Large seasonal and interannual variations of biogenic sulfur compounds in the Arctic atmosphere (Svalbard; 78.9° N, 11.9° E)

. Seasonal to interannual variations in the concentrations of sulfur aerosols (< 2.5 µ m in diameter; non sea-salt sulfate: NSS-SO 42 − ; anthropogenic sulfate: Anth-SO 42 − ; biogenic sulfate: Bio-SO 42 − ; methanesulfonic acid: MSA) in the Arctic atmosphere were investigated using measurements of the chemical composition of aerosols collected at Ny-Ålesund, 20 Svalbard (78.9° N, 11.9° E) from 2015 to 2019. In all measurement years the concentration of NSS-SO 42 − was highest during the pre-bloom period and rapidly decreased towards summer. During the pre-bloom period result, the mean ratio of MSA to the DMS-derived aerosols was low (0.09 ± 0.07) for the pre-bloom period but high (0.32 ± 35 0.15) for the bloom and post-bloom periods. Our results indicate that the contribution of MSA to the growth of the newly formed particles to a size at which they could act as condensation nuclei was considerably greater during the bloom and post-bloom periods than during the pre-bloom period. help define the climate-relevant impacts of oxidation products of biogenic DMS in the Arctic environment.

result, the mean ratio of MSA to the DMS-derived aerosols was low (0.09 ± 0.07) for the pre-bloom period but high (0.32 ± 35 0.15) for the bloom and post-bloom periods. Our results indicate that the contribution of MSA to the growth of the newly formed particles to a size at which they could act as condensation nuclei was considerably greater during the bloom and postbloom periods than during the pre-bloom period.

Introduction
Aerosols alter the radiative properties of the Earth's surface by means of direct (e.g., scattering and absorption of 40 solar radiation) and indirect (e.g., cloud life-time) effects, and thereby contribute to climate change (Albrecht, 1989;Haywood and Boucher, 2000;Sekiguchi et al., 2003). Moreover, acidification of the Arctic Ocean has been enhanced because of increasing addition of anthropogenic CO2 facilitated by ocean freshening and greater air-sea CO2 exchange (Lee et al., 2011). The recent acceleration of Arctic warming has highlighted the role of natural aerosols in influencing the radiative properties of the Arctic atmosphere (Dall'Osto et al., 2017;Willis et al., 2018). Nonetheless, current knowledge of 45 the effect of aerosols on climate regulation and the mechanisms of formation of natural aerosols is far from comprehensive, and more alarmingly is ambiguous (Mahowald et al., 2011;IPCC, 2013). In the atmosphere sulfate aerosols effectively form new particles through homogeneous nucleation and clustering reactions that are closely linked to water vapor and ammonia (negative ion-induced ternary nucleation; Kulmala, 2003;Kulmala et al., 2004), whereas methanesulfonic acid (MSA) particles tend to condense more onto existing particles and eventually contribute to particle growth (Wyslouzil, et al., 1991;50 Leaitch et al., 2013;Hayashida et al., 2017). The production of sulfuric acid and MSA (having low volatility vapors) when few condensation sites are available could result in an increase in new particle formation (NPF) (Boy et al., 2005), so dimethylsulfide (DMS) emissions from the Arctic Ocean could contribute considerably to NPF and climate regulation (Dall'Osto et al., 2017). The growth of particles following NPF is particularly crucial in generating cloud condensation nuclei (CCN), which eventually lead to cloud formation. As a result, naturally produced gas molecules can promote NPF and 55 subsequent growth of particles in the presence of sulfate and MSA (DMS oxidation products) (Chang et al., 2011a;Burkart et al., 2017). Hence, data on the quantities of non sea-salt sulfate (NSS-SO4 2− ) and MSA and their variations are crucial in elucidating NPF and particle growth, and ultimately the role of ocean phytoplankton in modulation of the radiative properties of the Arctic atmosphere. product ratio of DMS oxidized to MSA and biogenic sulfate (Bio-SO4 2− ) over the Arctic region reflect the complexity of aerosol chemistry. The product ratio of DMS oxidation is highly variable, and is affected by air temperature, relative humidity, precipitation, and solar radiation (Hynes et al., 1986;Yin et al., 1990;Bates et al., 1992b). Among those factors involved, air temperature is known to largely determine the oxidation pathways of DMS. At ambient temperatures the 70 proportions of MSA and Bio-SO4 2− are typically 0.25 and 0.75, respectively (Hynes et al., 1986). DMS is well known to be oxidized more to MSA at lower temperatures. The observed latitudinal variations in the product ratio of DMS oxidation are largely consistent with those predicted from the temperature dependence of the oxidation pathway of DMS (Hynes et al., 1986;Berresheim et al., 1990;Bates et al., 1992b), although equally available are reports on an absence of temperature dependence (Ayers et al., 1991;Prospero et al., 1991;Chen et al., 2012). The product ratio of DMS oxidation is a result of 75 the net effect of multiple processes, including concentration of atmospheric oxidants and meteorological factors influencing DMS oxidation. Therefore, the ratio could vary considerably among seasons and years.
To investigate DMS oxidation pathways in the Arctic atmosphere we measured sulfate aerosol concentrations at 3day intervals from 2015 to 2019; this provided comprehensive datasets encompassing seasonal and interannual variations in sulfate and MSA concentrations in aerosol particles in the Arctic atmosphere. In particular, S isotope ratios were measured 80 for all aerosol samples, and were used to partition the total NSS-SO4 2− into anthropogenic sulfate (Anth-SO4 2− ) and Bio-SO4 2− (the oxidative product of biogenic DMS). We also calculated the product ratio of MSA to biogenic aerosols (MSA + Bio-SO4 2− : Bio-aerosol). Analysis of Anth-SO4 2− , Bio-SO4 2− , and MSA concentration data, in conjunction with data on air mass back-trajectories enabled identification of the sources of S aerosols, and elucidation of factors governing variations in their concentrations. 85

