ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus GmbHGöttingen, Germany10.5194/acp-15-5599-2015Iodine observed in new particle formation events in the Arctic
atmosphere during ACCACIAAllanJ. D.james.allan@manchester.ac.ukhttps://orcid.org/0000-0001-6492-4876WilliamsP. I.NajeraJ.WhiteheadJ. D.FlynnM. J.TaylorJ. W.https://orcid.org/0000-0002-2120-186XLiuD.https://orcid.org/0000-0003-3768-1770DarbyshireE.https://orcid.org/0000-0002-5119-7259CarpenterL. J.ChanceR.AndrewsS. J.HackenbergS. C.McFiggansG.https://orcid.org/0000-0002-3423-7896School of Earth, Atmospheric and Environmental Sciences,
University of Manchester, Oxford Road, Manchester M13 9PL, UKNational Centre for Atmospheric Science, University of
Manchester, Oxford Road, Manchester M13 9PL, UKWolfson Atmospheric Chemistry Laboratory, Department of
Chemistry, University of York, Heslington, York, YO10 5DD, UKJ. D. Allan (james.allan@manchester.ac.uk)21May20151510559956093November201420November201417March201530April2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/15/5599/2015/acp-15-5599-2015.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/15/5599/2015/acp-15-5599-2015.pdf
Accurately accounting for new particle formation (NPF) is crucial to our
ability to predict aerosol number concentrations in many environments and
thus cloud properties, which is in turn vital in simulating radiative
transfer and climate. Here we present an analysis of NPF events observed in
the Greenland Sea during the summertime as part of the Aerosol-Cloud
Coupling And Climate Interactions in the Arctic (ACCACIA) project. While NPF
events have been reported in the Arctic before, we were able, for the first
time, to detect iodine in the growing particles using an Aerosol Mass
Spectrometer (AMS) during a persistent event in the region of the coastal
sea-ice near Greenland. Given the potency of iodine as a nucleation
precursor, the results imply that iodine was responsible for the initial
NPF, a phenomenon that has been reported at lower latitudes and associated
with molecular iodine emissions from coastal macroalgae. The initial source
of iodine in this instance is not clear, but it was associated with air
originating approximately 1 day previously over melting coastal sea-ice.
These results show that atmospheric models must consider iodine as a source
of new particles in addition to established precursors such as sulfur
compounds.
Introduction
In the Arctic, clouds are the dominant factor in the control of the incoming
and outgoing energy balance at the Earth's surface and, here and throughout
the troposphere, the largest single source of uncertainty in climate
predictions. Understanding processes governing atmospheric aerosol
concentrations is critically important to improved prediction of clouds and
thus weather and climate (Boucher et al., 2013). The optical thickness and
lifetime of clouds can be strongly influenced by the population of aerosol
particles available to act as cloud condensation nuclei (CCN) (Haywood and
Boucher, 2000). Particle concentrations in the summertime Arctic are
typically very low (of the order of 102 cm-3) and therefore cloud
properties in this region are highly sensitive to the mechanisms by which
new particles are formed and are grown to viable CCN sizes (roughly 50–100 nm,
depending on the cloud conditions) (Merikanto et al., 2009).
Understanding these processes is crucial to our predictive capability of
climate in the Arctic, as clouds can have a strong warming or cooling
effect, depending on a variety of conditions (Hodson et al., 2013).
New particle formation (NPF) can dramatically increase aerosol number
concentrations in the atmosphere (Kulmala et al., 2004; Spracklen et al.,
2006), alongside direct emissions of particles (e.g. through combustion, sea
spray and dust suspension), contributing up to half of the global CCN
burden (Merikanto et al., 2009; Yu and Luo, 2009). NPF generally occurs
through the rapid photochemical production of low vapour pressure secondary
material such that stable molecular clusters are able to grow to viable
sizes (nm) (Kulmala et al., 2013, 2000). As they grow, the
freshly nucleated particles act as sinks for the secondary condensable
material, potentially shutting off the nucleation process. NPF has been
observed in a variety of different environments across the world. The role
of sulfuric acid (produced in the atmosphere from the gas phase oxidation
of marine biogenic dimethyl sulfide or SO2 from fossil fuel burning or
volcanoes) and organic matter (chiefly from terrestrial biogenic sources)
has been extensively studied (e.g. Laaksonen et al., 2008; Q. Zhang et al.,
2004; Riccobono et al., 2014) and it has also been shown that ammonia and
amines have very important roles in promoting NPF through ternary processes
(Kirkby et al., 2011; Almeida et al., 2013; Berndt et al., 2014).
