Ice-nucleating particles (INPs) affect cloud development,
lifetime, and radiative properties, hence it is important to know the
abundance of INPs throughout the atmosphere. A critical factor in
determining the lifetime and transport of INPs is their size; however very
little size-resolved atmospheric INP concentration information exists. Here
we present the development and application of a radio-controlled payload
capable of collecting size-resolved aerosol from a tethered balloon for the
primary purpose of offline INP analysis. This payload, known as the SHARK
(Selective Height Aerosol Research Kit), consists of two complementary
cascade impactors for aerosol size-segregation from 0.25 to 10 µm,
with an after-filter and top stage to collect particles below and above this
range at flow rates of up to 100 L min-1. The SHARK also contains an
optical particle counter to quantify aerosol size distribution between 0.38
and 10 µm, and a radiosonde for the measurement of temperature,
pressure, GPS altitude, and relative humidity. This is all housed within a
weatherproof box, can be run from batteries for up to 11 h, and has a total
weight of 9 kg. The radio control and live data link with the radiosonde
allow the user to start and stop sampling depending on meteorological
conditions and height, which can, for example, allow the user to avoid
sampling in very humid or cloudy air, even when the SHARK is out of sight.
While the collected aerosol could, in principle, be studied with an array of
analytical techniques, this study demonstrates that the collected aerosol
can be analysed with an offline droplet freezing instrument to determine
size-resolved INP concentrations, activated fractions, and active site
densities, producing similar results to those obtained using a standard
PM10 aerosol sampler when summed over the appropriate size range.
Test data, where the SHARK was sampling near ground level or suspended from
a tethered balloon at 20 m altitude, are presented from four contrasting
locations having very different size-resolved INP spectra: Hyytiälä
(southern Finland), Leeds (northern England), Longyearbyen (Svalbard), and
Cardington (southern England).
Introduction
Atmospheric ice-nucleating particles (INPs) are not well understood, with
knowledge of their concentration, sources, temporal variability, transport,
and size in its infancy
(Kanji
et al., 2017; Murray et al., 2012). This is of importance because clouds
between 0 and around -35∘C can exist in a
supercooled liquid, mixed-phase (ice and water), or glaciated (ice only)
state depending in part on the presence or absence of INPs
(Kanitz et al., 2011; Vergara-Temprado
et al., 2018). In the absence of INPs, cloud droplets can supercool to below
∼-35∘C (Herbert et al., 2015),
but INPs can trigger freezing at much higher temperatures
(Kanji et al., 2017). These particles
usually have concentrations that are orders of magnitude smaller than cloud
condensation nuclei (CCN) and have a disproportionate impact on clouds
because the nucleated ice crystals grow rapidly and precipitate out
(Lohmann, 2017; Murray, 2017). In
a shallow cloud, heterogeneous ice nucleation can result in dramatic
reductions in cloud albedo by removal of supercooled liquid water
(Storelvmo, 2017; Vergara-Temprado
et al., 2018), whereas in deep convective clouds it can influence a web of
microphysical processes in a complex way
(Deng et
al., 2018; Kanji et al., 2017; Rosenfeld et al., 2011). Hence, a greater
understanding of INP lifetime, transport, and distribution in the vertical
profile is needed in order to better understand and model cloud processes
and their response to a changing climate.
The size of an aerosol particle significantly affects its lifetime and
therefore transport in the atmosphere, with particles of a few hundred
nanometres potentially having a lifetime of weeks, whereas particles of 10 µm have a lifetime of only hours (Jaenicke, 2007). While
composition is recognized to be an important controller of ice nucleation
ability (Kanji et al., 2017), it has also
been generally thought that the larger an aerosol particle, the more likely
it is to serve as an INP (Pruppacher and
Klett, 1997). However, the lifetime of coarse-mode aerosol particles
decreases rapidly with increasing size. Consistent with larger particles
being better ice nucleators, parameterizations of INPs in the atmosphere
have been proposed wherein the INP concentration is related to the
concentration of aerosol particles larger than 0.5 µm
(DeMott
et al., 2010, 2015; Tobo et al., 2013). However, most atmospheric
measurements of INPs report the sum of INPs below some threshold size set by
an inlet or size cut, specified by the aerosol sampler used. For instance,
DeMott et al. (2017) provides a
comparison between a selection of instruments for the collection and
subsequent INP analysis of aerosol, where the aerosol samplers either have a
defined size cut-off or have collection efficiencies that decrease in
magnitude above a defined size. Nevertheless, there are examples of field
studies in which INPs have been size resolved
(Berezinski
et al., 1988; Creamean et al., 2018b; Huffman et al., 2013; Mason et al.,
2016; Reicher et al., 2018; Santachiara et al., 2010; Si et al., 2018; Welti
et al., 2009). These studies generally show that while the fine-mode aerosol
particles are more abundant, coarse-mode aerosol particles often contribute
more to the INP population. In addition, the activated fraction (nn) of
coarse-mode aerosol is usually greater than fine-mode aerosol. However, in
some field studies
(Mason et
al., 2016; Si et al., 2018), fine aerosol sometimes contributes more to the
INP population than the coarse mode. Therefore, there is a need to determine
INP sizes when quantifying atmospheric INP concentrations, as size is
important for transport and lifetime and is therefore required to accurately
model global INP populations.
Measurements of INPs in and above the boundary layer are crucial to
understanding the contribution of local sources to the ice-nucleating
activity in clouds, compared to transported aerosol. Aircraft measurements
(e.g.
Price et al., 2018; Rogers et al., 2001) and mountaintop observatories
(e.g. Conen et al.,
2015) have been used to quantify INP populations above the boundary layer.
For example, it has been shown that there are differences in the INP
concentrations measured when in and out of the boundary layer at the High
Altitude Research Station Jungfraujoch (Switzerland)
(Conen
et al., 2015; Lacher et al., 2018). While these measurements are undoubtedly
useful, mountaintop measurements are only possible in locations with
sufficiently tall yet accessible mountains, and aircraft sampling is
expensive and not necessarily possible in remote regions. It is therefore
essential that instrumentation is available that can be used to sample
aerosol at selected altitudes (including ground level) in order to determine
INP concentrations throughout the vertical profile. Unmanned aerial vehicles
(UAVs) are becoming more widely used in atmospheric science; these allow the
collection of aerosol at altitude at significantly lower cost than with
manned aircraft but are limited by relatively short battery lives, usually
under 1 h, and potential propeller interference
(Jacob et al., 2018;
Villa et al., 2016).
