In a warming Arctic the increased occurrence of new
particle formation (NPF) is believed to originate from the declining ice
coverage during summertime. Understanding the physico-chemical properties of
newly formed particles, as well as mechanisms that control both particle
formation and growth in this pristine environment, is important for
interpreting aerosol–cloud interactions, to which the Arctic climate can be
highly sensitive. In this investigation, we present the analysis of NPF and
growth in the high summer Arctic. The measurements were made on-board
research vessel Polarstern during the PS106 Arctic expedition. Four
distinctive NPF and subsequent particle growth events were observed, during
which particle (diameter in a range 10–50 nm) number concentrations
increased from background values of approx. 40 up to 4000 cm-3. Based
on particle formation and growth rates, as well as hygroscopicity of
nucleation and the Aitken mode particles, we distinguished two different
types of NPF events. First, some NPF events were favored by negative ions,
resulting in more-hygroscopic nucleation mode particles and suggesting
sulfuric acid as a precursor gas. Second, other NPF events resulted in
less-hygroscopic particles, indicating the influence of organic vapors on
particle formation and growth. To test the climatic relevance of NPF and its
influence on the cloud condensation nuclei (CCN) budget in the Arctic, we
applied a zero-dimensional, adiabatic cloud parcel model. At an updraft
velocity of 0.1 m s-1, the particle number size distribution (PNSD)
generated during nucleation processes resulted in an increase in the CCN
number concentration by a factor of 2 to 5 compared to the background CCN
concentrations. This result was confirmed by the directly measured CCN
number concentrations. Although particles did not grow beyond 50 nm in
diameter and the activated fraction of 15–50 nm particles was on average
below 10 %, it could be shown that the sheer number of particles produced
by the nucleation process is enough to significantly influence the
background CCN number concentration. This implies that NPF can be an important
source of CCN in the Arctic. However, more studies should be conducted in
the future to understand mechanisms of NPF, sources of precursor gases and
condensable vapors, as well as the role of the aged nucleation mode
particles in Arctic cloud formation.
Introduction
Atmospheric new particle formation (NPF), during which particles with
diameters from 1 to 2 nm are formed, is a phenomenon observed in many
different environments around the world (Kerminen et al., 2018). Initial
steps involved in particle formation and subsequent growth are usually
clustering and condensation of both organic and inorganic vapors
(Schobesberger et al., 2013). Ions are also known to be involved in the
nucleation process (e.g., Jokinen et al., 2018). If newly formed particles
are not lost due to coagulation (Lehtinen, et al., 2007), and manage to grow
to sizes >50 nm, they can act as cloud condensation nuclei (CCN,
Kerminen et al., 2012). Under the presence of sufficient water vapor, CCN
activate to form cloud droplets (Köhler, 1936). Atmospheric NPF is
estimated to be a substantial source of the world's CCN budget (Merikanto et
al., 2009). Thus, in a highly sensitive atmosphere such as the Arctic, where
CCN number concentration is usually low (<100 cm-3, Mauritsen
et al., 2011), NPF may be an important phenomenon controlling the radiative
forcing (Allan et al., 2015; Croft et al., 2016).
During the last decade, Arctic regions have experienced remarkable changes.
Here, the near-surface temperature has increased at least 2-fold compared
to the Northern Hemisphere (a phenomenon known as Arctic amplification,
Overland et al., 2011; Jeffries and Richter-Menge, 2012). In parallel, a
substantial decline in multiyear sea-ice cover (e.g., Bi et al., 2018), an
increase in sea-ice mean speed and deformation (Rampal et al., 2009), and
development of melt ponds (Polashenski et al., 2017) were also
observed. Such changes are not only reflected in the dynamics of the Arctic
ecosystem (Meier et al., 2014), but are also predicted to impact
the mid-latitude climate (Serreze and Barry, 2011; Cohen et al., 2014; Walsh,
2014).
Recent studies suggest that the amplified warming in the Arctic and related
changes are a result of a complex interaction between different feedback
mechanisms including parameters such as temperature (Pithan and Mauritsen,
2014), surface albedo (e.g., Screen and Simmonds, 2010; Taylor et al., 2013),
water vapor (Graversen and Wang, 2009), cloud (Vavrus, 2004), and the
lapse rate (Bintanja et al., 2012). Additionally, variations in atmospheric
and oceanic heat transport were also identified as active players in the
changing Arctic climate (Spielhagen et al., 2011; Alexeev and Jackson,
2013). Increase in latent heat and moisture transport towards the poles may
drive the low-cloud formation, and thus, Arctic surface warming (Praetorius
et al., 2018). And while the mechanisms of lapse rate, surface albedo,
temperature and water vapor feedbacks are rather well understood, the net
cloud feedback still has one of the largest uncertainties (Zhang et al.,
2018).
The multi-year analysis of particle number size distributions from the sites
around the Arctic Ocean revealed frequent new particle formation, occurring
either locally or at higher elevations and prevailing mostly during spring
and summer months (Freud et al., 2017; Nguyen et al., 2016; Dall'Osto et al.,
2019). In the near future, the frequency of atmospheric NPF occurrences is
expected to increase due to Arctic sea-ice melt (Dall'Osto, et al., 2017,
2018a, b). This makes measurements of the ultrafine particle
physico-chemical properties in the Arctic increasingly valuable if
aerosol–cloud–climate interactions need to be understood (Willis et al.,
2018; Abbatt et al., 2019). Contrary to scientific interest, such studies in
this remote environment still remain limited, mainly because of logistic
challenges in the region (e.g., Willis et al., 2017; Wendisch et al., 2019).
The following are studies which focus on nucleation mode particles in
the Arctic. Wiedensohler et al. (1996) reported the occurrence of ultrafine
particles in the Arctic as a result of NPF. However, no correlation with
potential precursor gases has been found. Karl et al. (2012) found that a
sulfuric acid nucleation mechanism best explains the observed growth of
nucleation mode particles over the central Arctic Ocean. In another study by
Karl et al. (2013), marine granular nanogels were proposed as a novel route
to atmospheric nanoparticles in the high Arctic. Furthermore, NPF in the
Arctic region was associated with marine biological processes, such as the
seasonal cycle of the gel-forming phytoplankton by Heintzenberg et al. (2017). From the results of volatility measurements, Giamarelou et al. (2016) have proposed that particles during NPF events in the high Arctic
exist in the form of partly or fully neutralized ammoniated sulfates. Iodine
from coastal macro algae was detected in the growing particles (Allan et
al., 2015; Sipilä et al., 2016), suggesting the iodine as a nucleation
precursor. A large body of studies comes from the Canadian Arctic region.
For example, Croft et al. (2016) showed that ammonia from seabird-colony
guano is a key factor contributing to bursts of newly formed particles at
Alert, Nunavut, Canada. Aerosol particle growth in the Canadian Arctic
Archipelago during summer was correlated with organic species,
trimethylamine, and methanesulfonic acid (MSA), suggesting an important
marine influence (Leaitch et al., 2013; Willis et al., 2016, Abbatt et al.,
2019). Park et al. (2017) provided compelling evidence of the contribution
of marine biogenic dimethyl sulfide (DMS) to the formation of aerosol
particles. Collins et al. (2017) also reported frequent ultrafine particle
formation and growth in Canadian Arctic marine and coastal environments.
The authors emphasized that the low condensation sink, high solar radiation, low
sea-ice concentration, and marine microbial processes all contribute to a
higher frequency of particle formation and growth. Most recently, Tremblay
et al. (2019) correlated particle formation and growth events with the
melting of the sea ice. The authors indicated that besides oxidation of DMS to
produce particle-phase sulfate, other gas-phase organic compounds are
important for particle growth.
Compared to NPF research in Arctic environments, studies on whether
nucleation mode particles (diameter of 20 nm) can act as CCN are even
scarcer. Leaitch et al. (2016) investigated effects of 20–100 nm particles
on liquid clouds in the clean summertime Arctic and found that particles as
small as 20–50 nm can activate to cloud droplets. This was also confirmed by
Burkart et al. (2017b), who found that in the Canadian high Arctic marine
boundary layer, newly formed particles (approx. 30 nm in diameter) are
capable of being involved in cloud activation, suggesting that in the
pristine environment, where cloud radiative forcing is limited by the CCN
available (Mauritsen et al., 2011), information about aerosol sources is
crucial in understanding the link between sea-ice melt and low-altitude
clouds.
In this investigation, we analyzed four cases of NPF and a subsequent growth
from a perspective of particle physical (number concentration, number size
distribution, and formation and growth rates) and indirect chemical
(hygroscopicity) properties. Our main goal here is to test the hypothesis
that NPF and secondary aerosol production can influence the CCN budget in
the summertime Arctic. The study is structured as follows. After a short
description of materials and methods in Sect. 2, we proceed by describing
each NPF event separately (Sect. 3). This includes specification of the
meteorological conditions during which NPF occurred, characterization of
particle formation and growth rates, followed by the observed hygroscopicity
of newly formed particles, and the measured CCN concentrations during NPF
events. We start the discussion of the results (Sect. 4) with a general
overview of our observations, putting the results into perspective of other
studies. This leads to Sect. 4.1, where we discuss the indirect evidence
of the composition of newly formed particles. Here, we reflect on our
observational data as well as various techniques to gain information on
particle formation mechanisms, possible sources of precursor gases, etc.
The discussion section is closed by investigating the implication of NPF for
cloud formation. This is done by using zero-dimensional parcel model to
examine, whether newly formed and slightly grown particles can become CCN.
Model results are compared to measured number concentration of CCN during
the NPF events. The main results are summarized at the end of the work; general
conclusions are also provided.
Materials and methodsDescription of observations
The data used in this study were obtained during two legs of an expedition
of the German Research Vessel Polarstern (PS 106/1 and PS 106/2): the
“Physical feedbacks of Arctic boundary layer, Sea ice, Cloud and AerosoL
(PASCAL, PS 106/1)” and “Survival of Polar Cod in a Changing Arctic Ocean
(SiPCA, PS 106/2)” (Macke and Flores, 2018; Wendisch et al., 2019). Both
expeditions took place in the vicinity of Svalbard (Norway) from May to
July 2017. PASCAL was performed in the framework of the ArctiC
Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and
Feedback Mechanisms (AC)3 project and was designed to explore cloud
properties, aerosol impact on clouds, atmospheric radiation and
turbulent-dynamical processes. During the first leg of the trip (PS 106/1,
PASCAL), RV Polarstern reached approx. 82∘ north, where an
ice-floe camp was established (5–14 June). The first leg of the
expedition ended at Longyearbyen, Svalbard, by 21 June. On 22 June,
RV Polarstern left Svalbard for the SiPCA expedition. On the second expedition
leg aerosol particle measurements were performed until 16 July. The cruise
track and the ice drift are shown in Fig. 1.
