Measurement report: Spatial variations in snowpack ionic chemistry and water stable isotopes across Svalbard

Abstract. The Svalbard archipelago, between 74° and 81° N, is ∼60 % covered by glaciers and located at the Arctic sea ice edge. The region experiences rapid variations in atmospheric flow during the snow season (from late September to May) and can be affected by air advected both from lower and higher latitudes, which likely impact the chemical composition of snowfall. While long-term changes in Svalbard snow chemistry have been documented in ice cores drilled from two high-elevation glaciers, the spatial variability of the snowpack composition across Svalbard is comparatively poorly understood. Here, we report the results of the most comprehensive seasonal snow chemistry survey to date, carried out in April 2016 across 22 sites on 7 glaciers across the archipelago. At each glacier, three snow pits were sampled along altitudinal profiles and the collected samples were analysed for major ions (Ca2+, K+, Na+, Mg2+, NH+4, SO42−, Br−, Cl− and NO3−) and stable water isotopes (δ18O, δ2H). The main aims were to investigate the natural and anthropogenic processes influencing the snowpack and to better understand the influence of atmospheric aerosol transport and deposition patterns on the snow chemical composition. The snow deposited in the southern region of Svalbard was characterized by the highest total ionic loads, mainly attributed to sea salt particles. Both NO3− and NH4+ in the seasonal snowpack reflected secondary aerosol formation and post-depositional changes, resulting in very different spatial deposition patterns: NO3− had its highest loading in northwestern Spitsbergen, and NH4+ in the southwest. The Br− enrichment in snow was highest in northeastern glacier sites closest to areas of extensive sea ice coverage. Spatial correlation patterns between Na+ and δ18O suggest that the influence of long-range transport of aerosols on snow chemistry is proportionally greater above 600–700 m a.s.l.


contrasting mixtures of aerosol, varying by source area (Aas et al., 2016;Forsström et al., 2009;Möller 73 and Kohler, 2018). These regional differences are also associated with contrasts in sea ice cover. While 74 all Svalbard coasts are usually ice-free in summer, sea ice can form and cover large parts of the ocean 75 surface in the eastern and northern parts of the archipelago, while the southern and western parts often 76 remain ice-free (Dahlke et al., 2020), and therefore tend to experience greater snowfall owing to the 77 proximity of open water. In addition, the West Spitsbergen Current, a branch of the Atlantic Meridional 78 Overturning Circulation (AMOC) that flows to the west of the archipelago, causes markedly different 79 regional climatic conditions between its eastern and western parts (van Pelt et al., 2019): the west 80 exhibits higher temperatures and precipitation, while the east is less humid and cooler, and has also 81 experienced a stronger warming trend since 1957. 82

83
The seasonal snowpack contains a complex mixture of impurities that are either scavenged from the 84 atmosphere during snowfall or directly received through dry deposition (Kuhn, 2001). On land, the 85 majority of impurities found in seasonal snow are usually eluted during summer melting, influencing 86 terrestrial and aquatic systems (Björkman et al., 2014;Brimblecombe et al., 1987). However, in the 87 accumulation area of Arctic glaciers and ice caps, impurities can be retained within or below the seasonal 88 snow layer (Björkman et al., 2014;Pohjola et al., 2002;Vega et al., 2015b). For this reason, chemical 89 impurities such as major ions (Ca 2+ , K + , Na 2+ , Mg 2+ , NH 4 + , SO4 2-, Br -, Cland NO 3 -) in ice cores have 90 been widely used to study past trends of atmospheric and climatic conditions 91 Isaksson et al., 2003;Thompson et al., 2002;Wolff et al., 2010). Previous studies in Svalbard (Goto-92 Azuma et al., 1994;Nawrot et al., 2016;Semb et al., 1984;Winther et al., 2003) have shown that the 93 chemistry of the seasonal snowpack is dominated by sea salt ions (Hodgkins and Tranter, 2017). 94 However, the region is also a sink for atmospheric contaminants brought in by long-range transport 95 (Vecchiato et al., 2018). Investigations of precipitation and snow cover chemistry have predominantly 96 focused on the central and western parts of the archipelago (Kühnel et al., 2011;Nawrot et al., 2016;97 Vega et al., 2015a;Virkkunen et al., 2007), due to the accessibility of research facilities in these sectors. 98

