# Colloidal associations of major and trace elements in the snow pack across a 2800-km south-north gradient of western Siberia

Ivan Krickov, Artem Lim, Sergey Vorobeyev, Vladimir Shevchenko, Oleg Pokrovsky

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Ivan Krickov, Artem Lim, Sergey Vorobeyev, Vladimir Shevchenko, Oleg Pokrovsky. Colloidal associations of major and trace elements in the snow pack across a 2800-km south-north gradient of western Siberia. Chemical Geology, 2022, 610, pp.121090. 10.1016/j.chemgeo.2022.121090. hal-04907588

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# Colloidal associations of major and trace elements in the snow pack

across a 2800-km south-north gradient of western Siberia

Ivan V. Krickov<fnref n="1" />, Artem G. Lim<fnref n="1" />, Sergey N. Vorobyev<fnref n="1" />,

Vladimir P. Shevchenko<fnref n="2" />, Oleg S. Pokrovsky<fnref n="3" />, 4*

<footnote n="1">¹ BIO-GEO-CLIM Laboratory, Tomsk State University, Lenina av., 36, Tomsk, Russia</footnote>

<footnote n="2">²Shirshov Institute of Oceanology, Russian Academy of Sciences, Nakhimovsky prospect, 36, Moscow, Russia</footnote>

<footnote n="3">³ Geoscience and Environment Toulouse (GET), UMR 5563 CNRS University of Toulouse, 14 Avenue Edouard Belin, 31400 Toulouse, France,</footnote>

<footnote n="4">⁴ N. Laverov Federal Center for Integrated Arctic Research of the Ural Branch of the Russian Academy of Sciences (FECIAR UrB RAS), Arkhangelsk, Russia</footnote>

<footnote>*oleg.pokrovsky@get.omp.eu</footnote>

<footnote>Keywords: snow, colloids, carbon, trace element, river, Arctic</footnote>
ABSTRACT

Colloidal (size 1 nm to 1 µm) transport of major and trace elements, notably micronutrients and low-
solubility geochemical tracers, is a ubiquitous and well-established feature for all surface and soil waters in
boreal and subarctic regions. However, little is known on the colloidal associations of organic carbon (OC)
and major and trace elements in atmospheric precipitation such as snow. This is despite significant efforts
devoted to distinguishing the soluble and particulate transport of trace metals and contaminants by
atmospheric aerosols. To acquire a *snap-shot* of major and trace element size fractionation in the snow cover
of western Siberia, we sampled snow cores integrated over the entire depth (0-50 cm until bottom) across a
sizable (2800 km) south - north transect in the Ob River watershed (western Siberia). A number of trace
metal pollutants (Cr, Ni, Zn, Cd) exhibited significant linkage, pronounced over the first 20 km, to sources
of local pollution. Some elements (P, Mn, Zn, Ba) also demonstrated an increase in their colloidal fraction in
the proximity of pollution centers, possibly reflecting input from industrial centers and gas flares.

Following centrifuginal ultrafiltration, we analyzed total dissolved (< 0.22 µm), two colloidal (high
molecular weight, HMW<sub>50 kDa</sub> -0.22 µm; medium molecular weight MMW<sub>3 kDa</sub> - 50 kDa) and low molecular
weight (LMW< 3 kDa) fractions in the melted snow for all major and trace elements. We discovered sizable
(20 to 70%) proportion of some major (Ca, SO<sub>4</sub>) and many trace (Fe, Y, Zn, Sb, La, Ce, Yb, Pb) elements in
the colloidal (3 kDa - 0.22 µm) form, without significant link to latitude, type of biome, or the concentration
of possible colloidal carrier (DOC, Fe, Al, Ca, SO<sub>4</sub>). The origin of snow water colloids in snow can be
hypothesized to stem from solute freezing on lake surfaces (Fe, OC), frost flowers of the Arctic ice (Ca,
SO<sub>4</sub>), clays dispersion (Al, Si) and sulphur dioxide oxidation particles (SO<sub>4</sub>, oxyanions). Via hydrochemical
mass balance calculations, we demonstrate an overwhelming impact of snow melt on spring-time riverine
export of Cd, Pb, Zn, As, Sb and Cs. These preliminary results call for further studies of atmospheric
colloids including those originating from rainwater.
# 1. Introduction

A rising interest on the geochemistry of surface water, soil and vegetation in Arctic and subarctic regions stems from the pivotal role of these regions in planetray-scale carbon regulation, notably nutrient and metal exchange between the terrestrial, oceanic and atmospheric sources (Ciais et al., 2013; Tarnocai et al., 2009; Schuur et al., 2015). However, in contrast to a relatively good understanding of major and trace element concentrations and fluxes in inland waters in high latitude regions, the atmospheric input of elements from rain water and snow melt remain extremely poorly constrained. This limited understanding is mostly due to restricted access to remote areas all year long, sizable variations in atmospheric precipitates over the territory and difficulties in sampling/handling of contamination-vulnerable atmospheric precipitates. Due to these reasons, areal transect-like studies of snow cover remain the most efficient and representative way of assessing integral (over full depth of the snow cover, corresponding to the entire winter season) precipitation of the dissolved and particulate components of atmospheric aerosols (Tranter et al., 1986; Shaw et al., 1993; Colin et al., 1997; Shevchenko et al., 2017). Over recent years, a sizable number of studies were devoted to the chemical composition of winter time aerosols (especially particulate fraction) in Arctic and subarctic regions (Conca et al., 2019, 2021; Becagli et al., 2020; Bazzano et al., 2016; Koziol et al., 2021). The majority of these works represented either small regional studies of background concentrations or were devoted to tracing sources of local aerosol pollution (Moskovchenko and Babushkin, 2012; Moskovchenko et al., 2021; Pozhitkov et al., 2020; Salo et al., 2016; Shevchenko et al., 2016; Talovskaya et al., 2014; Topchaya et al., 2012; Vlasov et al., 2020; Walker, 2005; Xu et al., 2016). The dissolved (< 0.45 µm or < 0.22 µm) fraction of melted snow was extensively investigated in European subarctic regions (Caritat et al., 1998; Chekushin et al., 1998; Kashulina et al., 2014; de Caritat et al., 1997, 1998, 2005; Reimann et al., 1999; Reinosdotter and Viklander, 2005) and there were numerous studies on trace element geochemistry of the snow cover in high altitude zones of Asia and northern China (Dong et al., 2015; Kang et al., 2007; Lee et al., 2008; Wang et al., 2015; Zhang et al., 2013; Wei et al., 2019; Li et al., 2020), South America (Cereceda-Balic et al., 2012), glaciers in Greenland (Barbante et al., 2003; Boutron et al., 2011; Candelone et al., 1996; Lai et al., 2017), Spitzbergen (Kozak et al., 2015), and Alaskan and Canadian High Arctic areas (Barrie and Vet, 1984; Douglas and Sturm, 2004; Garbarino et al., 2002;
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Krachler et al., 2005; Snyder-Conn et al., 1997). However, the majority of these works dealt with rather
limited geographical coverage that did not allow assessing global river watershed-scale influence of the
snowfall on chemical element fluxes in surface waters. Only in the Western Siberian Lowland (WSL), has a
sizable (1700-2800 km) latitudinal gradient been covered over two sampling campaigns (Shevchenko et al.,
2017; Krickov et al., 2022). However, the first campaign dealt only with the surface (0-5 cm) snow layer
while the second campaign reported only a few heavy metals in the dissolved (< 0.22 µm) fraction.