Cruise track and particle number concentration (integrated in a
size range from 10 to 800 nm) during PASCAL and SiPCA expeditions. The days
which were picked to analyze NPF events and subsequent particle growth are
indicated with square boxes. Backward air mass trajectories (72 h) were
calculated using HYSPLIT (Draxler and Rolph, 2012) and are shown by solid
(200 m a.s.l) and dotted (2000 m a.s.l) lines corresponding to each NPF event.
Ice drift is shown in the insert. Thin blue and black lines are the observed
ice edge for June and July 2017, respectively (Fetterer et al., 2002).
Measurement setup and equipment
To measure aerosol particle physico-chemical properties, a temperature
controlled measurement container, prepared and operated by the Leibniz
Institute for Tropospheric Research, Leipzig, Germany, was installed on the
observation deck of RV Polarstern. The aerosol container was air-conditioned
to 24 ∘C and the aerosol inlet head was heated to 30 ∘C to ensure the stability of aerosol instrumentation and prevent icing,
respectively. The aerosol inlet was made of 6 m length stainless steel
tubing, with an inner tube diameter of 40 mm. It was placed on top of the
measurement container with an angle of 45 ∘, pointing away from the
ship. The aerosol flow in the 6 m long inlet was set to 40 L min-1 (Reynolds
number <2000, laminar flow) to minimize particle losses. Inside the
container, an isokinetic splitter was used together with short and vertical
conductive tubes to feed the measurement instrumentation with an aerosol
sample. Aerosol instrumentation (relevant to this study) included a neutral
cluster and air ion spectrometer (NAIS), a mobility particle size
spectrometer (MPSS), the Volatility/Hygroscopicity-Tandem Differential Mobility
Analyzer (VH-TDMA), and the Cloud Condensation Nuclei Counter (CCNC) to measure
aerosol particle number size distribution, volatility/hygroscopicity
properties of aerosol particles, and the number concentration of CCN,
respectively.
Neutral cluster and air ion spectrometer (NAIS)
A neutral cluster and air ion spectrometer (NAIS, Mirme and Mirme 2013) and
guidelines by Kulmala et al. (2012) were used to study early stages of NPF
and subsequent growth (including NPF event classification, formation (J), and
growth rate (GR) calculation). The NAIS measures the number size distribution of
neutral particles in the diameter range of approx. 2–40 nm and charged
particles and clusters in the size range of approx. 0.8–40 nm. The
instrument is an extended version of the air ion spectrometer (Mirme et al.,
2007) and utilizes a sample preconditioning section to enable measurements
of neutrally charged particles. Unipolar corona chargers are used for both
charging and charge neutralization. Charged particle classification is
carried out in the multichannel differential mobility analyzer (DMA) where
21 individual electrometers are used to record electric current carried by
the charged particles. Due to high total flow of NAIS (60 L min-1) a
dedicated 1.3 m long copper inlet (3.5 cm in diameter) was installed to
sample ambient air. Measurement data were inverted using the v14-lrnd
inversion algorithm (Wagner et al., 2016). Particle losses due to diffusion
were corrected before data processing.
Mobility particle size spectrometer (MPSS)
Particle number size distributions (PNSD), in a mobility size range from 10
to 800 nm, were measured with a TROPOS-type mobility particle size
spectrometer (MPSS, Wiedensohler et al., 2012). The MPSS consisted of a
Hauke-type DMA (effective length of 28 cm), a condensation particle counter
(CPC, model 3772, TSI Inc., USA, flow rate 1 L min-1), a closed-loop
sheath flow arrangement, and a bipolar diffusion charger, ensuring the
bipolar charge equilibrium as described in Wiedensohler (1988). The sample
flow rate was controlled by a CPC (1 L min-1) and the sheath flow rate
was 5 L min-1. The time resolution of an up-and-down scan was 5 min.
Electrical particle mobility distributions were inverted to PNSDs using the
inversion algorithm presented by Pfeifer et al. (2014). The final PNSDs were
corrected for transmission losses in the sampling lines using the method of
equivalent length and CPC counting efficiencies (Wiedensohler et al., 1997).
Sizing accuracy of MPSS was controlled using nebulized polystyrene latex
spheres (PSL, Thermo Scientific™, Duke Standards™) of 203 nm (Wiedensohler et al., 2018). High-voltage supply offset
calibration, instrument flows, and tests for leakage were performed on a
regular basis (once per week).
Aerosol particle affinity with water and volatility properties (not discussed
here) was measured using the TROPOS-type Volatility/Hygroscopicity-Tandem Differential Mobility
Analyzer (VH-TDMA, Augustin-Bauditz et al., 2016). The
instrument consists of a DMA-1 that selects chosen quasi-monodisperse
particles, a thermodenuder (not used in this study), an aerosol
humidification section that conditions the particles selected by the DMA-1,
and an MPSS-equivalent closed-loop sheath flow unit inside the temperature-controlled box, which is used to obtain the hygroscopic growth factor (HGF).
The HGF is defined as the ratio between the measured particle electrical
mobility diameter at a given RH as measured by the second DMA and the
initially selected dry diameter.
During the whole expedition, two constant aerosol particle sizes, 50 and 150 nm, were selected for the measurement of HGF at a target RH of 90 %.
Additionally, HGF of 15, 20 and 30 nm size particles were measured during
NPF and growth events. The system RH, measured by a humidity sensor, was
periodically calibrated by an automatic calibration unit, using pure
ammonium sulfate. Scans with RH ±2 % from target RH were excluded
from data analysis. Sizing accuracy, high-voltage supply offset calibration,
flow rates, and zero tests were performed regularly (once per week). In
general, recommendations have been followed as described in Massling et al. (2011).
The VH-TDMA data were inverted using a TDMAinv routine (Gysel et al., 2009)
to retrieve the probability density functions of GF (GF-PDF). Scans with RH
<20 % were used to calibrate size offset in the system, as well
as to define the width of the transfer function (Gysel et al., 2009). The
particle hygroscopicity parameter kappa (κ) was derived from VH-TDMA
data following the κ-Köhler theory by Petters and Kreidenweis (2007):
κ=GF3-1⋅1Sexp4σsMWRTρWDdGF-1,
where S is the saturation ratio; σs is the
surface tension of the solution; MW is the molecular
weight of water; R is the universal gas constant; T is the temperature;
ρW is the density of water; and Dd is the
particle dry diameter.
Cloud condensation particle counter (CCNC)
The CCNC (model CCN-100 from Droplet Measurement Technologies, Roberts and
Nenes, 2005) measured CCN number concentrations, subsequently at six
different supersaturations (0.1 %, 0.15 %, 0.2 %, 0.3 %, 0.5 % and 1 %), where each
supersaturation was sampled for 10 min. Hence an hourly average
concentration at each supersaturation is available. The instrument was
calibrated before and directly following the campaign using pure ammonium
sulfate particles of known sizes, based on the ACTRIS protocol (Gysel and
Stratmann, 2013). Only poly-disperse aerosol was sampled by CCNC.
Offline chemical analysis
The sampling of aerosol particles was conducted using five-stage
low-pressure Berner impactors (Hauke, Austria) with a flow rate of 75 L min-1, which was installed on the top of the observation deck facing
the ocean at a height of ca. 25 m. Particles were collected in the size
ranges 0.05–0.14 µm (stage 1), 0.14–0.42 µm (stage 2), 0.42–1.2 µm (stage 3), 1.2–3.5 µm (stage 4), and 3.5–10 µm (stage 5) aerodynamic particle diameter (50 % cut-off) on aluminum
foils as impaction substrates, which had been heated at 350 ∘C
for at least 2 h to reduce blank levels prior to sampling. To avoid
condensation of atmospheric water on the surface of these aluminum foils, a
conditioning unit was mounted between the impactor inlet and the sampling
unit consisting of a 3 m tube. By heating the sampled air, high relative
humidity of the ambient air was reduced to 75 %–80 % before the collection
of the aerosol particles. The temperature difference between the ambient air
at the impactor inlet and the sampled air after the conditioning unit did
not exceed 9 K. Thus, the losses due to evaporation of semi-volatile
compounds are expected to be minimal.
After sampling, the aluminum foils were stored in aluminum boxes at -20∘C and transported in dry ice to the TROPOS laboratories in
Leipzig, Germany. Field blanks were collected by loading the Berner impactor
with the aluminum foils at the sampling site with no air drawn through it.
Please note that the sampling time was set to 72 or 144 h (to accumulate
enough particle mass on the filters), thus, it does not exclusively comprise
the discussed NPF events. For example, during NPF Event 1, chemical particle
composition was determined from samples that were collected between 29 May
(midday) and 1 June (approx. 08:00). During NPF Event 3, sampling was
done between 25 June (11:00) and 28 June (09:00).
Particle mass determination was performed by weighing clean (blank) and
particle-loaded filters using a microbalance UMT-2 (Mettler-Toledo,
Switzerland). The concentrations of water-soluble methanesulfonic acid (MSA)
and inorganic compounds relevant to this study (SO42-,
NH4+, Na+) in filtered (0.45 µm syringe) aqueous
extracts (50 % of the filter in 2 mL) were determined using ion
chromatography (ICS3000, Dionex, Sunnyvale, CA,USA), as described in
Müller et al. (2010). Assuming that the ocean is the major source of the
measured atmospheric sodium, sea salt sulfate (ss-sulfate) was calculated
from the constant mass ratio (SO42-/Na+=0.251) in
bulk seawater (Galloway et al., 1993; Fomba et al., 2014). Non-sea salt
sulfate (nss-sulfate) was calculated by subtracting ss-sulfate from the
total sulfate concentration. The determination of total carbon (TC) as
organic carbon (OC) and elemental carbon (EC) was carried out by a two-step
thermographic method (C-mat 5500, Ströhlein, Germany) with nondispersive
infrared sensor (NDIR) detection as described in Müller et al. (2010).
Organic matter (OM) was calculated by considering OM as twice OC (OM=2×OC) for remote aerosols (Turpin and Lim, 2001).
