Marine biota is an important source of atmospheric
aerosol particles in the remote marine atmosphere. However, the relationship between new particle formation and marine biota is poorly quantified.
Long-term observations (from 2009 to 2016) of the physical properties of
atmospheric aerosol particles measured at the Antarctic Peninsula (King
Sejong Station; 62.2∘ S, 58.8∘ W) and satellite-derived
estimates of the biological characteristics were analyzed to identify the
link between new particle formation and marine biota. New particle formation
events in the Antarctic atmosphere showed distinct seasonal variations, with the highest values occurring when the air mass originated from the ocean
domain during the productive austral summer (December, January and February).
Interestingly, new particle formation events were more frequent in the air
masses that originated from the Bellingshausen Sea than in those that
originated from the Weddell Sea. The monthly mean number concentration of
nanoparticles (2.5–10 nm in diameter) was >2-fold higher when the air
masses passed over the Bellingshausen Sea than the Weddell Sea, whereas the
biomass of phytoplankton in the Weddell Sea was more than ∼70 %
higher than that of the Bellingshausen Sea during the austral summer
period. Dimethyl sulfide (DMS) is of marine origin and its oxidative
products are known to be one of the major components in the formation of new
particles. Both satellite-derived estimates of the biological
characteristics (dimethylsulfoniopropionate, DMSP; precursor of DMS) and
phytoplankton taxonomic composition and in situ methanesulfonic acid (84
daily measurements during the summer period in 2013 and 2014) analysis
revealed that DMS(P)-rich phytoplankton were more dominant in the
Bellingshausen Sea than in the Weddell Sea. Furthermore, the number
concentration of nanoparticles was positively correlated with the biomass of
phytoplankton during the period when DMS(P)-rich phytoplankton predominate.
These results indicate that oceanic DMS emissions could play a key role in
the formation of new particles; moreover, the taxonomic composition of
phytoplankton could affect the formation of new particles in the Antarctic
Ocean.
Introduction
Aerosols in the atmosphere significantly influence radiative forcing
directly (by scattering incoming radiation) and indirectly (by modifying
cloud microphysical properties) (IPCC, 2013). Considering that the ocean
surface accounts for approximately 70 % of the total surface of the Earth,
the marine aerosols are globally one of the most important natural aerosol
systems (O'Dowd et al., 2004; Leck and Bigg, 2005; O'Dowd and De Leeuw,
2007). Marine aerosols consist of primary and secondary aerosols. The
primary aerosols are produced via the bubble bursting process and include
mostly sea salts and organic matter (O'Dowd and De Leeuw, 2007). Secondary
aerosols (resulting from gas-to-particle conversion) are produced in the
marine atmosphere through several different processes (e.g., binary, ternary
and ion-induced) (Kulmala and Laaksonen, 1990; Korhonen et al., 1999; Lee et al.,
2003; Lovejoy et al., 2004; Kirkby et al., 2016; Jokinen et al., 2018).
Biogenic volatile organic compounds emitted into the marine atmosphere
through air–sea gas exchange and their oxidative products can be involved
in new particle formation events via the nucleation of stable clusters of
the order of 0.5–1 nm in size (O'Dowd and De Leeuw, 2007).
In the Antarctic, most submicron aerosol particles are derived from natural
sources rather than from long-range transport of anthropogenic sources (Ito,
1989; Kyrö et al., 2013). The Southern Ocean has been considered as the
most significant source of secondary organic aerosols in the Antarctic
atmosphere, especially during the phytoplankton bloom period (Asmi et al.,
2010; Yu and Luo, 2010). Recent studies reported that biological (mostly
derived by sea-ice algae) and abiotic (photochemical reaction of halogen
compounds) processes occurring near sea-ice regions could significantly
influence the formation and growth of aerosol particles (Atkinson et al.,
2012; Kyrö et al., 2013; Allan et al., 2015; Dall'Osto et al., 2017, 2018).