Because of the generally low CCN number concentrations present, the Arctic
atmosphere is highly sensitive to NPF. This in turn means that predictions
of CCN are highly sensitive to the processes responsible for NPF, which are
currently highly uncertain in this environment (Lee et al., 2012). NPF has
previously been observed during Arctic ship-based measurements and given the
lack of significant biogenic or anthropogenic sources of organic precursors,
most efforts to model these observations have only invoked NPF from the
oxidation of sulfur species (Korhonen et al., 2008). An alternative
hypothesis is that rather than nucleation, the initial source of the new
particles is the fission of organic biogels (aggregations of biological
macromolecules) in primary particles (Karl et al., 2013, 2012).
In coastal environments at lower latitudes, frequent daytime NPF events have
been observed associated with gaseous iodine at low tide. This suggests that
in these environments, iodine is the dominant source of nanoparticles, which
have been observed to grow to larger sizes able to scatter radiation and
contribute to CCN (McFiggans et al., 2004, 2010; O'Dowd et
al., 2002; Whitehead et al., 2009; Yoon et al., 2006; Lehtipalo et al.,
2010). Gaseous I2 is produced in abundance by macroalgae species
(Laminaria digitata, Fucus vesiculosus and Ascophyllum nodosum have been identified as being
responsible for NPF) in response to being exposed to the atmosphere
(Küpper et al., 2008; Huang et al., 2013) and is rapidly photo-oxidised
to iodine monoxide (IO) and higher iodine oxides, which polymerise to form
particles (Saiz-Lopez et al., 2012; Saunders et al., 2010). To date,
iodine-initiated NPF has most commonly been observed in seaweed-rich coastal
areas but the theoretical potential exists in low background aerosol
conditions with associated high iodine fluxes (Mahajan et al., 2010).
Atkinson et al. (2012) attributed NPF events observed in the Weddell Sea in
Antarctica to iodine emissions from sea-ice, although no data on aerosol
composition were presented.
Here we present data on NPF events recorded aboard the RRS James Clark Ross
in the Greenland Sea during the summer ACCACIA cruise. Through the analysis
of a particularly strong and persistent case study, we show evidence for the
role of iodine in NPF events in this region.
Methods
As part of the Aerosol-Cloud Coupling And Climate Interactions in the Arctic
(ACCACIA) project, intensive measurements of aerosol composition and
properties were made aboard the RRS James Clark Ross, an ice-hardened research vessel. The
cruise (JR288) consisted of a number of traverses in and out of the sea-ice
margin in the region of Greenland and Svalbard during July and August 2013
(see Fig. 1).
(a) Cruise track (purple), ice coverage and locations of
NPF events (red), defined by the presence of a mode of particles smaller than
10 nm not attributable to combustion or ship emissions (parts of the cruise
outside of the area depicted did not show evidence of NPF). (b)
HYSPLIT back trajectories from cruise track corresponding to the 25–27 July
case study. Markers are at 6-hourly intervals. (c) Ratio of
atmospheric concentrations of CH2Br2 (a product of ice diatom
activity) to its saturation levels in seawater.
The University of Manchester instrumentation was located in an instrumented
sea container on the foredeck of the James Clark Ross, sampling air through a 5 m stack
via a 3.5 µm cut cyclone, as has been performed during previous
measurement campaigns (Allan et al., 2009). No attempt to correct for
size-dependent particle losses has been made for this work, as it will not
affect the qualitative results presented here. No in-line drier was used, as
the relative humidity (RH) in the container was maintained low due to the
temperature differential. A number of instruments sub-sampled from the main
inlet manifold.