Analysis of PNSD measurements
Before NPF event classification, inverted and loss-corrected NAIS and MPSS
PNSDs were merged together. For the smallest particle diameter, from 2 to 10 nm, exclusively NAIS data were chosen. This is because the MPSS used in this
study was optimized to operate in a diameter range from 10 to 800 nm. The
diffusional losses of sub-10 nm particles were too great to accurately
recover the PNSD at initial steps of nucleation. Contrarily, uncertainties
in the NAIS measured particle number concentration increases for particle
diameters larger than 10 nm (Wagner et al., 2016). For these reasons, PNSDs
from both NAIS and MPSS were merged at 10 nm diameter. No additional
treatment (e.g., spline fit to smooth merging distributions) was performed on
merged PNSDs.
Following the protocol by Kulmala et al. (2012), NPF events were visually
identified from the merged PNSDs. Although different types of NPFs were
recorded (e.g., short bursts in the smallest particle number as, e.g.,
described for the Arctic region by Heintzenberg et al., 2017 and Dall'Osto
et al., 2017), in this work we will only focus on NPF events with subsequent
particle growth. This type of event includes not only particle
formation, but also includes later particle growth lasting for several
hours, thus representing a more regional phenomenon (Ström et al.,
2009). It also allows us to calculate the GR of the particles, which would not
be possible in the case of short nucleation mode particle bursts.
Different methods exist to determine the GR based on the measured PNSD. For
example, maximum-concentration and log-normal distribution function methods
were proposed by Kulmala et al. (2012). Tracking regions of PNSD and
interpreting the change rate of the size-integrated general dynamic equation
methods was suggested by Pichelstorfer et al. (2018). In this work, we used
a trial-and-error approach to find the best fit to determine the GR by selectively
applying all the mentioned methods for certain NPF cases. The formation rate of
particles of a certain size (J) was calculated as described by Kulmala et al. (2012), based on the observed changes in particle concentrations,
GR determined, and particle losses characterized by a coagulation sink (CoagS).
Adiabatic cloud parcel model
To study the climatic relevance of NPF in the Arctic, we have used a
zero-dimensional, adiabatic cloud parcel model. Thorough formulation of the
model is given by Rothenberg and Wang (2016) and will not be discussed here.
Model code is also freely available at https://pyrcel.readthedocs.io (last access: 21 August 2019).
Shortly, at the initial step, the model calculates an equilibrium wet-size
distribution from the set of given parameters. This includes the description
of the aerosol population and environmental specifications of temperature,
pressure, relative humidity, parcel ascending velocity, and the height of
the planetary boundary layer. The aerosol particle population, consisting of
two modes, is described by the total number concentration, the geometric
mean diameter, and the geometric standard deviation of the log-normal
distribution. The hygroscopicity parameter κ following Petters and
Kreidenweis (2007) is used to describe particle chemical composition. The
evolutions of the parcel supersaturation, temperature, pressure, and
liquid/vapor water content are then integrated forward in time to describe
the thermodynamic evolution of an adiabatically lifted, non-entraining
parcel. In the model, the evolution of supersaturation S is
dSdt=αT,P-γT,Pdwcdt,
where α and γ are functions depending on temperature and pressure
(Leaitch et al., 1986) and wc is the liquid cloud water mass mixing
ratio. Change in temperature is described as
dTdt=-gVcp-Lcpdwvdt.V is the updraft velocity, g is gravitational acceleration, cp is the specific heat of dry
air at constant pressure, L is the latent heat of water, and wv is the water
vapor mass mixing ratio. Water mass conservation is ensured as vapor
condenses into cloud water. Pressure change within the ascending parcel can
be written as
dPdt=-gVPRdTv,
where Tv is temperature, Rd – gas constant for dry air. The change in
cloud water is
dwcdt=4πρwρa∑i=1nNiri2GriS-Seq.
Here ρa and ρw is the density of air and water,
respectively. Ni is a number concentration and ri is radius in a
size bin, S is environmental saturation, Seq is the predicted equilibrium
supersaturation under framework described by Petters and Kreidenweis (2007).
G is a growth coefficient, which is a function of both the chemical and
physical properties of particles.
Contamination from ship exhaust
During the cruise, ship exhaust occasionally disturbed measurements on-board
RV Polarstern. This was mostly pronounced during the periods when the ship was
breaking the ice (rapid forward–backward direction change) and/or was
drifting during sea experiments. Ship exhaust contamination can be seen in
Fig. 2 contour plots as a sharp increase in particle number concentrations
over the whole particle diameter range. The contamination from online
measurements was removed manually. For this, we referred to total particle
number concentration observed by separate CPC with 2 s time resolution.
The comparison between the total particle number concentration and the signal
from the single-particle soot photometer (results are not shown here) confirmed
that the total CPC indeed is able to observe sharp increase in particle
number, which is related to ship exhaust (black carbon particles).
The NPF events observed during RV Polarstern cruise PS106. The
PNSDs from NAIS (negative polarity) and MPSS are shown as contour plots. The
color scale represents particle number concentration as dN/dlogDp. Inside the
contour plots, particle number concentration, integrated between two size
ranges (10 to 50 and 100 to 800 nm), is shown with dashed and dotted black
lines. The presence of corona charger ions (<2 nm, Manninen et al.,
2011) can also be seen in NAIS data. This artifact was excluded from data
analysis. Coagulation and condensation sinks, meteorological parameters
(wind speed and direction, global radiation, temperature, and relative
humidity), and formation rates (J) for each NPF event are shown in the panels
below the contour plots. Note: sample contamination by ship exhaust was
removed from data analysis; however, for better representation of particle
growth, the contour plots include all the data (contamination not removed).
For offline measurements, an automatic system (to measure relative wind
direction) was installed together with a high-volume sampler to stop the pumps
when the wind direction was associated with the pollution sector. A similar
approach was used by Huang et al. (2018). The Berner impactor, on the other
hand, did not have such a system to prevent samples from contamination. To
avoid measurement artifacts, only samples with the same order of organic
carbon as from high-volume samplers were used for data analysis and
discussion.
Results
During the PS106 cruise, a number of instances were recorded whereby a total
particle number concentration (integrated from MPSS between 10 and 800 nm)
steadily increased from the background concentrations of several hundred to
several thousand particles per cm3 (Fig. 1). After eliminating the
contribution from the ship exhaust (by filtering abrupt and short increases
in particle number concentration recorded by a total CPC with 2 s time
resolution), these cases were associated with new particle formation (NPF)
events. For further discussion, we have selected four NPF events with a
subsequent particle growth which represent the phenomenon on a regional
scale (Ström et al., 2009). To gain information about the scale of NPF,
additional data of PNSD information from the Villum Research Station
and Zeppelin Mountain Observatory were also taken into account (data for visual
inspection were taken from http://ebas.nilu.no/, last access: 18 March 2019).
The geographic location of the observed NPF events can be seen in Fig. 1
(indicated with black rectangles and date of occurrence), and took place
between 78.55 to 81.66∘ N and 7.28 to 33.96∘ E. The
most intense event (NPF 1) occurred on 1 June 2017, with the total particle
number concentration increasing from 100 to more than 4000 particles cm-3. During the NPF event, the lateral distance between RV Polarstern
and the nearest coast of Svalbard archipelago was 150 km. The least
intensive NPF event (NPF 3) was recorded on 26 June, during which the total
particle number concentration increased from 160 to 700 particles cm-3.
Nevertheless, the subsequent particle growth from 3 to approx. 50 nm
lasted for 3 d. All the events that were recorded during June (1, 18,
and 26 June) took place in the vicinity of the marginal ice zone. The most
northern event (NPF 4, 81.6 ∘ north) was observed on 2 July 2017. At
this time, RV Polarstern was further away from the marginal ice zone. The
average total particle number concentration before the NPF event was approx.
100 particles cm-3, which increased to 1400 particles cm-3 during
the event.
Overview of the NPF events
In this paragraph, a detailed overview of the events is presented with the
focus on environmental conditions during which NPF occurred, as well as the
formation and growth rates of newly formed particles.
NPF 1: 1 June
The first NPF event with a subsequent particle growth was observed from
around 06:00 onwards on 1 June 2017. RV Polarstern reached the marginal
ice zone at 11:00 and entered the pack ice at around 15:00 on 31 May 2017
(note that all times in this study are given in UTC). This can be seen from
the air and water temperature profiles (Fig. 2). The temperature of air and
water decreased from approx. +5 to -5∘C (air)
and -2∘C (water). In this area, the ice was broken up by leads,
which facilitated the passage of the vessel towards the north. Around 20:00 a
region with more densely packed ice was reached, which obstructed the
movement of the ship (Nicolaus, 2018). On these occasions, due to frequent
reverse–forward ship movement, pollution highly affected the measurements
on-board (see PNSDs in Fig. 1). On 1 June, the vessel could once again pass
through open leads in the pack ice, allowing for contamination-free scans
for the time period from 04:00 to 20:00. During this time, RV Polarstern moved
26 km (from 80.39∘ N 7.58∘ E to 80.62∘ N
7.94∘ E) in mostly cloud-free conditions. From 18:00 to 20:00, a
thin ice cloud was present at over 8 km altitude. Also, over a short period
from 14:00 to 15:00, intermittent low-level liquid clouds were present, which
however did not decrease the global radiation significantly. For a more
detailed description of local and associated large-scale weather patterns
during PS106, please refer to Knudsen et al. (2018).
Before the NPF event, the average particle number concentration in a size
range from 10 to 50 nm (PNC10–50) was 50 particles cm-3. The
particle number concentration in the size range from 100 to 800 nm
(PNC100–800) before the event decreased from 150 to as low as 2 particles cm-3. This resulted in a sharp decrease in the coagulation
sink for 3 nm particles from 7.6×10-5 to 8.6×10-6 s-1. The condensation sink also decreased by 1 order
of magnitude from 2.2×10-2 to 2.2×10-3 s-1, creating favorable conditions for particles to form. The NPF event
occurred when the RH was approx. 90 % and the particle formation rate peaked
when the global radiation approached the maximum (600 W m-2). The
wind speed gradually decreased from an average of 8 m s-1 on 31 May 2017 to 5 m s-1 during the NPF event. As a result of the NPF, the number of
ultrafine particles increased by almost 2 orders of magnitude.
The backward air mass trajectories (calculated for 200 and 2000 m above sea
level, Draxler and Rolph, 2012) showed possible intrusion of air from higher
altitudes and also that air was arriving at the ship following the 80 ∘
north latitude, passing over the Prince George Land and northeastern Svalbard
archipelago (Fig. 1). This can be confirmed by the increase in ozone
concentration at Zeppelin Observatory (Aas et al., 2018; data available from
http://ebas.nilu.no/). Following the NPF event on 1 June, the wind direction
gradually changed from northeast to southwest and brought in a sudden fog (at 19:00,
evident from a steep increase in ambient RH to 100 % and a simultaneous
decrease in visibility measured by the vessel's meteorology station). This
can be seen as a sharp increase in both air temperature and RH (to over
100 %) causing disruption in the PNSD (onwards from approx. 20:00, 1 June). At the same time, further observations of the event were corrupted by
the local pollution from ship exhaust.