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In the present study, the concentration, mass loading, spatial and altitudinal distribution of major ion 100 species (Ca 2+ , K + , Na 2+ , Mg 2+ , NH 4 + , SO 4 2-, Br -, Cland NO 3 -) in snow, together with its stable oxygen 101 and hydrogen isotope composition (δ 18 O and δ 2 H), were evaluated in the late winter snowpack at 22 102 glacier sites across Svalbard. This study was part of the larger Community Coordinated Snow Study in 103 Svalbard (C2S3) project and the most comprehensive survey of seasonal snow chemistry in Svalbard to 104 date. The snowpack survey, which was carried out by coordinated teams using a standardized sampling 105 protocol (Gallet et al., 2018) aimed to map and characterize regional differences in the chemical 106 composition and impurity load of the winter snow pack, and interpret the observed differences in relation 107 to meteorological and other environmental factors. In this way, we aim to identify the conditions 108 https://doi.org/10.5194/acp-2020-740 Preprint. Discussion started: 2 September 2020 c Author(s) 2020. CC BY 4.0 License. 1.0 mmol L -1 + Na 2 CO 3 3.2 mmol L -1 ). Cations were determined without suppression (column Metrosep 149 C4 + Metrosep C4 Guard; eluent: HNO 3 1.7 mmol L -1 + 2,6-pyridinecarboxylic acid [dipicolinic acid, or 150 DPA] 0.7 mmol L -1 ). Cation samples were acidified with 2 µL of 2mM HNO 3 per 10 mL sample prior to 151 analysis, as recommended for this device and column. The injection volume was 20 µL in the anion 152 system and 100 µL in the cation system. Nitric acid solutions were prepared from POCH S.A. ( Anion determination was performed using a Dionex TM ICS-5000 ion chromatograph 165 (ThermoScientific TM , Waltham, US) equipped with an anionic exchange column (Dionex IonPac AS 11, 166 2 × 250 mm) and a guard column (Dionex IonPac AG11 2 × 50 mm). Sodium hydroxide (NaOH), used 167 as a mobile phase, was produced by an eluent generator (Dionex ICS 5000EG, Thermo Scientific). The 168 injection volume was 100 µL. The IC was coupled to a single quadrupole mass spectrometer (MSQ 169 Plus™, Thermo Scientific ™) with an electrospray source (ESI) that operated in negative mode. To 170 determine cations, a capillary ion chromatograph (Thermo Scientific Dionex ICS-5000), equipped with a 171 capillary cation exchange column (DionexIonPac CS19-4µm, 0.4 × 250 mm) and a guard column 172 (Dionex IonPac CG19-4µm, 0.4 × 50 mm), was used, coupled to a conductivity detector. The injection 173 volume was 0.4 µL. All details about the anion and cation methods are reported by (Barbaro et al., 2017). 174 175

Instrumental performance of each laboratory 176
For all laboratories, calibration for ions were evaluated using analytical standards (Merck/Sigma 177 Aldrich). The calibrations in each lab gave different linear ranges for each ion due to the different 178 methods used (Table S1). Good linearity was demonstrated in each lab and all calibration curves had 179 R 2 >0.99. Samples that had ion concentrations beyond the calibration range were diluted with ultrapure 180 water before re-analysis. Analytical blanks of ultrapure water (>18 MΩ·cm) were included in the 181 https://doi.org/10.5194/acp-2020-740 Preprint. Discussion started: 2 September 2020 c Author(s) 2020. CC BY 4.0 License. analysis at all three labs. The method detection limit (MDL) was set to three times the standard deviation 182 of the blank values (Table S1) at the concentration of 10 mg L -1 ± 0.2%. Accuracy is expressed as a relative error calculated as 192 (Q−T)/T×100, where Q is the determined value and T is the "true" value. The accuracy for each ion in all 193 labs was always <±10%, except for Mg 2+ measurements at the Hornsund laboratory. The analytical 194 precision was quantified as the relative standard deviation (RSD) for replicates (n>3) of standard 195 solutions and was always <10% for each ion (Table S1). 196 197

Stable water isotopes 198
The determination of stable isotope ratios of O and H was performed at Tallinn University of Technology 199 using a Picarro L2120-i water isotope analyser with a high-precision AO211 vaporizer. Results are 200 reported in the standard delta notation as δ 18 O and δ 2 H relative to VSMOW. Reproducibility was ±0.1‰ 201 for δ 18 O and ±1‰ for δ 2 H, respectively. 202 203 https://doi.org/10.5194/acp-2020-740 Preprint. Discussion started: 2 September 2020 c Author(s) 2020. CC BY 4.0 License.