A Differential Mobility Particle Sizer (DMPS) system was used to measure
size-resolved particle number concentrations. This was built at the
University of Manchester (Williams et al., 2007) using dual `Vienna' design
Differential Mobility Analysers (DMAs) (Winklmayr et al., 1991) of different
lengths (to cover different particle size ranges) with stepping voltages,
selecting negatively charged particles. TSI (Shoreview, MN, USA) model 3010
and 3025a Condensation Particle Counters (CPCs) were used to count the
particles and the Wiedensohler (1988) charging parameterisation used to
invert the data. The sheath air system uses a recirculating system dried to
a low (< 20 % RH) humidity using a membrane drier linked to a dry
compressed air system. Total number concentrations were provided by a TSI
model 3776 CPC.
An Aerodyne (Billerica, MA, USA) Aerosol Mass Spectrometer (AMS) of the High
Resolution Time-of-Flight (HR-TOF) design (Canagaratna et al., 2007) was
also used to measure particle composition. Calibrations were performed using
monodisperse ammonium nitrate for mass and NIST-certified Polystyrene Latex
(PSL) Spheres (Thermo Scientific) for size. The data were collected in `V'
and `W' mass spectral modes, which have m/Δm resolutions of 2100 and
4300 at m/z=200 respectively (DeCarlo et al., 2006), although only `V' mode
data are presented here due because of the low signal-to-noise ratio of the
`W' mode data.
A Droplet Measurement Technologies (Boulder, CO, USA) Single Particle Soot
Photometer (SP2) was used to measure black carbon. This was a version `D'
instrument, calibrated using monodisperse Aquadag, scaled by a factor of
0.75 as recommended by Laborde et al. (2012)
Sub-saturated particle growth factors were measured using a Hygroscopicity
Tandem Differential Mobility Analyser (HTDMA). This was the second
Manchester-built instrument (Whitehead et al., 2014), conforming to EUSAAR
specifications (Duplissy et al., 2009). This uses two Brechtel Manufacturing
Inc. (Hayward, CA, USA) DMAs housed in temperature-controlled boxes and
linked in series. The first had dry sheath air (< 20 % RH) while
the sheath air in the second was maintained at 90 % RH, using a membrane
humidification system on a feedback loop with an Edgetech (Marlborough, MA,
USA) dew point monitor. The particles were counted using a TSI model 3782
water-based CPC. Sizes were calibrated with PSL spheres and humidity was
validated through the comparison of the measured deliquescence humidities of
ammonium sulfate and sodium chloride with modelled values (Topping et al.,
2005). Data were inverted using the method of Gysel et al. (2009).
Halocarbons were quantified in air and seawater using two Agilent 6850 gas
chromatographs (GC) with 5975C mass selective detectors (MSDs) coupled to
commercial thermal desorption units (TD, Markes Unity2-CIA8) in a system
described by Andrews et al. (2015). One instrument was dedicated to air
analysis and the other to water, and both instruments were calibrated daily
for halocarbons using NOAA gas standard SX-3570 (Jones et al., 2011).
Instrument drift was corrected for during (air analyses) or after (water
analyses) each sample using atmospheric carbon tetrachloride as an internal
standard. Underway seawater samples were collected from the pumped non-toxic
seawater supply of the ship using a semi-automated purge and trap system
plumbed directly into the underway supply. The sample lines and valves were
flushed with underway water before each sample. The 20 mL water samples were
pumped into the purge vessel (2 min sampling time) and purged with 1 L of
zero-grade nitrogen gas. Purge efficiencies were 100 ± 2 % for bromocarbons and 90 ± 10 %
for iodocarbons. All water samples were passed through an in-line
pre-combusted grade GF/F filter. A bake-out programme was also run between
each pair of air and water samples. The duration of each sampling cycle
(air–water–bake) was 65 min.
Back trajectory analysis was performed using HYSPLIT 4 (Draxler and Hess,
1998), employing GDAS reanalysis wind fields (NOAA Air Resources Laboratory,
Boulder, CO, USA). Back trajectories were started at 20 m a.m.s.l. and run using modelled vertical velocities.