Molecular level evidence of new particle formation via sequential
addition of iodine-containing species, which could be emitted from both open
water and sea-ice zones, was reported in the Arctic and Antarctic sites
(Sipilä et al., 2016). In addition, the emission of ammonia from seabird
colonies in polar regions could act as a key factor contributing to bursts
of newly formed particles (Weber et al., 1998; Croft et al., 2016). The
Antarctic Peninsula is one of the three areas of the globe facing drastic
regional warming, and it undergoes rapid environmental changes (i.e.,
increased temperature, acidification, shallowing mixed layer depth, sea-ice
decline, increased light, increased nutrient supply, reduced salinity and
glacial retreat) (Clarke et al., 2007; Deppeler and Davidson, 2017). Such
environmental changes in this region could significantly affect the marine
ecosystem. Marine phytoplankton influence aerosol properties by releasing
various organic compounds back into the atmosphere. The Antarctic Ocean is
known to be a significant source of numerous biogenic volatile organic
compounds including dimethyl sulfide (DMS), organic nitrogen and halogenated
organic compounds (Laturnus et al., 1996; Beyersdorf et al., 2010; Dall'Osto
et al., 2017; Giordano et al., 2017). In particular, the Antarctic Ocean is
the region with the highest sea-surface DMS concentration (Lana et al.,
2011). Observations of both DMS and its oxidative products (i.e.,
methanesulfonic acid (MSA) and non-sea-salt SO42-) in Antarctica
show a clear seasonal cycle with a minimum in austral winter and a maximum
in austral summer (Prospero et al., 1991; Minikin et al., 1998; Preunkert et
al., 2007; Read et al., 2008). DMS is produced by a complex marine biota
food-web mechanism (Stefels et al., 2007; Park et al., 2014a). Phytoplankton
produce dimethylsulfoniopropionate (DMSP) and then some of the DMSP is
converted into gaseous DMS through enzymatic cleavage (Simó, 2001). The
biogenic emission of DMS from the ocean is the largest natural sulfur source
to the atmosphere (Andreae, 1990), and the oxidation of DMS in the marine
atmosphere is a key process contributing to the formation of new particles
(Park et al., 2017). Once the DMS in the sea surface is emitted into the
atmosphere, it is rapidly converted into SO2 and MSA through the
photochemical oxidation process. The SO2 and MSA formed from DMS tend
to contribute to the formation of new particles via nucleation processes and
eventually serve as nuclei for cloud formation (Charlson et al., 1987).
Secondary organic aerosols contribute to a large fraction of the submicron
aerosol mass in the atmosphere, affecting clouds and climate (Jimenez et
al., 2009). However, secondary organic aerosols are a source of considerable
uncertainty in understanding current climate change (Shiraiwa et al., 2017).
In particular, the formation of new particles in the remote marine
atmosphere and their association with marine biota remain poorly
quantified.
In this study, we aimed to identify the link between new particle formation
and marine biota at a remote Antarctic site, where biological productivity
is the highest in the global ocean. To this end, we analyzed the physical
and chemical properties of aerosol particles at King Sejong Station
(62.2∘ S, 58.8∘ W) on the Antarctic Peninsula from 2009
to 2016. To study the oceanic biological characteristics surrounding the
observation site, we analyzed satellite-derived estimates including the
chlorophyll concentration, total DMSP concentration and taxonomic
composition of marine phytoplankton.
Experimental methodsAerosol measurements
King Sejong Station (62.2∘ S, 58.8∘ W) is located on the
Antarctic Peninsula, where severe climate change is occurring. The aerosol
observatory is approximately 400 m southwest of the main facilities of King
Sejong Station and approximately 10 m above sea level (m a.s.l.). Continuous
observations of the physical properties of aerosol particles in the
Antarctic atmosphere were conducted between March 2009 and December 2016 at
the observatory. The number concentration of aerosol particles (CN) was
measured using two condensation particle counters (CPCs) that have different
measurement range limits for particle diameter: particles larger than 2.5 nm
(CN2.5; TSI model 3776) and particles larger than 10 nm (CN10; TSI
model 3772) (Fig. 1a). The difference in the particle number concentration
between the two CPCs (i.e., particles between 2.5 and 10 nm in diameter) was
interpreted as an indication of the existence of newly formed nanoparticles
(CN2.5-10) (Fig. 1b). An Aethalometer (Magee Scientific model AE16) was
used to analyze the concentration of black carbon by measuring
light-absorbing particles at the 880 nm wavelength. To avoid local influence
on the aerosol properties, data with a black carbon concentration of
>100 ng were excluded. Data were also excluded when the wind
direction was between 355 and 55∘. This is because the
northeastern direction is designated the local air pollution sector due to
emissions from the power generators and crematory. More detailed information
regarding the aerosol particle analysis at King Sejong Station is provided
by Kim et al. (2017, 2019).