Spatial distribution of ionic species 205
To investigate differences in snowpack composition across all glaciers, we compared the total mass of 206 ions that accumulated in snow at the different sampling sites. On average, the snow cover season on 207 Svalbard lasts from early September to early May, but snow may also fall in summer months at high 208 elevations. The snow pits in this study were sampled in early to late April 2016 and might therefore not 209 contain the full annual ionic burden, since deposition might occur also in other months. Therefore, we 210 report these data as ionic loads (mg m -2 ) rather than annual fluxes. In each snow pit, the ionic load was 211 calculated as the cumulative sum of the ionic concentrations multiplied by the snow water equivalent in 212 each discrete layer. The snowpack chemical characteristics were then compared between glacier zones 213 (ablation zone, ELA, and accumulation zone; Table 2, Figure 1). 214 215 Snow pits samples collected in the Hornsund area (southern Spitsbergen) showed a markedly higher total 216 load for all major ions (Figures 1 and 2) than at all other sites. The samples collected in the accumulation 217 zones of WB and HB had total ionic loads of 8161 and 8023 mg m -2 , respectively, four times higher than 218 those collected in the same zone at KVG (2861 mg m -2 ), AF (2607 mg m -2 ) and ALB (1934 mg m -2 ) and 219 16 times higher than those sampled at LF (639 mg m -2 ) and HDF (583 mg m -2 ). Similar differences were 220 observed for the snow pits collected at lower altitudes ( Figure 2). 221

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In the accumulation zone of all glaciers ( Figure S1), Na + and Clwere generally the most abundant ionic 223 species, with percentages ranging from 29% (HDF) to 36% (AF) for Na + , and from 34% (LF) to 48% 224 (HB and WB) for Cl -, respectively. The snowpack on Hornsund glaciers (HB, WB) had higher Cl -225 percentages (48-49%) compared to that of other glaciers (34-39%), while conversely the SO 4 2percentage 226 was lower there (9%) than on other glaciers (11-23%). The ionic loads were generally highest in the 227 accumulation zone of glaciers, and lowest in the ablation zone (Figure 2), mostly due to the lower snow 228 accumulation and greater wind deflation at lower elevations. This pattern held true for Na + , Cl -, NH 4 + , 229 K + , Ca 2+ , and Mg 2+ at most glacier sites, except in the Hornsund region. The load of Brwas similar on 230 glaciers of the Ny-Ålesund sector (ALB, HDF, KVG) and on LF, but was higher in AF and Hornsund 231 glaciers (HB, WB; Figure 2). The load of NO 3 was similar for all glaciers, except for LF, where very low 232 loads were found. Unlike total SO 4 2-, the non-sea-salt fraction of sulphate (nss-SO 4 2-), calculated using a 233 seawater SO 4 2-:Na + mass ratio of 0.252, (Millero et al., 2008) showed lower loads on Hornsund glaciers 234 (15-107 mg m -2 ) when compared to glaciers in other parts of the archipelago (Figure 1, Table 2). The However, on other glaciers this pattern did not hold: on AF, we found an increase from AF1 to AF2, but 249 a decrease from AF2 to AF3; on WB the δ 18 O and δ 2 H were similar at WB1 and WB2, but less negative 250 at WB3. On HB there was no statistical difference between the mean δ 18 O and δ 2 H value in all snow pits. 251 A general, significant anticorrelation with altitude was found for SWE-weighted mean δ 2 H (ρ= -0.63, 252 p<0.01), and δ 18 O (ρ= -0.65, p<0.01). 253 254

256
There have been few published studies on recent seasonal snow or firn chemistry in Svalbard, hence 257 comparisons of our data with these earlier results are limited to a few sites. (Virkkunen et al., 2007) and 258 (Vega et al., 2015a) and unpublished data) quantified the annual chemical loads of Na + , Ca 2+ , NO 3 and 259 nss-SO 4 2at Lomonosovfonna summit (LF3) from 2002 to 2011 using snow and firn cores, and our study 260 extends these data to 2016. The range of annual ionic loads at LF3 over the 15-year period is remarkably 261 wide, but no clear temporal trend can be identified (Table 3). At Holtedahlfonna summit (HDF3), firn 262 core measurements by (Spolaor et al., 2013) found a mean Na + concentration of 110 ±73 ng g -1 over the 263