Calculated parameters for observed NPF events during RV Polarstern
cruise 106. The GR is obtained from the NAIS size spectrum using the methods
proposed by Kulmala et al. (2012) and Pichelstorfer et al. (2018). J is the
formation rate of 1.6 nm sized positive/negative ion clusters and 3 nm sized
particles. Please note that in some instances the size range for GR and J
calculations is different (due to measured PNSD). Nevertheless, we
calculated both parameters from the smallest possible particle/ion size
range. The value after “±” shows the standard deviation. Date format: mm/dd.
Some parameters describing newly formed particles and ions are shown in
Table 1. The particle GR in a size range from 3 to 7 nm was 1.2 nm h-1.
After the NPF event, subsequent particle growth lasted for about 12 h,
during which the particles were able to grow to approx. 30 nm in diameter
(geometric mean diameter). The GR for 1.6 to 3 nm ions was somewhat more
variable – 0.7 for negative and 1.4 nm h-1 for positive ions. Please
note that we were not able to calculate the positive ion GR in a size range
from 1.6 to 3 nm. Instead, the GR for a particle size range 1.6 to 4 nm was
calculated. The formation rate of 3 nm (J3-) sized neutral particles and
negative ions (1.6 nm, J1.6-) was approx. 0.4 and 0.045 cm-3 s-1, respectively.
NPF 2: 18 June
On 17 June, the ship was moving southward through packed ice area, breaking
floes and navigating through polynyas (Nicolaus, 2018). Over the complete
day of 17 June, low-level stratocumulus clouds were present, which were
broken up occasionally between 07:00 and 13:00 and between 04:00 and 22:00. Between 23:00
on 17 June and 01:00 on 18 June, measured visibility decreased, accompanied
by an increase in relative humidity (RH), indicating fog. This low-level
cloud layer was present until approx. 08:00 on 18 June, when RV Polarstern left the packed ice, entering the marginal ice zone. This resulted
in water and air temperature increases from -1.9∘C to approx. 2
and 0.5 ∘C above zero, respectively. At the same time, local wind
speed decreased from 5 to 2 m s-1. During the following hours, until 18:00, no clouds were present except for a very thin, high ice cloud at 8 km
from approx. 11:30 to 12:00. This period of high incident radiation
was only briefly interrupted by a short fog event from 15:00 to 15:30. During
this whole time, RV Polarstern moved through open water, but was always
surrounded by floating ice. Starting at 18:00, a thin low-level cloud layer
was present above the ship, which decreased the global radiation
significantly. This cloud layer was present until the next day, 19 June, at
approx. 12:00. During 19 June, RV Polarstern moved through open
water and ice along the western coast of Spitsbergen (Fig. 1). From
approx. 12:30 to 15:00 another short cloud-free period led to high
global radiation. At 16:00 at approx. 3 km altitude a cloud moved in,
decreasing the global radiation once again.
The PNC10–50 and PNC100–800 from 17 June prior to the NPF event
were rather stable, with an average value of approx. 30 cm-3. The
corresponding coagulation (for 3 nm particles) and condensation sink was 1.2×10-5 and 2.8×10-3 s-1, respectively.
Analysis of backward trajectories showed that since midnight of 17 June, air
masses were passing over the Arctic Ocean and Greenland Sea. From the
beginning of 18 June and onwards, air masses were already passing over the
northeastern coastal area of Greenland (Fig. 1). The NPF event occurred when the
global radiation reached its maximum at 570 W m-2 and the RH decreased
to 85 %. During the event, the PNC10–50 increased to 3200 cm-3.
Particle growth was slightly disturbed by a fog episode (this can be seen in PNSD
and as RH increase to 100 % in Fig. 2) at around 15:00 and drizzle at 23:00. Nevertheless, the particle growth remained observable until the evening
of 19 June. During this time (after a period of 32 h), newly formed
particles grew to approx. 50 nm (geometric mean diameter).
The GRs for particles in the size range from 3 to 7 nm were in a range from
3.6 to 4.9 nm h-1. The GR for 1.6 to 3 nm negative ions was 2.9 nm h-1, and 4 to 9 nm positive ions 3.3 nm h-1. The J3- of
particles was approx. 0.35 cm-3 s-1. Formation rate for positive
(J1.6-) and negative (J4-) ions were 0.05 and 0.06 cm-3 s-1, respectively. If compared to Event 1, it can be seen that despite
similar intensity of NPF, particle growth during the second event was
approx. 2 times faster, and particles were able to grow to larger diameters
(30 nm during event 1 versus 50 nm during Event 2).
NPF 3: 26 June
The third, least intensive NPF event occurred during the second leg of the
expedition, 26 June, when RV Polarstern was at the marginal ice zone, around
200 km east of Svalbard, moving towards the north. Areas dominated by open
water were passed by the vessel, as well as ice-covered water (Nicolaus,
2018). However, the ice was never very densely packed and the transit of the
ship did not require the ice to be broken. Low-level clouds and fog were present
during all of 25 to 27 June; on 28 June a short period of cloud-free
conditions was observed from around 04:00 to 06:00. There were two short floe
stations, one on 25 June from around 17:00 until midnight and the other on 27 June from around midnight to 03:00.
The formation and growth of particles were already observed on both 24 and 25 June during less pronounced NPF events (not shown), when the ship was
approx. 100 km south of the Svalbard coast. New particle formation along the
eastern coast of Svalbard can be seen in Fig. 1 as an increase in total particle
number concentrations, which were measured from 24 to 28 June, along a
distance of more than 600 km. The daily average of PNC10–50 and
PNC100–800 from 24 June up to the NPF event (26 June) were approx. 600
and 50 cm-3. As a result of NPFs on 24 and 25 June, an interesting
pattern emerged in 26 June PNSD (Fig. 2). At the beginning of 26 June
(midnight to 03:00), three distinctive modes with geometric mean diameters of
15, 40, and 150 nm can be seen. The smallest mode at 15 nm is a result of the
NPF, which occurred on 25 June. These newly formed particles slowly grew in
size and, by 08:00 on 26 June, the mode at 40 nm emerged, which was in turn a
result of NPF and subsequent particle growth observed on 24 June. Larger
size particles (150 nm in diameter) seem to exist independently of the NPF
events and were present before, during, and after the NPF on 26 June.
However, because we were not able to identify particle growth, the NPF
events on 24 and 25 June were excluded from the result and discussion
sections.
The event on 26 June started with relatively calm winds (2 m s-1),
which gradually increased to 10 m s-1 over a 3 d period (26 to 28 June) with a constant rate of 0.3 m s-1 h-1. The direction of the wind
remained stable during the event, with prevailing winds from the south-southwesterly (190 to 200∘) direction and stagnant air masses
coming from the marginal ice zone. At the beginning of the event, relative
humidity was at around 87 %, and remained below 95 % during the whole 3 d period. Air and water temperature during the event was approx. -1.5∘C. During the described 3 d period, water temperature
remained the same (with some short episodes of warmer water), while air
temperature steadily increased to 0 ∘C. The NPF event occurred
with a global radiation being at its maximum (200 W m-2); however, this
time solar radiation was at least 2-fold lower than observed during
previous cases. This is due to the presence of a low-level cloud layer
topped at 2 km during the whole day of 26 June. The corresponding
coagulation and condensation sink just before the event was 2.2×10-5 and 6.0×10-3 s-1, respectively.
The GR of 3 to 7 nm particles was in a range from 0.5 to 0.7 nm h-1.
The GRs of negative (1.6 to 3 nm) and positive ions (2 to 6 nm) were
accordingly 1.2 and 2.2 nm h-1. Despite the noticeable pollution from
ship exhaust, particle growth after the NPF event was observed over the
period of 3 d (Fig. 2). During this time period, particles grew from
several nanometers up to sizes of 50 nm (geometric mean diameter). The
formation rate of positive (J2-) and negative (J1.6-) ions were 0.03 cm-3 s-1, and the J3- for particles was approx. 0.08 cm-3 s-1.
NPF 4: 2 July
From midnight of 1 to 4 July, RV Polarstern was moving northwards from
81.64∘ N 32.62∘ E to 82.16∘ N 32.87∘ E. This region was mostly ice-covered with some open leads, through which
the vessel could pass without having to break the ice. At this time of the
expedition, melt ponds were observed frequently on the ice floes. On 1 July,
there was a thick (up to 3 km altitude) low-level cloud layer present until
14:00 associated with some snowfall. After 13:00, the cloud bottom height
increased steadily; however, some intermittent fog was still present at sea
level. A single fogbow was observed between 18:20 and 19:00. The fog dissolved
at midnight on 2 July. Almost throughout the entire day of 2 July, no clouds
were present except for optically thin cirrus clouds, allowing for high
solar irradiation.
On 2 July, RV Polarstern ventured further into the Arctic ice, more than
300 km from the coasts of Svalbard and Prince George Land (81.51∘ N, 32.97∘ E). The prevailing westerly winds were rather stable
during a 3 d period (from 1 to 4 June) at 6 m s-1. The same was true
for water temperature, which remained approx. 2 ∘C below zero
during the whole event period. The air temperature, on the other hand,
varied between -1 and -5 ∘C. The calculated
backward air mass trajectories indicated that before the midday of 1 July,
air was coming from the direction of Prince George Land. The average
PNC10–50 and PNC100–800 during this time was 60 and 70 cm-3,
respectively (Fig. 2). From 1 July onwards, air masses arriving at RV Polarstern passed closer and closer to the northeastern coast of Greenland,
but did not pass over the land, as was the case for Event 2 (Fig. 1). Effective wet removal of particles by fog could be observed during the
afternoon hours of 1 July, leading to extremely low particle number
concentrations prior to the NPF event. The PNC10–50 and PNC100–800,
respectively, decreased to 40 and 10 cm-3. The resulting coagulation and
condensation sink became 4.5×10-6 and 1.0×10-3 s-1, respectively. The NPF event started at 08:00 on 2 July at
an ambient RH of approx. 90 % and a maximum global radiation of 500 W m-2. In parallel to RV Polarstern measurements, the formation of new
particles was also observed at both Villum Research Station and Zeppelin
Observatory, indicating a regional phenomenon.
