The metallurgical industry in the Kola Peninsula, north-west Russia, form,
after Norilsk, Siberia, the second largest source of air pollution in the
Arctic and subarctic domain. Sulfur dioxide (SO2) emissions from the
ore smelters are transported to wide areas, including Finnish Lapland. We
performed investigations on concentrations of SO2, aerosol precursor
vapours, aerosol and ion cluster size distributions together with chemical
composition measurements of freshly formed clusters at the SMEAR I station
in Finnish Lapland relatively close (∼ 300 km) to the Kola
Peninsula industrial sites during the winter 2019–2020. We show that highly
concentrated SO2 from smelter emissions is converted to sulfuric
acid (H2SO4) in sufficient concentrations to drive new particle
formation hundreds of kilometres downwind from the emission sources, even at
very low solar radiation intensities. Observed new particle formation is
primarily initiated by H2SO4–ammonia (negative-)ion-induced
nucleation. Particle growth to cloud condensation nuclei (CCN) sizes was
concluded to result from sulfuric acid condensation. However, air mass
advection had a large role in modifying aerosol size distributions, and
other growth mechanisms and condensation of other compounds cannot be fully
excluded. Our results demonstrate the dominance of SO2 emissions in
controlling wintertime aerosol and CCN concentrations in the subarctic
region with a heavily polluting industry.
Introduction
Sulfur dioxide (SO2) is one of the main air pollutants, influencing
the acidification of soils and freshwaters, defoliation and reduced vitality
of forests, atmospheric aerosol formation, and cloud properties and cause adverse
health effects by air pollutants. Anthropogenic SO2 originates
primarily from the combustion of fossil fuels at power plants, other
manufacturing complexes and ships, as well as from the smelting of
sulfur-containing mineral ores. Because of the severe environmental and
health effects of SO2, efforts have been made in order to suppress its
emissions to the atmosphere. While the global SO2 emissions have not
shown any rapid decay, emissions in OECD (Organisation for Economic
Co-operation and Development) countries for example have decreased significantly within the last 3 decades (Solarin and Tiwari, 2020).
The metallurgical industry with large-scale smelter complexes in the Kola
Peninsula, north-west Russia, form the second largest source of air
pollution in the Arctic and subarctic region. Smelters emit large quantities
of SO2, metals and particulate matter to the atmosphere. These
pollutants, especially SO2, have large impacts on both atmosphere and
biosphere in the surrounding area, including the eastern parts of Finnish
and Norwegian Lapland. In the close proximity of industrial plants, these
pollutants have literally destroyed ecosystems, creating “industrial
deserts” (Paatero et al., 2008). Though emissions have significantly
decreased from about 600 kilotons yr-1 in the early 1990s (Tuovinen et
al., 1993; Ekimov et al., 2001), partly because of the collapse of the Soviet
Union and related socio-economical changes in Russia, they are still high.
Today, the SO2 emissions from the Kola Peninsula are around 200 kilotons yr-1 (Barentz Observer, 2019), far higher than the SO2 emissions
of the whole of Finland (37 kilotons yr-1 in 2017). Though vast, Kola
emissions are still far behind the emissions of the world's number one
SO2 polluter, Norilsk (Krasnoyarsk Krai, northern Siberia), with an
enormous emission rate of 1.5 Mt yr-1 (Barentz Observer, 2019).
Together with the few other smaller-scale industrial complexes, these
smelters are almost the sole local source of air pollution in the very
sparsely populated (sub-)Arctic Eurasia, and therefore understanding their
role in atmospheric chemistry and physics is of great importance.
Most of the atmospheric sulfate is formed from SO2 in a liquid phase in
cloud droplets, and these droplets either evaporate leading to sulfate
aerosol production or precipitate as acid rain. However, with very high
concentrations of SO2 downwind from the Kola Peninsula area, high production
rates of gas-phase sulfuric acid (H2SO4) due to photochemical
oxidation of SO2 is expected. The H2SO4 vapour can, in turn,
contribute to atmospheric new particle formation (NPF) via nucleation and
subsequent particle growth even up to sizes of cloud condensation nuclei
(CCN) by further condensation of H2SO4 and potentially some other
vapours (e.g. Weber et al., 1995; Kirkby et al., 2011; Jokinen et al.,
2018). Atmospheric NPF is an important process because, according to model
simulations, it accounts for more than a half of atmospheric CCN formation
globally (Merikanto et al., 2009; Gordon et al., 2017). At high latitudes,
the contribution of NPF has been estimated to be even larger, reaching
> 90 % of the cloud level CCN in the high Arctic and
approximately 70 %–80 % in our study area, the subarctic zone of northern
Finland and north-western Russia (Gordon et al., 2017).
Vehkamäki et al. (2004) were the first to report observations of NPF
(> 8 nm diameter particles) at the Värriö SMEAR I field
station in eastern Lapland, Finland, relatively close to the Kola Peninsula
smelter complexes. Their results on the contribution of SO2 pollution
were not completely definitive, so that during the 4 years of
measurements 15 out of the 147 observed NPF events were concluded to be
explained by SO2 pollution plumes. Kyrö et al. (2014) recorded
particle number size distributions down to 3 nm in diameter and showed that
NPF is connected to high concentrations of SO2. They observed NPF even
during winter in almost dark conditions, indicating that during episodes of
very high concentrations of SO2, a sufficient fraction of it is
converted to H2SO4 in the gas phase even in very low solar
radiation levels to initiate NPF. However, to date, no reports on
quantification of sulfuric acid concentrations by direct measurements, nor on
detailed mechanisms and chemical compounds involved in NPF, in this area
exist.
While observation of atmospheric NPF has been reported in hundreds of
publications since the times of John Aitken (Aitken, 1900), the details,
i.e. the dynamics and contributing compounds, of NPF have been
experimentally resolved only in a limited number of atmospheric
environments. Pioneering studies include the observations by Weber et al. (1995) on the connection between sulfuric acid and atmospheric nucleation,
and the first report on ion-induced nucleation and simultaneous detection of
sulfuric acid anion clusters using a mass spectrometer by Eisele et al. (2006). Parallel to the field work, several laboratory investigations by the
same research groups probed the properties of sulfuric acid – water and
sulfuric acid – ammonia – water clusters and their potential role in new
particle formation (Ball et al., 1999; Hanson and Eisele, 2002).