Tethered kite and balloon systems have historically been used to make
atmospheric measurements and collect aerosol samples with much longer
sampling times (many hours are readily achievable) at altitudes up to 2
and 5 km for tethered balloons and kites, respectively
(Armstrong et al., 1981; Balsley et al., 1998).
An advantage of a balloon or kite system is that an instrument can be held
at a chosen altitude for many hours without the balloon interfering with
measurements, as the instrument can be suspended on a line many metres below
the balloon. They can also stay inflated and in use for periods of many
weeks, making them ideal for longer campaigns in remote environments. A new
instrument called the Honing On VERtical Cloud and Aerosol properTies
(HOVERCAT) (Creamean et
al., 2018a) provides the capability to sample aerosol for subsequent INP
analysis on a tethered balloon or UAV, allowing both variable altitudes and
static collection of non-size-resolved aerosol smaller than 10 µm at
1.2 L min-1. In the past, aerosols have been size segregated using
cascade impactors on a tethered balloon system
(Hara et al.,
2013; Reagan et al., 1984), but balloon-borne cascade impactor systems have
not yet been adapted for the purpose of size-resolved INP analysis. The
downsides of balloon-based platforms include the need for wind speeds below
around 64.4 km h-1 to avoid damage to the balloon and the possibility
of “icing” of the balloon and lines when deployed in a cold and humid
environment, which could add to the weight of the payload and cause the
system to sink or fall slowly. Nevertheless, balloon- and kite-borne
measurements remain a valuable way to obtain continuous, high-resolution
measurements over a period of many hours in a single location at a range of
altitudes.
The SHARK. (a) The SHARK payload on a tethered balloon connected
to ground by a winch. The photograph was taken during deployment in the High
Arctic. (b) The components inside the SHARK payload labelled on a
photograph. The payload featured a large impactor inlet at the top of the
platform for Impactor 2, with the OPC inlet facing the front, and a small
impactor inlet at the bottom for Impactor 1. The radiosonde was at the bottom
of the box, and the outlet valve for the pump system is shown at the back of
the SHARK, where the 100 L min-1 pump for Impactor 2 vents.
In this paper, the design, testing, and operation of a payload named the
Selective Height Aerosol Research Kit (SHARK) is presented. It consists of
two separate cascade impactor systems, operating at 9 and 100 L min-1,
for the size sorting of ambient aerosol particles from 0.25 to 10 µm,
with an after-filter and top stage to collect particles below and above this
range for offline INP (or other) analysis. The SHARK also features an
optical particle counter (OPC) and a radiosonde, which provides real-time
measurements of relative humidity (RH), temperature, global positioning
system (GPS) altitude, and pressure. Weighing 9 kg, the payload is suitable
for use with a 21 m3 or larger tethered balloon such as in
Fig. 1a where the SHARK is shown in flight. The
use of a tethered balloon and a high-capacity battery allow aerosol to be
collected for up to 11 h at a user-selected altitude.
The design and development of the SHARKInstrument description
The SHARK, shown in Fig. 1, comprises two cascade
impactors and corresponding pumps, alongside an OPC (OPC-N2, Alphasense, UK)
and radiosonde (S1H2-R, Windsond, Sweden), all mounted within a weatherproof
enclosure with a tail fin to orient it into the wind. A photograph of the
internal components of the SHARK are shown in Fig. 1b. The two cascade impactors were employed to collect particles across
different size bins: Impactor 1 from 0.25 to 2.5 µm and Impactor 2 from
1 to 10 µm. Impactor 1 is a cascade impactor (U.S. patent no. 6786105,
Sioutas, SKC Ltd., UK), which requires a flow rate of 9 L min-1 and operates
with a portable pump (Leland Legacy, SKC Ltd., UK). Impactor 2 is also a cascade
impactor (MSP Model 128, TSI, USA), which requires a flow rate of 100 L min-1 at a pressure drop of 0.6 kPa
(Marple et
al., 1991; Misra et al., 2002), and for which a radial flow impeller (Radial
Blower U51, Micronel, UK) was used in reverse as a lightweight pump
(∼120 g). These pumps maintain the volumetric flow rate
through the impactors as temperature and atmospheric pressure change with
altitude. The pump for Impactor 1 was calibrated to apply this adjustment to
at least 2.3 km (SKC, 2020), although the presence of the after-filter may reduce the
battery life at this altitude. The pump for Impactor 2 is supplied by a
larger battery and should be able to maintain flow to at least the same
altitude as the Impactor 1 pump and over a longer period of time. The SHARK
records the volume of air sampled through Impactor 1 during the flight, and
so if the pump battery was depleted or the pressure drop became too great
before Impactor 2 had finished sampling, the Impactor 1 pump would shut down
and store the recorded value for later analysis. Further testing of the
SHARK would be required to define a maximum altitude limit that each SHARK
component could operate at. In order to provide RH, temperature, GPS
altitude, and pressure data in real time, the sensors and transmitter from a
radiosonde were integrated into the system. The OPC measured aerosol size
distributions, which were saved in the onboard memory. Servo-controlled
caps covered the sample inlets and outlets to reduce contamination during
ascent and descent, as well as to protect the components from cloud water.
The operation of the SHARK components was controlled remotely via a radio
link using an Arduino microcontroller board (16 km range); once the SHARK
was at the desired altitude according to the constantly transmitting
radiosonde, the inlet caps opened 10 s prior to the pumps and OPC starting
in order to initiate aerosol sampling and monitoring. The payload
components, including the servo inlet covers and Arduino control boards,
were powered by a 5000 mAh battery (4S 14.8 V LiPo, Overlander, UK). The
components were assembled into the SHARK payload with the static (i.e. no
wind) weight budget of 10 kg for a 21 m3 balloon (Skyhook
Helikite, Allsopp Helikites Ltd., UK) in mind; hence the SHARK weighs 9 kg
when fully instrumented.
