps represent degrees longitude and latitude,
respectively, while those axes for the time–height cross sections represent
the hours before reaching Oliktok Point and altitude (m a.m.s.l.), respectively. The locations of
Utqiaġvik and Oliktok Point are labeled in (a) but
indicated in all panels by the black circles. On land, white indicates snow-covered surfaces while green indicates open land (e.g., tundra). Land data
are missing in southern Alaska and most of Canada.
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The observed increase of warm-temperature INPs at Oliktok Point can be
attributed to air mass transport pathways and timescales over specific
sources. Transport of regional air was quite slow and remained predominantly
near the surface, as evidenced by the 5-day air mass back trajectories shown
in Fig. 6. At the beginning of May, frozen surfaces were prominent across the
entire region, including the areas over which air transported to Oliktok
Point traveled. On 9 May, the marginal ice zone (MIZ) started to develop off
the coast of Oliktok Point as evidenced by the < 100 % sea ice
coverage values in the 4 km data (i.e., areas of exposed open water
indicated by the light purple shading in the Fig. 6b inset). The MIZ may be a
combination of ice floes and/or open leads, but we cannot differentiate these
features using the 4 km data. Onset temperatures for stages A and B started
to increase on 9 May, coincident with the MIZ starting to expose open water.
Starting 16 May, polynyas were observed west of the Canadian Archipelago and
northeast of Oliktok Point, about 700 km away. Air mass trajectories show
low-altitude transport over this region, corresponding to a slight increase
in warm-temperature INPs on that day and the warmest onset temperatures
(Fig. 5a). Due to the distance between Oliktok and the open water, particles
within the size range of stage A likely gravitationally settled during the
5-day transit, yet such sources may still have provided small contributions
of aerosols to the observed enhanced INPs, as evidenced by the warmest onset
temperatures and only slightly elevated INP concentrations as compared to
samples collected before 16 May. Jaenicke (1980) showed that particles within
the size range of stage A have typical atmospheric lifetimes on the order of
minutes to days, particularly when in the boundary layer and near the
surface. Based on the minimum and maximum ambient air temperatures observed
at Oliktok Point on 16 May (-3 and 2 ∘C, respectively) and
altitudes of the trajectories over the polynya northeast of Oliktok Point
(40–90 h before reaching Oliktok Point), basic terminal
settling velocity calculations using on the Navier–Stokes equation indicate
particles within the stage A range would have gravitationally settled within
11 s to 6 h, indicating the polynyas were not the dominant source, and the
MIZ closer to Oliktok Point was more likely the source of the larger INPs.
However, this simple calculation assumes the starting temperature and does
not consider vertical updrafts and downdrafts that may affect particle
lifetime. On 22 May, there was a significant shift in air mass origin: air
reaching Oliktok Point traveled only over the MIZ and not the polynyas to the
northeast (Fig. 6d inset). This shift corresponded to the highest INP
concentrations observed from any sample analyzed. Sources were generally
regional in nature, with locations directly north of Oliktok Point until
26 May, after which they transitioned to originating predominantly south of
Oliktok Point from exposed tundra over the terrestrial North Slope and
interior Alaska. Ambient air temperatures at Oliktok Point starting on 26 May
were relatively warm and fluctuated until 29 May (Fig. 2), indicating air
originating from over warmer surfaces (i.e., darker land versus brighter
ice). Onset temperatures decreased following 26 May and INP concentrations
remained high, but only for colder freezing temperatures (i.e.,
-25 ∘C; Fig. 4a). On 29 May, INP concentrations dropped but were
still higher than March–early May samples, and air masses transitioned to
originating from the northeast. Like 16 May, terminal settling velocity
calculations indicate particles on this day were likely from closer to
Oliktok Point, ranging from 13 s to 7 h.
Recent work by May et al. (2016) has demonstrated that production of sea salt
aerosol in the Arctic can occur under non-stagnant conditions from open leads
(i.e., wind speeds > 4 m s-1). The main mechanisms behind
aerosol production from open ocean surfaces is bubble bursting from
wind-induced wave breaking, although this process is far less studied over
leads. A recent study by Gabric et al. (2018) describes the generation of marine
biogenic aerosols (MBAs) from sea ice leads and the MIZ. Thus, other primary
aerosols – such as bacteria or marine organisms that have been shown to
serve as efficient INPs – may be generated by the same mechanisms that
produce sea salt aerosol and MBA. Recent studies by Wilson et al. (2015) and
Irish et al. (2017) have shown that the Arctic Ocean surface microlayer and
bulk seawater can harbor large concentrations of INPs, indicating physical
mechanisms that generate aerosols from the surface waters may eject these INPs
into the atmosphere. Additionally, several previous High Arctic ice
nucleation studies have demonstrated that leads and other open water sources
are vital in influencing atmospheric INP concentrations (Bigg, 1996; Bigg and
Leck, 2001, 2008; Leck and Bigg, 2005). Based on our source analysis and a
combination of conclusions from these previous studies, we conclude that INPs
from open water features are likely produced via bubble bursting and are
likely composed of bacteria or fragments of marine organisms.