Later advances in understanding the molecular steps of nucleation and growth in the
atmosphere include the discovery that iodic acid (HIO3) is primarily
responsible for nucleation and growth in coastal areas and in the vicinity
of the Arctic sea ice (Sipilä et al., 2016; Baccarini et al., 2020).
Jokinen et al. (2018) demonstrated that in coastal Antarctica,
H2SO4 originating from the oxidation of dimethyl sulfide (DMS,
emitted by pelagic phytoplankton) and ammonia (NH3, from penguin
colonies) nucleate via a negative-ion-induced mechanism, with sulfuric acid
condensation accounting for most of the subsequent particle growth. Further
observations on nucleation mechanisms indicate the key role of highly
oxidized organic molecules, HOMs (Ehn et al., 2014), in NPF during the
spring–summer time in a boreal forest environment (e.g. Kulmala et al.,
2013; Rose et al., 2018) and in the mid-latitude continental free
troposphere (Bianchi et al., 2016) in parallel with sulfuric acid–ammonia
nucleation (Bianchi et al., 2016; Schobesberger et al., 2015; Yan et al.,
2018). Amines, especially dimethyl amine, were found to contribute to the
initiation of nucleation in polluted urban air (Yao et al., 2018; Brean et
al., 2021; Cai et al., 2021). In addition to these yet rare molecular-level
atmospheric observations, several laboratory studies have investigated the
details of these nucleation mechanisms (e.g. Kirkby et al., 2011, 2016; Almeida et
al., 2013; Kürten et al., 2014). Recent laboratory
studies that probed nucleation of nitric acid and ammonia suggest that this
mechanism may contribute to new particle formation and growth, especially in
the upper troposphere (Wang et al., 2020).
Mass spectrometers (Junninen et al., 2010; Jokinen et al., 2012) and air ion
spectrometers (Mirme and Mirme, 2013) have largely facilitated the recent
progress in the field of atmospheric NPF. By utilizing them in conjunction
with aerosol and meteorological observations, this work aims to shed light
on the molecular steps of NPF resulting from (sub-)Arctic air pollution
during wintertime. Investigations were carried out at the SMEAR I research
station in the Värriö strict nature reserve in Finnish Lapland close to
the industrial plants (most of them located approximately 300 km east from
the station) of Kola Peninsula, north-west Russia, during the winter
2019–2020.
Map of the study area. Our measurement site is located in
Värriö. Industrial cities of Nikel, Zapoljarnij, Monchegorsk and
Kandalaksha have large-scale metal smelters emitting vast quantities of
SO2 into the atmosphere. Kovdor and Olenegorsk mines produce
nickel and/or iron ore but have no smelter industry. Kirovsk and Apatity are
phosphate mining and processing sites.
MethodsSite and time of the study
Measurements were carried out at the Värriö SMEAR I research station
(Hari et al., 1994) located in the Värriö strict nature reserve, Finnish
Lapland, in the vicinity (5 km) of the Russian border (Fig. 1)
(67∘45′19′′ N, 29∘36′37′′ E). The station
stands on top of a hill (390 m a.s.l.), being surrounded by untouched pine
and spruce forests, bogs, fells, small lakes, and rivers. Several large
smelter complexes are located ∼ 300 km away from the
station on the Russian side of the border, while on the Finnish side no
smelters or other large-scale energy intensive (polluting) industrial plants
are located within a distance of several hundreds of kilometres. The closest,
relatively small coal burning plant is located 550 km away. The SMEAR I
station was set up in 1991 for monitoring air pollution, especially sulfur
dioxide (SO2) originating from the Kola Peninsula smelters. In this
work we present 4.5 months of data from wintertime, covering the period 1 November 2019–16 March 2020.
Instrumentation
The aerosol number size distribution between 3 and 750 nm of particle
diameter was recorded by a twin differential mobility particle sizer (DMPS)
(Aalto et al., 1999), comprising Hauke-type differential mobility analysers
(lengths 110 and 280 mm) and TSI-3776 and TSI-3772 condensation particle
counters (TSI Inc., Shoreview, MN, USA) as detectors. The DMPS measuring
3–10 nm particles malfunctioned during 9–10 and 14–27 January, resulting
in the loss of data from this size range on those days.
The number size distribution of charged particles and molecular clusters
between 0.8 and 40 nm was recorded by a Neutral Cluster and Air Ion
Spectrometer (NAIS, Airel Ltd., Estonia; Mirme and Mirme, 2013).
Aerosol precursor vapour concentrations of H2SO4, methane
sulfonic acid (MSA), HIO3 and HOM were measured by a nitrate-ion
chemical-ionization atmospheric-pressure-interface time-of-flight mass
spectrometer (CI-APi-TOF, Jokinen et al., 2012), equipped from 26 January
onwards with a switcher inlet, with which the instrument can switch between
chemical ionization (CI) operation mode and natural ion detection mode. This
instrument was calibrated in the CI mode for sulfuric acid, as described by
Kürten et al. (2012). The same calibration coefficient was used for the
reported MSA and HIO3 concentrations. However, the instrument was not
fully operational at all times during the measurement campaign, so a
significant fraction of data (including all data collected before 25
December and a long period in January) was disregarded.
SO2 was recorded with a TEI 43 i-TLE pulsed fluorescence analyser,
O3 by a TEI 49 i photometric analyser and NOx by a TEI 42C TL
chemiluminescence analyser with photolytic NO2-to-NO converter, all
manufactured by Thermo Fisher Scientific (Franklin, MA, USA). The wind
speed and direction as well as the air temperature were measured with a
Vaisala WTX sensor at 16 m a.g.l.