The cascade impactors allow for the collection of size-segregated aerosol
(further details are provided in Sect. 2.2) onto thin films (0.25 mm
thickness) for subsequent offline analysis, which can be used alongside
information about the aerosol size distributions obtained via the OPC and
atmospheric conditions from the radiosonde. Our initial focus concerns the
analysis of the ice-nucleating properties of the collected aerosol, but an
array of analytical techniques could be applied to characterize the
size-selected aerosol, including mass spectrometry, DNA analysis, scanning
electron microscopy (SEM), and transmission electron microscopy (TEM)
(Ault and Axson,
2017; Garcia et al., 2012; Huffman et al., 2013; Laskin et al., 2018).
Size-segregated collection of aerosol
Two separate cascade impactors were installed, each operating over different
size ranges. This enabled size-resolved aerosol sampling onto substrates
across both the fine and coarse modes at high flow rates, while keeping
power consumption low enough to be run from batteries. Single impactor
systems designed to operate across the accumulation and coarse modes
simultaneously require a relatively large pressure drop that would typically
require a prohibitively large (and heavy) pump and battery for this
application.
Impactor 1 sorts aerosol into five size categories: < 0.25 µm
(this size bin is defined by the impactor after-filter and is hereafter
referred to as 1a), 0.25–0.5 µm (from stage 1b), 0.5–1.0 µm
(from stage 1c), 1.0–2.5 µm (from stage 1d), and > 2.5 µm (from stage 1e). The size categories b to e correspond to the
impactor stages where the 50 % collection cut-off diameter (d50) is the
lower bound of each bin. The size bins and collection efficiencies for each
impactor were digitized from data provided by the manufacturers,
(Misra et al.,
2002; Product Information Sheet – MSP, 2019) and are shown in
Fig. 2. Several collection substrates were tested
by Misra et al. (2002), and
the dataset from the Teflon substrates was chosen to represent Impactor 1
here as that substrate most closely resembled those used in this study. For
Impactor 1, the particles were collected on 25 mm diameter filters of pore
size 0.05 µm (Nuclepore track-etched membrane polycarbonate filters,
Whatman, UK). Filters were used as impactor substrates rather than films
since they have very low background contamination and are easier to obtain.
Size category 1a corresponds to an after-filter situated after Impactor 1,
which comprised a 47 mm diameter polycarbonate filter with a pore size of 5 µm (Nuclepore track-etched membrane) to maintain the flow rate. The
collection efficiency of the after-filter was estimated to be 50 %–100 % at
0.25 µm and below
(Soo et al., 2016).
Impactor 2 collected aerosol particles into three size categories: 1.0–2.5 (2d), 2.5–10 (2e), and > 10 µm (2f), also
illustrated in Fig. 2. The 75 mm diameter filters of
pore size 0.05 µm (Nuclepore track-etched membrane polycarbonate
filters) were used in Impactor 2. An after-filter could not be used with
this impactor since its inclusion increased the required pressure drop to
beyond what the pump could supply at 100 L min-1.
Collection efficiencies of each size bin of the two cascade
impactors in the SHARK. (a) The size bins for each stage of Impactor 1 and 2
at flow rates of 9 and 100 L min-1, respectively. (b) Impactor
efficiency curves for each stage. Impactor 1 has four stages (1b–e) and one
after-filter (1a), while Impactor 2 has three stages (2d–f). Stages 1d and 2d as
well as 1e and 2e should be approximately equivalent in terms of the aerosol
size ranges collected.
A further benefit of using these two impactors in tandem is that, in the
size ranges where they overlap of 1.0–2.5 (stage d) and 2.5–10 µm (stage e), the impaction efficiencies are very similar, allowing a
direct comparison between the two impactors in this size range. The stages
are labelled a through f for the smallest to largest impactor stage sizes
(including the after-filter), such that 1d and 2d refer to stage d (1.0–2.5 µm) on Impactors 1 and 2, respectively (see
Fig. 2). Background runs were produced by placing
the substrates in the SHARK as if setting up to sample, before removing and
analysing them as normal to determine the contamination introduced through
the installation and recovery of the substrates.
Particle bounce, the bouncing of particles off the impaction substrate and
the collection of these particles on the lower stages, has previously been
identified as a factor that can cause biases when aerosol is collected by
cascade impactors (Cheng and Yeh, 1979;
Dzubay et al., 1976). The collection efficiency curves shown in
Fig. 2 for Impactor 1 already account for some
degree of particle bounce, having been determined experimentally by
Misra et al. (2002) using
monodispersed polymer particles on a variety of substrates. However, the
efficiency curves for Impactor 2 are based on theoretical predictions
(Rader and Marple, 1985) and so do not account for any
bounce effects. Since two of the stages of Impactors 1 and 2 overlap (stages
d and e), it is possible to comment on the possible effects, or lack thereof,
of particle bounce, based on the results obtained using each of the
comparable stages. This is briefly addressed in Sect. 3.4 where we show good agreement between these two
impactors.
SHARK sampling efficiencies. (a) The sampling efficiencies of
Impactor 1, with and without wind, when sampling at 90∘ to the
wind direction. (b) The sampling efficiencies of Impactor 2, with and
without wind, when sampling at 90∘ to the wind direction. (c) The
sampling efficiency of the OPC, with and without wind, when sampling at
0 and 90∘ to the wind direction (the OPC was deployed
at 0∘ to the wind, based on this calculation). Solid lines denote
model predictions within the validity range of the formulas, and dotted lines
represent approximations (Von Der Weiden et al.,
2009).
Size distribution measurements
The OPC produced binned particle size distributions from 0.38 to 17 µm
every 1.38 s at a typical flow rate of 1.2 L min-1. The OPC was
remotely operated through the use of its serial link via an Arduino
microcontroller board. Particle size, surface area, and mass concentration
data were produced from the raw OPC data, and these were then used to calculate
the fraction of the aerosol that acts as an INP – activated fraction,
nn(T) – and to weight the INP data to particle surface area, generating
the ice-active site density per surface area, ns(T), of aerosol. The
particle density used was 1.65 g cm-3, as assumed by the OPC software,
and they were assumed to be spherical. No correction was made for the
hygroscopic growth of aerosol particles as this required assumptions about
the chemical nature of the particles, and hygroscopic growth effects were
minimized by avoiding sampling when the RH was above about 80 % (see next
section).