(a) Hourly variations in the number concentration of
particles >2.5 nm in diameter (CN2.5, blue symbols) and the
number concentration of particles >10 nm in diameter (CN10,
red symbols), (b) hourly variations in the number concentration of
nanoparticles (ranging from 2.5 to 10 nm in diameter) calculated using the
differences between CN2.5 and CN10, and (c) hourly variations in
the retention time of 2 d air mass back trajectories over the three
domains including ocean (blue), sea-ice (red), and land (black) domains from
March 2009 to November 2016.
For analysis of chemical properties of aerosol particles, an air sampler
equipped with a PM10 impactor (collecting particles <10µm
in aerodynamic equivalent diameter) was used to collect aerosol
particles. The sampler was mounted on the roof of the aerosol observatory
and sampled particles every 24 h during the summer period in 2013 and
2014 (explicitly, from 14 January to 28 February in 2013 and from 2 December 2013
to 18 January 2014). Half of a 47 mm Teflon filter was used to
measure major ions including MSA. The MSA (and the other ions) collected on
the filter was extracted into about 10 mL (18 MΩ Milli-Q) in
ultrasonic bath for 20 min. MSA was determined by an ion chromatography
system (Dionex, Thermo Fisher Scientific Inc.) following the procedure
described by Becagli et al. (2012). For MSA, reproducibility on real samples
was better than 5 %. Filter blank concentrations for methanesulfonate
were always below the detection limit.
Air mass back trajectories
The air mass back trajectories and meteorological parameters were obtained
using the Hybrid Single-Particle Lagrangian Integrated Trajectories model
(Draxler and Hess, 1998). In general, the growth rate of submicron
particles in the remote marine environment ranges from 0.2 to 5.0 nm h-1
(Järvinen et al., 2013; Weller et al., 2015; Kerminen et al.,
2018), and the mean growth rate of the aerosol particles measured at the
King Sejong Station was approximately 0.7±0.3 nm h-1 during the
8 years (Kim et al., 2019). Therefore, the 2 d air mass back
trajectories and hourly positions were determined and combined with
satellite-derived geographical information to identify the travel history of
the air mass arriving at the observation site. Daily geographical
information on sea-ice, land and ocean area was obtained from the Sea Ice
Index at a 25 km resolution provided by the National Snow and Ice Data
Center (NSIDC). The oceanic region adjacent to the observation site was
surrounded by two different ocean basins, namely, the Bellingshausen and
Weddell seas. To evaluate the influence of the oceanic biological
characteristics on the occurrence of new particle formation, we limited our
analysis to the air masses that had exposure predominantly to the ocean
area. Specifically, the origin of the hourly air mass arriving at the
observation site was divided into two ocean domains (i.e., the
Bellingshausen and Weddell seas). Then, all air mass back trajectories were
grouped into one of the two ocean domains by only selecting the 2 d air
mass back trajectories that had >90 % retention in a given
ocean domain.
A total of 84 PM10 samples for MSA analysis were collected daily during
the summer periods in 2013 and 2014. The retention time of the aerosol
particles with a diameter <10µm is known to be
approximately 3–5 d in the atmosphere (Mishra et al., 2004; Budhavant et
al., 2015). Therefore, 3, 4 and 5 d air mass back trajectories were
applied to identify the potential origin of MSA during the sampling period.
Phytoplankton biomass, DMSP and taxonomic composition analysis
Satellite-derived ocean color provides a good measure of analyzing the
phytoplankton characteristics of the Southern Ocean (Siegel et al., 2013;
Haëntjens et al., 2017). The phytoplankton biomass of the two ocean domains
was estimated by calculating the chlorophyll concentration from the Moderate
Resolution Imaging Spectroradiometer on the Aqua (MODIS-Aqua) satellite at
4 km resolution during the study period (2009–2016). The trajectory
concentration of the air masses originating from the two ocean domains was
calculated from the ratio of the number of hourly trajectory points passing
over each grid cell (1∘× 1∘) to the total
number of hourly trajectory points (Kim et al., 2011), as shown in Fig. 2a.