A typical feature of high latitude regions is a relatively high concentration of organic matter which provokes enrichment of all inland waters in typically low mobility trace metals. Organic-rich soils and sediments, dissolved (< 0.22 or 0.45 µm) organic matter, and Fe / Al oxy(hydr)oxides are the main vectors of trace metal transport in rivers, lakes and soil porewaters of high latitude regions (Pokrovsky et al., 2016; Cuss et al., 2018; Raudina et al., 2021). Trace elements and DOM are usually present in the so-called colloidal fraction, having a size between 1 nm and 1 µm [or operationally defined as 1-3 kDa and 0.22-0.45 µm]. These groups of colloids have been evidenced to dominate surface waters of Arctic and subarctic regions across boreal and subarctic zones from Northern Europe (Ilina et al., 2016; Lyvén et al., 2003; Pokrovsky et al., 2012, 2010; Pokrovsky and Schott, 2002) to Central Siberia (Bagard et al., 2011; Pokrovsky et al., 2006a), Alaska (Stolpe et al., 2013) and Canada (Cuss et al., 2018). The colloidal status of DOM and related metals is a fairly well established feature of all humic (organic-rich) surface waters (Shirokova et al., 2013; Loiko et al., 2017; Pokrovsky et al., 2014), rivers (Krickov et al., 2019), peat porewaters (Raudina et al., 2021) and ice (Lim et al., 2022) of the Western Siberia Lowland. However, to the best of our knowledge, any information on colloidal associations of trace metals in the snow, notably from Siberian peatlands, is absent. The only exception is a recent work from Jensen et al. (2021) who demonstrated that Arctic snow contained higher concentrations of colloidal metals (Fe, Zn) relative to the seawater.

Information on snow colloids is of fundamental importance for assessing the origin and pathways of trace metal in snow. This information might also have crucial influence on our understanding of climate warming-induced future changes in atmospheric precipitation and surface water distribution in Arctic and subarctic regions - given that the contribution of liquid atmospheric aerosols and soluble forms of some
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metals and metalloids is comparable to or may even exceed the export of these elements by Arctic rivers (Shevchenko et al., 2017; Krickov et al., 2021). In the present work, we used the unique geographical position, the WSL being the largest peatland in the world, to assess the colloidal associations of major and trace elements in the snowpack across a sizable south - north gradient within the Ob River watershed. Further, the Ob River watershed encompasses both boreal and subarctic biomes (southern and northern taiga, forest-tundra and southern tundra). Via sampling of snow cores integrated over the entire depth (0-50 cm to bottom) with unprecedented geographical coverage of more than 2700 km in a latitudinal transect, we focused on the following objectives: (1) estimate the average concentrations of colloidal forms of major and trace elements (TE) in the snowpack of western Siberia; (2) quantify the distribution of TE between different colloidal fractions; (3) test the role of latitude (south-north profile) and physio-geographic zones on colloidal proportions of elements in snow; (4) assess the chemical nature of major colloidal carriers of TE, and finally (5) quantify the contribution of snow precipitation to element export as total dissolved and low molecular form by the WSL rivers.

## 2. Study site and Methods

### 2.1. Geographical setting and snow sampling

We used existing road infrastructure to sample a sizable (2800 km) latitudinal transect of the WSL. Snow cores were collected along a south → north gradient, from the vicinity of the Barnaul city (forest-steppe zone) to the Ob estuary (tundra zone) from February 8 to February 19, 2020. The entire snow cores (50±10 cm long, from surface to the ground, minus the bottom 2–3 cm layer to avoid sampling grass) were collected at 36 locations along the transect. Sampling sites were evenly distributed along the transect (Figure 1). All sampled points were located more than 500 m from the nearest road. Note that the traffic density of these temporal (winter, or zimnik) roads in western Siberia is quite low (less than 10 vehicles per hour).

Snow collection was performed using a clean sampling technique in a protected environment. We used only plastic / PVC equipment and vinyl single-use gloves. First, a pit was dug in the snow with a plastic shovel to examine the representability of the studied location and the evenness of the bottom. Next, a
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two-person team sampled the snow in a fashion so that no contamination from external surfaces (other than plastic shovel) was possible. The plastic shovel was inserted 2 cm above the ground in order to avoid touching any ground vegetation during sampling. The snow was collected in duplicates via a 10-cm diameter PVC tube which was inserted in the snow till the shovel surface was a few cm above the grass surface to avoid any contamination from plant debris. Prior to sampling, the tube and shovel were "rinsed" several times with fresh snow via insertion into snow cover 1-2 m from the sampling site.

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Approximately 5 L of duplicated snow cores were transferred into single-use polyethylene bags, which were doubly closed with a PVC collar. Prior to sampling, polyethylene bags were washed thoroughly with 1 M HCl and abundant MilliQ water in a class A 10,000 clean room. Collected snow samples were transported to the laboratory in the frozen state and processed within 2 weeks of sampling. In the laboratory, snow was melted at ambient temperature and immediately processed for analyses and filtration. The pH and conductivity were measured on unfiltered samples using Hanna portable instruments. Melted snow was filtered through acetate cellulose filters (Millipore, 47 mm diameter) of 0.22 µm pore size. The filtration apparatus was rinsed with large amount of MilliQ water prior to any filtration. The first 200-mL portion of snow water that passed through the filter was used for rinsing the recipient reservoir and discarded. Blanks of MilliQ water from the clean room were also placed in polyethylene bags for the same duration as snow melt (< 3 h) and processed via filtration and ultrafiltration similar to the snow water samples. Filtrates were acidified with double distilled HNO₃ acid and stored in pre-cleaned HDPE tubes for ICP MS analysis. Another portion of filtrate was also stored without acidification and used for DOC and anion analyses.