Radiosonde data
Utilizing the radio control built into the payload, real-time data informed
decisions of when to turn the pumps on and off to sample. Continuous
monitoring of the radiosonde data allows the user to avoid sampling under
conditions where RH approached 100 %, at which point aerosol particles
become excessively swollen with water or activated to cloud droplets. Hence,
the influence of hygroscopic growth or cloud droplets on the collected
aerosol could be minimized. The temperature and pressure measurements
allowed the volume of air sampled by the impactors and OPC to be corrected
to standard conditions (1 atm at 0 ∘C).
Housing and instrument orientation
The weatherproof housing consisted of an acrylonitrile butadiene styrene
(ABS) polymer box with dimensions of 560mm×380mm×180mm (IP67, Fibox).
Holes to mount the impactors and OPCs were drilled so that Impactor 2 sat
vertically upright, and Impactor 1 was oriented 180∘ to Impactor 2
so that it faced downwards, ensuring that both impactors were always
oriented 90∘ to the wind. The OPC was at 90∘ to both
impactors and facing towards the front of the box, into the wind (see
Fig. 3a–c). See Sect. 2.6 for the rationale of
the positioning of the OPC and impactor inlets. The tail fin, which is
mounted to the lid of the box, was designed to keep the SHARK orientated
into the wind and was fabricated from rigid polyvinyl chloride (PVC) sheet.
Impactor 1 had its own mounting screws by which it was attached to the box,
whilst for Impactor 2 a custom mount was built. Securing ropes were threaded
through reinforced holes in the box and connected via a carabiner for quick
and easy attachment to the balloon instrument line, as seen in
Fig. 1a. Modular foam was used to keep all
components in place during flight.
Inlet sampling efficiencies via particle loss modelling
Calculation of the particle losses associated with the instrument inlets due
to excessive wind speeds in various configurations were used to inform the
design of the SHARK and to minimize sampling biases in higher wind
conditions. The calculations were done using an open-source particle loss
calculator program in Igor Pro, the details and assumptions for which are
presented in Von Der Weiden et al. (2009). The
particle loss characteristics of the impactor and OPC inlets at their
required flow rates were calculated for a wind speed of 0 and 24 km h-1, the latter used as a maximum representative wind speed for
operation. The wind speeds required for optimum performance are < 8 km h-1 for the impactors and OPC, but the system may experience higher
wind speeds. Hence, we use this modelling to guide our choice of positioning
of the instrument relative to wind direction in order to minimize sampling
biases at the inlets. The modelling also allows us to better understand
which impactor stages (and OPC size bins) will be most affected by such
biases. We make no attempt to correct the measurements for sampling biases,
since this correction itself would carry substantial uncertainty but used
the calculations to inform us of the best configuration for the various
inlets.
The inlet sampling efficiencies in the orientations chosen for the final
design of the SHARK are shown in Fig. 3. It is
important to note that, due to their dissimilar inlet dimensions and
operational flow rates, Impactors 1 and 2 are affected differently by the
wind. The particle losses for the largest stages of each impactor are the
most affected. Stages a to d on both impactors are only minimally affected by
losses. The losses are more significant in stage e on both impactors, but
the losses on 1e are greater than on 2e with a 50 % cut-off at around 5.5 µm and a negligible sampling efficiency above about 8 µm on
1e. These calculations also demonstrate that the losses are wind-speed-dependent but that in situations where there is significant wind, the
results from Impactor 2 will be less influenced by losses than Impactor 1 at
sizes above 2.5 µm.
The OPC suffers up to 1.6 times oversampling for 10 µm particles when
sampling into 24 km h-1 wind, but when oriented at 90∘ to the
wind the collection efficiency of > 6 µm particles
approaches 0 % (see Fig. 3c). Therefore, the
OPC has been positioned in the SHARK to be oriented into the wind to ensure
data are collected for the whole size range, with the caveat of a
sub-isokinetic oversampling of larger particles.
Results and discussion
The SHARK has been deployed at ground level and on a tethered balloon during
development and testing at four locations for the collection and monitoring
of aerosol: Cardington (UK), Hyytiälä (Finland), Leeds (UK), and
Longyearbyen (Svalbard). Details of the sampling locations, periods, and
instrumentation can be found in Table S1 of the Supplement. In this section, we present the results for this set of four SHARK
deployments to illustrate the capabilities of the SHARK for quantifying
ice-nucleating particle spectra as well as demonstrating that the technique
is consistent with more established methods.
Windsond and optical particle counter (OPC) data for a flight
during a campaign to the High Arctic. (a) The altitude of the SHARK payload
throughout the 4.5 h flight. The sampling start and end times are
indicated as solid lines. The SHARK reached 450 m a.m.s.l.
and in the last hour of flight was lowered to 350 m due to ice formation on
the balloon, instrument, and tether. (b) The humidity during the flight was
monitored to ensure the SHARK was not sampling during unfavourable
conditions. The SHARK was brought back down to ground level once the
sampling had been stopped. (c) The ambient temperature was monitored
alongside the dewpoint temperature. (d) Total particle counts throughout the
sampling period, as monitored by the OPC.
Meteorological and aerosol size distribution data from a SHARK flight
An example of the radiosonde and OPC data that were collected during a SHARK
flight are shown in Fig. 4. The data were from a
sampling event in the High Arctic in the summer of 2018, during which the
meteorological data from the radiosonde and aerosol particle data from the
OPC were collected alongside impactor films for INP analysis (the INP
results will be published elsewhere). Throughout the 4.5 h flight the
altitude, humidity, and temperature were closely monitored to inform
decisions on sampling. The sampling start and end times are indicated as
solid lines in Fig. 4. The SHARK reached 450 m a.m.s.l.
and in the last hour of flight lowered to 350 m
due to ice formation on the balloon, instrument, and tether. The RH during
the flight was monitored to ensure the SHARK did not sample in humidity
approaching saturation; the impactor and OPC manufacturers' specified
threshold for the components is 95 % RH, but we aim to only sample with
the RH below this value (∼80 %) in order to reduce the
influence of hygroscopic growth on aerosol size. After sampling was stopped,
the SHARK was brought down to ground level, resulting in the humidity
rising. The ability to stop the sampling during the flight meant the
impactors were covered, and the pumps turned off during the descent and so
did not sample the more humid environment. The ambient temperature was
monitored alongside the dewpoint temperature to follow the surface
inversions. The temperature inversion was used to determine where to
stabilize the SHARK and begin sampling, as sampling was desired above the
surface inversion for this run.