Nucleation rate calculation
Negative (-) and positive (+) ion-induced nucleation rates of 1.5 nm particles, J1.5-/+, were calculated assuming a steady state between
formation and loss of particles in the size range of 1.5 and 2.5 nm:
J1.5-/+=dN1.5-2.5-/+dt+GR2ΔdpN1.5-2.5-/++CoagSN1.5-2.5-/++krecN<1.5+/-N1.5-2.5-/+,
where N1.5-2.5-/+ is the total concentration of negative or positive
ions in the size range between 1.5 and 2.5 nm, krec is the recombination
coefficient between negative and positive small ions which was here
approximated by a size-independent constant of 1.6×10-6 cm3 s-1 (Tammet, 1995), and N<1.5+/- is the concentration of
positive or negative sub-1.5 nm cluster ions. GR2 is the 2 nm particle
growth rate, Δdp is the width of the size interval for which the
concentration is defined (Δdp=2.5–1.5=1 nm), and
CoagS is the coagulation sink of 2 nm particles to the pre-existing background
aerosol population. CoagS was calculated from the following equation:
CoagS=∑i=1nK2nm,iNi,
where Ni is the concentration of particles in the channel i of DMPS and
K2nm,i is the coagulation coefficients between a 2 nm particle and
a particle in the size bin i calculated based on Seinfeld and Pandis (1998).
An accurate determination of the particle growth rate for 2 nm particles
from the size distribution is challenging, and therefore GR2 was
approximated by assuming irreversible sulfuric acid condensation as the
sole mechanism of growth similar to Jokinen et al. (2018) and Beck et al. (2021), and it was calculated according to the formula given by Stolzenburg
et al. (2020):
GR2=1.45⋅2.68⋅dpnm-1.27+0.81⋅H2SO4×10-7molec.-1cm3.
Here the pre-factor 1.45 accounts for dipole–charge interaction in charged
particle growth (Stolzenburg et al., 2020). The justification for this
approach will be discussed later. A more standard method for the GR
determination is to approximate the GR2 by the average growth rate of the
formed particle population, including mainly particles grown far above the 2 nm size, during a few hours starting from the beginning of the event as
demonstrated in Fig. 2a. This method leads to the average GR of 4.5 nm h-1. However, this approach neglects the effect of air mass advection
which, as will be discussed later, may largely determine the time
development of the size distribution and thus also the apparent growth.
Particle formation event recorded by the NAIS (negative ions) on
29 January 2020, depicted on a linear diameter scale. The average growth
rate determination by a linear fitting to the growing nucleation mode yields
an average growth rate of 5 nm h-1(a) while the 50 % appearance
time method (Lehtipalo et al., 2014) applied in cluster mode growth yields
growth rates from about 0.35 to 1.8 nm h-1(b). Both methods likely
overestimate true growth rate as the particle size distribution is affected
by air mass advection. Therefore, the growth rate applied in nucleation rate
calculations is derived from sulfuric acid concentration (Stolzenburg et
al., 2020).
Rather than the average GR of the whole particle population, the 50 %
appearance time method (Lehtipalo et al., 2014) could be used to estimate the
growth rate of nucleating clusters in the size range of 1.3–2.7 nm (Fig. 2b). Here, the cluster appearance time in each size channel represents the
time when cluster concentration reaches 50 % of its maximum concentration
during the event. The growth rate can be assessed from the cluster diameter
vs. appearance time curve (black line), resulting in ∼ 0.35 nm h-1 during 10:10–11:30 UTC+2 and ∼ 1.8 nm h-1 during
11:30–11:50 UTC+2, and in the average growth rate of ∼ 0.9 nm h-1 during the period 10:10–11:50 UTC+2. A drawback of this analysis is that
the GR cannot be obtained for the period where the concentration has passed
the 50 % threshold or the period of decaying concentration. Furthermore,
the temporal variability of GR cannot be properly obtained due to
fluctuations in the data. Nevertheless, the above-mentioned values of
0.35–1.8 nm h-1 can be compared to those obtained from Eq. (3), which
yields the maximum GR of 0.51 nm h-1 around noon on the example
day (29 January 2020). A comparison to the value of 1.8 nm h-1 obtained
from the 50%-appearance time method slightly before noon leads to a
factor of ∼ 3.5 difference in GR2 on that day, which, in
turn, is reflected in a 22 % difference in the calculated nucleation rate
(Eq. 1). The effect of the different approaches to determine GF is
visualized in Fig. S1. To conclude, ion-induced nucleation rate
calculation is not very sensitive to GR2 because the ion–ion recombination
term (Eq. 1) dominates the loss in our conditions.
Particle number size distribution in the diameter range 4–700 nm (a), number concentration of 4–10 nm particles (b), measured (only between
27 and 31 December 2019) and calculated (Dada et al., 2020) sulfuric acid
concentration (c), wind direction (d), SO2 concentration (e), and UV-B
radiation (f) over the time period 1 November 2019–7 January 2020. The
grey shaded areas depict the times with observed < 10 nm new
particle formation. The polar night (sun constantly below horizon) period is
from 9 December 2019 to 4 January 2020.
Sulfuric acid proxy calculation
Because of significant gaps in the measured data, [H2SO4] was also
calculated using a proxy developed by Dada et al. (2020). This proxy takes
into account the oxidation of SO2 to H2SO4 by both OH
(estimated from the global radiation intensity) and stabilized Criegee
intermediates (estimated from monoterpene and ozone concentrations;
Sipilä et al., 2014), as well as losses of H2SO4 by
dimerization (negligible in observed concentrations) and condensation onto
pre-existing aerosol particles (the primary loss term). Unfortunately, there
are no VOC measurements available at SMEAR I, but, because the data were
collected during winter well outside of the growth period, we assumed the
monoterpene concentration to be zero. Global radiation measurements showed
unexplained fluctuations (maybe caused by low solar zenith angles or
freezing of the sensor) during the measurement period, and therefore we used
UVB radiation and the relation between UVB and global radiation determined
by Dada et al. (2020). During the times when the CI-APi-TOF mass spectrometer was operational, the
agreement between the measured and calculated concentrations was good
(Fig. S2), with mean concentrations agreeing within 8 %. The obtained
correlation coefficient was R=0.790 and coefficient of determination
R2=0.624.
Trajectory analyses
Trajectories were calculated by using the Hybrid Single-Particle Lagrangian
Integrated Trajectory model HYSPLIT (Stein et al., 2015) with GFS 0.25∘ meteorology as an input. We calculated 24 h backward trajectories
arriving at 50 and 250 m a.g.l. for the period 28 January
2020 at 00:00 UTC+2 to 30 January 2020 at 00:00 UTC+2, arriving every 6 h.
The trajectory calculations included mixing layer depth along the
trajectory.