## 2.2. Size separation and analyses

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Filtered (< 0.22 µm) solutions were processed for colloidal size separation using Amicon Ultracell (50 mL) centrifugal/ultrafiltration single-use cartridges. This technique allows for straightforward assessment of the colloidal and truly dissolved pools of elements in natural waters with minimal contamination from the external environment; it is easily performed both in the field and in the laboratory (Banc et al., 2021; Oleinikova et al., 2018, 2017; Raudina et al., 2021). Amicon polypropylene vials were fitted with membranes of 3 kDa and 50 kDa molecular poresize (regenerated cellulose) and were initially
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treated with 1% HNO₃ and then rinsed 3 times via passing between 50 and 100 mL of MilliQ water through the membrane. The concentration of DOC, major and trace elements in the blanks were a factor of 3 to 10 times lower than the minimal concentrations of these components in the snow water. The first 15-mL portion of sample that was ultrafiltrated through the membrane was discarded. Note that unlike polysulfone ultrafiltration membranes with high surface areas (i.e., Guo et al., 2001) there is no charge separation and preferential retentions or electrostatic repulsion of ions by the 15-mL Amicon ultracentrifugal vials of small filter surface area, in which the retentate is in contact with permeate. At the same time, instead of using integrated ultrafiltrates, rejection of the first portion of ultrafiltrate should eliminate potential sample contamination but may underestimate colloidal abundance if the specific chemical species, notably of inorganic ions, follows the ultrafiltration behavior of macromolecular organic matter (Guo et al., 2000; Guo and Santchi, 2006). Furthermore, one has to keep in mind that size-dependent organic matter, major and trace metal distribution is highly related to sample types and filters/membranes material (Xu and Guo, 2017).

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All analytical approaches used in this study followed methods developed for western Siberian surface and atmospheric waters (Pokrovsky et al. 2016a, b; Shevchenko et al., 2017; Shirokova et al. 2013). In this work we define colloids as entities having sizes between 0.22 µm and 3 kDa. Further, we distinguish a group of high-molecular weight (HMW) (HMW<50 kDa - 0.22µm) and medium molecular weight (MMW) (MMW<3kDa - 50 kDa) colloids, and low molecular weight fraction (LMW<3kDa). Each fraction of filtrate (< 0.22 µm) and ultrafiltrate (< 3 and < 50 kDa) was sub-divided into non-acidified and acidified portions for carbon/anions/pH and trace element measurements, respectively. All samples were preserved via refrigeration 1 month prior to analysis. The pH of the snow water was measured using a combined electrode with an uncertainty of ±0.02 pH units. DOC was analyzed using a Carbon Total Analyzer (Shimadzu TOC VSCN) with an uncertainty better than 3% and a detection limit of 0.1 mg L⁻¹. The DOC concentration in the blank was within the detection limit of the analysis (0.1 ± 0.1 mg L⁻¹). Major anion (Cl⁻, SO₄²⁻) concentrations were measured by ion chromatography (HPLC, Dionex ICS 2000) with an uncertainty of 2%. International certified samples ION, PERADE, and RAIN were used for validation of the analyses. Major cations (Ca, Mg, Na, K), Si, and ~40 trace elements were determined with an Agilent iCap Triple Quad
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(TQ) ICP MS using both Ar and He modes to diminish interferences. About 3 µg L⁻¹ of In and Re were added as internal standards along with 3 various external standards. Detection limits of TE were determined as 3× the blank concentration. The typical uncertainty for elemental concentration measurements ranged from 5-10 % at 1-1000 µg/L to 10-20 % at 0.001 – 0.1 µg/L. The MilliQ field blanks were collected and processed to monitor for any potential contamination introduced by our sampling and handling procedures.

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The SLRS-6 (Riverine Water Reference Material for Trace Metals certified by the National Research Council of Canada) was used to check the accuracy and reproducibility of analyses (Heimburger et al., 2013; Yeghicheyan et al., 2013). Only those elements that exhibited good agreement between replicated measurements of SLRS-6 and the certified values (relative difference < 15%) are reported in this study. In addition, we used an in-house standard with low concentrations of major and trace elements, which was prepared via 10-fold dilution of the SLRS-6 Reference Material. Although the 10× diluted SLRS-6 sample was not certified, it was used as a surrogate for assessing elementary concentrations in low-mineralized snow samples. We accepted 20% agreement as satisfactory, between the calculated concentrations of this diluted standard and the actual measured concentrations for all elements.

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## 2.3. Statistical treatment of element concentration data

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Solute concentrations at each sampling site were tested for normality using a Shapiro-Wilk test. Because at least a part of the data were not normally distributed, we used non-parametric statistics. Thus, in addition to mean values with s.d., the median and interquartile range (IQR) were used to represent element concentration in each colloidal fraction. We used Spearman pairwise correlations (p < 0.05) to assess the link between element concentrations in the 0.22 µm fraction (the main colloidal carriers) and the proportion of TE in the colloidal (3 kDa – 0.22 µm) fraction. Note that measurements of DOC in the < 3 kDa fraction often yielded a concentration below or comparative to the quantification limit or the MilliQ blank. Therefore, we used the maximum possible concentration of the DOC in this fraction (0.1 mg L⁻¹) to calculate the proportion of organic carbon in the snow water colloids. The differences in element concentration among main colloidal fractions for a given physio-geographical biome and among different biomes for the same colloidal or LMW fractions were tested using Mann-Whitney test.
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Further statistical analysis was used to quantify the relationship between the major and trace element
proportion in the colloidal or LMW< 3 kDa fraction and concentration of Fe, Al, or DOC in the < 0.22 µm
fraction (as main colloidal carriers). We also tested the significance of the impact of latitude and distance to
potential object(s) of contamination on the elemental concentration in the 0.22 µm fraction and colloidal
fractions.

3. Results

3.1. *Average element concentration and proportion of colloids*

The concentrations of elements in 3 main fractions (< 3 kDa, < 50 kDa, and < 0.22 µm) separately in
four main physio-geographical biomes, and averaged over for the whole territory of western Siberia, are
listed in **Table S1** and **Table 1**. All raw data for each sampled site are provided in the Mendeley database
(Pokrovsky et al., 2022). There were significant pairwise Spearman correlations between all elements in the
< 0.22 µm fraction as well as in the < 3 kDa ultrafiltrates (although the latter was less pronounced; **Table S2**
**A and B**). Examples of the most significant (p < 0.05) correlations between some elements and Al or sulfate
(as major inorganic colloid constituents, see section 3.2 below) are illustrated in **Fig. 2**.