Size distribution data produced from OPC measurements. (a) Particle
number, (b) particle surface area, and (c) particle mass size distribution
data above the surface temperature inversion during a test run of the SHARK
suite whilst deployed on a tethered balloon in the High Arctic. Comparisons
to previous studies at Arctic sites are shown
(Freud
et al., 2017; Hegg et al., 1996; Seinfeld and Pandis, 2016). The August
aerosol number size distributions for all listed sites in Freud et al. (2017)
including Zeppelin, Nord, Alert, Barrow, and Tiksi are shown. The data from
Hegg et al. (1996) at altitudes of 0.7 and 0.4 km in Prudhoe Bay, Alaska, are
presented. The size distributions from Seinfeld and Pandis (2016) are calculated
given the parameters for multimode distributions given in their Table 8.3.
The total particle counts per 1.38 s interval from the OPC are shown in
Fig. 4d. Processing of the OPC data yielded the
results shown in Fig. 5 for the particle number
(dN/dlogDp), particle surface area (dS/dlogDp), and particle mass
(dM/dlogDp) size distribution data for the sampling period, where
Dp is the particle diameter. We present this data to demonstrate
that the OPC produces reasonable data when used facing into wind while
suspended from a balloon at altitude. Unfortunately, there is no direct
comparison with other aerosol size distribution measurements at the sampling
location. While the particle number concentration decreases roughly linearly
with size, the surface and mass concentration curves have a mode at around 4 µm in Fig. 5b and c. This is consistent
with previous studies conducted within the boundary layer in the Arctic
(Freud
et al., 2017; Hegg et al., 1996; Seinfeld and Pandis, 2016).
The sum of INP concentrations, [INP]T, for labelled stages
measured at (a) Cardington (UK) and (b) Hyytiälä (Finland)
alongside data from a standard sampler. Cardington data were taken from
Impactor 2 whilst on a tethered balloon at 20 m above ground level and are
shown against a PM10 sampler at ground level. Hyytiälä data were
collected using Impactor 1 at ground level, alongside a PM2.5 sampler.
The dotted lines indicate the sum of the INP concentrations for the SHARK
impactor stages, calculated by weighting fice(T) to the volume of sampled
air and summing the concentrations in each temperature bin.
Deriving size-resolved INP concentrations from the SHARK samples
The ability to measure INP concentrations and properties using samples
collected via the SHARK was tested by performing immersion mode droplet
freezing assays on the sampled aerosols. Following a flight, impactor films
were removed from both cascade impactors of the SHARK, then each immersed in
5 mL of water and mixed on a vortex mixer for 5 min to wash the collected
particles into suspension (O'Sullivan et al., 2018). This suspension was
then analysed via a droplet freezing assay using the microlitre Nucleation
by Immersed Particle Instrument (µL-NIPI)
(Whale et al., 2015), in which 40–50 droplets of
1 µL volume were pipetted onto a hydrophobic glass slide atop a cold
plate. A Perspex shield was placed over the cold stage and N2 gas
introduced to purge the chamber of moisture as the cold plate was cooled to
-40∘C at 1 ∘C min-1. The temperatures at which
droplets froze were recorded using video analysis until the entire
population had frozen. This allowed the fraction of droplets frozen as a
function of temperature, fice(T), to be calculated
(O'Sullivan et al.,
2018; Whale et al., 2015) using the equation fice(T)=Nf/Nt, where Nf is the number of frozen droplets at
temperature T, and Nt is the total number of droplets. The INP
concentration per volume of sampled air as a function of temperature,
[INP]T, was then calculated for each film using fice(T),
according to Eq. (1) adapted from (Vali, 1971) to
include weighting to the volume of air sampled:
[INP]T=-ln(1-fice(T))Vdroplet⋅VwashVair,
where Vdroplet is the droplet volume (i.e. 1 µL), Vwash is the
amount of water into which the filter is immersed to produce the suspension
for analysis (i.e. 5 mL), and Vair is the volume of air sampled.
Testing the SHARK INP concentrations against a standard aerosol sampler
In order to test whether the SHARK impactors were sampling in a
representative manner, the SHARK was run concurrently with a filter-based
particle sampler (BGI PQ100, Mesa Labs) and which is used as an EPA Federal
Reference Method for PM10 (designation no. RFPS-1298-124). This sampler
was equipped with a PM10 head and an optional cyclone impactor which
provided a size cut at 2.5 µm. Aerosol was collected onto 0.4 µm pore size Nuclepore track-etched membrane polycarbonate filters at a flow
rate of 16.7 L min-1 (i.e. 1 m3 h-1). This type of filter
collects particles across the full range of available aerosol sizes, even at
sizes smaller than the pore diameter, with high collection efficiencies
(Lindsley, 2016;
Soo et al., 2016). These polycarbonate filters have also been successfully
employed in other ice nucleation field measurements
(DeMott
et al., 2016; Harrison et al., 2018; Huffman et al., 2013; McCluskey et al.,
2016; Reicher et al., 2019; Tarn et al., 2018). These substrates are known
to have a low ice-nucleating ability and allow the collected particles to be
released into suspension for subsequent INP analysis
(O'Sullivan et al., 2018). The filters were
analysed using the µL-NIPI in the same manner as for the impactor films
collected using the SHARK. The PQ100 filter sampler was deployed alongside
the SHARK in Cardington (UK) and in Hyytiälä (Finland).
In order to compare the SHARK-derived, size-resolved INP data with the
results of the PM10 or PM2.5 PQ100 filter sampler, the INP
concentrations determined across the appropriate SHARK size categories were
summed. In Fig. 6a, data are presented from
Cardington, where the sum of 2d and 2e from SHARK is compared with the filter
sampler fitted with a PM10 head (Impactor 1 was not available during
this test). The SHARK was suspended from a tethered balloon roughly 20 m
from the ground, whereas the filter sampler was on the ground (inlet
∼150 cm above the surface), where both samplers were within
the well-mixed boundary layer. The agreement is very good apart from two
highest temperature points from the filter sampler, but note that the
Poisson uncertainties for these points are substantial and also that the two
samplers were separated vertically by 20 m.