Results
During the measurements, a number of events were noted in the DMPS data
whereby a large number of small particles contributed dramatically to the
ambient population. Contributions from combustion sources (e.g. ship plumes)
were eliminated by the lack of black carbon (BC) detectable by the SP2. The
data were also filtered according to short-lived spikes seen with the CPC
that could be associated with other sources from within the ship. The DMPS
occasionally showed “open” distributions, whereby the peak existed at or
below the lower size limit of the instrument (3 nm), providing evidence for
NPF (Fig. 2). Time periods where a significant portion of the detected
particles were smaller than 10 nm are identified in Fig. 1a, on an overlay
of the cruise track and sea-ice concentration data using the polar
stereographic product from the Special Sensor Microwave Imager/Sounder
(SSMIS) instrument on the Defense Meteorological Satellite Program (DMSP)
F17 platform (Cavalieri et al., 2013).
Temperature (T), relative humidity (RH) and total incident
radiation (TIR) during the cruise, with DMPS size-resolved number
concentration plotted data against electrical mobility diameter
(Dm). White areas on the plot denote instrument downtime or when
it was otherwise not sampling ambient air. Distributions from the seven
candidate events in Fig. 1 are shown below to illustrate the shapes of the
distributions during these events. Axis labels have been omitted for clarity,
but are the same as the plot above, i.e. dN/dlog(Dm)
(cm-3) vs. Dm (nm).
These periods all occurred in proximity to coastal locations around Iceland,
Greenland and Svalbard and the influence of terrestrial air is seen in the
lowering of the RH in Fig. 2, which is otherwise close to saturation. The
most significant and persistent of these events occurred between
25 and 27 July, when the ship was close to the sea-ice
margin off the coast of northeastern Greenland and the air had previously
travelled over the breaking sea-ice off Greenland (Fig. 1b). Markers for
microalgal activity in the form of CH2Br2 were also observed to be
elevated during this period (Fig. 1c). During this period, the nonrefractory
aerosol composition was mainly organic, with only around 0.1 µg m-3 of sulfate present (Fig. 3).
AMS-derived organic and sulfate mass concentrations, as calculated
using the standard fragmentation tables (see Sect. S2 in the Supplement).
Other commonly reported species (nitrate and ammonium) were below detection
limit outside of areas in close proximity to ports in the UK or Svalbard and
thus considered irrelevant. The period of the main case study is highlighted
in orange.
The candidate NPF events were also associated with elevated number
concentrations, with transitions over periods of hours (Figs. 2 and 4),
indicating that the new particles last long enough to grow to the larger
sizes that can contribute to CCN. It is likely that the transitions in the
size distributions resulted from changes to the source footprint in relation
to the position of the ship rather than in situ growth of the observed new
particles. While the growth events reported here may seem to resemble the
characteristic `banana' events observed at coastal sites and other locations
(Kulmala et al., 2004; Ehn et al., 2010; Yli-Juuti et al., 2011), they
differ in the following behaviour: (1) there are breaks in the growth
observed (e.g. 25 July, 00:00 UTC); (2) the apparent growth around 26 July, 20:00 is
exponential rather than linear in diameter space, and (3) the growth apparently
reverses at 26 July, 00:30 and 27 July, 09:00. It is worth noting that the
previously reported behaviours result from the diurnal modulation of
boundary layer dynamics and photochemistry caused by the local day–night
cycle in conjunction with a stable source footprint. This is not the case
here, due to continuous insolation and reduced dynamics of the marine
boundary layer, combined with a varying source footprint (due to the
movement of the ship and varying wind direction). Therefore, analogies with
the temporal behaviour at other locations cannot necessarily be drawn.
Size-resolved number concentrations
(dN/dlog(Dm)) from a differential mobility particle
sizer (DMPS) as a function of electrical mobility diameter (Dm),
total number concentrations (N) from a condensation particle counter (CPC)
and uncalibrated iodine ion concentrations from an AMS based on the signal at m/z=127 (I+) during the main case study.