Results and discussionNew particle formation during the measurement period
Figures 3a and 4a depict the aerosol number size distribution between 3 and
700 nm, as recorded by the DMPS. Several new particle formation events were
observed during the measurement period. Clear NPF events with the
concentration of 4–10 nm particles, N4-10nm (Figs. 3b and 4b),
exceeding 50 cm-3 are marked with grey shadings. Since the DMPS data on
sub-10 nm particles were missing from 9–10 band 14–27 January,
N4-10nm could not be derived for those time periods. Still, at least
on 18 and 19 January we can see that NPF eventually produced particles
larger than 10 nm in diameter. The observed NPF events coincided mostly (ca.
50 % of the cases) with clearly easterly (∼ 90∘)
winds (Figs. 3c and 4c), and with elevated H2SO4 concentrations
(Figs. 3d and 4d) calculated based on Dada et al. (2020). H2SO4
concentrations depend, besides condensation sink and UVB radiation, on the
SO2 concentration that is connected to both wind direction and air mass
origin. Clear examples of such SO2 pollution-driven NPF events are,
for example, those occurring during three consecutive days on 10–12
November 2019, on 28 and 29 January 2020, and on 13 March 2020. The data
from the period 28–29 January are discussed in detail below, whereas the
data from the other two exemplary periods are presented in the Supplement
(Figs. S3–S11).
Particle number size distribution in the diameter range 4–700 nm (a), number concentration of 4-10 nm particles (b), measured and calculated
(Dada et al., 2020) sulfuric acid concentration (c), wind direction (d),
SO2 concentration (e), and UV-B radiation (f) over the time period 8
January–15 March 2020. The grey shaded areas depict the times with
observed < 10 nm new particle formation.
Not all the NPF events occurred during the easterly winds. The events
observed close to the mid-winter, from early December until early January,
occurred with westerly winds or during the transition of the wind direction
from west to east, in relatively low concentrations of SO2 and in the
virtual absence of daylight and H2SO4. These low-H2SO4
mid-winter events were observed to start from sizes larger than a few nanometres,
which means that nucleation did not take place in situ in the surroundings of the
SMEAR I station. Those particles had thus formed elsewhere and were
transported to the measurement site by either horizontal advection or
vertical downdrafts from above the mixed layer. Compared with particles of a
few nanometres in diameter, gas-phase H2SO4 is lost much more rapidly onto
pre-existing particles after its production ceases, so the lack of
H2SO4is not excluding its primary role in NPF, even though it
is not supporting such a role either. Some of the mid-winter NPF events
coincided with elevated SO2 concentrations, suggesting that sulfuric
acid may have been formed in the measured air mass earlier. Some other
mid-winter NPF events, especially the relatively strong NPF event on 3
December presented in the Supplement (Figs. S9–S11), occurred in a virtual
absence of SO2, suggesting that sulfuric acid had not been formed to a
significant extent in that air mass. Currently, we thus cannot explain the
mechanism of NPF on that day. However, the NO2 concentration was
slightly (Fig. S9) elevated in the measured air mass, which might have
been connected with the elevated source of particles. Nevertheless, most of
the NPF events seemed to be connected with the presence of H2SO4.
Wind speed and direction at the 16 m height (a); air temperature
at two heights (b); UV-B and UVA radiation (c); and concentrations of
SO2, NO2 and O3(d) during the period 28–29 January 2020.
Case study 28–29 January 2020
To resolve the details of new particle formation and growth, we focus on 3
time periods with clear signs of nucleation and particle growth. Here we
show results from analysis of a 2 d period of 28–29 January 2020. To
demonstrate that this 2 d period is not only a unique observation, we
represent data from the time period 10–12 November 2019 (Figs. S3–S5) and
from 13 March 2020 (Figs. S6–S8) in the Supplement. The data from the
event on 3 December 2019, which differs from the overall picture, are also
depicted in the Supplement (Figs. S9–S11).
Meteorological situation and trace gas concentrations
Throughout the period of 28–29 January, the wind was blowing from the east
(∼ 50–150∘) (Fig. 5a). The ambient temperature
ranged from -16 to -28∘C (Fig. 5b). The sky was
clear but, because of the low solar zenith angle (maximum 4.4∘ at noon of 29 January), the UVB radiation intensity needed for a
photochemical H2SO4 formation reached only 35 mW m-2
(summertime UVB radiation intensity maxima at Värriö are
> 2000 mW m-2). The HYSPLIT back trajectory calculations
showed that the air masses arriving between 28 January at 06:00 UTC+2 and 30
January at 00:00 UTC+2 passed the industrial areas of the Montchegorsk region
(Fig. 6).
At around 03:00 UTC+2 on 28 January, coinciding with the change in the air mass
origin to the Montchegorsk–Kandalaksha region (Fig. 6) a few hours after
the change in the wind direction from west to east in the evening of 27
January, air pollutant levels started to increase steeply (Fig. 5d). During
the course of the day, both SO2 and NO2 concentrations increased by
ca. 2 orders of magnitude, with [SO2] peaking at 27 ppb and
[NO2] peaking at 7 ppb. The ozone (O3) concentration declined from
about 40 to a 30 ppb range. To put the high level of SO2
concentrations into some perspective, the highest concentration recorded in
the Helsinki Metropolitan area was 8.4 ppb (24 µg m-3, 1 h
average) in 2019 and the yearly-average concentration was about 0.2 ppb
(∼ 0.5 µg m-3) (Helsinki Region Environmental
Services Authority, 2020). The yearly-average SO2 concentration at the
SMEAR I station in 2019 was 1.1 ppb.
Aerosol precursors
Despite the low UVB radiation, required for O3 photolysis that
initiates the H2SO4 production via OH radical formation, the
H2SO4 concentration increased from close to the lowest detection
limit values of ∼ 105 molec. cm-3 up to
8×105 molec. cm-3 during 29 January and up to
1.5×106 molec. cm-3 on 29 January (Fig. 7e).