Sampling site and aerosol sampling
Aerosol samples were collected at 50 m above sea level at the Gruvebadet observatory (78.9° N, 11.9° E; Fig. 1a) at Ny-Ålesund, Svalbard. Sampling covered the phytoplankton pre-bloom (defined as March to the 2nd week of April), bloom (3rd week of April to the 2nd week of June), and post-bloom periods (3rd week of June onwards). Division of these periods 90 was subjectively made based on the mean chlorophyll-a (Chl-a) concentration in the Greenland and Barents seas near Svalbard. The period during which the concentration of Chl-a was > 0.5 mg m −3 was defined as the phytoplankton bloom period, whereas the periods when the concentration of Chl-a was < 0.5 mg m −3 prior to and following the bloom were defined as the pre-bloom and post-bloom periods, respectively.
Aerosol samples were collected at 3-day intervals using a high volume sampler (HV-1000R; SIBATA, Japan) 95 outfitted with a PM 2.5 impactor (collecting particles < 2.5 µm in aerodynamic equivalent diameter). The aerosol sampler was mounted on the roof of the Gruvebadet observatory. Particulate matter in the atmosphere was collected on a quartz filter https://doi.org/10.5194/acp-2020-1270 Preprint. Discussion started: 2 February 2021 c Author(s) 2021. CC BY 4.0 License. over approximately 72 h at a flow rate of 1000 L min −1 , corresponding to a total air volume of 4320 m 3 . The method of aerosol sampling has been described elsewhere .

Atmospheric DMS mixing ratio and major ions in aerosol samples 100
The analytical system enabling measurement of atmospheric DMS mixing ratio at parts per trillion levels is equipped with a DMS trapping component, a gas chromatograph, and a pulsed flame photometric detector. The detection limit of the DMS system was close to 1.5 pptv with a sampling air volume of 6 L and the description of the system can be found elsewhere (Jang et al., 2016).
For determination of concentrations of major ions, a disk filter (47-mm diameter) was taken from a whole quartz 105 filter (20.3 cm × 25.4 cm), soaked in 50 mL of Milli-Q water and sonicated in a bath for 60 min; aliquots of this solution were used for analysis. Milli-Q water used for the ion extraction was produced using a water purification system (Milli-Q Direct 16, Merck Millipore, USA). The concentrations of water-extractable inorganic anions and cations including MSA, were measured using ion chromatography (Dionex ICS-1100, Thermo Fisher Scientific Inc., USA) fitted with an IonPac AS 19 column (Thermo Fisher Scientific Inc., USA). The instrumental detection limits were 0.02 μg L −1 for MSA and 0.02 μg 110 L −1 for SO4 2− . From replicate injections, the analytical precision was determined to be < 5 % (relative standard deviation).