Analysis of element size fractionation over the latitudinal gradient demonstrated general independence of the colloid concentration from geographical location, as illustrated in a box plot of the four main physio-geographical biomes (Fig. 3 A - G for Mg, Ba, V, As, Mn, Co, Cd, and Pb) and detailed as a function of latitude for Mg, Ba, V, As, Co, Mn, Na and Si in Fig. S1 A-H of the Supplement. The Mann-Whitney U-test for the difference in element concentration between four physio-geographical zones demonstrated significant (at p < 0.05) differences for the 0.22 µm and 3 kDa fractions (Table S3 A and B, respectively), but not for the < 50 kDa fraction (not shown). It can be seen from this table that, for both < 0.22 µm filtrates and < 3 kDa ultrafiltrates, the differences between zones were pronounced for a limited number of elements in the southern part of the WSL (between forest-steppe and southern taiga); these differences were significant for a large number of elements in the northern part of the transect between middle taiga and northern taiga.
The U-test for the difference in element concentration in 0.22 µm, 50 kDa and 3 kDa filtrate and ultrafiltrate for the full dataset demonstrated significant (p < 0.05) differences in SO₄, Si, V, Fe, Cu, As, Y, Zr, Sb, Cs, REE, Pb and U concentration in the 0.22 µm and the 3 kDa fractions and in Cl, SO₄, Si, P, K, V, Fe, Ni, As, Sr, Y, Zr, Sb, Cs, Ba, REE, Pb and U concentration in the 50 kDa and the 3 kDa fraction, but with limited difference in element concentrations between the 50 kDa and the 0.22 µm fractions (Table S4 of the Supplement).

The average fraction of total colloids (3 kDa - 0.22 µm) in the WSL amounted to 20-80 % for a number of major and trace elements (Fig. 4). Based on this histogram, we tentatively distinguished two main group of elements depending on the share of colloids: (1) Cl, Na, P, K, Si, Mg, Ca, Sr, Ba, Al, Cr, Mn, Co, Ni, Zn, Mo, Rb and Cd that exhibited between 10 and 30% of colloidal fraction and (2) SO₄, Fe, V, As, V, Cs, Sb, Y, REE, Zr, Pb and U whose colloidal fraction ranged between 30 and 80%.

## 3.2. Potential colloidal carriers

Based on general knowledge of major colloidal carriers of trace elements in surface waters of the WSL (Shirokova et al., 2013; Pokrovsky et al., 2016; Krickov et al., 2019), we tested the impact of DOC, Fe and Al concentration (in the < 0.22 µm fraction) on elemental concentration in the colloidal (3 kDa – 0.22 µm) forms (Table 2). The Spearman rank order correlations demonstrated significant (p < 0.05) impact of DOC< 0.22 µm concentration on the colloidal forms of Na, Mg, Si, Ca, Sr, Zr, Ba and Al< 0.22 µm concentration and on colloidal forms of Na, Mg, Si, Ca, Sr, Zr and Cs. Presumably, DOC and Al are important colloidal carriers in melted snow and they approximate aerosol organic constituent matter and the fine fraction of clays, respectively. Note that [Al<0.22 µm] exhibited the highest correlation with colloidal Si ($R_s$ = 0.54, p < 0.05; Table 2). In contrast, iron, which often acts as a main colloidal constituent in the WSL surface waters (i.e., Pokrovsky et al., 2016), exhibited sizable correlations only with Na, Ca, Zn, Rb, Zr and Ba, and these correlations were generally lower (except Zn, Rb, and Ba) than those with other major colloidal constituents. Given that a sizable proportion of sulfate resided in the colloidal fraction (Fig. 4), sulfate in the snow water was also tested as a potential colloidal carrier of other major and trace elements. We found that the
concentration of SO₄ exhibited significant (p < 0.05) correlations with the largest number of colloidal elements (Na, Si, Ca, Zn, Sr, Zr, Cs and Ba). Note that the pH of the snow water did not exhibit any sizable (p < 0.05) correlation to the colloidal proportion of major and trace elements (Table 2).

The latitudinal pattern of colloid stoichiometry exhibited either a northward increase in Organic Carbon (OC) : element mole ratio (i.e., OC : Ca, OC : SO₄, OC : Fe and SO₄ : Ca) or a local depletion in Al relative to Fe, SO₄ and Ca in the southern taiga zone (Fig. S2). The OC : Al, SO₄ : Fe and Ca : Fe ratios in the colloids did not vary across the south-north transect (Fig. S2). When averaged over the entire area of western Siberia, the molar OC : SO₄ : Ca : Al : Fe stoichiometry of major colloidal (3 kDa - 0.22 µm) carriers ranged from 2000:175:39:1.4:1 in the south of the WSL to 3000:180:37:1.6:1 in the north (Table S5 of the Supplement).

### 3.3. Impact of pollution point source on element concentrations and proportions of colloids.

To better constrain the sources of elements in the snow water, we attempted distinguishing between local and global (far range) transfer. For this, we defined the distance to the nearest human-related object (gas flare, small settlement located within the initial 20 km of a sampling point, or large town) taking into account the dominant wind direction during winter as detailed in Table S6 of the Supplement. The components of the total dissolved fraction (< 0.22 µm) of snow water that were impacted by distance to potential contamination objects were major anions and cations, alkaline-earth and divalent transition metals, toxic metals (Zn, Cd), some geochemical tracers (Al, Ga, Y, Zr, REE, U) and Mo as illustrated in Fig. 5 A-F and Table S2 A. For the LMW<3 kDa fraction, only alkaline-earth metals, Rb, Al, Fe, Ga, V, Mn, Cd and U demonstrated significant (p < 0.01) correlations with the distance to the local pollution center (Table S2 B). We thus suggest that, in addition to far-range atmospheric transfer, these elements are strongly controlled by multiple sources of local (< 20 km) and near-local (20–100 km) pollution.

We also tested the link between the proportion of colloidal forms of elements in snow and the distance to the local pollution spot. The majority of solutes affected by the point sources (SO₄, K, Ca, Cr, V, Fe, Co, Ni and Cd) did not exhibit any link (R² < 0.2; p > 0.05) between their colloidal fraction and distance. Only
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for P, Mn, Zn and Ba were the colloidal forms significantly ($R^2$ > 0.2; p < 0.05) affected by the distance to a potential contamination spot (Fig. 6 A-D).

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## 4. Discussion

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### 4.1. Snowmelt is capable of providing a sizeable amount of trace elements in riverine flux during spring flooding in western Siberia

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The unprecedented geographical coverage and assessment of the full depth of the snow cover performed in the present study allowed for quantification of snowmelt impact on riverine fluxes of major and trace elements in western Siberia at the scale of whole watersheds. The ratio of the winter-period stock of the dissolved (< 0.22 µm) fraction of snow to the mean dissolved spring-time flux of small and medium-size rivers across all latitudinal zones of the WSL is illustrated in Fig. 7. For simplicity, we considered average concentration of trace elements in snow water from two zones of the territory: the southern (54.5 - 60 °N) and the northern (60 - 66.5 °N) parts of the WSL as detailed in Fig. S3. For this calculation, we used the snow volume (in millimeters of water) accumulated over a full winter which is fairly well known for Western Siberia (Karnatzevitch and Khruschev, 2014; Shevchenko et al., 2017) and ranges from 110-120 mm in the 56-60 °N zone to 140-150 mm in the northern part of the Ob River basin (60-68 °N). The spring-time river runoff (in mm during May and June) was taken as calculated in Pokrovsky et al. (2020).