The main ion sources in the Svalbard seasonal snow 267
The composition of the Svalbard seasonal snowpack sampled during the C2S3 project clearly indicates 268 that the ocean is the main source of ions in snow, as was shown by Hodgkins and Tranter (2017). At all 269 sites, the dominant ions are Na + , Cl -, and SO 4 2-, with comparatively minor amounts of K + , Ca 2+ and Mg 2+ 270 ( Figure S1). To help clarify the possible sources and modes of deposition of ions in snow, we computed 271 Spearman rank correlations between total ionic loads (ρ load ), as well as between volume-weighted mean 272 ionic concentrations (ρ conc ), across all snow pits (n = 22; Table 4). The chemical species that are 273 predominantly wet-deposited and sharing common sources and not undergoing significant composition 274 changes in transport should exhibit similar concentration patterns (high ρ conc ) (Schüpbach et al., 2018). 275 The concentrations of Mg 2+ , K + and Ca 2+ were all positively correlated with those of Na + and Cl -, 276 https://doi.org/10.5194/acp-2020-740 Preprint. Discussion started: 2 September 2020 c Author(s) 2020. CC BY 4.0 License.
indicating a common sea spray source. The ρ load correlations are very similar for these ionic species, 277 which points to both wet and dry deposition being a significant mechanism in their accumulation in 278 snowpack. 279

280
The concentrations of Mg 2+ were positively and significantly correlated with both Ca 2+ and nss-Ca 2+ (ρ conc 281 = 0.70 and 0.47, respectively; the latter coefficient was higher for loads at 0.56; Table 4), suggesting they 282 share some non-marine source(s). Furthermore, all glaciers had greater Ca 2+ :Mg 2+ ratios than seawater 283 Another plausible source of nss-SO 4 2deposition in Svalbard is long-range transport of SO 4 2aerosols 296 from biomass burning in the spring, or from fossil fuel combustion throughout the winter (Barrie, 1986;297 Law and Stohl, 2007;Nawrot et al., 2016). The nss-SO 4 2did not correlate significantly with other ionic 298 species, suggesting a separate origin. An extra consideration is that in the southern region of the 299 archipelago, the higher sea spray input could partially mask the nss-SO 4 2signal, which is a derived 300 variable, because the larger uncertainty for greater Na + concentrations would disproportionately affect 301 estimations of nss-SO 4 2at these sites.

304
(ρ load = 0.55) and NH 4 + (ρ load = 0.68), but the correlations between weighted mean ionic concentrations 305 were not significant, hinting at co-deposition (wet) rather than shared sources (Table 4). These species 306 are known to form secondary aerosols (Karl et al., 2019;Schaap et al., 2004) and thus their proportions 307 in aerosols may differ significantly from those in their source emissions. It is also possible that nitrogen 308 species underwent further post-depositional photochemical reduction and evasion, thereby reducing their 309 concentrations in snow (Curtis et al., 2018). Finally, we remark here that the snow pit sampling was done 310 in April, earlier than the beginning of the oceanic algal bloom in the surrounding Svalbard basin, which 311 could have led to underrepresentation of biological emissions from late spring in our samples. 312 313 https://doi.org/10.5194/acp-2020-740 Preprint. Discussion started: 2 September 2020 c Author(s) 2020. CC BY 4.0 License. Spatial variations of ammonium loads (NH 4 + ) across Svalbard glaciers mirrored the pattern shown by sea 314 salt ions, with higher loads in the Hornsund region and lower loads in other areas. This was also reflected 315 by significant correlations between bulk loads of NH 4 + with those of Na + and Cl -(ρ load = 0.64 and 0.73, 316 respectively), and with Na + , K + and Mg 2+ by concentration (ρ conc = 0.47, 0.62 and 0.47, respectively), the 317 latter relationships suggesting that some ammonium is deposited as coatings on crustal aerosols 318 (Eastwood et al., 2009). Ammonium has been linked to biogenic, forest fire, and anthropogenic 319 agricultural emissions (Trachsel et al., 2019). The higher annual snowpack load of NH 4 + , determined in 320 the Hornsund region is more likely connected with biological sources than anthropogenic activities, 321 although some contribution from biomass burning events cannot be excluded. The marine primary 322 productivity in spring 2016 (April and May) was higher in the south-eastern ocean sector of the Svalbard 323 archipelago ( Figure S4), which could partially explain the higher NH 4 + load. This would also explain the 324 correlation between ammonium and sea-salt ions (Table 4) with the long-range atmospheric transport of NO x and related N species from anthropogenic source 330 regions at lower latitudes (Björkman et al., 2014;Fibiger et al., 2016;Vega et al., 2015a). Differences in 331 NO 3 loads in snow in various parts of Svalbard might therefore reflect differences in the transport 332 pathways of precipitating air masses, including formation of secondary aerosols, or post-depositional 333 processes, rather than local emissions. While local shipping routes and the settlement of Ny Ålesund 334 itself may contribute NO 3 emissions (Winther et al., 2014), the highest share of the total ionic load of 335 NO 3 was found in the accumulation zone of HDF (9% of the total ionic load; Figure S1). Given that 336 HDF is the most remote site from Ny Ålesund relative to KVG or ALB, it should not capture a high 337 share of local pollution. The highest correlation coefficient for NO 3 -, both in terms of concentrations and 338 loads, was found with nss-Ca 2+ . This would support both the formation of calcium nitrate in the