Stable S isotope ratio in sulfate aerosols
For measurement of stable S isotope ratio (δ 34 S) in an aerosol sample, half of the quartz filter was soaked in 50 mL Milli-Q water and sonicated for 60 min. Then, 50-100 µL of 1 M HCl was added to the solution (resulting in a pH of 3-4), after which 100 µL of 1 M BaCl2 solution was injected into the solution, leading to gradual precipitation of BaSO4. 115 Following the completion of precipitation over 24 h, the BaSO4 precipitates were filtered onto a membrane filter and dried for another 24 h prior to S isotope ratio measurement. Each membrane filter was packed into a tin capsule and analyzed using an isotope ratio mass spectrometer (IsoPrime100; IsoPrime Ltd, UK) and an elemental analyzer (Vario MICRO cube; Elementar Co., Germany). Each filter treatment was carried out in a laminar flow hood to minimize contamination.

Black carbon
An aethalometer (model AE31; Magee Scientific Co., USA) installed at the Zeppelin station was used to analyze the concentration of equivalent black carbon by measuring light-absorbing particles at a wavelength of 880 nm, as described by Eleftheriadis et al. (2009). The good congruence between the concentrations of Anth-SO4 2− and black carbon measured during the pre-bloom period (March to April) indicates that variations in black carbon were reasonably consistent with 150 variations in Anth-SO4 2− , reflecting that both Anth-SO4 2− and black carbon had common sources (i.e., fossil fuel combustion and forest burning) (Text S1; Figs. S1 and S2).

Air mass origin, chlorophyll-a concentration, and meteorological parameters
Both 8-day and monthly mean Chl-a concentration data level-3 MODIS Aqua were downloaded from the NASA OCEAN Color website (http://oceancolor.gsfc.nasa.gov/) at a 4-km resolution. The three-dimensional 5-d (120 h) back 155 trajectories were calculated using the Hybrid Single-Particle Lagrangian Integrated Trajectory model from the NOAA Air Resources Laboratory (Draxler and Hess, 1998). Meteorological parameters including solar radiation, relative humidity, and air temperature at each time point were also calculated along the air mass trajectories. The calculations were made based on https://doi.org/10.5194/acp-2020-1270 Preprint. Discussion started: 2 February 2021 c Author(s) 2021. CC BY 4.0 License. meteorological data from Global Data Assimilation System (at 1° latitude × 1° longitude resolution) produced by the National Centers for Environmental Prediction. Air masses were modelled to arrive at an altitude of 50 m above sea level at 160 the Gruvebadet station at each hour of the study period. To identify the major air mass pathways prior to reaching to the Gruvebadet station, the calculated air mass trajectories were grouped into several clusters using the k-means clustering algorithm. Monthly mean air temperature data at 900 hPa were obtained from European Centre for Medium-Range Weather Forecasts Reanalysis 5 at a 30-km resolution. Sea level pressure data were obtained from the National Oceanic and Atmospheric Administration Physical Sciences Laboratory (http://psl.noaa.gov/). 165

Atmospheric DMS mixing ratio
The mixing ratio of atmospheric DMS, a precursor of Bio-SO4 2− and MSA, showed considerable (several orders of magnitude) variability at daily to weekly intervals during the bloom and post-bloom periods (Figs. 2a and 3b). The atmospheric DMS mixing ratio generally corresponded to the phytoplankton biomass in the oceans surrounding Svalbard 170 (Figs. 2a and S3). During the bloom period the maximum monthly mean mixing ratio of DMS occurred in May 2015 (68.4 ± 86.8 pptv); an increase in the DMS mixing ratio continued until August of that year, reflecting the persistent phytoplankton biomass producing DMS in the vicinity of Svalbard. Based on our atmospheric DMS concentration data, we conclude that DMS was ubiquitous in the Arctic atmosphere for the entire period of warming from the phytoplankton bloom to post-bloom periods (Park et al., 2013). 175