Because the OH production rate must have been low, a high SO2
concentration is a prerequisite for the H2SO4 production during cold
and dark winter months. While stabilized Criegee intermediates (sCIs) formed
in alkene ozonolysis can oxidize SO2 to produce H2SO4 during
summertime (Mauldin et al., 2012; Sipilä et al., 2014), alkene (terpene)
emissions from the vegetation and thus the sCI production rate are
negligible during the winter season. The proxy calculations agree well with
the measured sulfuric acid concentration on 29 January but show clearly
higher values on 28 January. The cause of the disagreement on 28 January is
probably the stable and shallow boundary layer. The temperature gradient
close to the surface was almost +0.2 ∘C m-1 at noon on 28
January (Fig. 5b). Solar radiation from close to the horizon does not
penetrate efficiently inside the canopy, so the UVB measured above the
canopy and used in the proxy calculation does not reflect the situation at
the ground level. Sulfuric acid produced above the canopy, on the other
hand, does not mix downwards due to the strong temperature inversion and
calm winds. On 29 January, the temperature gradient was absent or slightly
negative, allowing the surface air to mix with the air above the canopy.
Besides H2SO4, minute signals of iodic acid (HIO3) were
also observed during the day (Fig. 7e). The exact production mechanism of
HIO3 remains globally unknown despite the emerging evidence on its
critical role in new particle formation especially in the Arctic regions
(Sipilä et al., 2016; Baccarini et al., 2020). Methane sulfonic acid
(MSA), which has been observed in larger aerosol particles (Beck et al.,
2021) and could potentially also contribute to NPF, hardly exceeds the
detection threshold. This was expected since MSA originates from dimethyl
sulfide (DMS) photo-oxidation. DMS ends up in the air mainly from the
metabolism of pelagic phytoplankton during summer months, not during the
dark winter. No other condensable vapours, such as HOM which dominates the
new particle growth in the summertime boreal forest environment (Ehn et
al., 2014), were observed during this case study period or during other
periods depicted in the Supplement.
The 24 h back trajectories with an arrival height of 50 m (a) and
250 m (b) above ground level (AGL), and with arrival times between 28
January at 00:00 UTC+2 and 30 January at 00:00 UTC+2.
New particle formationIon size distribution
Figure 7a and b show the NPF events on 28 and 29 January, as observed by
the NAIS operated in the ion mode. Omnipresent small (<1.5 nm) ions
are continuously produced by the galactic cosmic radiation, terrestrial
gamma radiation and gas phase radon decay. At approximately 11:00 UTC+2 on 28
January, coinciding with the increase in the H2SO4 concentration,
small negative cluster ions started to grow, which is seen as small
increases in the ∼ 1.5–2 nm negative ion concentration.
During their growth beyond ∼ 2 nm in diameter, those clusters
were neutralized by collisions with positively charged ions, so that they
disappeared from the spectrum. They still obviously continued to grow in
size, as charged particles reappeared in the spectrum after reaching some 5 nm in diameter when diffusion charging becomes effective enough; an
equilibrium charging state for 2 nm particles is 0.8 %, while 5 nm particles are charged with an efficiency of 2.3 %, and out of 20 nm particles 11 % are negatively charged (Wiedensohler et al., 2012).
Opposite to the negative ions, positive cluster ions did not grow in size.
Larger (> 5 nm) positive particles (charged by diffusion charging
during the course of their growth) grew similarly to the negative ones. On
29 January, with clearly higher H2SO4 concentrations, the
appearance of > 1.5 nm negative clusters was more pronounced,
suggesting higher nucleation rates and the critical role of H2SO4 in the
initial steps of NPF. Positive cluster ions were again only bystanders and
did not contribute to nucleation. This observation suggests that negative-ion-induced nucleation is the primary pathway to NPF similar to
H2SO4–NH3 (–H2O) ion-induced nucleation observed
by Jokinen et al. (2018) in Antarctica and Kirkby et al. (2011) in CERN
CLOUD chamber experiments. However, due to the lack of information on neutral
∼ 1.5–3 nm cluster concentrations, this observation alone
does not exclude parallel neutral nucleation mechanisms.
Number size distribution of negative (a) and positive (b) clusters
and particles; concentration of freshly nucleated, charged 1.5–2.5 nm clusters (c); formation rate of negative and positive 1.5 nm clusters (d);
measured concentrations of sulfuric acid (H2SO4), methane
sulfonic acid (CH3SO3H) and iodic acid (HIO3) as well as
sulfuric acid concentration estimated by proxy calculation (e); and the
signal intensity of nucleating ion clusters with different composition (f) during the period 28–29 January 2020.
Nucleation rates
Even though a weak growth of the small negative ions at around noon on 28
January is visually observable in Fig. 7a, the concentration of clusters in
the 1.5–2.5 nm size range (N1.5-2.5-) is hardly distinguishable
from the noise (Fig. 7c). The nucleation rate, calculated using the filtered
concentration data, only slightly exceeded the baseline (caused by the presence of minute, almost omnipresent signal from ion clusters extending above 1.5 nm but which is not connected to sulfuric acid nucleation), being
approximately 0.005 cm-3 s-1 with a high relative uncertainty
(Fig. 7d). On 29 January, with a 2.3-fold sulfuric acid concentration, the
concentration of 1.5–2.5 nm negative clusters was well above the instrument
noise, reaching 20 cm-3 around noon. The nucleation rate peaked at
0.067 cm-3 s-1. The ambient temperatures during nucleation
(∼ noon) were almost identical, around -22 ∘C, on
both days and therefore they can be directly compared. An approximately
10-fold difference in the nucleation rate between the two days accompanied
by a factor of 2.3 difference in the sulfuric acid concentration is in line
with the results from the CLOUD-chamber experiment on sulfuric acid–ammonia–water nucleation (Kirkby et al., 2011). The so-called “slope”
that approximately (not exactly in real atmospheric situations) equals
the number of sulfuric acid molecules in the critical cluster
(Vehkamäki et al., 2012) is given as
Slope=dlogJ1.5-dlog[H2SO4]
and yields a value of 2.9 for the numbers discussed above. Though this value
is subject to a significant uncertainty, it would agree with observations of
Kirkby et al. (2011) and parameterizations by Dunne et al. (2016), which
yield a “slope” of approximately 3 under similar conditions to those visualized
in Fig. 8. In the same figure, data from all the days with clearly
observable ion-induced nucleation are depicted. There, hourly average
nucleation rates J1.5- that exceed a threshold value of
J1.5-=0.01 cm-3 s-1 are plotted against the
concurrent calculated sulfuric acid concentration and air temperature.