The particle GR, in a size range from 3 to 7 nm, was 0.9 nm h-1. After
40 h of growth, the geometric mean diameter of the particles reached 30 nm.
The GR of negative ions was 1.5 nm h-1 (in a size range from 2 to 3 nm). Once again, it has to be noted that, for ions, the GR in the 1.6 to 3 nm
size range was difficult to obtain. Particle formation rate J3- was
approx. 0.15 cm-3 s-1. The formation rate of negative ions
(J2-) was 0.02 cm-3 s-1. As in the case of Event 1, negative
ions seemed to be more prominent than positive ones.
Particle hygroscopicity during NPF events
The size segregated HGF and hygroscopicity parameter κ during NPF
events is presented in Table 2. Diameters and scan times of dry particles
that were selected for HGF measurements are also indicated in Fig. 2. The
HGF scans were performed following the growth of freshly formed particles
from MPSS PNSD measurements. In most of the instances newly formed particles
grew rather slowly and took between 2 and 7 h to grow to diameters of 20–30 nm, when its HGF was measured. The HGF of 30–50 nm particles was
measured between 20 and 40 h after the initial NPF event. Despite the
size of selected dry particles, the measured HGF distributions were
exclusively mono-modal, indicating internal mixture of the aerosol particle.
The highest HGF of nucleation mode particles (15–20 nm) was observed
during Event 1 and Event 4. The HGF of 20 nm particles during Event 1 was
measured 7 h after the beginning of the NPF and was 1.46±0.02
(± standard deviation, SD; κ=0.41±0.02). At the
time of Event 4, HGF of the 15 nm particles was 1.34±0.01 (κ=0.33±0.02). The lowest HGF of 20 nm particles was observed
throughout both Event 2 and Event 3 and was 1.17 (κ=0.13±0.00) and 1.16 (κ=0.12±0.02), respectively. Hygroscopicity
of slightly grown Aitken mode particle (30 to 50 nm) varied from 1.17±0.02 (κ=0.11±0.00) to 1.55±0.01 (κ=0.38±0.00). In general, the longer the particles aged, the more
hygroscopic they became. For example, 8 h after the new particles were
formed during Event 2, the HGF of 20 nm particles was 1.17±0.02.
After another 15 h, these particles grew to sizes of approx. 30 nm,
which HGF increased to 1.43±0.05 (κ=0.36±0.08).
Interestingly, the HGF of 50 nm particles was somewhat lower, 1.25±0.01 (κ=0.16±0.04). Nevertheless, it followed the same
pattern and with time increased to the values recorded before the NPF event.
Hygroscopic growth factor (at 90 % RH) and hygroscopicity
parameter κ during NPF events. Here: time of scans – a time window during which hygroscopicity distributions were measured; tJ – approx. time between the observed formation rate maximum and the measurements of HGF. In other words, tJ indicates how long before/after the NPF events the HGF was measured. For example, if tJ=7, the HGF was measured 7 h after the maximum in J. Negative tJ indicates the measurements of
HGF prior NPF event; d0 – selected diameter of dry particles; Nscans – number of scans; SD – standard deviation. Date format: mm/dd.
Concentrations of CCN (NCCN) measured during the four NPF events can be
seen in Fig. 3. An increase in NCCN during these events can be seen
across all supersaturations. To determine the increase, measured data were
fitted, visible as lines in Fig. 3. Data included in the fitting were taken
from times on when formation rates of particles were noticeably increased
(10 % of the maximum signal) and go up to the time when the NPF event was
interrupted by a change in air mass or fog formation. These periods span 10,
39.5, 44.5, and 29 h for NPF events 1 to 4, respectively. Independent
of the duration of the event, the observed increases in NCCN during these
periods were mostly roughly a factor of 2 for supersaturations from 0.1 % to
0.5 % and roughly a factor of 3 to 6 at 1 %. This larger increase at the
highest supersaturation is related to the fact that the number
concentrations of smaller particles, which are only activated at higher
supersaturations, increased the strongest. During NPF event 2, the increase
was somewhat lower, mostly below a factor of 2. These measurements clearly
show that during NPF events not only new particles are generated, but also
that particulate mass is gained on particles of all sizes, increasing their
size and hence their ability to act as CCN at a given supersaturation. A
similar observation was made in Antarctica (Herenz et al., 2019), where NPF
events with increases in total particle number concentrations from a few
hundred to thousands of particles per cm3 were also accompanied by an
increase in NCCN of at least a factor of 2 at all examined
supersaturations. Burkart et al. (2017b) came to similar conclusion. This is
in agreement with modeling results by Merikanto et al. (2009), where CCN in
Arctic regions were found to almost exclusively originate from NPF.
The CCN number concentration measured during NPF events (1 to 4).
The lines and corresponding values show the increase in CCN concentrations
(prior to NPF versus particles that have grown to the Aitken mode).
Chemical composition of size-resolved particles
The size-resolved absolute atmospheric concentrations of ammonium, MSA,
nss-sulfate, and sea salt (sodium) for the selected periods versus campaign
average are shown in Fig. 4. On average, the highest concentrations of
nss-sulfate (81 and 70 ng m-3), MSA (18 and 10 ng m-3), and
ammonium (16 and 8.7 ng m-3) were found in a size range of 0.14–0.42 µm (impactor stage 2) and 0.42–1.2 µm (impactor stage 3),
respectively. While the concentrations of nss-sulfate and ammonium on the
impactor samples from 25 to 28 June were comparable to the average values,
the impactor samples from 29 May to 1 June stood out with much higher
values, especially in the accumulation mode (nss-sulfate: 251 and 295 ng m-3 and ammonium: 34 and 17 ng m-3 in size range of 0.14–0.42 and 0.42–1.2 µm, respectively). Also for smaller
particles (size range of 0.05–0.14 µm, stage 1), nss-sulfate was
found at a much higher concentration (35 ng m-3) than the average (8.3 ng m-3).
Size-resolved atmospheric concentrations for ammonium, MSA,
nss-sulfate, sodium, and OM for two sampling periods and the whole campaign
average. Stages 1, 2, 3, 4, and 5 correspond to aerodynamic particle
diameter ranges of 0.05–0.14, 0.14–0.42, 0.42–1.2, 1.2–3.5, and
3.5–10 µm, respectively.
It must also be noted that no action was taken (e.g., sampling interrupt-dependent on the specific wind sector) to reduce ship contamination for the
size-segregated aerosol particle measurements. Thus, the contamination from
the ship exhaust cannot be ruled out completely. However, the high
concentrations of biogenic compounds like MSA and the presence of sodium on
the aerosol particles suggested a strong marine influence on the particle
composition.
The highest organic matter (OM) mass concentrations were found at stage 2
(106 ng m-3) and the lowest at stage 5 (39 ng m-3). OM mass
concentration for the period from 25 to 28 June strongly exceeded the
average concentration, especially in the accumulation mode (218
and 147 ng m-3 for stages 2 and 3, respectively). For a time period
from 29 May to 1 June the OM mass concentration ranged close to the average
values.
Sodium was mainly found at Berner stages 3–5. The sodium values for the
sampling period from 25 to 28 June (Berner stage 4: 49 ng m-3) were quite
similar to the average values, while the impactor samples from 29 May to 1 June showed much higher atmospheric concentrations (Berner stage 4: 386 ng m-3). This agrees well with previous studies, which show that atmospheric sea
salt is mostly present in super-micron particles, while OM contributes
strongly to the submicron particle composition (e.g., Müller et al.,
2010). Previous works also suggest that OM is strongly enriched during the
bubble bursting process (compared to sea salt), and therefore OM and sea salt
are not transferred to the same extent from seawater to the aerosol
particles (Keene et al., 2007; Quinn et al., 2015; Van Pinxteren et al.,
2017). It is possible that increased sodium and OM, observed during NPF 1,
is a result of sea spray; however, due to the low sampling time resolution of
the Berner cascade impactor, we do not allow ourselves such a conclusion.
Moreover, please note that the increased values of sodium during this time
period may be related to the ship's proximity to open water (RV Polarstern
reached the marginal ice zone only on 31 May), while the increase in OM
could have happened later (e.g., 1 June) but been included in the same sample.
In chemical sample analysis, we did not find any positive correlation
between OM/OC and sodium concerning the different aerosol size classes. A
more detailed chemical characterization of the aerosol particles during the PS
106 cruise will be addressed in a separate publication.
DiscussionGeneral overview
Although NPF events in the high Arctic were reported by several studies,
there are no observations using the same or equivalent measurement
equipment as in this study which are able to observe the dynamic changes in the
smallest particles (formation and growth of >1.6 nm clusters).
Because of this, we have also calculated the rate at which new particles
appear at larger diameter (10 nm, J10-). The values of so-called
apparent nucleation rates are more frequently reported in the literature.
For example, in several studies from the Svalbard region, GRs for 5 to 25 nm particles were reported to be from 0.1 to 0.6 nm h-1, but in general
≤1.0 nm h-1 (Ström et al., 2009; Giamarelou et al., 2016;
Heintzenberg et al., 2017). The corresponding J10- values were in a
range from 0.1 to 1.4 cm-3 s-1. Nieminen et al. (2018), on the
other hand, reviewed NPF events based on long-term measurements and reported
GRs for the Arctic region to be 1.1–1.2 nm h-1 (for the June–August
time period). The reported formation rates were somewhat lower, 0.008–0.032 cm-3 s-1. In the case of this study, the GRs for 5–25 nm and
J10- values varied correspondingly from 0.7 to 5.4 nm h-1 and from 0.04 to 0.4 cm-3 s-1, respectively. The GR of 5–25 nm size particles in
this study was on average 0.9 nm h-1. The GR of 5–25 nm particles on
18 June, however, exceeds other NPF events, with the GR being significantly
higher, 5.4 nm h-1. During the same event, the J10- was also
higher, 0.4 cm-3 s-1. Nevertheless, on average, the observed GR
and J10- values were on the same order as reported in other studies from
the Arctic region (e.g., Asmi et al., 2016; Nieminen et al., 2018). Some studies
for similar environmental conditions also exist. Jokinen et al. (2018)
provided a comprehensive study on the particle formation in coastal
Antarctica. The growth and formation rates for 3 nm particles were found to
be between 0.3 and 1.3 nm h-1 and between 0.03 and 0.14 cm-3 s-1. It was
concluded that ion-induced nucleation of sulfuric acid and ammonia is a
major source of secondary aerosol particles in the pristine Antarctic
environment. Kyrö et al. (2013) reported formation rates of negative
clusters (J1.6-, 0.01 to 0.4 cm-3 s-1) measured at the Finnish
Antarctic Research Station, Aboa, in Dronning Maud Land. In addition,
apparent nucleation rates of 10 nm particles at Aboa ranged from 0.003 to
0.3 cm-3 s-1. In yet another Antarctic study, Weller et al. (2015)
reported the average growth and formation rates (in a size range from 3 to
25 nm) to be 0.9 nm h-1 and 0.06 cm-3 s-1, respectively.