Summary of results from single-particle and bulk compositional
measurements during the late May time period. Relative number fractions of
CCSEM-EDX single-particle types for samples (> 1.15 µm)
for (a) 23 May (1156 particles), (b) 24 May (918
particles), and (c) 28 May (723 particles). SSA represents sea spray
aerosol. Examples of SEM images of the particle types classified are shown in
(d), with the length of the bar scaled to 1 µm. S-XRF
results for May for elements in the 0.75 to 5.0 µm size range
associated with either marine (Cl and non-soil K) or terrestrial (soil K, Al,
Ca, and Fe) sources are shown in (e). Cl and non-soil K
concentrations are provided as × 0.5 and × 5 their
concentrations, respectively, to show on the same axis. (f) Wind
direction is also shown, colored by wind speed. For both CCSEM-EDX and S-XRF
classifications, shades of blue and brown represent marine and terrestrial
sources, respectively.
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Collocated single-particle and bulk chemistry measurements support the
sources of the air masses during the transition period in late May (Fig. 7).
Here, we briefly discuss results from the compositional analyses in support
of the ice nucleation measurements. Analysis of May periods by CCSEM-EDX
identified marine, terrestrial, and combustion influences based on particle
composition and air mass trajectories (Fig. 7a–d). Particle types from
marine (fresh and aged sea spray aerosol – SSA) and terrestrial (dust)
sources comprised the greatest number fractions of supermicron
(> 1.15 µm) aerosol particles for all samples (54 %
and 37 %, respectively). Each May sample demonstrated a large fraction of
marine influence, with nearly 50 % of supermicron particles, by number,
comprised of fresh and aged SSA. The largest marine influence was observed on
23 May when air masses originated from the north over open water, local wind
speeds were low and northerly, and INP concentrations, particularly in the
warm-temperature regime, were elevated compared to samples prior to 22 May.
However, periods with more terrestrial influence were observed, based on
increased number fractions of supermicron dust and southerly winds on 24 May
(Fig. 7e). Additionally, some periods experienced more combustion influence
from local industrial emissions, characterized by relatively greater
fractions of organic aerosol, fly ash, and soot (Gunsch et al., 2017; Kirpes
et al., 2018) observed by CCSEM-EDX on 28 May. The S-XRF data
(0.75–5.0 µm) also demonstrated influences from marine and
terrestrial sources but had the highest marine signature (i.e., from fresh
sea salt indicated by the Cl mass concentrations) during 16–20 May, when local winds
were elevated (∼ 10 m s-1) and originated from the north over
the Beaufort Sea. The S-XRF indicated the highest dust influence was observed
from 25 to 30 May, when episodic southerly winds from over the tundra influenced
Oliktok Point (Fig. 7e). The observed dust could be due to local road dust in
addition to terrestrial dust sources along the air mass back trajectories.
Combined with air mass trajectory analysis, the single-particle and bulk
chemistry support the conclusion that regional mineral and marine sources
largely contributed to the enhanced warm-temperature INP concentrations
during late May. Very little contributions from soot and fly ash were observed
(4 % and 16 % on 23 and 28 May, respectively), indicating local
pollution was not a large source of the particles in general. Additionally,
soot and fly ash can serve as INPs, but only at temperatures much lower than
-15 ∘C (Kanji et al., 2017; Murray et al., 2012). Aside from the
composition, we would not expect pollution sourced from Prudhoe Bay (which
tends to be sub-100 nm) to overlap with the sizes of the INPs observed
(i.e., > 2.96 µm) (Creamean et al., 2018a; Maahn et al.,
2017). Another possible source that has been shown to influence this region
in the spring is long-range transported aerosol. Recent work by Kylling et
al. (2018) demonstrates surface dust impacts from several midlatitude sources
to the entire Arctic is predominant during May. Yet, they also show that the
major source of dust at the surface is from North America north of
60∘ N, indicating regional source influences. Specific to our
region, supermicron mineral dust has been shown to be transported during
Arctic haze as demonstrated by Quinn et al. (2002) at Utqiaġvik, but at
very low mass concentrations relative to other aerosol species. Additionally,
given the size in which we observed the INPs
(> 2.96 µm), it is unlikely such large particles were
transported from very distant sources, especially considering the air mass
transport pathways were near the surface in the boundary layer for several
days prior to arrival at the site. Thus, based on the combination of previous
parallel studies, freezing temperatures, size, single-particle composition,
bulk composition, local meteorology, and air mass transport, we demonstrate
that it is unlikely local pollution largely influenced the INP concentrations
during late May.