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These first-order mass balance calculations demonstrate that in the southern, permafrost-free zone, more than half of spring-time riverine export of the total dissolved fraction (< 0.22 µm) Cd, Zn, Pb, Cs and Sb can be provided by snowmelt (Fig. S3 A). In the northern, permafrost-affected part of the WSL, riverine export of the < 0.22 µm fractions of Pb, Cd, Zn, As, Sb, Cs, SO₄ and Cu during spring flooding can be sizably (> 30 %) impacted by snowmelt (Fig. S3 C). The elements mostly affected by snowmelt are Cd, Pb and Zn whose riverine fluxes are 2-4 times lower than the input from the snowpack (Fig. 7 A). Given the excess of these metals in the snowpack relative to the riverine export, we hypothesize that during snowmelt and surface water influx into the river a sizable share of these metals, which are present in the snowpack, may be retained by ground vegetation, scavenged in river and lake sediments or adsorbed onto river suspended matter (> 0.22 µm) and thereby transported in particulate form from land to ocean.
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The effect of the snow water on the low molecular weight (truly dissolved and potentially bioavailable fraction) in the river flux is more drastic. The LMW<3 kDa riverine fluxes of Pb, Cd, Zn, Cr, Cs, Ce, Ga, Sb, Y, Co, heavy REEs and Cu in the south and Pb, Cd, Zn, Cu and As in the north are strongly (≥ 50%) affected by the snowmelt (Fig. S3 B). A mass-balance comparison of the LMW<3 kDa stocks in snow and the spring-time LMW<3 kDa export fluxes (Fig. 7 B and Table S7 of the Supplement) demonstrates that the majority of riverine fluxes of Zn, Cd, As, Pb, Cu and Sb in the LMW form during spring freshet can be provided via snowmelt. However, among these elements, divalent transition metal cations, trivalent and tetravalent hydrolysates are unlikely to remain in the LMW forms in the river water. This is because, upon their release into freshet surface waters enriched in DOM, these cations transform into organic colloids (Krickov et al., 2019). In contrast, snowmelt could be responsible for delivery of almost half of the trace oxyanions (As and Sb) present in the LMW form in river waters.

Overall, these comparisons demonstrate the highly important and previously underestimated impact of snowfall on spring flood time period riverine export not just on total dissolved fraction, but also on the LMW<3 kDa fraction and thus potentially bioavailable trace elements in western Siberia. Given that the freshet period accounts for more than 40-50% of the total annual lateral export of riverine solutes (Pokrovsky et al., 2020), changes in winter-time atmospheric precipitation may play an overwhelming role in inland aquatic ecosystem response to on-going climate change. The complexity of this response is thought to be related to two main factors: quantity of the precipitation and total dissolved chemical composition of snow water. The present study confirms the importance of snow water solutes in riverine export but also adds another dimension that was previously unknown: colloidal and low molecular weight inorganic solutes of the snowpack. Particular feature of snow water colloids is that they have sizable proportion of inorganic constituents, such as Ca and SO4, in contrast to surface water colloids which are dominated by organic associations.

## 4.2. Impact of local pollution versus global atmospheric transfer on the total dissolved and low molecular weight fraction of western Siberian snow
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The impact of pollution sources on major and trace element concentrations established in the WSL is consistent with former studies of local pollution impact on the chemical composition of snow. Generally, a distance of 10 to 20 km is reported as the range where impact of a local pollution source is most pronounced (Jaffe et al., 1995; Walker et al., 2003; Javed et al., 2022). Thus, Walker et al. (2003) analyzed snow water in the European Arctic and demonstrated elevated concentrations of elements associated with alkaline combustion ash around the coal mining towns of Vorkuta and Inta. The increases in concentrations of Ca, K, Sr, Mn, Ba, Sr and As were pronounced within a distance of 10 to 20 km around the local point source of pollution. Other studies of point pollution impact on snowpack chemical composition demonstrated significant increase in dissolved concentrations of Cu, Ni, Co and As in the vicinity of the nickel industry (Reimann et al., 1996). The latter authors distinguished four different sources of these elements in the snow pack whose role varied depending on proximity to a local pollution source: industrial emissions, sea spray, geogenic dust and anthropogenic dust. Telmer et al. (2004) demonstrated that dissolved Cu, Pb, and Zn have a strong enrichment near the metal smelter (Quebec) and exhibit strong negative correlation with distance (up to 45 km), indicating that the smelter is the dominant source of such elements to regional snowpack. At the same time, Mn, K, Rb and Cs had little to no relationship to the smelter and any emission of these elements by the smelter was suggested to be minimal compared to long-range delivery from natural emissions.

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The total and dissolved concentrations of 29 metals and metalloids were analyzed in the snowpack collected in the Athabasca oil sand region of Canada (Guéguen et al., 2016) and based on the depositional pattern in this industrial region three groups of elements were found: 1) V and Mo showing significant exponential decrease with distance, suggesting oil sands development sources; 2) Al, Sb, As, Ba, Fe, Ni, Tl, and Ti and Zn exhibiting exponential decline patterns but with some local point sources, and 3) Cd, Cl, Cr, Mn, Sr and Th whose depositional pattern represents local sources. The background sites located at a distance of 25-35 km from Tyumen City were characterized by increased concentrations of dissolved Cd, Cu, Zn, Pb, Ni, As and Mo when compared to average levels documented in the snowpack of Western Siberia (Moskovchenko et al., 2021). A similar assemblage of pollutants is also reported from metallurgical districts of the Southern Ural (Udachin, 2012) which are located 250-350 km southwest of Tyumen. Due to
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the predominance of the southern and southwestern winds in the study area during winter, increased concentrations of these elements can be explained via long-range atmospheric transport from the Urals (Moskovchenko et al., 2021).

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Overall, the results of the present study are consistent with previous works on the importance of local pollution spots in the formation of total dissolved (< 0.22 or 0.45 µm) load of the snow water. The elements indicative for pollution sources in the WSL are quite diverse, ranging from major cations and anions (SO₄, K, Ca) to alkaline-earth metals and heavy metal pollutants. At the same time, this study adds a new previously unknown feature to pollution impact in demonstrating an increase in the colloidal (3 kDa - 0.22 µm) forms of several environmentally important elements such as P, Mn, Zn and Ba in the vicinity of local pollution sources.