S isotopic composition (δ 34 S) and sources of sulfate aerosols
The δ 34 S values for sulfate aerosols ranged from 2.2 to 17.6 ‰ between March and August ( Fig. 2b). In all years of measurement, the δ 34 S values were low in April or earlier months, rapidly increased towards May to June, and remained high towards August (Fig. 3c). As warming progressed, the trend of increasing δ 34 S in the sulfate aerosols was broadly consistent with the increasing mixing ratio of atmospheric DMS. The δ 34 S values for the pre-bloom, bloom, and post-bloom periods 180 averaged over five years were 7.5 ± 2.6 ‰, 9.5 ± 2.8 ‰, and 11.3 ± 2.8 ‰, respectively, reflecting an increasing enrichment in the heavier 34 S towards summer. The maximum monthly mean δ 34 S (13.5 ± 2.6 ‰) occurred in July 2018, whereas the lowest mean (3.7 ± 1.8 ‰) occurred in April 2019. The mean pre-bloom δ 34 S value in 2017 (9.2 ± 1.8 ‰) was higher than in 2018 (5.9 ± 1.2 ‰), whereas the mean bloom and post-bloom δ 34 S values were marginally lower in 2017 (11.0 ± 2.0 ‰) than in 2018 (12.5 ± 2.8 ‰). 185 On monthly scales the greatest contribution of Bio-SO4 2− occurred in August 2018 (59.4 ± 17.2 %) (Fig. S4). The proportion of Bio-SO4 2− among all SO4 2− particles was 18.1 ± 16.6 % during the pre-bloom period, and then sharply https://doi.org/10.5194/acp-2020-1270 Preprint. Discussion started: 2 February 2021 c Author(s) 2021. CC BY 4.0 License. increased to 37.2 ± 21.0 % during the bloom and post-bloom periods, whereas the contribution of anthropogenic SO2 was 79.2 ± 16.9 % during the pre-bloom period and 57.9 ± 21.4 % during the bloom and post-bloom periods. It is surprising that Anth-SO4 2− was found to be the largest contributor to total SO4 2− during all three periods (Fig. S4).

Ratio of MSA to Bio-aerosol (RBio)
In all years of this study the RBio values derived from δ 34 S data were lowest during the pre-bloom period and increased in the transition to the spring bloom, as biogenic DMS production peaked (Figs. 3i and 5c) Similar RBio values were also reported at Ny-Ålesund. For example, Udisti et al (2016) reported a MSA to Bio-225 SO4 2− ratio of 0.33 (RBio = 0.25) during the spring-summer period in 2014. This ratio was derived from a multi-seasonal asymptotic value in a plot between the MSA to NSS-SO4 2− ratio and the MSA concentration. Implicit in this calculation is the assumption that the fraction of Bio-SO4 2− in the total NSS-SO4 2− aerosols is overwhelming when the MSA to NSS-SO4 2− ratio approaches the asymptotic value (Udisti et al., 2016;Park et al., 2017). Other investigators also reported comparable RBio values in other Arctic environments: 0.18-0.20 at the central Arctic Ocean (Chang et al., 2011b;Leck and Persson 230 1996); 0.28 at the Eastern Antarctic Plateau (Udisti et al., 2012); and 0.28 at Alert (Norman et al., 1999). These RBio values were all derived from a multi-seasonal asymptotic value in a plot between the MSA to NSS-SO4 2− ratio and MSA concentration. The analytical accessibilities associated with measurements of MSA and NSS-SO4 2− concentration (i.e., less laborious and requires fewer aerosols than is needed for the technique measuring the S-isotope ratio) make data on the MSA to NSS-SO4 2− ratio more widely available. 235