We limited our analysis of satellite-derived chlorophyll concentration to
the ocean area for which the trajectory concentration was approximately over
0.1 % (55–65∘ S, 40–60∘ W for the Weddell Sea and
55–65∘ S, 60–80∘ W for the Bellingshausen Sea). DMSP
is produced by marine phytoplankton and is the most important precursor of
oceanic DMS production. However, the dependence of the oceanic DMS emission
on phytoplankton biomass and DMSP concentration is not straightforward, owing
to the strong variabilities across taxonomic groups and the interplay with
environmental factors. Nevertheless, temporal and spatial distribution of
sea-surface DMSP could be an indicator of contemporary DMS emission. In
particular, the DMSP-to-chlorophyll ratio could represent the potential DMS-production capacity of the ocean because the phytoplankton species with
higher cellular DMSP content (i.e., higher DMSP-to-chlorophyll ratio) mostly
possess an enzyme that can convert cellular DMSP into DMS, whereas
phytoplankton species containing lower DMSP content (i.e., lower
DMSP-to-chlorophyll ratio) do not have a DMSP cleavage enzyme (Stefels et
al., 2007; Park et al., 2014b, 2018). The total DMSP concentration in the
sea surface was estimated using the algorithm developed by Galí et
al. (2015). The algorithm for the total DMSP concentration was based on the
satellite-derived chlorophyll concentration and the light exposure regime
(see Supplement for more information). We estimated the taxonomic
phytoplankton composition of the two ocean domains using the PHYSAT method.
This method is a bio-optic model that was specifically developed to identify
the dominant phytoplankton groups from ocean color measurements.
Phytoplankton groups are generally characterized by specific pigment, shape
and size and have different light scattering and absorption properties
(Alvain et al., 2005). The PHYSAT method was first developed in 2005 and was
used to classify sea-surface phytoplankton into four groups: diatoms,
Prochlorococcus, nanoeucaryotes, and Synechococcus (Alvain et al., 2005).
Subsequently, the modified PHYSAT method, which can estimate the
contribution of the Phaeocystis group, was reported in 2008 (Alvain et al.,
2008). The PHYSAT method was developed and calibrated based on global data
obtained from the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) operated
from September 1997 to December 2010. In this study, the monthly dataset of
five phytoplankton groups at a resolution of 9 km was obtained from the
PHYSAT database (http://log.univ-littoral.fr/Physat, last access:
15 Marhc 2019) estimated using
climatology over the SeaWiFS period (1997–2010). Note that “dominant” has
been defined as situations in which a given phytoplankton group is a major
contributor to the total pigment in a given 9 km resolution (Alvain et al.,
2005, 2008).
(a) Back trajectories of the air masses arriving at King Sejong
Station (62.2∘ S, 58.8∘ W; star symbol), Antarctic Peninsula. The
colors indicate the percentage (%) of the air mass located at that spot
during the 2 d prior to arriving at the observation site. Note that the
air mass back trajectories that did not have >90 % retention
in the two selected ocean domains (i.e., Bellingshausen and Weddell seas)
were excluded. (b) Seasonal variation of nanoparticles (2.5–10 nm in
diameter, CN2.5-10) observed at King Sejong Station between March 2009
and December 2016. Blue and red symbols indicate the number concentration of
nanoparticles that originated from the Bellingshausen and Weddell seas,
respectively. The error bars indicate the 95 % confidence interval
estimated by bootstrap method from the monthly CN2.5-10 data.
Results and discussionSeasonal variabilities of nanoparticles at King Sejong Station
The number concentration of aerosol particles increased gradually from early
spring, peaked in the austral summer period (December, January and February)
and then began to decrease (Fig. 1a). The number concentration of
nanoparticles (2.5–10 nm in diameter, CN2.5-10), which is an
indication of newly formed particles, also shows distinct seasonal variation
(Fig. 1b). A detailed explanation of physical characteristics of new
particle formation events (e.g., frequency, formation rate and growth rate)
at King Sejong Station during the same period is explained in Kim et
al. (2019). The observation site is surrounded by ocean, sea-ice and land
domains, which may influence new particle formation in different ways. The
2 d air mass back trajectory combined with geographical information showed
that approximately 66 % of the hourly trajectory points were assigned to
the ocean, followed by sea ice (29 %) and land (6 %) during the entire
study period (Figs. 1c and S1a in the Supplement). The percentage of hourly trajectory points that passed over the ocean domain was at its maximum during the
summer period (79 %) when the extent of sea ice was at its minimum
(Fig. S1b). Kim et al. (2019) reported that a total of 101 days were defined as new particle formation events during the 8 years and 80 days of new
particle formation events occurred when the air mass originated from the
ocean domain. Furthermore, 16 days of new particle formation events were
observed for the air masses originating from the Antarctic Peninsula. The
remaining five days of events were considered as those of South American
origin (three events) and undefined (two events) (see Kim et al., 2019, for
the detailed definition and categorization of new particle formation
events). The relationship between new particle formation and environmental
parameters is complicated, owing to the interplay among multiple sources and
complicated processes. The number concentration of the nanoparticles was at
its maximum during the productive summer period, and the frequency of new
particle formation was the highest when the air mass originated from the
ocean domain. Therefore, we focused on the influence of marine biota on the
formation of nanoparticles. The hourly mean concentration of nanoparticles
matched with the hourly air mass back trajectory in this study. A total of
22 469 hourly mean number concentrations of nanoparticles were measured
above the Antarctic atmosphere over the 8 years. Approximately 38.2 %
of the hourly mean number concentration of nanoparticles, which satisfies the
>90 % retention of hourly trajectory points over the two ocean
domains, was used to estimate the link between new particle formation and
the oceanic biological characteristics around the observation site. The
remaining 61.8 % of the hourly mean number concentration of nanoparticles,
which does not satisfy the >90 % retention over the two ocean
domains, was excluded from further analysis. Interestingly, the monthly
mean number concentration of nanoparticles that originated from the
Bellingshausen Sea was highest in January (836±2673 cm-3) and
∼2.5 times greater than that which originated from the
Weddell Sea (332±921 cm-3; Fig. 2b and Table S1). The
differences in the number concentration of nanoparticles that originated
from the two ocean domains were particularly noticeable during the austral
summer period (568±249 cm-3 for the Bellingshausen Sea and
262±66 cm-3 for the Weddell Sea). However, the differences were not
evident between March and November (97±51 cm-3 for the
Bellingshausen Sea and 73±57 cm-3 for the Weddell Sea; Fig. 2b).