White areas in the DMPS data show periods of ship influence or when the
instrument was not sampling ambient air.
AMS data for 25–27 July showed a
signal at m/z=127 during the periods when larger particles were present
(Fig. 4), which is identified as I+ ions by its precise mass/charge
ratio of 126.90 (Fig. S1.1 in the Supplement) (Wang et al., 2012). I+ has previously been
reported as the largest peak in photochemically produced iodine oxide AMS
mass spectra in the laboratory (McFiggans et al., 2004; Jimenez et al.,
2003), but this is the first time that it has been reported in ambient
particles. In previous coastal studies, owing to the proximity to the
initial source of iodine, particles did not grow to sizes large enough
(around 30 nm) to be transmitted by the AMS aerodynamic lens inlet (Liu et
al., 2007; Q. Zhang et al., 2004; X. F. Zhang et al., 2004). In this study, the
particles grew to sufficient sizes; however, it should be noted that the AMS
is still not able to observe iodine during the periods where the particles
were smaller than this, so does not see iodine during the very early stages
of growth.
To investigate whether the I+ signal could be associated with processes
governing the formation of organic aerosols (Fig. 3), Positive Matrix
Factorisation (PMF) was performed on the data (Paatero and Tapper, 1994;
Ulbrich et al., 2009). This assigns the organic mass to different `factors'
according to the temporal behaviour of the mass spectral matrix and is
detailed in Sect. S2 of the Supplement. Once shipping emissions
and misattributed sea salt are excluded, this analysis found that the
organic matter detected by the AMS could be attributed to methyl sulfonic
acid (MSA) (Phinney et al., 2006; Decesari et al., 2011) and
highly oxygenated organic material (McFiggans et al., 2005; Jimenez et al.,
2009). The I+ signal was not represented in any of the factors derived,
only manifested in the residual data, which implies that the particulate
iodine had a source that was distinct from the processes controlling the
formation of particulate organic matter (be they primary or secondary). A
further implication of the MSA observation is that this compound was at
least partly responsible for the reported sulfate concentrations, as this
also produces SO+ and SO2+ ions in the mass spectrum (Zorn et
al., 2008). Therefore, the actual non-sea salt sulfate concentration is
likely to be lower than what is reported, but the quantitative fraction of
MSA is difficult to estimate, as the fragmentation behaviour is highly
variable and not calibrated during this study.
Discussion
Size-resolved data from the DMPS and AMS, against electrical
mobility and vacuum aerodynamic diameters respectively, during the period of
highest iodine loading (26 July, 22:50–23:45 UTC) with lognormal nonlinear
least squares fits and associated standard errors, comparing DMPS volume with
AMS mass at m/z=127, corresponding to I+, and sulfate and organic
matter. The low signal-to-noise ratios of the AMS data are due to the low
concentrations and short averaging time. Note that the widths of the AMS
distributions should not be directly compared against the DMPS, as the AMS
distributions are subject to broadening introduced by the chopper wheel and
variations in particle density.
HTDMA-derived growth factor probability distribution functions for
50 nm dry particles at 90 % relative humidity, with associated mean growth
factors. The low growth factors associated with the case study time period
(26 July, 22:50–23:45 UTC) are highlighted.
To link the I+ signals detected by the AMS to the particles seen by the
DMPS, the size-resolved data from the two instruments were quantitatively
compared through the fitting of lognormal distributions. Shown in Fig. 5 are
the DMPS volume-weighted size distributions from the period of peak I+
concentrations (26 July, 22:50–23:45 UTC), together with the AMS Particle
Time-of-Flight size-resolved data for I+, organics and sulfate. The
AMS data were of a low signal-to-noise ratio, due to the short averaging time
and low signal levels (Allan et al., 2003); however, the fits converged
consistently using a standard Levenberg–Marquardt algorithm, with the peak
centres, widths and heights allowed to vary freely. The DMPS distribution is
bimodal, with the Aitken mode related to the I+ peak in the AMS data
and the accumulation mode related to the sulfate and organic modes. The
ratio of the fitted Aitken mode diameters yields a particle effective
density of 1.77 ± 0.23 g cm-3, which is typical of an inorganic
aerosol (Cross et al., 2007). Given that this quantity is a product of the
material density and the Jayne shape factor (DeCarlo et al., 2004; Jayne et
al., 2000), this may be an underestimate of the material density if the
particles are nonspherical, as has been suggested by electron microscopy of
laboratory-generated particles (McFiggans et al., 2004).