Factors affecting variations in the S aerosol concentration in the Arctic atmosphere
Seasonal variations in NSS-SO4 2− aerosols were strongly associated with variations in Anth-SO4 2− . In particular, the tight association of these parameters indicates that Anth-SO4 2− aerosols were the largest contributor to NSS-SO4 2− during the pre-bloom period, when the intrusion of Arctic haze is considerable (Figs. S4 and S5). During the transition from the pre-240 bloom to bloom periods, the input of Anth-SO4 2− particles to our study area rapidly decreased because of weakening of the northward transport of air masses (containing Anth-SO4 2− ) from Europe and increasing removal of Anth-SO4 2− aerosols by increasing precipitation as the seasons progress (Li and Barrie, 1993) (Fig. 4b). The decreasing input of Anth-SO4 2− particles to the observation site during the bloom and post-bloom periods was also independently confirmed by the trend of decrease in the measured black carbon concentration at our observation site (Figs. 3a and S2). The large interannual variability in NSS-SO4 2− from March to April was strongly associated with changes in the trajectory of the air masses reaching Svalbard, and the sea level pressure along those air mass trajectories (Fig. 6) The MSA concentration remained low during the pre-bloom period (i.e., no apparent high peaks), largely because 260 of the greater removal of MSA relative to Bio-SO4 2− aerosols during long-range transport to Svalbard from the distant source regions to the south. For example, MSA tends to more easily condense onto existing particles (Hoppel, 1987;Pszenny et al., 1989) because of its higher vapor pressure, and is thus more rapidly removed from the atmosphere with larger particles through wet deposition; this results in greater loss of MSA relative to SO4 2− . Greater enrichment of MSA occurs in supermicron sized particles than in submicron particles (Legrand and Pasteur, 1998). The higher ratios of MSA to NSS-SO4 2− in 265 rainwater and fresh snows than in aerosol particles is also indicative of the greater removal of MSA (Berresheim et al., 1991;Jaffrezo et al., 1994). The production mechanism of MSA (via DMS oxidation by OH radicals) (Gondwe et al., 2004) could also lower the MSA concentration during the pre-bloom period, when the low levels of OH radicals (as a result of low light conditions) resulted in less MSA production. The elevations of MSA occurred in May or June, when the production of OH radicals was high and associated with increasing solar radiation and biological production ( Fig. S8 and S9a). 270 The concentrations of Bio-aerosol during the bloom and post-bloom periods were comparable in all three years (214 ± 124 ng m −3 in 2017, 204 ± 174 ng m −3 in 2018, and 160 ± 153 ng m −3 in 2019), despite differing phytoplankton biomass (derived from Chl-a) among those years (Fig. S9b). This mismatch has been reported previously, and suggests that estimations of marine organic aerosols based on Chl-a data only are unreliable (Rinaldi et al., 2013). In particular, the summer DMS-driven aerosols produced from the Barents Sea were not proportional to the Chl-a concentrations (Becagli et 275 al., 2016). Different compositions of phytoplankton species in different ocean domains (Greenland Sea versus Barents Sea) could also result in changes in DMS production because phytoplankton have differing cellular levels of dimethylsulfoniopropinate (DMSP; a precursor of DMS) and the DMSP cleavage enzyme (enabling the transformation of https://doi.org/10.5194/acp-2020-1270 Preprint. Discussion started: 2 February 2021 c Author(s) 2021. CC BY 4.0 License. DMSP to DMS) (Park et al., 2014b). The DMS production capacity in the Greenland Sea (where prymnesiophytes dominate) was found to be 3-fold higher than that in the Barents Sea (where diatoms dominate) (Park et al., 2018). Other studies have 280 also reported that the concentrations of MSA or Bio-SO4 2− do not always follow the atmospheric DMS mixing ratio, highlighting the involvement of other factors in the oxidation of DMS to MSA or Bio-SO4 2− (Read et al., 2008;Yan et al., 2020a). Therefore, the amounts of DMS produced and its oxidation products may not be solely explained by variations in the ocean biomass.
In the Arctic summer atmosphere the low abundance of large particles (i.e., Aitken and accumulation mode) could 285 probably enhance the formation of new particles via the gas-to-particle conversion process and the ultimate initiation of CCN formation (Boy et al., 2005;Dall'Osto et al., 2018). The concurrent increase in biogenic sulfate aerosols and small sized particles (3-10 nm and 10-100 nm, respectively) reported for the Arctic atmosphere in May  is a prime example that biogenic DMS is a major contributor to NPF. A model study reported that DMS enhanced the mass of sulfate particles in the size range 50-100 nm in regions north of 70° N (Ghahremaninezhad et al., 2019). During the bloom 290 and post-bloom periods a decline in anthropogenic sources and an increase in oceanic DMS source strength resulted in the transition of major sulfate sources from Anth-SO4 2− to Bio-SO4 2− , which highlights the increasing importance of biogenic sulfur aerosols in the summer Arctic atmosphere. Biogenic organic aerosols in the high Arctic were reported to contribute considerably to the concentrations of ultrafine and CCN particles from summer to early autumn when anthropogenic source is lowest (Dall'Osto et al., 2017;Lange et al., 2019). Nonetheless, Anth-SO4 2− contributed considerably to the total SO4 2− 295 budget during the post-bloom period, indicating that even in summer the Anth-SO4 2− transported from Europe or local emissions can exert a significant influence on the sulfate budget in the Arctic atmosphere (Fig. S4) (Chen et al., 2016;Gogoi et al., 2016;Dekhtyareva et al., 2018).