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### 4.3. Snow water colloids are rich in SO₄ and Ca and present a sizable contrast with humic surface waters

The colloids of the snow water characterized in this study are drastically different from colloids identified in earlier works on surface waters of western Siberia. Unlike humic freshwater colloids, these meltwater colloids are rich in Ca and SO₄ and poor in Fe and Al and cannot be qualified as purely organo-iron / organo-aluminium entities. Indeed, the average colloidal stoichiometry of the WSL snow water ((OC)₂₈₉₀(SO₄)₁₈₀Ca₃₇Al₁.₅₆Fe₁) is sizably different from that of soil porewaters (OC₂₀₀-₆₀₀Fe₀.₅-₁.₅Al₁.₀) as documented by Raudina et al. (2021) and Lim et al. (2022), river waters (OC₂₆₀-₈₆₀Ca₂.₃Fe₁.₇Al₁.₀) as documented by Krickov et al. (2019), and peat ice (OC₅₀₀-₂₀₀₀Fe₁-₁.₅Al₁.₀), as documented by Lim et al. (2022).

The exact mechanisms of colloid generation in atmospheric aerosols remain poorly understood but may include the disintegration of flying ash particles, condensation of volatile forms of industrial fumes, or dissolution/dispersion of soil minerals such as clays. It should also be noted that an extremely low ionic strength of meltwater (S.C. = 10±2 µS cm⁻¹) facilitates clay dispersion, leading to generation of colloidal particles with large diffusional layer (Russell et al., 1989). The low salt concentration also enhances the stability of colloidal particles given that the increasing electrolyte concentration inhibits colloidal dispersion
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and facilitates flocculation (van Olphen, 1977). Therefore, a combination of specific sources contributing to the origin of dissolved elements in the snow and specific processes operating within atmospheric aerosols during winter period may shape the chemical composition of snow water colloids as discussed below.

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The freezing of solutes in the sea and on the land may enrich atmospheric aerosols in salts. Clusters of these sparingly soluble compounds (i.e., CaSO₄, CaCO₃), having sizes less than 0.22 µm but larger than simple ions or molecular complexes, can temporary persist after thawing of snow, despite solution being undersaturated with respect to relevant solid phases. A likely source of major sea salt in snow aerosols is frost flowers that are formed on Arctic sea ice (i.e., Barber et al., 2014; Rankin et al., 2000; Alvarez-Avilez et al., 2008; Lim et al., 2019). The colloidal composition of these presumably soluble (< 0.22 µm) aerosols is not known but it is not excluded that some fraction of these salts is present in the ionic associates or ikaite (CaCO₃ × 6H₂O) particles (Rysgaard et al., 2013) larger than 3 kDa. Hydrated calcium carbonate is capable of retaining some divalent alkaline-earth metals similar to calcite and aragonite. Divalent cations coprecipitation with Ca sulfate is also possible (Deng et al., 2013; Ma et al., 2020). Altogether, this can explain the co-existence of a sizable proportion of alkaline-earth metals in the colloidal fraction of the snow water, given that Ca concentration in the < 0.22 µm fraction is an order of magnitude higher than that of Mg and Zn and two orders of magnitude higher than that of other alkaline-earth metals.

In a similar way, thermokarst lakes which freeze solid may contribute to generation of organo-ferric colloids. In the WSL, the freezing of abundant thermokarst lakes leads to complete ice formation with seeps of deep, organic and Fe-rich waters on the surface that are detectable in the end of winter (Manasypov et al., 2015). Such seeps may generate some colloidal particles after freezing of this water, similar to the frost flowers generated from the Arctic ice. Sulphur dioxide emissions and associated trace metal pollutants are frequently detected in the dissolved and particulate load of the snow water (i.e., Walker et al., 2003).

Both methanesulphonic acid and non-sea salt sulfate can contribute to the SO₄ concentration in atmospheric aerosols (Hur et al., 2021). Further, gaseous adsorption of SO₂ on the snow surface (Thakur and Thamban, 2019) followed by S(IV) → S(VI) oxidation can also contribute to the ionic and colloidal load of sulphate in the snow water. Under these conditions, mobilization of other soluble oxyanions (B, As, Mo and Sb) together with subcolloidal SO₄ forms in the snow water may become possible. Note that, in the
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atmospheric aerosols, the oxyanions are known to form double (S, Se) or triple (N, P, As) bonds with carbon
(Goldstein and Galbally, 2007).

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Organic aerosols are present in both micro- and nano-particulate form and can exist in different phases including liquid, semi-solid and solid, or glassy depending on temperature and relative humidity (Knopf et al., 2018). As a result, organic matter (OM) present in snow water colloids is likely to include (i) organic aerosols such as stearic and cis-pinonic acid (Luo and Yu, 2010), (ii) humic-like compounds (Graber and Rudich, 2006), (iii) black carbon in the form of sooty subcolloidal particles (Nichman et al., 2019), (iv) OM-coated mineral dust (such as feldspar or kaolinite, Knopf et al., 2018). Although studying the exact molecular nature of DOM in the colloidal and LMW fractions of snow water was beyond the scope of this study, relatively high ratios of carbon to SO₄ and cations in the colloids (Fig. S2) suggest a dominance of organic aerosols, black carbon and humic-like compounds in snow water rather than organo-iron and organo-alluminium associates typical of inland waters in permafrost peatlands.

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The nature of colloidal trace metals in snow waters also remains poorly constrained. Miller and
Gosar (2015) demonstrated that anthropogenic metal-bearing phases in snow particles are represented by
irregular ferrous oxides, ferrous alloys, spherical ferrous oxides, and ferrous silicates with variable contents
of Cr, Mn, Ni, V, W and Mo. They also identified secondary weathering products such as Al silicates, Fe
oxy-hydroxides and Fe oxy-hydroxy sulfates with minor contents of transition metals. It can be
hypothesized that some solid aerosol particles can de disintegrated to fine fractions (< 0.22 µm) and partially
contribute to the colloidal load of snow waters. Low solubility-low mobility elements that are present in a
sizable amount of the colloidal fraction in river, lake and soil waters of western Siberia with Fe, Al
hydroxides and organic matter as main colloidal carriers (Pokrovsky et al., 2016; Krickov et al., 2019;
Raudina et al., 2021) are much less abundant in snow water from this region. In fact, concentrations in the <
0.22 µm fraction of the snow water of DOC (0.6 to 1.0 mg L-1), Fe (1 to 10 µg L-1) and Al (1 to 15 µg L-1)
are quite low for accommodating a sizable proportion of other trace metals. Consistent with this, correlations
of these elements with the colloidal fraction of other trace elements were quite low whereas the concentraton
of SO4 and Ca exhibited significant (p < 0.05) correlations with the colloidal fraction of the largest number
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of elements (Na, Si, Zn, Sr, Zr, Cs and Ba). It is thus not excluded that Ca- and SO₄-rich colloids in the
meltwater also accommodate some trace metals.

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5. Conclusions

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An additional factor of colloid generation and transformation in the aerosols is freeze-thaw cycles (FTC), which may become especially pronounced at the beginning and end of the winter season. Colloidal load of boreal and subarctic freshwaters is subjected to strong modification under freeze-thaw regimes; these cycles can produce large subcolloidal particles and generate low molecular weight organic compounds (i.e. Pokrovsky et al., 2018; Payandi-Rolland et al., 2021). However, special FTC experiments are needed to assess the degree to which these processes can impact the snow / rain water organic- sulfate- and Ca-rich colloids.