Calculated nucleation rates, Jgcr, represent the total nucleation rates
(ion-induced plus neutral) at different temperatures and ammonia
concentrations under the influence of ions producing galactic cosmic radiation (GCR) at the fixed rate of 1.8 ion pairs per cubic centimetre per second.
Negative-ion-induced nucleation, however, should be the dominant mechanism
under these conditions (Kirkby et al., 2011), so these results can be
compared. Our data are reasonably close to the range predicted by the
parameterization, considering that this simple calculation does not include
air mass transportation, vertical mixing, terrestrial radiation sources or
any other real-world phenomena. Also, sources and concentration of ammonia
in our study area are unknown.
The 1 h average negative ion-induced nucleation rates calculated
vs. calculated sulfuric acid concentration (Dada et al., 2020) for days
with visible and clear nucleation events (11–12 and 18–19
November 2019, 28–29 January, 13 March 2020) coloured according to the
air temperature. A nucleation rate of 10-2 cm-3 s-1 was
used as a threshold for reliable determination below which instrument noise
becomes predominant. No positive ion-induced nucleation was observed. For
comparison, total (negative, positive and neutral) nucleation rates
Jgcr calculated based on CLOUD parameterization (Dunne et al., 2016) are
presented. The calculation assumes a ground-level galactic cosmic ray
ionization rate of 1.8 ion pairs per cubic centimetre per second and no contribution from
terrestrial radioactivity. The calculation was performed at -22∘C and at -6∘C assuming an ammonia concentration of either 50 or
500 ppt.
Cluster time series
To confirm the role of sulfuric acid and to solve the contribution of
ammonia to the nucleation process, we measured the negative ion cluster
composition and signal intensity with the APi-TOF mass spectrometer in the ion mode without
chemical ionization. The time series of the most abundant clusters show the
appearance of HSO4- ions in the morning of 28 January, together
with an increasing [H2SO4] accompanied with a decay of
NO3- ion signal which typically dominates the anion spectrum at
low [H2SO4] and low [HIO3] globally (Fig. 7f). Since
H2SO4 is a stronger acid than HNO3, the proton transfer from
H2SO4 to NO3- explains the observed behaviour when
[H2SO4] started to rise. When [H2SO4] still increased
during the course of the day,
(NH3)m(H2SO4)nHSO4- clusters started to
form. The cluster signals peaked at around noon coinciding with the
highest [H2SO4] and N1.5-2.5-, after which they started to
decay. On 29 January, the same behaviour was observed, but with somewhat
stronger cluster signals due to the higher [H2SO4].
Mass defect plot (with a 2 h effective integration time) of the
anion cluster distribution recorded by the APi-TOF mass spectrometer during intensive cluster
formation on 29 January 2020. The size of the circles is proportional to the
concentration. See text for a detailed description.
Cluster composition
To get more insight into the chemical composition of clusters, the
ion-cluster mass spectrum was integrated over 4 h (2 h effective
data collection due to switching between CI and ion inlet). The resulting
spectrum is presented in Fig. 9 by means of a mass defect plot, where the
mass-to-charge ratio (m/z, unit Th) corresponds – with only singly charged ion
clusters present in the air – to the mass of the cluster (m, unit Da, equal
to unified atomic mass unit, u). Mass defect is the mass difference (in Th
or Da) between the exact mass of a cluster and the integer mass defined as
the sum of nucleons in the atomic nuclei of this cluster. For example, the
exact mass of a HSO4- ion that has 97 nucleons is 96.960103 Da
and the mass defect is thus 0.039896 Da. The area of a dot is proportional
to the logarithm of the observed signal intensity. In the mass defect plot,
each addition of a molecule or atom is represented by a vector. An addition
of H2SO4 for example, with a negative mass defect, leads to an
increasing mass and a decreasing total mass defect, while an addition of a
positive mass defect NH3 molecule leads to an increasing total mass
defect. Successive additions of certain molecules to an ion results in a
straight line in the mass defect plot, so that different cluster formation
pathways are readily distinguishable from that plot.
Particle number size distribution (a) and
concentrations of particles larger than 3, 50 and 100 nm (b) recorded by the DMPS.
Average particle number size distributions during the
∼ 1-week period of easterly winds (28 January–3 February
2020), during the preceding and succeeding time period with westerly winds,
and average number size distribution between 1 November and 29 February.
In Fig. 9, the largest signals are associated with the omnipresent nitrate
ion and its cluster with nitric acid (NO3- and HNO3⋅NO3-). The rest of the small (< 180 Da) ions are mainly
different sulfur species, with bisulfate ions partly clustered with nitric
acid (HSO4- and HNO3⋅HSO4-) being the most
abundant ones. Other small sulfur ions present in the spectrum are
SO4-, SO5-, HNO3⋅SO3- and
HNO3⋅SO4-. Deprotonated iodic acid (IO3-)
and its nitric acid cluster (HNO3⋅IO3-) are also
abundant. Despite the presence of multiple different types of these core
ions, their initial growth is solely caused by the attachment of sulfuric
acid molecules. We observed clusters with 1–4 H2SO4 molecules
attached to the SO4- ion one H2SO4 molecule
attached to the to SO5- and SO3- ions, and 1–3
H2SO4 molecules attached to the IO3- ion. For
simplicity, we assume that the negative charge remains in the core ion. This
is not necessarily true, but H2SO4 may lose a proton, e.g. to
IO3-, resulting in the composition of HIO3⋅
(H2SO4)n-1⋅HSO4- instead of
-(H2SO4)n⋅IO3-. Furthermore, water, if
present in the clusters, efficiently evaporates in the vacuum of a mass
spectrometer and therefore information on the role of water in the cluster
formation is lost.
None of the clusters discussed above seem to adopt ammonia efficiently
enough for their signals to exceed the detection threshold of the APi-TOF spectrometer
(mass dependent, ∼ 10-3 to few 10-3 ions per second for
2 h integration for m/z>400 Th). Only clusters made solely
of sulfuric acid with a bisulfate ion (HSO4-) as a core seem to
efficiently attach ammonia, resulting in the formation of
(NH3)m⋅ (H2SO4)n⋅HSO4--clusters (n>=3). This sequential addition of NH3 and
H2SO4 has been shown to be an effective (ion-induced) cluster
formation and growth mechanism in coastal Antarctica (Jokinen et al., 2018)
as well as a secondary pathway in the free troposphere (Bianchi et al.,
2016) and in the spring–summer time southern Finland boreal forest (Yan et
al., 2018).