Seasonal variations in RBio 300
Our data spanning five years show two distinctive trends in RBio among seasons or years. The first is that the values of RBio during the bloom and post-bloom periods (0.32 ± 0.15) were a factor of three higher than the pre-bloom values (0.09 ± 0.07) (Fig. 5c). The large seasonal difference in RBio could be explained by known factors including the concentration of OH radicals (directly influenced by light intensity), air temperature (determining the oxidation pathway of DMS to either MSA or Bio-SO4 2− ), and the chemical properties of existing particles (e.g., the black carbon concentration) (e.g., Saltzman et 305 al., 1986;Gondwe et al., 2004;Yan et al., 2020b). Among those, a major factor is the concentration of OH radicals. BrO radicals also help facilitate the addition pathway in the oxidation of DMS, even at concentrations > 1 pptv level (von Glasow and Crutzen, 2004). It has been hypothesized that the reactive bromines produced photochemically and heterogeneously at sea ice and snowpack surfaces lead to the BrO enrichment over ice-covered regions (Abbatt et al., 2012;Fernandez et al., effectively mediated by photochemically activated species including OH and BrO. The solar radiation (51.3 ± 36.1 W m −2 ) over the distant DMS source regions during the pre-bloom period was much lower than over the Greenland Sea and the Barents Sea during the bloom (243.0 ± 63.4 W m −2 ) and post-bloom (222.5 ± 70.5 W m −2 ) periods (Fig. 7). The low OH radical and reactive bromine concentrations during the pre-bloom period probably lowered the production of MSA from DMS oxidation (i.e., weakening the addition pathway), and thereby resulted in the lower RBio value (0.09 ± 0.07) than was 315 found during the bloom (0.32 ± 0.17) and post-bloom (0.32 ± 0.13) periods. Consequently, solar radiation was likely to be a major driver of the seasonal RBio change in the Arctic atmosphere.
Another established factor that could affect the seasonal variations in RBio is air temperature. At lower air temperatures DMS is oxidized more to MSA (leading to higher RBio values), whereas at higher temperatures it is oxidized more to Bio-SO4 2− (leading to lower RBio values) (Hynes et al., 1986;Yin et al., 1990). For example, the values of RBio 320 measured near the equator (where the air temperature is high) are an order of magnitude lower than the values measured at high latitudes (where air temperature is low) (e.g., Bates et al., 1992b;Chen et al., 2012;Lin et al., 2012); these findings substantiate the linear dependence of the RBio on the air temperature. Equally available is evidence against the temperature dependence of RBio at given locations (Li et al., 1993;Legrand and Pasteur, 1998;Norman et al., 1999). In our study the air temperature (-1.8 ± 2.2 °C) in the distant DMS source regions (Region 2 in Fig. S10) during the pre-bloom period (March to 325 April) was slightly lower than that (-0.1 ± 4.4 °C) during the bloom and post-bloom periods (May to August) over the local Greenland and Barents seas (Region 1 in Fig. S10), where the higher RBio values were more determined by the local DMS source. The empirical relationship between temperature and DMS oxidation products points to lower RBio values at higher air temperatures (MSA/SO4 2− (%) = -1.5 × temperature (°C) + 42.2; Bates et al., 1992b). In contrast, our measurements pointed to the opposite trend, and further indicates that factors other than air temperature might be more important in the partitioning 330 of DMS into MSA or Bio-SO4 2− . Similar to our results, in other high latitude studies light intensity has been reported to be more important than air temperature in determining the seasonal variations in RBio (Gondwe et al., 2004).
The chemical properties of existing particles could influence the seasonal variations in RBio. In recent field studies the uptake of gaseous MSA onto particles was found to be sensitive to the chemical properties of those particles (Yan et al., 2020b). In particular, hydrophobic and acidic particles in the atmosphere tended to hinder the adhesion of gaseous MSA to 335 particles, while alkaline sea-salt particles tended to accelerate the adhesion process (Pszenny, 1992;Jefferson et al., 1998;Yan et al., 2020b). Elemental carbon particles emitted from fossil fuel combustion are highly hydrophobic, and sulfates in the aerosol particles are acidic. As a result, the air masses (rich in black carbon and sulfate) that originate from northern Europe would likely contain low MSA concentration in PM 2.5 particles, despite the fact that those air masses swept through the productive ocean areas during the pre-bloom period (Fig. 5a). In contrast, during the bloom period we found an elevation 340 of the MSA concentration, primarily as a result of two reinforcing processes: the greater DMS oxidation to MSA, and the enhanced condensation of gaseous MSA to the existing particles under less hydrophobic and acidic conditions. For each group of RBio values, the lower concentrations of black carbon and sulfate resulted in the greater uptake of gaseous MSA, https://doi.org/10.5194/acp-2020-1270 Preprint. Discussion started: 2 February 2021 c Author(s) 2021. CC BY 4.0 License. and thereby resulted in higher RBio values (Fig. 8). We also found significant inverse correlations between black carbon and RBio (r = -0.79; Fig. 9a) and between total SO4 2− and RBio (r = -0.73; Fig. 9b); these tight correlations substantiate the 345 importance of the chemical properties of atmospheric particles in determining the rate of uptake of gaseous MSA by the particles present in air. The number of samples measured during the bloom and post-bloom periods was higher in the groups having large RBio values (Fig. 8c). Therefore, the seasonal variations in RBio measured at Ny-Ålesund were probably controlled by the concentration of OH radicals (largely determined by light intensity) and the chemical properties of the particles containing black carbon and sulfates. 350 The RBio values in the present study, and those determined in other high latitude regions including Barrow in Alaska (USA) and Neumayer station in the Antarctic coastal region, consistently pointed to the highest RBio values occurring in summer (Li et al., 1993;Legrand and Pasteur, 1998;Norman et al., 1999). We found that seasonal variability in RBio measured in the Arctic region can be better explained by light conditions and the chemical properties of particles, rather than by air temperature. Specifically, the RBio values measured during the pre-bloom period poorly represent the oxidative 355 conditions of DMS in the Arctic atmosphere, because of the considerable intrusion of anthropogenic pollutants from the distant northern Europe. Thus, the RBio values measured during the bloom and post-bloom periods probably more accurately represent the ratio of the oxidation products of DMS produced in the ocean regions surrounding Svalbard under the less polluted conditions of the Arctic atmosphere.