Comparison of atmospheric immersion mode INP measurements
presented here with previous studies in the Arctic. Study reference,
location, dates, and average INP concentrations converted to units of per
liter (L-1) reported for up to the four different temperatures
shown. The superscripts “g”, “s”, and “a” represent ground-based, shipborne, and
airborne measurements, respectively. “None” refers to no reported
concentrations (or observed, in the case of the current study) measured at
that temperature.
Max volume
INPs-10
INPs-15
INPs-20
INPs-25
Study
Location
Dates
air (L)
(L-1)
(L-1)
(L-1)
(L-1)
Bigg (1996)
High Arcticg
early 1991
3000
none
1 × 10-2
none
none
Aug–Oct 1991
none
3 × 10-3
none
none
Borys (1989)
Alaska, Canada,
Apr 1986
1400
none
2 × 10-2
none
5 × 10-1
Greenlanda
Conen et al. (2016)
Norwayg
Jul 2015
24 000
6 × 10-4
7 × 10-3
none
none
DeMott et al. (2015)
Bering Seas
Summer 2012
13 500
none
3 × 10-3
3 × 10-2
none
Fountain and
Alaskag
Aug 1978–Apr 1979
250
none
none
1 × 10-1
none
Ohtake (1985)
Mason et al. (2016)
Canadag
Mar–Jul 2014
32 400∗
none
5 × 10-2
2 × 10-1
1
Prenni et al. (2009)
Alaskaa
Oct 2004
n/a∗∗
2 × 10-1
none
4 × 10-1
none
Radke et al. (1976)
Alaskaa
Mar 1970
3000
none
none
2 × 10-2
none
This study (2018)
Alaskag
Mar–May 2017
38 428
8 × 10-4
5 × 10-3
2 × 10-2
4 × 10-2
Mar 2017
none
7 × 10-4
6 × 10-3
3 × 10-2
Apr 2017
7 × 10-5
2 × 10-3
1 × 10-2
7 × 10-2
May 2017
1 × 10-3
8 × 10-3
2 × 10-2
4 × 10-2
late May 2017
2 × 10-3
1 × 10-2
3 × 10-2
4 × 10-2
n/a = not applicable.
∗ Not directly
provided by citation. Estimated from average total volume of air per sample
and standard flow rate specification for the sampler.
∗∗ Immersion freezing assumed to be dominant mode of INP
concentrations measured via an online continuous flow diffusion chamber.
Comparison to other Arctic INP measurements
Immersion mode INP measurements in the Arctic are rare, but here we provide a
synopsis of previous measurements in comparison to ours. Table 2 shows
ground-based, shipborne, and airborne studies dating back to 1976 in
locations throughout the Arctic during various seasons. We excluded a review
of diffusional chamber INP measurements, as these instruments predominantly
measure deposition mode INPs and are thus not directly comparable to our
results (Kanji et al., 2017; Cziczo et al., 2017). While the objective of
this comparison is to determine whether our measurements align with previous
immersion mode INP observations, a detailed review of Arctic INPs is outside
the scope of this paper.
Overall, our concentrations at selected temperatures were within range of
with those previously reported (Bigg, 1996; Borys, 1989; Conen et al., 2016;
Mason et al., 2016; Fountain and Ohtake, 1985; Radke et al., 1976; Prenni et
al., 2009), even though there are
likely dependencies on time of year and location and
several orders of magnitude of apparent spread.
Figure 8 shows the range of our results in comparison with those in Table 2.
In general, our INP concentrations agree with or are on the lower end of
those previously reported in the spring. One explanation could be that due to
the proximity to the Prudhoe Bay oilfield, we are sampling in a location that
is more polluted at the ground than those previously used to document Arctic
haze (Borys, 1989; Mason et al., 2016; Radke et al., 1976). Additionally,
Borys (1989) and Radke et al. (1976) measured via airborne platforms, in
which they predominantly measured long-range transported Arctic haze as
compared to Arctic boundary layer aerosols. Other sources of variation in the
results could be the result of discrepancies in the sample volumes and drop
sizes used under different DFA techniques (Vali, 1971; Mossop and Thorndike,
1966). Also, unlike some of the studies presented in Table 2 and Fig. 8, we
collected substantial volumes of air per sample to enable measurement of the
rare warm-temperature INPs (38 428 L in the present study versus
250–32 400 L). Despite these differences, our concentrations are
consistent with Bigg (1996), Conen et al. (2016), and DeMott et al. (2016),
with those studies conducted during summer or fall. Those previous studies
were apportioned to either marine or terrestrial sources, resulting in an
analogous set of studies to our current effort. Overall, our measured INP
concentrations are comparable to those previously conducted in a similar
fashion in the Arctic and predominantly fall within the overall global
picture of INPs presented by Kanji et al. (2017) and Petters and
Wright (2015).