Our results on negative cluster composition can be compared to the results
from the CLOUD experiment at -25 ∘C for varying
NH3/ H2SO4 ratios (Schobesberger et al., 2015). Based on that
data, with the NH3/ H2SO4 ratio exceeding approximately 100,
both cluster composition and nucleation rate saturate (Kirkby et al., 2011)
and become unaffected by further increases in the NH3 concentration. In
those conditions, a cluster comprising 3 molecules of sulfuric acid on a
bisulfate ion, (NH3)n⋅ (H2SO4)3⋅HSO4-, contains on average approximately n∼1 molecules of ammonia, whereas a cluster composed of 4 molecules of sulfuric
acid and a bisulfate ion, (NH3)n⋅
(H2SO4)4⋅HSO4-, carries on average
approximately n∼ 1.5 NH3 molecules (Schobesberger et al.,
2015). In our case (Fig. 9), corresponding average ammonia numbers were n∼ 0.4 and n∼0.8 for (NH3)n⋅(H2SO4)3⋅HSO4- and (NH3)n⋅(H2SO4)4⋅HSO4-, respectively, which would
suggest that the NH3/ H2SO4 ratio in our case was well below
100, and likely below 10 (Schobesberger et al., 2015). If true, that would
indicate an ammonia concentration of the order of ∼ 107
molecules cm-3, or ∼ 1 pptv. However, cluster
fragmentation inside the mass spectrometer can be totally different between
our experiment and the Schobesberger et al. (2015) study, and therefore no conclusions on ammonia concentrations should be drawn. Nevertheless, if the
NH3/ H2SO4 ratio was low, the system would not saturate with
respect to NH3 and the nucleation rate should therefore be sensitive to
both H2SO4 and NH3, similar to Jokinen et al. (2018). This,
together with unknown effects of cluster fragmentation, highlight the
importance of understanding NH3 sources, transportation and atmospheric
mixing ratios down to ppt levels for a proper description of new particle
formation, also in the subarctic region. Unfortunately, NH3
concentrations in the range of 1 pptv are not (reliably) detectable with any
present-day measurement technology.
The present analysis shows that the sulfuric acid–ammonia ion-induced
nucleation can trigger new particle formation in the wintertime subarctic and boreal environment with a high level of anthropogenic SO2 pollution but
a low UV-radiation intensity. Data on neutral 1.5–3 nm particles are not
available, so that neutral nucleation rates could not be derived. However,
based on all the evidence obtained from the field (mainly Jokinen et al.,
2018) and especially from the CLOUD experiments (Kirkby et al., 2011;
Schobesberger et al., 2015), in the absence of significant amounts of
compounds other than H2SO4 and NH3, and with the nucleation
rates being below the ion pair production rate (typically 2–4 ion pairs per cubic centimetre per second in the Earth's surface layer), ion-induced nucleation
seems to dominate over the neutral one. In our case, HOMs were below the
detection limit, and amines, if important, would also appear in the anion
spectrum in H2SO4 clusters. HIO3 and MSA were present,
but significant neutral homogeneous nucleation of HIO3 would require
∼ 100-fold concentrations of it compared to what was measured
here (Sipilä et al., 2016).
The observation of clusters containing IO3- or HIO3 together
with H2SO4 is, however, highly interesting. HIO3 has been
shown to nucleate homogeneously, and also mixed clusters containing both
HIO3 and H2SO4 have been reported from the Alps (Frege et
al., 2017), Atlantic coast (Sipilä et al., 2016) and Arctic (Beck et
al., 2021). If the SO2-rich pollution plumes from the smelters are
advected to iodine source areas (Arctic Ocean and especially sea ice zone as
well as macroalgae-rich coasts) or vice versa, this mixed mechanism may
become important.
Particle growth and relevance for CCN concentrations
Based on the above analysis, particle nucleation is clearly driven by
sulfuric acid and ammonia, with the nucleation rate being most probably
sensitive to concentrations of both of these vapours. But how do the freshly
nucleated clusters grow? Assuming irreversible condensation, even the peak
sulfuric acid concentration of 1.5×106 molec. cm-3
can explain only a small fraction of the observed growth rate. Consistent
with an earlier report on wintertime particle growth rates at Värriö
(Kyrö et al., 2014), the apparent average growth rate on 29 January was
approximately 4.5 nm h-1 (Fig. 2). Based on Stoltzenburg et al. (2020),
such a rate would require a steady [H2SO4] of 2.6×107 molec. cm-3 throughout the growth process, which would continue long
after the sunset when the [H2SO4] already decays. Obviously, there
are two possible explanations for this disagreement; either sulfuric acid
was not responsible for most of the growth, or the air was not homogenous
and the apparent growth was caused by the air mass advection (Kivekäs et
al., 2016).
Besides sulfuric acid, the only condensable vapours detected were MSA and
HIO3 (and NH3). However, their concentrations were clearly lower
than that of sulfuric acid, and therefore condensation of those vapours in
a homogeneous air mass cannot explain the apparent growth either. It could
be speculated that compounds not recorded by the CI-APi-TOF mass spectrometer, such as
SO2 or some less oxidized volatile or semi-volatile organic compounds,
(S)VOCs, condense or react in particle phase forming low volatile compounds
thereby contributing to growth (Stolzenburg et al., 2018). However, the
complete absence of highly oxidized compounds does not support (though it does not
fully exclude either) the presence of less oxidized compounds at a high
abundance. The NO2 concentration was moderate, up to 7 ppb, and
therefore nitric acid concentrations were likely insufficient to have a
measurable effect on the growth (Wang et al., 2020). However, the
temperature was low during the studied time period, and therefore HNO3
or some other semi-volatile compound could have contributed to the growth,
provided that such compounds were present. Ammonia was detected in small ion
clusters, but its contribution to the particle volume concentration,
assuming that the measured cluster NH3/ H2SO4 ratio reflects
the composition of larger particles, was marginal. Assuming the particle
composition to be ammonium bisulfate, i.e. the NH3/ H2SO4
ratio of unity, ammonia would contribute 17 % to the particle volume and
5 % to particle diameter growth rate.