To better understand the dissolved load of major and trace elements in the snow water of western Siberia, we sampled snow cores integrated over the entire depth (0 to 50 cm) along a 2800 km south-north gradient and analyzed the concentration of solutes in the total dissolved (< 0.22 µm) colloidal (0.22 µm - 50 kDa and 50 kDa - 3 kDa) and low molecular weight (< 3 kDa) fractions. A number of major and trace metals in the snow water collected across western Siberia demonstrate a non-negligible proportion (30 to 50 %) of total colloidal (3 kDa - 0.22 µm) forms. Snowfall may represent a sizable contribution of trace elements, in both total dissolved< 0.22 µm (Cd, Pb, Zn, As, Sb and Cs) and LMW< 3 kDa (Cd, Pb, Zn, As, Sb, Cs, Cu) forms, to riverine export during spring flooding in western Siberia. In addition to tracing local pollution sources by dissolved (< 0.22 µm) concentrations of SO4, Cl, alkalis an alkaline-earths, divalent transition metals, V, Cr, Mo, Ga, Y, Zr, REE, Cd and U, we demonstrated enrichment in snow water of colloidal forms of P, Mn, Zn and Ba in the vicinity of local pollution source. The average stoichiometric composition of snow water colloids demonstrates that they are enriched in OC, Ca and SO4 but poor in Al and Fe. In addition to anthropogenic sources of snowwater colloids (submicron particles of flying ash and other anthropogenically-derived substances), natural pathways of colloid generation may include but are not limited to: (i) solute freezing along thermokarst lake surfaces producing dispersed subcolloid particles (iron hydroxide and
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organic matter), (ii) frost flowers of the Arctic ice (hydrous Ca carbonate and sulfates), (iii) terrigenous clay dispersion/dissolution in low ionic strength snow water and (iv) sulfur dioxide oxidation on the snow surfaces.

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Overall, we demonstratre the previously undervalued importance of colloidal forms of toxicants and geochemical tracers in the snow water. Climate warming in Siberia may not only change the quantity of snow and dissolved fraction but also the colloidal and low molecular weight forms of macro- and micronutrients and toxicants. Further quantification on the impact of atmospheric precipitation as it relates to elementary input of inland waters on an annual scale highlights the need for a systematic study of colloidal load in rain water across this territory.

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**Data availability:** The full data set of measured DOC, major and trace element concentrations (< 0.22 µm, < 50 kDa and < 3 kDa) in the snow water in all sites and different sampling depths is presented in the Mendeley portal database:

Pokrovsky, O., Krickov, I.V., Shevchenko, V., Vorobyev, S., Lim, A. (2022), "Major and trace element concentrations in the snow water of western Siberia", Mendeley Data, V1. https://data.mendeley.com/datasets/3vnfk6s9tb.

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**Acknowledgements**

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We acknowledge support from RFBR grants No 19-05-50096, 20-05-00729, 19-29-05209 and the Tomsk State University Development Program "Priority-2030". We thank two anonymous reviewers and the Editor Don Porcelli for very insightful comments and corrections. C. Benker is thanked for editing the English of the manuscript.

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<figure><img src="image_2.png" /><figcaption>**Figure 1.** Studied area of the Western Siberian Lowland (WSL) with physio-geographical zones shown by different colors and sampling points (grey circles) along the winter road.</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Pairwise correlations between elements in the 0.22 µm fraction of snow water illustrating the impact of Al on P, Mg, Cd and Ba (A-D) as well as SO₄ on V, Cd, Ba and Yb (E-H).</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**Fig. 3.** Median (with IQR) values of colloidal (medium molecular weight, MMW<3-50 kDa and high molecular weight, HMW<50 kDa - 0.22 µm) and low molecular weight (LMW<3 kDa) fractions in snow water averaged for each biome of the WSL.</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Fig. 4.** Average (with s.d.) colloidal (3 kDa – 0.22 µm) fractions in snow water across all WSL zones. Percentage for DOC is calculated assuming a quantification limit in the 3 kDa fraction (0.1±0.1 mg L⁻¹). This value is likely to be underestimated.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 5.** Examples of dissolved (<0.22 µm) metal concentrations in snow water as a function of distance to potential objects of contamination in the WSL. A full list of elements exhibiting significant (p < 0.01) impact from local pollution centers for the < 0.22 µm and < 3 kDa fractions is provided in **Table S2**.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Fig. 6.** Decrease in proportion of colloidal (3 kDa - 0.22 µm) forms of P<sub>tot</sub> (A), Mn (B), Ba (C) and Zn (D) with distance to potential contamination objects.</figcaption></figure>

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<figure><img src="image_8.png" /></figure>