These authors also concluded that due to an insufficient concentration of low-volatility organic compounds, the particle growth was restricted to the
nucleation mode. All of these studies showed some resemblance to the results
observed in our study.
The question is which mechanism drives the nucleation and which are the
condensable vapors responsible for the observed particle growth in the
pristine high-altitude environments. Most recent studies indicate the
importance of semi-volatile organics (Willis et al., 2016; Burkart et al.,
2017a). The subsequent growth of newly formed particles was associated with
organic precursors from meltwater ponds (Kyrö et al., 2013), while Weller
et al. (2015) speculated that low-volatility organic compounds of marine
origin govern the growth of newly formed particles in Antarctica. It was
also shown that in a clean environment, sufficiently high sulfuric acid
concentrations (107 molecules cm-3) can fully explain particle
growth (Jokinen et al., 2018). The GRs observed in our study are somewhat
similar to those from similar environments; however, they remain difficult to
compare because of case-to-case variability.
Insights on the chemical composition of nucleation mode particles and the
climatic relevance of NPF can be drawn from the hygroscopicity measurements
either at water vapor sub-saturation (measurements of HGF) or
supersaturation (measurements of the number of CCN). While κ is a
parameter that is independent of experimental conditions, HGF still depends
on the dry particle size and RH for which it was determined. Still, for the
Arctic more data are available for HGF, so that we will use this parameter
for comparison with the literature in the following. Zhou et al. (2001) measured
the HGF during the Arctic Ocean Expedition 1996. The HGF of nucleation mode
particles (just after a NPF event, dry diameters of 15) was 1.38. The HGF of
35 nm particles was 1.56. After some time, the particles that grew to sizes
of 50 nm were found to be less hygroscopic (HGF of 1.05). It was suggested
that these particles were produced at the sea surface and not in the free
troposphere. However, the authors could not derive the composition of those
nucleation mode particles. Park et al. (2014) reported HGF values of 50 nm
particles during enhanced number concentration of the Aitken mode to be
1.46. Sulfate and biogenic volatile organic species were identified to
contribute to the Aitken mode particle formation. Compared to our measured
HGF of 15 and 20 nm particles, we can see that during events 1 and 4 values
agree reasonably well with previously measured particle hygroscopicity. The
HGF values of nucleation mode particles during events 2 and 3, on the other hand,
are significantly lower. The hygroscopicity of the Aitken mode particles,
measured during Event 4 was almost identical to that noted by Park et al. (2014). On the other instances, for example Event 2, the HGF of the Aitken
mode particles was lower (1.33 versus 1.46) than previously reported values.
It clearly indicates that different condensable vapors were driving the
growth of newly formed particles into sizes of 30 to 50 nm.
Based on particle hygroscopicity, formation and growth rates of
positive/negative ions and neutral clusters, and offline chemical analysis,
our observed NPF events represent two different cases: (1) more hygroscopic
particle formation favored by negative ions, events 1 and 4 (1 June and 2 July, respectively); and (2) relatively low hygroscopicity particle formation
during events 2 and 3 (18 and 26 June, respectively), suggesting the
presence of condensable organics in particle growth. Further, we would like
to discuss event-specific particle growth/formation rates and hygroscopicity
with respect to formation mechanism and condensable vapors.
Indirect evidence of the composition of newly formed particlesNPF 1 and 4
Occurrences of nucleation mode particles in the summer Arctic were
associated with intrusion from higher altitudes and new particle production
in upper layers of the marine boundary layer (MBL, e.g., Wiedensohler et al.,
1996). It is possible that the NPF precursors can be brought from either
open ocean or anthropogenic continental sources by air masses. Coupled with
low condensation and a coagulation sink and with plentiful global radiation, it
creates favorable conditions for new particles to be formed. However, in all
of our observed NPF cases the particle formation started from nucleation of
1–2 nm clusters, suggesting that the NPF took place right at the sea level,
rather than in upper layers of the MBL. In this study, unfortunately neither
the high-resolution online chemical composition of aerosol particles nor
relevant gases (e.g., SO2, O3) were directly measured on-board RV Polarstern. To gain some insights into the chemical composition of newly
formed and slightly grown particles, as well as precursor gases, we used
measured particle physico-chemical properties (e.g., hygroscopicity, growth
rate) as well as satellite imagery.
Sea-ice concentration (white – 100 %, dark blue – 1 %; from
NASA Worldview; Maslanik and Stroeve, 1999) and chlorophyll-a surface
concentration (taken from http://marine.copernicus.eu, last access: 29 April 2019) during NPF events (a, b, d, e). On the right – the ice alga and diatom
Melosira arctica(c, f) observed from the ship deck during NPF Event 1. RV Polarstern
track and location during the NPF event are indicated by the red line and black
circle, respectively. Orange lines mark the 72 h backward air mass trajectory
at 200 m a.s.l.
It is known that Arctic phytoplankton contributes to the production of
dimethyl sulfide (DMS), which is the main source of biogenic sulfur (Stefels
et al., 2007; Levasseur, 2013, and reference therein). Released into the
atmosphere, DMS can be involved in NPF through oxidation and creation of
sulfuric acid (H2SO4) (Kulmala et al., 2001; Park et al., 2017).
In a study by Nguyen et al. (2016), NPF and particle growth at Station
Nord, Greenland, were found to be linked to O3, most likely through
creation of a hydroxyl (OH) radical and oxidation of sulfur dioxide (SO2)
and volatile organic compounds. The satellite-derived chlorophyll-a mass
concentration in surface seawater, as an indicator of phytoplankton biomass
(Becagli et al., 2016), can be seen in Fig. 5 (left). It is evident that
during all NPF events RV Polarstern was in close proximity to an area
of increased biological activity in the Arctic Ocean. During Event 1, we
also observed large ice-attached mats of the Melosira arctica (Fig. 5), which suggests the
presence of DMS (Levasseur, 2013). It can also be seen from Fig. 5 that sea-ice retreat is somewhat linked to increase in chlorophyll-a mass
concentration in surface seawater. For example, on 26 June some ice coverage
in the southern part of Prince George Land can still be visible, while on 2
July it is all gone, replaced by biological activity. This is most likely
because the ice edge provides increased stability from the meltwater, which
facilitates the seasonal production of phytoplankton (Conover and Huntley,
1991).
An interesting feature was observed with respect to formation rates and the
number size distributions of positive and negative ions during events 1 and
4 (Fig. 2; see also Fig. S1 in the Supplement). Firstly, it seems that the
formation of ions occurred before that of neutral particles. The peak ion
formation rate was observed approx. half an hour prior to the formation of
neutral particles. Although not in the polar regions, similar behavior was
noticed in several other studies, suggesting the importance of ions in NPF
events (Manninen et al., 2010; Jayaratne et al., 2016). The role of ions in
NPF was investigated in both laboratory and field studies (e.g., Wagner et
al., 2017; Jokinen et al., 2018). It was shown that ions enhance the
nucleation and condensation of the vapor molecules by stabilizing the
molecular clusters and/or are involved in charged cluster neutralization via
recombination with oppositely charged clusters. The second interesting
feature that was observed only during events 1 and 4 was the absence of
the smallest (<1.6 nm) positive ions. Negatively charged ions seemed to
be involved in the particle formation more favorably than the positive ones.
This was also observed in previous studies (e.g., Hirsikko et al., 2007; Asmi
et al., 2010; Jokinen et al., 2018) and was associated with sulfuric-acid
nucleation. Although H2SO4 concentrations were not determined
directly, the presence of negative clusters suggests that in the case of events 1 and 4, sulfuric acid was somewhat involved in observed NPF, too.
From previous studies, it was shown that H2SO4 concentration of
107 molecules cm-3 are sufficient to explain the observed new
particle GRs in coastal Antarctica (Jokinen et al., 2018). In our case, the
hypothesis was tested that H2SO4 was involved in NPF events 1 and
4 by using the look-up tables from an ion-mediated nucleation model for the
H2SO4–H2O binary system (Yu, 2010). At a given temperature
(TEvent1=268.8 K; TEvent4=268.4 K), relative humidity
(RHEvent1=96.3 %; RHEvent4=96.23 %), and surface area
concentration of pre-existing particles (SEvent1=2.9µm2 cm-3; SEvent4=0.5µm2 cm-3), and
assumed ionization rate (Q=2 ion-pairs cm-3 s-1) – the
corresponding H2SO4 concentration was calculated to be approx.
106 molecules cm-3. If compared to a study from Antarctica (Jokinen
et al., 2018) or laboratory studies by Dunne et al. (2016) from the CERN
CLOUD (Cosmics Leaving Outdoor Droplets) chamber, our calculated
H2SO4 concentration is 10 to 30 times lower than that from
previous studies. On the other hand, the results of this study are in
agreement with a study by Ehn et al. (2007), who studied the relationship
between particle hygroscopicity and sulfuric acid concentration in boreal
forest. The authors reported that the concentration of H2SO4,
corresponding to 15 and 20 nm particle HGFs of 1.34 and 1.46, was in a range
of 107 molecules cm-3. Nevertheless, there were numerous instances
when the same hygroscopic growth was also observed at lower H2SO4
concentrations (<107). Moreover, both in the Arctic and
Antarctica, H2SO4 concentrations of 106 molecules cm-3
were associated with NPF by Croft et al. (2016) and Kyrö et al. (2013),
respectively.
The fraction of the particle growth that can be explained by sulfuric acid
can be found from the comparison of observed versus predicted particle
growths. From Vakkari et al. (2015), the particle growth due to sulfuric
acid can be found from the relation
GRcalc=CH2SO4A,
where coefficient A is equal to 1.58×107, 1.99×107, and 2.28×107 for particle growth in the size range from 1.5 to 3, 3 to 7, and 7
to 20 nm, respectively. Using our estimated concentration of H2SO4
we found that growth (in a size range from 1.5 to 3 nm) due to sulfuric acid
alone accounts only from 4 % to 10 % of the observed growth during Event 4
and 1, respectively. The contribution to particle growth in a size range
from 3 to 20 nm gets even lower, 4 %–5 %. Our values are somewhat comparable
to those observed in Antarctica (Kyrö et al., 2013). It suggests
that besides sulfuric acid, other vapors have to be present to reach the
observed particle growth. From offline chemical analysis, we see that during
Event 1, ammonium and nss-sulfate in accumulation and the Aitken mode
particles were somewhat higher than campaign average (Fig. 4). Some studies
(e.g., Croft et al., 2016; Köllner et al., 2017) identified that certain
nitrogen-containing species such as ammonia and amines are linked to
particle growth in the Arctic region. To test this, we investigate the
formation rate of critical clusters using a parametrization of the ternary
H2SO4–NH3–H2O system, presented by Napari et al. (2002).