We then show data from Hyytiälä in Fig. 6b
where we compare the INP spectrum from the filter sampler, with a PM2.5
cut-off installed, with the sum of stages 1b, 1c, and 1d (the after-filter;
stage 1a was not used on Impactor 1 in this case). Here, both samplers were
positioned within a few metres above the ground. Again, the agreement
between the SHARK and the filter sampler was very good. For both Cardington
and Hyytiälä, the smallest particles (< 0.25 µm) were
not sampled using the SHARK, but the agreement between the filter sampler
and the SHARK implies that, in these cases, the smallest particles made a
minor contribution to the overall INP population, which is what we would
generally anticipate from the literature
(Berezinski
et al., 1988; Huffman et al., 2013; Mason et al., 2016; Santachiara et al.,
2010; Si et al., 2018; Welti et al., 2009). The consistency between the
SHARK and the filter sampler indicates that there are no major losses of
aerosol in the SHARK sampler, at least relative to the PQ100 filter sampler.
Ice-nucleating particle (INP) analysis of samples collected in
Leeds (UK) using the SHARK. (a) The fraction of droplets frozen as a
function of temperature, fice(T), for each stage of Impactors 1 and 2.
The handling blank is shown in grey. (b) The INP concentrations for stage
“e” of both impactors (2.5–10 µm), highlighting their excellent agreement.
Consistency of INP concentrations between SHARK impactors
An example of data from the size-resolved collection and analysis of INPs is
shown in Fig. 7, from a sampling run performed in
Leeds (UK). The fice(T) curves for each impactor stage are illustrated
in Fig. 7a. As discussed in Sect. 2.2, there are two stages, d and e, which have similar
size cuts on both stages. Using stage e as an example, it can be seen that
while the fraction frozen curves for the two samplers are shifted by about 3 ∘C (Fig. 7a), normalizing to the
volume of air sampled to yield [INP]T in
Fig. 7b shows that the INP spectra derived from
stages 1e and 2e are consistent with one another. Stage 2e covers a lower range
of INP concentrations than stage 1e by about 1 order of magnitude, because
the flow rate through this impactor was more than a factor of 11.1 (100 L min-1/9 L min-1) higher, and the probability of collecting
rarer INP was increased by this factor. The agreement between the two
impactors indicates that aerosol was collected with no significant
losses/enhancements due to factors like particle bounce or wind observed.
Based on the inlet particle loss calculations in
Fig. 3, higher losses may have been expected in
impactor stage 1e, but these are not apparent here.
Size-resolved ice-nucleating particle (srINP) spectra at four locations
The derived size-resolved INP (srINP) concentrations for all four test sites
are shown in Figs. 8 and 9. The fice(T) curves for these test
sites can be found in Figs. S1 to S4 in the Supplement.
Figure 8 shows the INP concentration spectra in the
classic form, wherein INP concentrations are plotted against temperature for
each size bin, whereas Fig. 9 shows the same data
in novel srINP plots to allow more intuitive comparison of the INP
concentration contribution from each stage with respect to temperature. In
Fig. 9, where there were measurements from two
impactors for the same stage (e.g. d and e), the INP concentrations were
merged by taking an average at temperature intervals of 0.5 ∘C
(also for Fig. 6). The colour gradient in
Fig. 9 represents the temperature-dependant
concentration for each size bin and the overall steepness of the
d[INP]T/dT curve. The steepness of the INP spectra can be useful in
discriminating between different INP species. On inspection of
Figs. 8 and 9, it can be seen that the spectra in the
four locations have very different characteristics. Not only does the
general shape of the spectra vary, but the size-dependence is also very
different in the four locations. Due to the sample size, these variations
could be attributed to the different aerosol population in each location,
the time of year, and meteorology, which could affect the INP concentrations
and spectra
(Kanji
et al., 2017; Šantl-Temkiv et al., 2019; Tobo et al., 2019; Wex et al.,
2019). We now discuss the size-resolved INP concentration spectra from these
tests, bearing in mind that these four tests were one-offs and should not be
regarded as characteristic of those sampling sites but rather illustrative
of the importance of making size-resolved measurements.
INP concentrations determined from each impactor stage of the
SHARK at the four testing sites: (a) Cardington (UK), (b) Hyytiälä
(Finland), (c) Leeds (UK), and (d) Longyearbyen (Svalbard). Handling blank
data, which determine the baseline of the results, are shown in grey.
Samples of the error bars are shown.
The first site testing of a prototype of the SHARK in which all of the
components were installed was conducted in Cardington (UK) on the 15 May 2018, but only Impactor 2 was used (see Figs. 6a and 8a). The Cardington site is an
airfield, with large areas of grassy land near a main road, and the sampling
was conducted during spring. In order to demonstrate the utility of the
SHARK to make balloon-borne INP measurements whilst providing a comparison
with a commercial ground-based sampler, the SHARK was sampling whilst
suspended from a tethered balloon, flying roughly 20 m above the ground. The
INP spectra (Figs. 8a and 9a) in this location are
steep, increasing by 2 orders of magnitude within 2.5 ∘C, and are
centred around -18 to -20∘C; the [INP]T for 2f and 2e
increases by an order of magnitude in just ∼1∘C.
The INPs in this location were dominated by particles greater than 2.5 µm, whereas particles between 1 and 2.5 µm made a smaller
contribution and show a shallower d[INP]T/dT, seen in
Fig. 9a as a larger spread of data. We speculate
that the coarse-mode INPs at this site were of biological origin, such as
fungal material, pollen, or bacteria with a steep INP spectrum
(Kanji et al., 2017). Some fertile and
agricultural soil samples have also been shown to be very active
(Hill
et al., 2016; O'Sullivan et al., 2015; Steinke et al., 2016; Tobo et al.,
2014), and a mechanism for emissions of soil material into the atmosphere
has been proposed (Wang et al., 2016). However,
the steep portion of the INP spectrum for fertile soils tends to be at
temperatures above ∼-10∘C, warmer than observed in
the Cardington sample. The steepness of the curve and the temperature are
consistent with ice nucleation by pollen
(O'Sullivan
et al., 2015; Pummer et al., 2012; Tarn et al., 2018). Although the size of
whole pollen grains are often larger than 10 µm, pollen is known to
release nanoscale materials that nucleate ice, which might be internally
mixed with aerosol in this size bin.