Biological characteristics surrounding the observation site
In general, the abundance and composition of phytoplankton show distinct
spatial and seasonal variation in the Antarctic Ocean (Sullivan et al.,
1993). Primary production in the Antarctic Ocean is strongly controlled by
various factors such as iron limitation, light availability and mixed layer
depth (Arrigo et al., 1999; Sedwick et al., 2007; Park et al., 2013a). The
composition of the phytoplankton community is poorly studied in the
Antarctic Ocean except for the marginal zone at the Antarctic Peninsula.
Nevertheless, both Phaeocystis and diatoms (mainly Phaeocystis antarctica
and Fragilariopsis cylindrus) are well known as
dominant phytoplankton groups in the Antarctic Ocean during the
phytoplankton bloom period (Kropuenske et al., 2009; Arrigo et al., 2010).
Both diatoms and Phaeocystis, considered the most ecologically important
phytoplanktonic groups, contribute >20 % of the global primary
productivity and are particularly abundant at high latitudes (Schoemann et
al., 2005; Malviya et al., 2016). The monthly mean chlorophyll concentration
around the observation site (55–65∘ S, 40–80∘ W)
began to increase in October and reached its maximum in November and
December during the study period (Fig. S2a). The biological characteristics
of the two ocean domains showed notable differences. The monthly mean
chlorophyll concentration in the Weddell Sea (0.49±0.07 mg m-3)
was ∼70 % higher than that of the Bellingshausen Sea (0.29±0.05 mg m-3)
during the phytoplankton growth period
(October–February; Figs. 3a and S2b). The PHYSAT analysis, which was
estimated using the SeaWiFS climatology map, revealed that the distribution
of the dominant phytoplankton groups showed distinct patterns (Fig. 3c).
Diatoms were the most abundant, and the dominance of the diatoms was
∼35 % during the austral summer period in the Weddell Sea,
followed by nanoeucaryotes (20 %), Phaeocystis (17 %), Prochlorococcus
(15 %) and Synechococcus (14 %) (Figs. 3c and S3b). Conversely, the
dominance of Phaeocystis increased significantly and accounted for more than
50 % in the Bellingshausen Sea during the austral summer period, while the
contribution of the diatoms decreased below 10 % (Figs. 3c and S3a).
Although the period considered for the SeaWiFS archive (from September 1997
to December 2010) did not coincide with the period of aerosol particle
observation at the King Sejong Station (from March 2009 to December 2016),
the PHYSAT analysis performed using the SeaWiFS climatology map was
successfully applied to the Southern Ocean and could represent the general
seasonal trend of the taxonomic composition of marine phytoplankton in the
study area (Alvain and d'Ovidio, 2014; Mustapha et al., 2014). Recently, a
regional PHYSAT algorithm for the Mediterranean Sea was developed by
applying linear interpolation between SeaWiFS and MODIS wavelengths and
reflectance threshold (Navarro et al., 2014). However, challenges remain in
high-latitude areas such as the Southern Ocean, especially because of the
rather sparse matchup available for the calibration and validation of the
PHYSAT algorithm (Alvain et al., 2014).