Chlorine depletion 344
Although Na + and Cl -, the main species of sea salt, were significantly correlated (ρ conc = 0.95), the values 345 of the Cl -/Na + ratio in snow were lower than that in seawater on most studied glaciers, except those near 346 Hornsund (Figure 3), suggesting a Cldeficit at the more northerly sites. A possible explanation of this 347 Cldeficit might be de-chlorination of the sea spray aerosol during transport or, less likely, at the snow-348 atmosphere interface. This reaction occurs between sea salt particles, containing NaCl, and NO 3 -, SO 4 2-, 349 or organic acids to release gaseous HCl (Zhuang et al., 1999). We calculated the percentage of Cl -350 https://doi.org/10.5194/acp-2020-740 Preprint.  Newly-formed sea ice has been shown to release gas phase Br into the polar atmosphere, thus supplying 377 an extra Br source in addition to sea spray (Spolaor et al., 2016). The spatial distribution of the Br-378 enriched snow pit sites supports this : sites closest to areas covered by first-year sea ice have the largest 379 Br enrichments, and the latter decrease with greater distance from the eastern shores of Svalbard (  showed that only beyond 79.2 °N, i.e. in Austfonna snow pits, was d significantly different than at other 400 sites (Kruskal-Wallis test, z = 4.23, p < 0.04). This is consistent with lower temperatures and evaporation 401 rates in the more northern waters around Svalbard, and suggests that snowfall on AF is at least partly 402 affected by a different, more northerly moisture source than the rest of the archipelago. 403 404

Effect of elevation: a case study of Na 405
The glacier survey carried out during the C2S3 project afforded the opportunity to investigate the 406 possible effect of elevation on the ionic composition of the snowpack. To do this, we compared the bulk 407 load and SWE-weighted mean concentration of Na + across all studied snow pits, ordered by elevation 408 (Figure 4). Overall, both Na + loads and concentrations decreased with increasing altitude (ρ load = -0.24, p 409 >0.05; ρ conc = -0.72, p < 0.05). This likely reflects greater local sea spray aerosol deposition at lower, 410 compared to higher, glacier sites. We then computed linear (Pearson) correlation coefficients (R, with 411 associated p-values) between log-transformed Na + loadings (log(Na load )) and δ 18 O for all snow pits in the 412 accumulation zones of glaciers ( Figure 5). The calculation was performed with all snow layers. The Na + 413 load was used as sea-spray tracer, while the δ 18 O was assumed to vary with moisture source between 414 discrete snowfall events. We found that the positive correlation between log(Na load ) and  suggests that the co-registered Na + enhancements were associated with precipitation of relatively warm 428 air, probably advected from lower latitudes. Air masses arriving from the south travel across the ocean 429 for an extended time, which can enrich them in sea spray aerosol and hence in Na + . It is also possible that 430 the poorer log(Na load )-δ 18 O correlation at lower altitude glacier sites is partly due to stronger post-431 depositional modification of isotopic and ionic signals in snowpack related to more frequent melt-432 refreeze episodes. 433 434