Size-resolved ice-nucleating particle concentrations
(sr[INP]T) for the four test sites: (a) Cardington (UK), (b) Hyytiälä (Finland), (c) Leeds (UK), and (d) Longyearbyen (Svalbard).
The colour bars indicate the INP concentration. The dotted lines on the
y axis indicate the size cuts of the impactors. The data from Fig. 8 are
presented here in an alternative format, which has the advantage of more
clearly and concisely displaying the features of the INP spectrum in each
size bin than the plots in Fig. 8.
In Hyytiälä (Finland), a field site in the boreal forest, the INP
spectra contrast quite strongly with those in Cardington (see
Figs. 6b and 8b).
Sampling took place on the 11 March 2018, when the
Hyytiälä site was snow covered, and sampling was performed at the
surface (inlet ∼150 cm above surface). In this case only
Impactor 1 was used without the after-filter installed. The complex nature
of the size-dependence of INP is clear here. Intriguingly, in this location,
the INP concentration was greatest for the smallest stage used (1b; 0.25–0.5 µm) and accounted for the majority of the INPs between -17 and
-22∘C. The fewest INPs came from the next smallest stage 1c
(0.5–1 µm), while at temperatures below -23∘C, stage
1e contained the majority of the INPs. These results indicate that the INP
spectra are complex and that concentrations of INPs do not always increase
with increasing size as might be expected. Huffman et al. (2013) reported
INP concentration measurements in a forest ecosystem, where the particles
between 1.8 and 5.6 µm enhanced during rain. Hence, as in the present
study, Huffman et al. (2013) showed that INP activity does not always
increase with size. The highest INP concentrations in Hyytiälä were
measured for aerosol sizes of 0.25–0.5 µm, and we note that these
accumulation mode INPs would have lifetimes of many days to weeks in the
atmosphere and could therefore be transported to locations and altitudes
where they may influence clouds. Clearly, this would be an interesting
location for more measurements with the full SHARK payload to gain further
information on the long-term INP concentration variations and the aerosol
sizes responsible for them.
The testing in Leeds (UK) used both impactors at ground level with the SHARK
suspended from a frame to allow orientation into wind. The Leeds sampling
was conducted within the University of Leeds campus on a patch of grass on
the 7 June 2018 in close proximity to the School of Earth and
Environment. In this test the full suite was deployed, including the
impactors, after-filter, and OPC. The particle number, surface, and mass size
distribution data for this test can be found in Figs. S5 to S7.
It can be seen in Fig. 8c that generally, the
larger bins contained more active INP. The only exception to this occurred
with the after-filter (< 0.25 µm), which had slightly higher
INP concentrations below about -25∘C than the next two size
bins (0.25–1.0 µm). As with the measurements in Hyytiälä,
clearly more measurements illuminating the contribution of the smaller
particles in similar environments would be beneficial since the atmospheric
lifetime of these fine particles is relatively long. We note that a
substantial proportion of INPs quantified just outside of Leeds in a
previous study were heat sensitive and therefore most likely of biological
origin (O'Sullivan et al., 2018). In the future, conducting heat tests, as
well as using mass spectrometry, SEM, and DNA analysis with the size-resolved
INP samples may help to identify the INP types in the various size fractions
and highlight any differences between size ranges.
The final test was in Longyearbyen (Svalbard) from the seventh deck of the
icebreaker Oden, 25 m above the surface, when moored ∼200 m
from the shore, overnight from 23 to 24 September 2018. The full SHARK payload was used in this case, with the OPC, both
impactors, and the after-filter on Impactor 1. The particle number, surface,
and mass size distribution data for this test can be found in Figs. S8 to S10. The INP spectra in this location, shown in
Fig. 8d were quite distinct from the other three
locations in that all size fractions contributed similarly to the INP
population, and there is a very shallow slope of dln[INP]T/dT
(Fig. 9d). We detected INPs at temperatures of up
to -10∘C with concentrations of around 0.01 INP L-1.
These high-temperature INP concentrations are consistent with the summertime
measurements reported at other Arctic locations, including Ny-Ålesund
(Svalbard) (Wex et al., 2019).
The INP in this region potentially originate from a range of sources.
Tobo et al. (2019) recently reported
that dust and biological material from glacial valleys in Svalbard may be an
important source of INPs in the region. We also note that we sampled while
the Oden was moored in the port of Longyearbyen where local pollution
sources may have been significant (Zhao et al.,
2019).
Ice-active surface site density, ns(T), and the activated fraction,
nn(T)
The addition of size distribution information to the INP concentration
spectra allowed the calculation of the number of active sites per unit
surface area, ns(T), and the activated fraction, nn(T), of the
size-resolved samples. These quantities are determined by weighting the
srINP concentrations to the total surface area and the aerosol number in
each size bin, respectively, as shown in Eqs. (2) and (3).
ns(T)=-ln(1-ficeT)As,
where As is the total surface area of the particles per droplet in a
µL-NIPI droplet freezing assay. This was calculated for each impactor
size range, using data from the relevant size bins of the OPC data.
nn(T)=-ln(1-ficeT)N,
where N is the total number of particles sampled by the impactor in each size
bin, calculated using the number concentration in each size category as
measured by the OPC and the volume of air sampled by the impactor. The size
bins from the OPC which have been included in the calculations were matched
to those in the impactors. The bin boundaries for the OPC calculations were
within tens of nanometres of the impactor bin boundaries.
Calculating the ns(T) and nn(T) values from the INP data was only
possible for some of the size ranges due to the sampling ranges of the
instrumentation employed. The smallest particle diameter measured by the OPC
is 0.38 µm, i.e. above the lower limit of impactor stage 1b, while the
largest impactor stage, 2f (> 10 µm), has no defined upper
bound. Therefore, the three bins (i.e. impactor stages) that were used to
produce ns(T) and nn(T) were c (0.5–1.0 µm), d (1.0–2.5 µm),
and e (2.5–10 µm). The ns(T) and nn(T) data were calculated for
the field tests in Leeds and Longyearbyen; data from Cardington and
Hyytiälä are not provided as the OPC was not in use at these sites.
Plots showing (left) the activated fraction of aerosol, nn(T), and (right) the number of active sites per surface area, ns(T), for samples tested from two measurement sites: (a) Leeds (UK) and
(b) Longyearbyen (Svalbard). The colours of the data points indicate the
size bins of each impactor, and the different symbols represent the two
impactors. Samples of the error bars are shown.