(a) Monthly mean chlorophyll concentration during the months of
December, January and February in 2009–2016; (b) monthly mean DMSP
concentration during the months of December, January and February in
2009–2016; (c) phytoplankton taxonomic composition including diatoms (DIA),
Prochlorococcus (PRO), nanoeucaryotes (NEU), Synechococcus (SLC) and
Phaeocystis (PHA) estimated using the PHYSAT method with the climatology map
obtained from the SeaWiFS archive; and (d) monthly mean DMSP-to-chlorophyll
ratio during the months of December, January and February in 2009–2016.
Enzymatic cleavage of planktonic DMSP into DMS is the major source of DMS,
and the production of DMS and DMSP is species-specific. For example,
diatoms, picoplankton (i.e., Synechococcus and Prochlorococcus) and most
nanoeucaryotes are known to be DMS(P)-poor species. Conversely, Phaeocystis
and dinoflagellates have a high cellular DMSP content and many of them
possess a DMSP cleavage enzyme that can convert DMSP into gaseous DMS
(Keller et al., 1989; Stefels et al., 2007; Park et al., 2014b). The conversion of
cellular DMSP into DMS is controlled by not only the concentration of DMSP
but also, more importantly, by the DMSP cleavage enzyme. DMS is often
produced following the local chlorophyll maxima, leading to a lag period
(several weeks to months) (Polimene et al., 2012). This phenomenon is
evident when the concentration of DMSP is largely contributed by DMSP-poor
species such as diatoms. Most DMSP-poor species do not possess a DMSP
cleavage enzyme, and therefore the conversion of DMSP into DMS occurs when
the cellular DMSP is released into the ocean as a form of dissolved matter.
Subsequently, some dissolved DMSP degrades into gaseous DMS through the
bacterial DMSP enzymatic cleavage (Simó, 2001; Stefels et al., 2007).
However, a larger proportion of dissolved DMSP is assimilated into bacterial
tissues through demethylation processes, which do not produce gaseous DMS
(Todd et al., 2007; Reisch et al., 2011). A direct correlation between the
local chlorophyll concentration and atmospheric DMS mixing ratio in the
absence of lag periods was observed in the Arctic Ocean where Phaeocystis pouchetii (containing
both high cellular DMSP and DMSP cleavage enzyme) dominates (Park et al.,
2013b). Moreover, the DMS-production capacity in the Arctic Ocean was more
significantly controlled by the abundance of DMSP-rich phytoplankton than
the total biomass of phytoplankton (Park et al., 2018). These results
indicate that the blooming of phytoplankton species containing higher
cellular DMSP content results in a much higher DMS-production capacity than
the blooming of DMSP-poor phytoplankton species. Therefore, the
DMSP-to-chlorophyll ratio is commonly used to explain the differences in
taxonomic compositions affecting the oceanic DMS-production capacity (e.g.,
Belviso et al., 2000; Stefels et al., 2007; Tison et al., 2010; Park et al.,
2014b, 2018). In particular, Phaeocystisantarctica was reported to be a dominant species in
terms of DMS production in the Antarctic Ocean during the bloom period
(Gibson et al., 1990; Schoemann et al., 2005), exhibiting a cellular DMSP
concentration in Phaeocystis several times that of diatoms (Hatton and
Wilson, 2007; Stefels et al., 2007). The sea-surface DMSP concentration
surrounding the observation site was estimated using a newly developed
algorithm and was 30 % higher in the Weddell Sea than in the
Bellingshausen Sea during the summer period, possibly owing to intense
blooming of DMSP-containing diatoms in the Weddell Sea (Figs. 3b and
S4a). This could illustrate that, despite having lower cellular DMSP content
than Phaeocystis, diatoms dominated the overall DMSP production in the
Weddell Sea owing to their much larger biomass. However, the
DMSP-to-chlorophyll ratio in the Bellingshausen Sea (110.2±27.8 mmol g-1)
was ∼2-fold higher than that of the Weddell Sea
(72.2±8.3 mmol g-1) between December and February in 2009–2016
(Figs. 3d and S4b), possibly owing to the relatively higher contribution
of the DMSP-rich Phaeocystis group in the Bellingshausen Sea.