That is, we adjust the concentrations of H2SO4 and NH3 until we get the formation rate close to that of observed value. The
estimated concentrations of H2SO4 and NH3 varied from 1×104 to 5×106 cm-3 and 0.1 to 100 ppt, respectively (see
Supplement). According to Wentworth et al. (2016), such
concentrations of NH3 can be indeed found in the Arctic region. There is
evidence that H2SO4–NH3–H2O clusters are only partly
neutralized under atmospheric conditions (e.g., Kurtén et al., 2007;
Schobesberger et al., 2015). On the other hand, Asmi et al. (2010) reported
that Aitken mode particles are somewhat more neutralized. Now, if we assume
that the newly formed particles were partly neutralized by ammonia (as
suggested by Giamarelou et al., 2016), we would expect particle
hygroscopicity to be close to that of ammoniated sulfates. However, our
observed HGFs of 20 and 30 nm particles during both events were somewhat
lower (e.g., 1.46 versus 1.64, Asmi et al., 2010). Similar hygroscopicity of
ultrafine particles (HGF = 1.38 for 15 nm particles) in the Arctic was
observed by Zhou et al. (2001). However, the authors excluded the water–sulfuric
acid nucleation as a source of such particles because <50 nm
particles did not appear to be composed of either sulfuric acid or
ammonium sulfate. Kim et al. (2016) measured the hygroscopicity of
nanoparticles produced from homogeneous nucleation in the CLOUD experiment.
If compared to CLOUD experiment results, the measured hygroscopicity of 20 nm particles during Event 1 was closest to the results of experiment, during
which sulfuric acid and dimethylamine (DMA) concentrations were 7.6×106 molecules cm-3 and 23.8 ppt, respectively. With that being said,
experiments with sulfuric acid (15.1×106 molecules cm-3) and
organics produced from α-pinene ozonolysis (420 ppt) resulted in 15 nm particles with HGF = 1.33, which is identical to those observed during
Event 4.
To conclude, one can only assume that during events 1 and 4, the NPF was
initiated by sulfuric acid. Although the involvement of ammonia in new particle formation is possible, it cannot be proven by this work. The organics
of marine origin could have been involved in particle growth to some extent.
However, low (compared to the campaign average) organic matter concentrations,
observed by offline chemical analysis, contradict the aforesaid conclusion. The
hypothesis that NPF is driven by sulfuric acid can be supported by the
results of neutral cluster and ion number size distribution and
hygroscopicity measurements of nucleation mode particles.
NPF 2 and 3
Following the same line of thought as in the previous section, we
investigate to what extent sulfuric acid may have been involved in the NPF
and growth during events 2 and 3. From satellite imagery of chlorophyll a
(Fig. 5), we can see that RV Polarstern remained in close proximity to
somewhat decreased but still present biological activity in the Arctic
Ocean. In addition to that, some depletion in sea-ice cover close to
Greenland as well as an increase in biological activity south of Svalbard were
also observed (Fig. 5). Thus, it is safe to say that air masses arriving at
RV Polarstern were passing over regions which are a potential source of
both DMS and organics of marine origin. Assuming a H2SO4–H2O
binary system, the H2SO4 concentrations corresponding to formation
rates of those observed for events 2 and 3 were 15 % to 50 % higher,
compared to events 1 and 4. This is mainly because during events 2 and 3
both the condensation sink and temperature were higher too. Only between 1 %
and 3 % of observed particle growth during Event 2 can be explained by
H2SO4 alone. This fraction is somewhat higher on Event 3
(6 %–9 %). At the initial states of nucleation mode particle growth,
particle hygroscopicity on both events was rather low (HGF between 1.16 and
1.18). Such low hygroscopic particle growth, coupled with a rather rapid
increase in size (Event 2, from 3 to 20 nm, GR = 4.2 nm h-1), suggests
that in these events the organics must have played a much bigger role during
initial particle growth than during events 1 and 4. The observed particle
hygroscopicity agrees rather well with less-hygroscopic particle values
reported by Zhou et al. (2001). During Event 2, particle hygroscopicity did
not change much when particles from nucleation mode grew into the Aitken
mode, with HGF remaining between 1.16 and 1.18. Only after approx. 30 h
after the new particles were created did they grow to a diameter of 50 nm with
slightly increased hygroscopicity, HGF = 1.33. Contrarily, in Event 3 the
HGF of 50 nm particles (after approx. 40 h after the nucleation) reached
a value of 1.55. It is expected that with time newly formed particle
hygroscopicity will increase due to the process known as aging. From smog
chamber experiments, Tritscher et al. (2011) showed that organic aerosol
photochemical aging increases the particle hygroscopicity mainly due to
O3 induced condensation of organic molecules onto particles. The rate
at which particle hygroscopicity parameter κ increases can be
calculated from the change in κ over the time period (Δκ/Δt). We found that during events 2 and 3 κ changed
with the rates of 0.0027 and 0.0067 h-1, respectively. These values are
surprisingly close to those observed by Tritscher et al. (2011), further
supporting the evidence of organics participating in our observed particle
growth.
Using our calculated formation rates (0.06 and 0.026 cm-3 s-1
during events 2 and 3, respectively) and sulfuric acid values from previous
studies (5×106 molecules cm-3, Croft et al., 2016) as a
guideline, we calculate the extremely low-volatility organic compound
concentration from the parameterization of particle formation rate as a
function of sulfuric acid and EL-VOC concentration (Riccobono et al., 2014):
J=3.27×10-21cm-6s-1×H2SO42×EL-VOC.
The resulting EL-VOC concentration for Event 2 was found to be approx. 8.0×106 molecules cm-3. This is 40 times higher than what is expected
from monoterpene air–sea flux in the Arctic Ocean (Croft et al., 2016). On the
other hand, during Event 3, the estimated concentration of EL-VOC was in
pair with results published by the same authors. The question is where the
EL-VOC comes from. Kyrö et al. (2013) showed that NPF can be a result of
precursor vapor emission from meltwater ponds. In Fig. 5, we can see that
air masses during Event 2 are arriving from the coast of Greenland, with a
pronounced sea-ice index change, indicating ice retreat. Moreover,
measurements of PNSD at Villum Research Station also indicated the
occurrence of NPF. However, it remains unclear whether the ice and biological
activity development at the coast of Greenland could have produced the
organic vapors that participated in NPF observed at RV Polarstern. Yet
another source of condensable organic vapor could be the aged phytoplankton
blooms, presented as irregularities in chlorophyll-a spatial distribution,
at the marginal ice zone, close to the research vessel.
Atmospheric particulate methanesulfonic acid (MSA) and non-sea salt sulfate
(nss-sulfate) are considered to be oxidation end products of DMS, which is
released as a gas during biogenic processes and indicates the formation of
secondary aerosol with biogenic origin (Leck et al., 2002; Miyazaki et al.,
2010). MSA was shown to be involved in nucleation mode particle growth in
the Arctic by Willis et al. (2016). The authors found that MSA and condensable
organic species, originating from marine-derived biogenic volatile organic
compounds, drive particle growth in a shallow marine inversion layer.
Organic matter in Arctic submicron particles was found to be of both
continental and biogenic marine origins (Kerminen et al., 1997; Chang et
al., 2011). Orellana et al. (2011) showed that submicron OM can be composed
of phytoplankton exudates in form of marine hydrogels. If we look at offline
chemical analysis of aerosol samples, OM was found on all impactor stages,
especially on the submicron particles between 0.14 and 1.2 µm. While
submicron particles of the impactor samples for Episode 1 were mainly
dominated by ammonium and nss-sulfate (see Fig. 4), higher concentrations of
OM (together with MSA) were found for the sampling period between 25 and 28 June. These results corresponded to the observed differences between
particle hygroscopicity during events 1 and 3.
To summarize, the rapid particle growth (Event 2) and the low but steadily
increasing hygroscopicity (events 2 and 3) suggest that organics must have
been involved in both NPF and subsequent particle growth. Although our
observed results agree with previously made conclusions that particle growth
in the Arctic is largely via organic condensation (Burkart et al., 2017a),
due to a lack of measurements, we cannot specify which organic species
may/or may not have been involved in these processes. We also cannot exclude
either the role of iodine (Allan et al., 2015) in the initial steps of NPF
or other pathways for initial particle growth (e.g., aminium salts; Smith et
al., 2010). In the future, measurements of the chemical composition of naturally
charged air ions and ion clusters and low-volatility aerosol precursor gases
would greatly improve our understanding of NPF processes and particle
growth in the Arctic.
Implication for CCN abundance
In the last section of this work, the climatic relevance of the newly formed
particles in the Arctic is discussed. In several studies (e.g., Allan et al.,
2015; Willis et al., 2016; Burkart et al., 2017b) it was reported that
nucleated particles in the Arctic atmosphere rarely grow beyond the Aitken
mode. It is the result of low organic vapor/precursor gas concentrations
involved in NPF and subsequent growth, as well as particle lifetime
(particles being scavenged by fog or precipitation, Karl et al., 2012).
These findings are also comparable to those from Antarctica. Weller et al. (2015) reported that particle growth is governed by the deficit or
availability of low-volatility organic compounds of marine origin and drew
the conclusion that particles do not grow to a diameter range relevant for
action as CCN. On the other hand, some studies both from Arctic and
Antarctica proved that particles do not have to grow beyond 50–60 nm in
diameter to be able to act as CCN (Kyrö et al., 2013; Croft et al.,
2016; Leaitch et al., 2016). This is because in the pristine Arctic
environment the absence of larger particles may lower water uptake, which
will increase supersaturation, enabling cloud water to condense on smaller
particles (Leaitch et al., 2016).