The shift in composition of these particles is also reflected in the HTDMA
data, which shows that during this period, the growth factor of 50 nm dry
particles at 90 % RH is 1.34, whereas for the rest of the cruise, values
were always greater than 1.5 (Fig. 6). The low growth factor and the density
estimate are consistent with iodine oxide making up a significant portion of
the particulate volume; I2O5 has a material density of 5 g cm-3 and laboratory studies have shown iodine oxide particles to
exhibit low growth factors (Jimenez et al., 2003; McFiggans et al., 2004;
Murray et al., 2012). This is different to what would be expected of organic
matter, which tends to be of a low density and low growth factor, and
inorganic salts and sulfuric acid, which are high density and high growth
factor (Cross et al., 2007; Gysel et al., 2007).
While the data discussed above provides strong evidence for the presence of
iodine in the particles during these events, it does not prove that iodine
was responsible for the initial NPF, which will have occurred upwind prior
to measurement. However, given the rapidity of the iodine oxidation process
and the very low volatility of the products (McFiggans et al., 2010;
Whitehead et al., 2009; Lehtipalo et al., 2010), it is reasonable to assume
that the presence of iodine-based secondary particulate matter implies that
iodine-initiated NPF was also occurring. It is also worth noting that
sulfate concentrations were low during the main case study, so this NPF
event did not occur during a period of particularly strong sulfuric acid
production.
In situ sea–air fluxes and atmospheric mixing ratios of iodocarbons
(CH3I, CH2I2 and CH2ICl) measured during the NPF event
were very low (< 2 nmol m-2 d-1 and ≈ 0.5 pptv
for CH3I; < 1 nmol m-2 d-1 and < 0.02 pptv
for both CH2I2 and CH2ICl, see Fig. S1.2). Although these
compounds are found in sea-ice (Atkinson et al., 2012; Granfors et al.,
2014) and have been shown to cause NPF in the laboratory (Jimenez et al.,
2003), the iodocarbon emissions and atmospheric concentrations found in this
and earlier studies are insufficient to sustain the very high local
concentrations of IO required for iodine nucleation (McFiggans et al.,
2004), suggesting the gaseous precursor may have been an inorganic form of
iodine such as I2.
The initial source of the iodine responsible for these events is not known.
Macroalgae have been identified as a molecular iodine source in midlatitude
coastal studies (Küpper et al., 2008; Huang et al., 2013) and macroalgae
beds containing kelps and wracks also occur on the northeast coast of
Greenland (Borum et al., 2002), albeit with a different species composition.
Elevated CH2Br2 levels would be consistent with a macroalgal
source (e.g. Laturnus, 1996). However, the biomass density of the Northeast
Greenland kelp beds may be considerably less than found at
temperate locations such as Galway Bay (Werner and Kraan, 2004), and ice
scouring may reduce macroalgal density in shallower waters where the algae
are more likely to be exposed to the atmosphere (Wiencke and Amsler, 2012;
Borum et al., 2002).
A source of inorganic iodine from the marginal sea-ice zone is plausible,
and would be consistent with the findings of Atkinson et al. (2012).
Microalgae, particularly diatoms, may be considered as a potential source of
iodine in this region. Diatoms are prominent members of microalgal blooms
occurring at the receding ice edge, and also in communities growing within
the ice itself. Ice diatoms have previously been shown to be a potential
direct source of HOI and I2 to the Arctic atmosphere (Hill and Manley,
2009). The presence of elevated levels of CH2Br2 in air compared
to levels in seawater during the iodine particle event (Fig. 1c) is
consistent with this suggestion, as polar diatoms are known to be a strong
source of bromocarbons (Sturges et al., 1992, 1993). Note
that it is not expected that the observed bromocarbons directly participate
in the NPF; the molecules are too small to form low-volatility organic
oxidation products, and bromine, unlike iodine, does not form a series of
stable condensed-phase oxides. Furthermore, there was no trace of any
bromine-containing signal in the AMS data.