Influence of phytoplankton on aerosol formation
Biogenic trace gases produced by marine phytoplankton (i.e., DMS, isoprene
and halogenated gases) are known to be the key compounds contributing to the
formation of new particles in the remote marine environment; however,
quantifying the relationship between new particle formation events and
marine biology is a major challenge (Brooks and Thornton, 2018). MSA in the
marine atmosphere forms exclusively from the photooxidation of DMS and
shows strong seasonal variation (Ayers and Gras, 1991; Savoie et al., 1993;
Preunkert et al., 2008). A previous study has reported that the highest
values for both MSA and the scattering Ångström exponent (SAE;
qualitative examination of the aerosol optical mean size) were observed at
the Marambio Station (64.3∘ S, 56.6∘ W) on the Antarctic
Peninsula during austral summer in 2013–2015 (Asmi et al., 2018). The MSA
concentration of the fine aerosol particles measured at the King Sejong
Station during the summer period in 2013 and 2014 was broadly consistent
with the number concentration of nanoparticles. The MSA concentration shows
distinct daily variations. The mean MSA concentration was 72.6±99.1 ng m-3
(ranged from 4.2 to 657.0 ng m-3) (Fig. 4a), similar to the
values observed at six Antarctic sites during the productive summer period
(e.g., Prospero et al., 1991; Minikin et al., 1998; Preunkert et al., 2007;
Read et al., 2008; Zhang et al., 2015; Asmi et al., 2018). To identify the
potential origin of MSA, air mass back trajectories were determined and the
retention time above each domain was averaged for the corresponding 24 h
sampling time. When applying 3, 4 and 5 d air mass back trajectories,
the number of samples that satisfy >90 % retention in the
Bellingshausen and Weddell seas was less than 20 % of the total MSA
samples, owing to the longer transport pathway of the fine aerosol particles. Inevitably, the air mass
origin of MSA was divided into two sectors, i.e., the Bellingshausen Sea
sector (<58.8∘ W) and the Weddell Sea sector (>58.8∘ W),
by selecting the air mass back trajectories with >50 % retention in a given sector. Although the limited number of samples
of MSA (84 samples at daily intervals) collected during the summer periods
in 2013 and 2014 may not be sufficient to identify its source origin
exactly, the MSA concentration also showed distinct differences depending on
the air mass origin. The inflow of the air masses from the Bellingshausen
Sea increased the concentration of MSA in the aerosol particles. Notably,
the MSA concentration that originated from the Bellingshausen Sea sector
(87.6±110.0, 86.6±110.0 and 83.9±109.0 ng m-3
for 3, 4 and 5 d estimates based on air mass back trajectories,
respectively) was ∼3 times higher than that which originated
from the Weddell Sea sector (27.4±19.3, 30.6±27.5 and 33.9±30.4 ng m-3 for 3, 4 and 5 d estimates based on air mass back trajectories, respectively) during the austral summer period in
2013–2014 (Fig. 4b). Although the period of satellite observations and in
situ chemistry analysis is not exactly the same, both satellite-derived
biological characteristics and aerosol chemistry data support the
interpretation that there was higher abundance of DMS(P)-rich phytoplankton
in the Bellingshausen Sea than in the Weddell Sea during the austral summer
period (Figs. 3, 4, S2, S3 and S4).
(a) Daily concentration of MSA collected at the sampling site
during the summer periods in 2013 and 2014 (explicitly, from 14 January to
28 February in 2013 and from 2 December 2013 to 18 January 2014). (b) The
mean MSA concentration that potentially originated from the Bellingshausen
Sea sector (<58.8∘ W) and the Weddell Sea sector
(>58.8∘ W) estimated by applying 3, 4 and 5 d air mass back
trajectories during the austral summer periods in 2013 and 2014. The error
bars indicate 1 standard deviation (1σ) from the mean values.
In the 8-year record, the monthly mean chlorophyll concentration was
positively correlated with the monthly mean number concentration of
nanoparticles for the air masses that originated from the Bellingshausen Sea
in January and February (r2=0.69, n=12, P<0.05; Fig. 5a).
During this period, the contribution of the DMS(P)-rich Phaeocystis to the chlorophyll concentration was highest in the Bellingshausen Sea (i.e.,
DMSP-to-chlorophyll ratio >100 mmol g-1; dominance of
Phaeocystis>50 %; dominance of diatoms <10 %; Figs. 3, S3a
and S4). Conversely, the increase in the chlorophyll
concentration was not correlated with the increase in the number
concentration of nanoparticles in the Weddell Sea (Fig. 5b). As a
consequence, the higher occurrence of nanoparticles from the Bellingshausen
Sea inferred from our analysis was likely to be associated with a higher
abundance of DMS(P)-rich phytoplankton, whereas the lower occurrence of
nanoparticles from the Weddell Sea appeared to be associated with a higher
abundance of DMS(P)-poor phytoplankton.