Interannual variations in RBio 360
The second distinctive trend is the interannual difference in RBio. The RBio values measured in 2017 were much lower than the values in other years (2015Fig. 10). One explanation for large interannual variations in RBio is the difference in the condensation of gaseous MSA onto particles in the Arctic atmosphere. As noted above, the chemical properties of particles largely determines the rate of MSA condensation onto them (Jefferson et al., 1998;Yan et al., 2020b). During the pre-bloom and bloom periods in 2017, higher concentrations of black carbon and sulfate were found 365 relative to other years, and consequently, lower RBio values found in 2017 (Fig. 10). However, we found no discernible interannual difference in the concentrations of black carbon (8.3 ± 4.9 ng m −3 in 2017 and 9.5 ± 6.1 ng m −3 in other years) and total SO4 2− (235 ± 101 ng m −3 in 2017 and 232 ± 134 ng m −3 in the other years) during the post-bloom period (Fig. 10).
To our surprise, during the post-bloom period the RBio value (0.22 ± 0.07) in 2017 was only half the rate measured in the other years (0.39 ± 0.11). The lack of association between black carbon and sulfate concentrations and the RBio values 370 indicates that the chemical properties of particles may only partially impact the interannual variations in RBio values measured during the post-bloom period.
Air temperature difference may explain the interannual variations in RBio during the post-bloom period (Fig. S11).
However, the lack of correlation (e.g. Bates et al., 1992b) we found between RBio values and the mean temperatures of air masses along the entire pathway to Svalbard (Fig. S11b) is consistent with the results of other studies (Savoie et al., 1992;375 https://doi.org/10.5194/acp-2020-1270 Preprint. Discussion started: 2 February 2021 c Author(s) 2021. CC BY 4.0 License. Legrand and Pasteur, 1998;Zhan et al., 2017), implying that variations in air temperature were not a driver of determining the DMS branching ratio. We also found no discernible differences in solar radiation and relative humidity between year of 2017 and other years, thus neither solar radiation nor relative humidity showed any association with RBio ( Fig. S11c-d).
Thus, no meteorological factors adequately explain the interannual variations in RBio during the post-bloom period. The concurrent measurements of DMS and MSA during summer in the Southern Ocean reinforce our finding that temperature 380 and relative humidity have negligible effects on the conversion of DMS to MSA (Yan et al., 2020a). arguing against this hypothesis. In a similar vein, differences in RBio may also arise for local air masses within different airborne periods. This would be expected to apply to the local air masses over the Greenland and Barents Sea near the observation site. Because MSA (which contributes more to the growth of existing particles) and Bio-SO4 2− (which contributes more to new particle formation) have different fates in the atmosphere, local air masses with different airborne periods would be expected to have different RBio values. This is another possible cause of the observed interannual variations 390 in R during the post-bloom period. The interannual variations in RBio may also be associated with changes in the heterogeneous oxidation of MSA to sulfate by OH radicals on wet aerosol particles or cloud droplets (Hoffmann et al., 2016;Mungall et al., 2018), although assessment of this possibility was beyond the scope of the present study.
As sulfate and MSA particles have different roles in terms of particle formation and growth, the importance of RBio is worth highlighting. Sulfate particles (including sulfuric acids) are known to produce 4-6 times more submicron sized 395 particles than MSA, leading to a 10-fold stronger cooling effect via scattering of solar radiation (i.e., a direct effect), whereas the impacts of sulfate and MSA particles on cloud microphysics (i.e., an indirect effect) are comparable (Hodshire et al., 2019). Our results showing considerable seasonal or interannual variations in RBio indicate that the use of a single ratio for determining the oxidation products of DMS and evaluating the contribution of biogenic sources to the total sulfur budget at particular locations is problematic. 400