I2 and HOI may also be formed by the abiotic oxidation of iodide,
either by gaseous ozone on the sea surface (Carpenter et al., 2013), or
within sea-ice brine channels followed by emissions from the quasi-liquid
layer on the surface of the sea-ice (Saiz-Lopez et al., 2015). High levels
of iodide associated with biological activity in the sea-ice region have
sometimes been observed (Chance et al., 2010). More recently, microalgal
aggregates released from melting sea-ice have also been proposed as an
iodide source (Assmy et al., 2013; Boetius et al., 2013). Although such
aggregates were not observed from the ship during this work, given that the
initial source of the iodine was upwind, the possibility this was an iodine
source is not ruled out. Indeed, we note that previous observations of elevated
iodide associated with microalgal aggregates were made at higher latitudes
than the ship position during the NPF event. An additional suggestion for
the source of iodine is chemical production from the ice surface itself,
promoted by the freezing of sea salt in the presence of nitrite ions
(O'Driscoll et al., 2006) It should be noted that no NPF events were
recorded near the ice margin to the northeast of Svalbard during the latter
stages of the cruise, so it may be that the phenomenon observed here is
restricted to coastal areas or certain stages of the ice melt process.
Conclusions
Herein we show observations of new particle formation (NPF) over the
Greenland Sea in summer. A long-lasting event, associated with air
originating over the breaking sea-ice off Greenland, featured NPF and
particles growing to sizes in excess of 50 nm. During this period, iodine
was unambiguously detected by an Aerodyne Aerosol Mass Spectrometer.
Furthermore, measurements of hygroscopicity and effective density were
consistent with iodine oxide comprising a significant portion of the
particulate volume. This strongly implies that iodine had a role in the
initial NPF events, which is a phenomenon previously associated with coastal
locations at lower latitudes (Huang et al., 2013; McFiggans et al., 2010, 2004). The initial source of the iodine in this case is
unlikely to be the macroalgae identified during previous studies, but could
be speculatively related to other macroalgae species or microalgae
associated with the sea-ice, which would be consistent with the findings of
Atkinson et al. (2012) based on measurements in Antarctica.
These results show that correct prediction of Arctic aerosol number
concentrations requires knowledge of iodine processes in new particle
nucleation and growth. Our observations suggest that the source of iodine is
related to processes associated with coastal sea-ice, so this could
represent a potentially significant source of particles during periods of
ice loss and thus a potential climate feedback mechanism. As yet we have
insufficient data to predict how widespread these processes are, but if this
phenomenon is limited to coastal areas, it would not explain the events
above 80∘ N studied by Karl et al. (2012). More work is required
to identify the initial source of the iodine and the exact mechanisms for
iodine NPF at a molecular level (Kulmala et al., 2013).
Data availability
Processed data are archived at the British Atmospheric Data Centre ACCACIA
archive. Raw data available on request.
The Supplement related to this article is available online at doi:10.5194/acp-15-5599-2015-supplement.
Acknowledgements
This work was supported by the UK Natural Environment Research Council
through the Aerosol-Cloud Coupling And Climate Interactions in the Arctic
(ACCACIA) project (Grant refs: NE/I028696/1; NE/I028769/1) and a PhD
studentship (E. Darbyshire). For the cruise planning, operation and support,
the authors thank the British Antarctic Survey (BAS), the crew of the RRS
James Clark Ross and Ian Brooks (U. Leeds) as PI of ACCACIA. Coastline data were
obtained from the National Geophysical Data Centre (Boulder, CO, USA). Sea-ice data was obtained from the NASA Distributed Active Archive Center at the
National Snow and Ice Data Center (Boulder, CO
USA).Edited by: W. T. Sturges
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