The most plausible explanation for the observed growth is that the particle
growth was driven by H2SO4 condensation, but its concentration
was not uniform over the source area. In that case, particles would nucleate
and grow to their final sizes during the few hours of sunlight. Particles
formed and grown close to the emissions sources with high SO2 and thus
H2SO4 concentrations grow to larger sizes than particles formed
near the measurement site. Air mass advection would then transport particles
through the dark hours, leading to a steadily increasing nucleation (and
later Aitken) mode diameters at SMEAR I, observed as an apparent steady
growth even through the night. Modelling efforts and measurement of chemical
composition or hygroscopicity of growing modes would be required for an
unambiguous explanation of the particle growth.
New particle formation in the subarctic winter would be irrelevant if formed
particles would not grow to sizes (above few tens of nanometres) where they can act
as CCN. We did not measure CCN concentrations at different supersaturations,
but the air masses originating from the Murmansk–Kandalaksha region from
about 03:00 UTC+2 onwards on 28 January (Fig. 6) contained elevated concentrations
of Aitken and accumulation mode particles, mainly in the size range of
∼ 20–500 nm (Fig. 10). New particle formation clearly
increased the concentration of >3 nm particles, and the
concentration of particles larger than 50 nm also showed an increase, especially
on 29 January. The concentration of particles larger than 100 nm was
relatively constant and apparently unaffected by NPF during the times when
these NPF events could be observed. Air mass advection and particle loss
processes, however, naturally have an impact on measured concentrations and
are largely responsible for the development of particle populations.
Figure 11 presents the average particle number size distribution during
about the 1-week period of eastern winds (28 January–3 February 2020),
when the two clear NPF events presented above occurred. Concentrations of
particles in all the size classes were remarkably higher, even by an order
of magnitude for the 10–200 nm particles, than the average concentrations
during the preceding and succeeding periods with westerly winds.
Concentrations during that 1-week period were also clearly higher than the
average concentrations between 1 November and 29 February, suggesting that
new particle formation may be a significant source of particles in eastern
air masses. However, primary emissions from the smelters and the surrounding
cities would naturally show up in the size distribution plot as well. A more
thorough analysis is needed to separate the roles of secondary NPF and
primary emissions in the aerosol and CCN budgets. March, with almost
continual NPF, was excluded from this analysis since the light conditions in
March differ significantly from those between early November and end of
February.
For an accurate assessment of the contribution of secondary aerosol formation to
CCN concentrations at SMEAR I or regionally, the meteorological situation,
including boundary layer dynamics, wet deposition of particles, etc., should
be considered. However, our observations on clearly elevated CCN-size
aerosol particle concentrations in eastern air masses (Figs. 10 and 11)
point towards a clear contribution of Kola Peninsula SO2 emissions to
wintertime CCN concentrations in the region.
Conclusions
Wintertime new particle formation and growth was investigated at the SMEAR
I station, in the Värriö strict nature reserve, Finnish eastern Lapland.
Sulfur dioxide concentrations in the air masses arriving from Kola
Peninsula were often very high, occasionally over 30 ppb. At such high
concentrations, enough sulfuric acid was formed to initiate new particle
formation and growth, even in the presence of a very low solar radiation
intensity.
New particle formation was observed mostly, but not solely, with easterly
winds and in air masses arriving from the direction of Kola Peninsula
smelters. Newly formed (4–10 nm, concentration >50 cm-3)
particles were observed on 34 d altogether between 1 November 2019 and 15
March 2020, and out of these days about 60 % were associated with eastern
winds or with the period of wind direction change from ∼ west
to east. Nucleation was observed in situ at the SMEAR I station at H2SO4 concentration exceeding 1×106 molec. cm-3. These
cases were identified based on the appearance of ∼ 1.5–2 nm ion clusters. Other NPF events were observed as appearances of particles of
a few nm in diameter, and these particles gradually grew in size over time.
Nucleation at SMEAR I was shown to proceed via a negative-ion-induced
sulfuric acid–ammonia(–water) channel which, based on prior
understanding from laboratory experiments, can be hypothesized to dominate
the NPF process at our site. Closer to SO2 emission sources where
H2SO4 concentrations are likely remarkably higher, nucleation can
also proceed via a neutral channel and could, theoretically, involve
compounds other than H2SO4NH3 and water.
Larger particles with a diameter of at least a few nanometres observed at SMEAR I were probably not formed in the immediate vicinity of the site, so they had
grown in size during the air mass advection. Secondary aerosol formation
associated with the emissions from the Kola Peninsula together with primary
particle emissions impact the aerosol number size distribution, clearly
increasing the concentrations of particles in all the size classes, and
therefore unavoidably also CCN concentrations. For a better understanding of
the contribution of SO2 emissions from the Kola Peninsula to local and
regional CCN concentrations, and for upscaling our results to cover all of (sub)arctic Eurasia with vastly polluting industrial cities such as
Norilsk, require more measurements. Such measurements should be complemented
with CCN or cloud residual measurements – ideally in more than only one
location (SMEAR I) around the Kola Peninsula. Regional chemical transport
and aerosol dynamic modelling would be necessary for a thorough assessment.
Data availability
Mass spectrometer data related to this article are available from Zenodo
(10.5281/zenodo.5524857) as well as upon request
to the corresponding author. The rest of the data are available for download
from https://smear.avaa.csc.fi/ (last access: 20 November 2021, Junninen et al., 2009).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-21-17559-2021-supplement.
Author contributions
MS designed the experiment. MS, NS, KN, TL, DK, SK, LB, TL, JL, PPA, PK,
ES, PAR and TJ prepared the instruments, performed calibrations, collected
the data and processed the data. MS and NS analysed the data. EMD calculated
the back trajectories. MS wrote the paper. All authors contributed to
the interpretation of data and commented on the paper.
Competing interests
The authors declare that they have no conflict of interest.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
We thank the GiGAS-UHEL calibration centre for at-site CI-APi-TOF calibration,
Värriö research station staff for technical support and Lubna Dada
for discussions related to sulfuric acid calculation.
Financial support
This research has been supported by the H2020 European Research Council (grant no. 714621), the Academy of Finland (grant nos. 296628, 328290, 310627 and 334514), and the European Commission, Horizon 2020 Framework Programme (grant no. ACTRIS IMP (871115)).
Review statement
This paper was edited by Paul Zieger and reviewed by two anonymous referees.
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