Summary of ranges of atmospheric immersion mode INP concentrations
from the current study and those previously reported in the Arctic. Study
details can be found in Table 2. For the current study, “all” and “case”
correspond to samples from the entire INPOP study and to the 22–29 May time
period, respectively. Additionally, the bars and whiskers represent the range
between the minimum and maximum INP concentrations at the four temperatures
in Table 2 per study. Measurements are colored to the season in which they
are predominantly collected. The dashed line separates results from
the current study from those presented in previous works.
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Summary and broader implications
We present the first INP measurements in an Arctic oilfield location and
demonstrate how local and regional transport from marine and terrestrial
sources to an industrial region can introduce high concentrations of coarse,
warm-temperature INPs that are possibly of biological origin. Three time- and
size-resolved aerosol impactors were deployed from 1 March to 31 May 2017 for
offline ice nucleation and chemical analyses and were co-located with routine
measurements of aerosol number, size, chemistry, and radiative properties.
The largest particles (i.e., ≥ 3 µm or “coarse mode”) were
the most efficient INPs. During periods with snow- and ice-covered surfaces,
coarse mode INP concentrations were very low (maximum of
6 × 10-4 L-1 at -15 ∘C), but higher
concentrations of warm-temperature INPs were observed during late May
(maximum of 2 × 10-2 L-1 at -15 ∘C). These
higher concentrations are attributed to air masses originating from over open
Arctic Ocean water and tundra surfaces and were likely primary marine
aerosols and dust, respectively. In general, our concentrations agree with
similar immersion mode ice nucleation evaluations at other Arctic locations,
even though such studies vary in terms of location, volume of air per sample,
drop freezing technique, and time of year.
Although our measurements were conducted at the ground level, such particles
could influence Arctic MPC (AMPC) formation under conditions where the cloud
is coupled to the surface by a well-mixed boundary layer. Previous long-term
studies have evaluated the annual cycle of AMPC properties and, relevant for
our measurements, have concluded that, climatologically, a large number of
AMPCs occur over the North Slope of Alaska in May (up to 84 %–90 % cloud
fraction), with cloud bases over the North Slope reaching down below
500–700 m (Shupe, 2011; Shupe et al., 2010; Dong et al., 2010).
Specifically, the AMPC fraction is at a maximum in the fall, followed by the
spring, with the lowest cloud bases occurring over the Arctic Ocean (Shupe et
al., 2005, 2006; Shupe, 2011). Combined, these studies indicate that INPs
from surface sources may be important for such low, persistent clouds.
Further, average cloud temperatures in the Arctic have been shown to be
relatively warm in the spring and into the summer (up to -10 ∘C on
average) (de Boer et al., 2009; Shupe, 2011), indicating that biological INPs
from Arctic sources are relevant to AMPC conditions typical for this time of
year.
We have demonstrated that the spring to summer transition on the North Slope
and beyond can have implications for a shift in INP properties, potentially
impacting cloud phase, precipitation amounts, and cloud lifetime. Given
significant shifts in broadband radiation regimes starting in March,
manifesting in a sign change in cloud radiative forcing (CRF) from winter and
spring months to summer (Dong et al., 2010), understanding aerosol–cloud
interactions is crucial during this time of year. Additionally, with
increasing likelihood of earlier melting of frozen surfaces in the Arctic in
the coming decades (Markus et al., 2009; Stroeve et al., 2014; Screen and
Simmonds, 2010), the influence of INP on CRF may be shifting in season along
with the sign of CRF, with the latter resulting from a complex mix of
shifting atmospheric temperatures and surface albedos. Understanding the role
of INPs in modulating CRF is important as this forcing can act as a positive
or negative feedback on the acceleration of surface melt, and the timing of
such melt can potentially lead to impacts on a variety of features,
midlatitude weather, and climate (Cohen et al., 2018). Together, these items
demonstrate a strong need to continue to improve understanding of
high-latitude INPs, with additional INP concentration and characterization
measurements required to confirm the findings presented here and evaluate
this cycle beyond spring months.