The plots of activated fraction shown in Fig. 10 are addressed first. For
the Leeds sample, there is a difference in the nn(T) values between bins
c and e (Fig. 10a), where the smallest bin is 1–3 orders
of magnitude lower than the largest bin, with the middle bin in the centre
of the two. In Longyearbyen (Fig. 10b), the
nn(T) for bin e is about a factor of 10 larger than bin c, but bins c and
d produce very similar values of nn(T). Overall, these nn(T) plots show
that the coarse-mode aerosol generally have a higher fraction of aerosol
that serve as INPs than the fine mode, but there is variability in the
dependence on size between the two samples. In contrast to the nn(T)
values, the size-resolved ns(T) data for both Leeds and Longyearbyen show
that the data from the three size categories are all within a factor of 2–10
(close to our uncertainty estimates). Given the activity of aerosol across
these bins scales with surface area, this data might indicate the same INP
species is active across each bin at these sites.
Summary and conclusions
This paper describes a lightweight and portable payload, the SHARK, that is
capable of collecting size-resolved aerosol particles alongside measurements
of ambient temperature, relative humidity, pressure, GPS coordinates,
aerosol number distribution, and aerosol size distribution. The 9 kg payload
was designed for use on a tethered balloon for measurements at user-selected
altitudes for up to 11 h via radio-controlled instrumentation but can be
used wherever it can be suspended. During a SHARK flight, the atmospheric
conditions the SHARK experiences can be monitored in real time via a
radiosonde, and sampling is controlled remotely, allowing the SHARK to be
held at a user-defined height and to only sample under specific conditions
(for instance above the surface boundary layer).
The SHARK samples aerosol onto filter/film substrates using two cascade
impactors to allow aerosol size-segregation from 0.25 to 10 µm, with
an after-filter and top stage to collect particles below and above this
range. One impactor samples at 9 L min-1, while the other samples at
100 L min-1. The filters were collected here for the offline analysis
of INP concentrations and properties, but they could equally be used for
other analyses such as mass spectrometry, DNA analysis, SEM, TEM, and ion
chromatography. A comparison of ambient INP concentrations measured using
the SHARK to those measured using PM10 and PM2.5 aerosol
samplers at ground level demonstrated excellent agreement between the
instruments. Field testing was conducted in four locations close to ground
level and suspended on a tethered balloon at 20 m to demonstrate the
capabilities of the SHARK.
The size-resolved INP concentration spectra reveal complex behaviour. For
example, in Hyytiälä the 0.25–0.5 µm aerosol size fraction
had the most active INP, whereas in Leeds the INP concentration generally
decreased with decreasing particle size. Ambient aerosol size distribution
measured using the onboard OPC allowed the calculation of the activated
fraction, nn(T), and ice-active surface site density, ns(T), data for
the sampled INPs in the tests at Leeds and Longyearbyen. It was shown that
ns(T) was consistent between 0.5 and 10 µm in these two locations
at the times of sampling. It is the intention to make similar measurements
in other locations and at higher altitudes in the future.
Generally, it is expected that larger aerosols are more likely to nucleate
ice (Pruppacher and Klett, 1997), and our
results are consistent with other size-resolved INP measurements which
indicate that the size distribution of INP varies spatially and temporarily
e.g.
(Mason et
al., 2016; Si et al., 2018). Quantifying the size of INP, possibly in
conjunction with other analytical techniques, is a useful means of
identifying different INP types and their sources
(Huffman et al., 2013). In addition, knowledge
of their size will allow the improved representation of INP in global
aerosol models where size is key determinant of lifetime and transport
(Atkinson
et al., 2013; Perlwitz et al., 2015; Vergara-Temprado et al., 2017).
Clearly, more systematic and widespread measurements of INP size are needed
in the future in a range of target locations.
The high sample flow rate, choice of low-contamination aerosol collection
substrates, and long sampling durations mean that the payload is well suited
for INP measurements, including those in low-aerosol environments and
locations with relatively low INP concentrations (down to below
∼0.01 INP L-1 and at temperatures down to about -25∘C and below). The SHARK is an accessible tool for quantifying
size-resolved atmospheric INP concentrations from a tethered balloon. This
will allow improved determination of INP sizes, properties, and sources,
towards ultimately improving model representations of atmospheric INP
distributions.
Data availability
The datasets for this paper are available at 10.5518/744 (Porter et al., 2020).
The supplement related to this article is available online at: https://doi.org/10.5194/amt-13-2905-2020-supplement.
Author contributions
GCEP led the development of the SHARK, performed the bulk of the experiments,
and led the writing of the paper. The initial instrument concept was
conceived by GCEP, SNFS, and BJM with advice from IMB. The building and
testing of the SHARK and its electrical components was done by SNFS with the
assistance of GCEP. The collection and analysis of field samples were
performed by GCEP, MPA, UP, ADH, MDT, and IMB. All authors contributed to the
writing of this paper. BJM oversaw this project as part of his MarineIce ERC
fellowship.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
The personnel of Hyytiälä forestry station, the HyIce project team,
the Cardington meteorological research unit, and those aboard the icebreaker
Oden during 2018 are sincerely thanked for support during field testing. One
of the field tests was completed as part of the Arctic Ocean (AO) 2018
expedition. The Swedish Polar Research Secretariat (SPRS) provided access to
the icebreaker Oden and logistical support in collaboration with the US
National Science Foundation. We are grateful to the Chief Scientists
Caroline Leck and Patricia Matrai for planning and coordination of AO2018,
as well as to the SPRS logistical staff and icebreaker Oden's Captain
Mattias Peterson and his crew for expert field support. Anthony Windross and Stephen Burgess are thanked for help
with the fabrication of the SHARK housing.
Financial support
The authors thank the European Research Council for funding
(H2020 ERC; 648661 MarineIce) and the Natural Environment Research Council (NERC; NE/M010473/1 and NE/R009686/1). We
are grateful to the EU H2020 ACTRIS-2 for a mobility grant to access
the Hyytiälä forestry station as part of the HyIce project (SMR7
RP3 HyICE18, 654109).
Review statement
This paper was edited by Mingjin Tang and reviewed by two anonymous referees.
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