Input parameters and the results from parcel model
(Rothenberg and Wang, 2016). Here: P – pressure (Pascal), T – temperature (Kelvin), RH – relative humidity (%), GMD – geometric mean diameter of two modes fitted to PNSD (in nanometers); N – number
concentration of particles in the mode (in particles per cubic centimeter),
κ – hygroscopicity parameter kappa (derived for particle sizes indicated in bracket), σ – the shape parameter (standard
deviation of the log of the distribution), NCCN,0.1, and
NCCN,3.2 – the number concentration of CCN at two different vertical wind velocities, 0.1 and 3.2 m s-1. Note: κ for specific GMDs was adopted from the nearest value of measured
15, 20, 30, 50, and 150 nm particle hygroscopicity. For example,
hygroscopicity of 20 nm particles was used as an input value for the GMD of 16 nm mode particles. Date format: yyyy-mm-dd.
To examine to which degree NPF may influence the CCN nuclei budget in the
Arctic, we used an adiabatic non-entraining cloud parcel model (described in
Sect. 2.4). All the initial parameters and simulation results can be found
in Table 3. The change in CCN number was calculated for two different
updraft wind velocities, 0.1 and 3.2 m s-1, representing the 75th
percentile and maximum value, respectively. The measurements of vertical
wind velocity was performed during the ice-drift station, as described by
Egerer et al. (2019). We define the CCN number
concentration (NCCN) increase due to particles created in the nucleation
process as
increaseinNCCN=NCCN,bp+NCCN,NPFNCCN,bp,
where (NCCN,bp+NCCN,NPF) is the number concentration of CCN
resulting from the particles created in NPF event (calculated from bi-modal
PNSD using parcel model; see Table 3 for simulation parameters) and
NCCN,bp is the CCN number concentration resulting entirely from
accumulation mode particles present during the NPF event (the newly formed
particle mode is suppressed in parcel simulation). For a more detailed
discussion about the CCN increase calculation, please refer to the Supplement. It can be seen that for most of the cases (when RH >90 %), the CCN number concentrations increased by a factor of 2 to 5 (at
upward wind velocities of 0.1 m s-1) and 4 to 32 (at upward wind
velocities of 3.2 m s-1). Although the activated number fraction in a
size range from 15 to 20 nm was rather low (1.5 %–4 %), the high number of
nucleation mode particles resulted in a noticeable increase in total CCN.
The CCN fraction was higher (30 %–50 %) when 3.2 m s-1 updraft wind
speed was assumed. For the Aitken mode particles, CCN fraction was approx.
12 % and 80 % for updraft wind speeds of 0.1 and 3.2 m s-1,
respectively. In some cases, the particles did not activate to CCN. This is
because activation supersaturation was not reached during the parcel
updraft. The maximum supersaturation achieved with an updraft velocity of
0.1 m s-1 was 0.17 %. The updraft velocity of 3.2 m s-1 would
represent, although rare, however, a not unlikely situation when
supersaturations of 0.9 % can be reached. It can be anticipated that an
even higher fraction of CCN may result from nucleation mode particles when
higher supersaturation values are reached. Measurements of CCN number
concentration on-board RV Polarstern corroborate the results obtained by our
modeling efforts, which all are in good agreement with previous works. For
example, Croft et al. (2016) reported maximum supersaturation in the Arctic
region of 0.15 %–0.25 % for the updraft speed of 0.1 m s-1. From a
comprehensive study on the ultrafine particle effects on liquid clouds in
the clean summertime Arctic, Leaitch et al. (2016) determined the
supersaturation for low- and high-altitude clouds to be approx. 0.3 % and
0.6 %, respectively. In the Arctic environment with the lack of aerosol
particles upon which clouds may form, even a small increase in aerosol
loading can lead to cloud formation and thus influence the ice-covered
Arctic surface (Mauritsen et al., 2011). From our results, we conclude that
NPF in the Arctic can play a significant role in determining the future
changes in this pristine and remote environment.
Summary and conclusion
Aerosol particle physico-chemical properties were determined in the summer
Arctic on-board research vessel (RV) Polarstern from 26 May to 16 July 2017
as a part of the PASCAL/SiPCA campaign. Here, regional NPF events are
analyzed and put into prospective of producing the CCN. From the
measurements of neutral cluster and air ion number size distributions, it
can be concluded that new particles were formed within the marine boundary
layer and not mixed down from aloft. Therefore, the majority of particles in
a size range up to 50 nm in diameter can be related to secondary aerosol
production rather than primary emissions. Two different types of NPF were
distinguished: (a) NPF favored by negative ions, and more-hygroscopic
nucleation mode particles; and (b) NPF with subsequent rapid growth (Event 2), resulting in less-hygroscopic particles. From analysis of particle
formation and growth rates, as well as the hygroscopicity of slightly grown
particles, it seems that sulfuric acid–water ion-mediated nucleation is an
acceptable mechanism explaining the observed NPF during events 1 and 4.
Meanwhile, low particle hygroscopicity and rapid growth suggest that
condensable organics were somewhat involved in particle growth during events 2 and 3. Although the imagery from satellites confirms the biological activity as a possible source of marine sulfur and organics, due to the lack of appropriate measurements, we cannot provide quantitative information about the extent to which these precursor gases may have been involved in the observed particle formation and growth. For the same matter, we also
cannot exclude other species (e.g., iodine) participating in NPF. To answer
these questions, high temporal resolution measurements of nucleation and the
Aitken mode particle chemical composition after the NPF are necessary, which
remain a topic for future research.
After the nucleation, in 12 to 56 h newly formed particles grew to the
Aitken mode sizes (approx. 30–50 nm). We have traced particle growth and
measured particle hygroscopicity for dry diameters of 15, 20, 30, and 50 nm. Here, one of our main objectives was to test whether particles
created in the Arctic marine boundary layer can act as CCN. To accomplish
this task we have used a zero-dimensional, adiabatic cloud parcel model.
Measured particle physico-chemical properties and ambient information
(relative humidity, pressure, temperature) were used to simulate particle
population activation to cloud droplets at two different updraft velocities
of 0.1 and 3.2 m s-1. Simulation results showed that although the
activated fractions of nucleation mode particles were below 5 % at an
updraft wind velocity of 0.1 m s-1, background CCN number concentration
increased by up to a factor of 5. The Aitken mode particle activation was
somewhat higher, approx. 12 %. Such an increase in CCN number concentrations
was also confirmed by direct measurements for supersaturations from 0.1 % to
1 % on-board RV Polarstern. Our findings support previous observations
suggesting that in a pristine Arctic environment particles do not have to grow
to sizes above 50 nm to act as CCN. We conclude that in a changing Arctic,
NPF can be an important source of CCN. New particle formation and the Aitken
mode particles' ability to become CCN require more in-depth studies with the
focus on mechanisms of NPF, chemical composition of the precursor gases and
condensable vapors, as well as the identification of their sources and
impact on Arctic clouds.
Data availability
Processed and raw data are available on request from the corresponding author.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-14339-2019-supplement.
Author contributions
SK operated aerosol instrumentation on-board RV Polarstern, evaluated
data, and wrote the manuscript.
TV operated aerosol instrumentation on-board RV Polarstern and
contributed to the manuscript writing.
PP, JL, and MK contributed to the NAIS data evaluation, discussion, and
manuscript writing.
DR contributed to the simulation of CCN.
HW contributed to the writing of the manuscript.
SZ and MvP collected samples for chemical analysis and contributed to the writing
of the manuscript.
MH operated the CCNC on-board RV Polarstern and evaluated CCNC data.
XG and AWe operated CCNC on-board RV Polarstern.
SH calibrated the CCNC prior measurement campaign.
FS, HH, and AWi participated in fund raising for the measurement campaign.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “Arctic mixed-phase clouds as studied during the ACLOUD/PASCAL campaigns in the framework of (AC)3 (ACP/AMT inter-journal SI)”. It is not associated with a conference.
Acknowledgements
We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft
(DFG, German Research Foundation) – Projektnummer 268020496 – TRR 172,
within the Transregional Collaborative Research Center “ArctiC
Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and
Feedback Mechanisms (AC)3, as well as funding of
RV Polarstern cruise PS106 (expedition grant number AWI-PS-106-00) by AWI.
The authors would also like to acknowledge a number of people who were involved
in this work. We acknowledge the discussions and support (H2SO4–H2O
nucleation look-up tables) by Fangqun Yu (UAlbany). We also thank Sebastian Ehrhart (MPIC), Joachim Curtius (IAU), Steffen Münch (ETHZ), and Andreas Kürten (IAU) for the discussions concerning sulfuric acid–water
nucleation, Ella-Maria Duplissy, Veli-Matti Kerminen, Jenni Kontkanen,
Stephany N. Buenrostro Mazon from Helsinki University for their time,
valuable suggestions, and discussions, Ulrike Egerer for providing the
updraft wind velocities during the ice-drift station, Hannes Griesche, Ronny Engelmann, and Martin Radenz for providing ship-based remote sensing data to
characterize the cloud situations during the selected events, Peter Gege
(DLR), Svenja Kohnemann (UniTrier), and Marcel Nicolaus (AWI) for sharing
the ship-deck photos, Andreas Macke (TROPOS) and Hauke Flores (AWI), Chief
Scientists of PS106 cruise, for the attitude and phenomenal attention to all
our requests regarding scientific activities on-board RV Polarstern and on
the ice, and finally, the RV Polarstern crew, staff members, numerous
scientists, and polar bear guards and watchers, who made the expedition not
only exceptional, but also a safe experience. Villum Research Station,
Robert Lange, Andreas Massling, Henrik Skov, and Niels Bohse Hendriksen are
acknowledged for providing PNSD data. We acknowledge Hartmut and Andrea Haudek for building the conditioning system for both the aerosol inlet and the
Berner impactor for these Arctic environmental conditions. Maik Merkel and
Rene Rabe were a huge technical support for setting up the measurement
container and Berner impactors. Susanne Fuchs performed the ion
chromatography analysis and Anke Rödger the OC/EC thermographic
analysis. We also acknowledge the use of imagery from the NASA Worldview
application (https://worldview.earthdata.nasa.gov, last access: 3 June 2019), part of the NASA Earth
Observing System Data and Information System (EOSDIS). Also, this study has
been conducted using E.U. Copernicus Marine Service Information (Arctic
Chlorophyll Concentration from Satellite observations (daily average)
Reprocessed L3 (ESA-CCI). We acknowledge two anonymous referees for their
time, comments, and suggestions, which improved the final version of the
manuscript.
Financial support
This research has been supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (grant no. 268020496 – TRR 172) and the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (grant no. AWI-PS-106-00).
Review statement
This paper was edited by Amy Solomon and reviewed by two anonymous referees.
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