5.Summary and Conclusion 435
We have quantified and described, for the first time, the spatial distribution of major ion loads (Ca 2+ , K + , 436 Na 2+ , Mg 2+ , NH 4 + , SO 4 2-, Br -, Cland NO 3 -) and variations of δ 18 O and δ 2 H in the snowpack on glaciers 437 across Svalbard for a single accumulation season (2015)(2016). The highest total ionic loads were found 438 in the southern region of Spitsbergen (Hornsund area), and exceeded 8 g m -2 . Conversely, the lowest total 439 ionic loads (≤ 0.6 g m -2 ) were found at sites in central or northwestern Spitsbergen (LF and HDF). Sea 440 salt ions (Cl -, Na + and SO 4 2-) dominated the ionic loads at all sites, but their share was highest at sites 441 near Hornsund, for e.g., 48% Cl -, compared to only 29% on Holtedahlfonna. Relatively elevated 442 Ca 2+ /Mg 2+ ratios in snow at all sites indicated non-sea-salt Ca 2+ inputs, most likely in the form of 443 carbonate dust. Unlike other ions, NO 3 had the highest loads in glaciers of northwestern Spitsbergen, and 444 the lowest at LF. The nitrogen species, NO 3 and NH 4 + , showed distinct spatial distribution patterns. The 445 highest NO 3 loads were found in the northwestern part of Svalbard, while the highest NH 4 + loads were in 446 the southwest. Bromide (Br -) was most enriched in snow relative to seawater at AF and LF, the glacier 447 sites located closest to areas with first-year sea ice cover. This supports first-year sea ice being an 448 important source of non-sea salt Brin the polar atmosphere. 449 450 An increasing, positive correlation between log(Na load ) and δ 18 O as a function of elevation sites suggests 451 that locations above 600-700 m a.s.l. are influenced by a proportionally higher share of ions from distant 452 sources, while the lower sites are exposed to more local sources, especially sea spray. These findings 453 confirm that the optimal sites to study the effects of long-range pollution deposition in Svalbard are those 454 found at higher elevations sites, such as the accumulation zones of HDF or LF, because they are the least Kuhn, M.: The nutrient cycle through snow and ice, a review, Aquatic Sciences, 63, 150-167, 2001. 558 Kühnel, R., Roberts, T. J., Björkman, M. P., Isaksson, E., Aas,W.,Holmén,K.,and Ström, Climatology of NO3 and NH4+ Wet Deposition at Ny-Alesund, Svalbard, Advances in Meteorology, 560 2011, 10, 2011 Law, K. S. and Stohl, A.: Arctic Air Pollution: Origins and Impacts, Science, 315, 1537Science, 315, , 2007 Maturilli, M., Herber, A., and König-Langlo, G.: Climatology and time series of surface meteorology in 563 Ny-Älesund, Svalbard, Earth Syst. Sci. Data, 5, 155-163, 2013. 564 Millero Oceanographic Research Papers, 55, 50-72, 2008. 567 Möller, M. and Kohler, J.: Differing Climatic Mass Balance Evolution Across Svalbard Glacier Regions 568 Over 1900-2010, Frontiers in Earth Science, 6, 128, 2018 Nawrot, A. P., Migała, K., Luks, B., Pakszys, P., and Głowacki, P.: Chemistry of snow cover and acidic 570 snowfall during a season with a high level of air pollution on the Hans Glacier, Spitsbergen, Polar 571 Science , 10, 249-261, 2016. 572 Nordli, Ø., Przybylak, R., Ogilvie, A. E. J., and Isaksen, K.: Long-term temperature trends and 573 variability on Spitsbergen: the extended Svalbard Airport temperature series, 1898-2012, Polar Res, 574 33, 21349, 2014 Peterson       Table 4. Spearman rank order correlations of a) ionic loads (mg m -2 ) and b) SWE-weighted mean concentrations of major ions across all 7 glaciers (n=22 locations). ns = non-significant correlations (p-value > 0.05). Ionic loads were calculated from all snow pit layers, while SWE-weighted mean concentrations were calculated by dividing the ionic loads in each snow pit by its total SWE. Non-sea-salt (nss) components were estimated based from seawater ratios to Na +