Conclusion and Implication
This study shows that in the Arctic atmosphere extensive production of the oxidation products of DMS (i.e., Bio-SO4 2− and MSA) occurred from the onset to the termination of phytoplankton blooms between 2015 and 2019. Anth-SO4 2− was found to be the largest contributor to total sulfate aerosols during the pre-bloom periods, as a result of the influence of 405 Arctic haze. Its contribution was comparable to that of Bio-SO4 2− during the bloom and post-bloom periods. We also found large interannual variations in anthropogenic and biogenic sulfur aerosols. Moreover, the ratio of MSA to Bio-SO4 2− (RBio) https://doi.org/10.5194/acp-2020-1270 Preprint. Discussion started: 2 February 2021 c Author(s) 2021. CC BY 4.0 License. tended to be higher (0.32 ± 0.15) in summer than in early spring (0.09 ± 0.07), indicating that in summer only 30 % of the oceanic DMS was oxidized to MSA, and the remainder was oxidized to Bio-SO4 2− aerosols. Our results imply that NPF, and subsequent growth of those particles to form CCN, are governed by both Bio-SO4 2− and MSA when RBio is high (bloom and 410 post-bloom periods), but that when RBio is low (pre-bloom period) MSA makes only a small contribution to particle growth and other molecules with low-volatility vapors (e.g., highly oxygenated organic molecules) are more involved in particle growth near Svalbard. The large interannual variability of RBio further indicates that condensational growth following NPF can be affected by MSA or other molecules with low-volatility vapors, depending on the branching ratio of DMS oxidation.
In modelling studies (Vallina et al., 2006(Vallina et al., , 2007 the annual contribution of biogenically induced CCN to total global 415 CCN has been estimated to be > 30 %, and up to 80 % in the austral summer in the Southern Ocean. This is similar to findings for the Northern hemisphere, where Bio-SO4 2− particles accounted for > 60 % of CCN in late spring (May and June) in the North Atlantic (Sanchez et al., 2018). An acceleration of sea ice retreat and an increase in melt ponds in the Arctic Ocean will increase biogenic DMS production, resulting in a greater contribution of biogenic S aerosols to atmospheric aerosol formation and climate regulation (Arrigo et al., 2008;Gourdal et al., 2018;Park et al., 2019). Our measurements 420 primarily focused on the particle phase of sulfur species (particles < 2.5 µm), but did not cover the initial phase of DMS oxidation and particle growth (i.e. nano size scales), including the gas-phase composition of sulfur species. Therefore, the integrated study of both the gas and particle phases of sulfur compounds (including gaseous MSA, SO4 2− , and hydroperoxymethyl thioformate), ocean colors, and sea ice properties will help define the climate-relevant impacts of oxidation products of biogenic DMS in the Arctic environment. 425 https://doi.org/10.5194/acp-2020-1270 Preprint. Discussion started: 2 February 2021 c Author(s) 2021. CC BY 4.0 License.

Data availability
All data needed to draw the conclusions in the present study are presented in this report and/or the Supplementary Materials.
For additional data related to this study, please contact the corresponding author (Kitack Lee; ktl@postech.ac.kr).

Supplement 430
The supplement related to this article is available on line at https:// Author contributions S.J., K.P., Y.Y., and K.L. designed the data analysis and wrote the manuscript. S.J. and K.P. performed the data evaluation and analyses. K.K. and H.C. performed the ion chromatograph measurements. K.E. provided the black carbon data. R.T. and S.B. were involved in aerosol sample collection. B.L., R.K., and O.H. contributed to the interpretation of the results. 435

Competing interests
The authors declare that they have no conflict of interest.