(a) Relationship between the monthly mean chlorophyll
concentration for the Bellingshausen Sea (55–65∘ S,
60–80∘ W) and the monthly mean number concentration
of nanoparticles that originated from the Bellingshausen Sea in 2009–2016.
(b) Relationship between the monthly mean chlorophyll concentration for the
Weddell Sea (55–65∘ S, 40–60∘ W) and the monthly mean number concentration of
nanoparticles that originated from the Weddell Sea in 2009–2016. The filled
blue, filled red and open red symbols indicate the data obtained in
December, January and February, respectively. The solid lines represent the
best fit.
Conclusions
The physical properties of aerosol particles measured above the remote
Antarctic Peninsula over 8 years were analyzed in conjunction with the
satellite-derived biological characteristics around the observation site.
These results show that the formation of nanoparticles was strongly
associated not only with the biomass of phytoplankton but, more importantly,
also its taxonomic composition in the Antarctic Ocean. Previous studies have
reported that diatoms have a competitive advantage under conditions in which
the mixed layers are shallow and the light levels are relatively high.
Conversely, Phaeocystis is well adapted to conditions in which mixed layers
are deep and light levels are variable (e.g., Weber and El-Sayed, 1987;
Arrigo et al., 1999, 2010; Goffart et al., 2000; Alvain et al., 2008). These results are consistent with the distribution of
phytoplankton groups in the Bellingshausen and Weddell seas. Given that the
mixed layer depth in the Bellingshausen Sea (45.6±4.1 m) was
relatively deeper than that of the Weddell Sea (36.2±3.8 m; Fig. S6)
during the austral summer period, the growth of DMS(P)-rich Phaeocystis may
therefore be more favorable in the Bellingshausen Sea. Sea-surface warming
and freshening is commonly associated with a shallowing of the mixed layer
depth (Capotondi et al., 2012). The warming trend has shown the spatial
complexity across the Antarctic Ocean in recent decades (Turner et al.,
2005). Therefore, all regions of the Antarctic Ocean will experience
different changes in phytoplankton productivity and taxonomic composition in
response to the climate change (Deppeler and Davidson, 2017).
In this study, we have focused on the relationship between the formation of
nanoparticles and marine biota. The formation of secondary aerosols
contributes significantly to the atmospheric aerosol number and accounts for
30 %–80 % of the global cloud condensation nuclei (Merikanto et al., 2009;
Westervelt et al., 2014; Sanchez et al., 2018; Sullivan et al., 2018). Our
results indicate that changes in the taxonomic composition of marine
phytoplankton (i.e., DMS(P)-rich species vs. DMS(P)-poor species) could have
a significant impact on the aerosol properties in the remote marine
environment. Precursors other than biogenic DMS could play a key role in the
formation of new particles in the Antarctic atmosphere. In fact, 16 days of
new particle formation events out of 101 events were observed when the air
mass originated from the Antarctic Peninsula during the study period.
Penguin colonies are dispersed throughout the Antarctic Peninsula (Croxall
et al., 2002), and the emission of ammonia from these colonies could trigger
the formation of nanoparticles (Weber et al., 1998; Croft et al., 2016).
Moreover, iodine molecules produced by biotic and abiotic processes near
sea-ice regions are known to influence the formation of aerosol particles
(Allan et al., 2015; Sipilä et al., 2016). Future studies are required
to minimize the knowledge gaps related to multiple precursors and their
source origins. Specifically, continuous measurements of the physiochemical
properties of aerosol particles and molecular-scale measurements of chemical
species (e.g., sulfur-, nitrogen-, and halogen-containing compounds)
involved in nucleation processes are required to provide direct evidence for
the contribution of these compounds to the formation and growth of aerosol
particles and to understand their climate feedback roles in the remote
marine environment.
Data availability
The data used in this publication will be readily provided
upon request to the corresponding author (ktpark@kopri.re.kr).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-7595-2019-supplement.
Author contributions
KTP, JEH, JSK, TWK and YYJ designed the study.
YYJ and YTG analyzed the physical properties of the aerosol particles.
HSB, SB and RT operated the air sampler and analyzed the MSA. KTP and
JEH wrote the manuscript. KTP and JEH contributed equally to this work.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
We thank the overwintering staff for assisting us in maintaining the aerosol equipment at the King Sejong Station.
Financial support
This research has been supported by the Korea Polar
Research Institute (grant no. PE19010 and PE19140).
Review statement
This paper was edited by Veli-Matti Kerminen and reviewed by three anonymous referees.
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