**Figure 7.** The ratio of winter-period stock of dissolved< 0.22 µm (A) and LMW< 3 kDa (B) fractions of snow water (from this study) to the mean dissolved spring-time flux for small and medium-size rivers averaged across all latitudinal zones of the WSL (54-66 °N). For this calculation, snow volume (in millimeters of water) accumulated over full winter (110-120 mm in the south and 150-150 mm in the north) and mean river runoff over May and June together with riverine concentrations (Pokrovsky et al., 2020) were used.
<table><caption>Table 1. Mean values with s.d. (median with IQR in parentheses) of dissolved (< 0.22 µm), colloidal (< 50 kDa) and low molecular weight (LMW< 3 kDa) forms of elements in snow water across western Siberia Lowland. For individual colloidal fractions measured in each natural zone of the WSL, please refer to Fig. 3 and Table S1.</caption><thead><tr><th>Component, unit</th><th>&lt; 3 kDa</th><th>&lt; 50 kDa</th><th>&lt; 0.22 µm</th></tr></thead><tbody><tr><td>DOC, mg/l</td><td>0.10±0.10* (0.10±0.10)*</td><td>0.10±0.10* (0.10±0.10)*</td><td>0.81±0.11 (0.81±0.14)</td></tr><tr><td>Cl, mg/l</td><td>0.15±0.18 (0.089±0.11)</td><td>0.23±0.15 (0.22±0.17)</td><td>0.18±0.21 (0.11±0.12)</td></tr><tr><td>SO<sub>4</sub>, mg/l</td><td>0.14±0.083 (0.11±0.06)</td><td>0.5±0.2 (0.46±0.24)</td><td>0.49±0.22 (0.43±0.25)</td></tr><tr><td>B, µg L<sup>-1</sup></td><td>0.48±0.29 (0.39±0.26)</td><td>0.4±0.22 (0.44±0.29)</td><td>0.61±0.49 (0.45±0.44)</td></tr><tr><td>Na, µg L<sup>-1</sup></td><td>77±115 (39±49)</td><td>59±73 (34±29)</td><td>85±129 (42±64)</td></tr><tr><td>Mg, µg L<sup>-1</sup></td><td>15±15 (11±12)</td><td>15±10 (12±12)</td><td>20±19 (15±16)</td></tr><tr><td>Al, µg L<sup>-1</sup></td><td>4.6±5.7 (3±2.6)</td><td>5.3±5.8 (3.6±3)</td><td>5±5.3 (3.2±2.3)</td></tr><tr><td>Si, µg L<sup>-1</sup></td><td>12±5.6 (11±5.9)</td><td>14±3.6 (15±3.6)</td><td>16±4.3 (16±5.5)</td></tr><tr><td>P, µg L<sup>-1</sup></td><td>5.2±3.6 (3.9±2.6)</td><td>11±8.5 (9.4±7.8)</td><td>5.7±6.1 (3.8±4.4)</td></tr><tr><td>K, µg L<sup>-1</sup></td><td>31±20 (26±20)</td><td>36±43 (21±7.3)</td><td>31±24 (23±17)</td></tr><tr><td>Ca, µg L<sup>-1</sup></td><td>170±449 (72±107)</td><td>122±105 (72±119)</td><td>120±106 (82±128)</td></tr><tr><td>V, µg L<sup>-1</sup></td><td>0.057±0.039 (0.047±0.034)</td><td>0.077±0.041 (0.071±0.035)</td><td>0.082±0.046 (0.076±0.05)</td></tr><tr><td>Cr, µg L<sup>-1</sup></td><td>0.057±0.029 (0.047±0.031)</td><td>0.06±0.03 (0.049±0.035)</td><td>0.068±0.032 (0.06±0.031)</td></tr><tr><td>Mn, µg L<sup>-1</sup></td><td>1.4±1.2 (1.1±1.5)</td><td>1.8±2.2 (0.91±1.4)</td><td>1.7±1.5 (1.3±1.5)</td></tr><tr><td>Fe, µg L<sup>-1</sup></td><td>1.9±2 (1.1±1.5)</td><td>2.5±2.4 (2.1±1.2)</td><td>2.9±2.4 (2.2±1.8)</td></tr><tr><td>Co, µg L<sup>-1</sup></td><td>0.011±0.011 (0.0074±0.0086)</td><td>0.017±0.022 (0.011±0.0074)</td><td>0.013±0.014 (0.009±0.011)</td></tr><tr><td>Ni, µg L<sup>-1</sup></td><td>0.059±0.026 (0.053±0.032)</td><td>0.076±0.047 (0.049±0.081)</td><td>0.057±0.036 (0.045±0.039)</td></tr><tr><td>Cu, µg L<sup>-1</sup></td><td>0.17±0.11 (0.17±0.13)</td><td>0.16±0.078 (0.14±0.052)</td><td>0.24±0.17 (0.22±0.16)</td></tr><tr><td>Zn, µg L<sup>-1</sup></td><td>7.6±12 (3.6±3.5)</td><td>11±25 (3.2±1.8)</td><td>8.3±14 (3.4±3.9)</td></tr><tr><td>Ga, µg L<sup>-1</sup></td><td>0.0017±0.0017 (0.0011±0.0016)</td><td>0.0019±0.0022 (0.0011±0.0013)</td><td>0.0019±0.002 (0.0012±0.0015)</td></tr><tr><td>As, µg L<sup>-1</sup></td><td>0.21±0.14 (0.17±0.12)</td><td>0.29±0.15 (0.24±0.089)</td><td>0.32±0.19 (0.26±0.12)</td></tr><tr><td>Rb, µg L<sup>-1</sup></td><td>0.037±0.026 (0.029±0.027)</td><td>0.041±0.036 (0.033±0.028)</td><td>0.043±0.032 (0.036±0.035)</td></tr><tr><td>Sr, µg L<sup>-1</sup></td><td>0.51±0.68 (0.23±0.35)</td><td>0.99±1.2 (0.41±0.72)</td><td>0.81±1.23 (0.3±0.56)</td></tr><tr><td>Y, µg L<sup>-1</sup></td><td>0.0027±0.007 (0.00082±0.001)</td><td>0.0041±0.0065 (0.0027±0.0021)</td><td>0.0053±0.0077 (0.0032±0.0024)</td></tr><tr><td>Zr, µg L<sup>-1</sup></td><td>0.001±0.00073 (0.00067±0.001)</td><td>0.002±0.0014 (0.0011±0.0024)</td><td>0.0025±0.002 (0.0018±0.0021)</td></tr><tr><td>Mo, µg L<sup>-1</sup></td><td>0.010±0.008 (0.0075±0.0087)</td><td>0.012±0.01 (0.0078±0.0056)</td><td>0.013±0.011 (0.01±0.0076)</td></tr><tr><td>Cd, µg L<sup>-1</sup></td><td>0.025±0.011 (0.025±0.016)</td><td>0.029±0.011 (0.033±0.017)</td><td>0.03±0.012 (0.028±0.019)</td></tr><tr><td>Sb, µg L<sup>-1</sup></td><td>0.017±0.031 (0.0085±0.0085)</td><td>0.022±0.012 (0.016±0.012)</td><td>0.029±0.039 (0.017±0.014)</td></tr><tr><td>Cs, µg L<sup>-1</sup></td><td>0.0012±0.0008 (0.001±0.00076)</td><td>0.0017±0.001 (0.0014±0.0009)</td><td>0.0018±0.001 (0.0017±0.0012)</td></tr><tr><td>Ba, µg L<sup>-1</sup></td><td>0.56±0.63 (0.31±0.47)</td><td>1.1±1.0 (0.64±1.4)</td><td>0.75±0.81 (0.43±0.81)</td></tr><tr><td>La, µg L<sup>-1</sup></td><td>0.0029±0.0095 (0.00055±0.0011)</td><td>0.0045±0.0067 (0.0024±0.0019)</td><td>0.004±0.0052 (0.0027±0.0021)</td></tr><tr><td>Ce, µg L<sup>-1</sup></td><td>0.0037±0.010 (0.00079±0.0016)</td><td>0.0084±0.012 (0.0048±0.004)</td><td>0.0082±0.01 (0.0055±0.004)</td></tr><tr><td>Yb, µg L<sup>-1</sup></td><td>0.00019±0.00046 (0.00007±0.000061)</td><td>0.00035±0.00053 (0.00022±0.00016)</td><td>0.00038±0.00057 (0.00025±0.00016)</td></tr><tr><td>Pb, µg L<sup>-1</sup></td><td>0.43±0.25 (0.37±0.23)</td><td>0.58±0.25 (0.61±0.27)</td><td>0.67±0.31 (0.63±0.28)</td></tr><tr><td>U, µg L<sup>-1</sup></td><td>0.00071±0.0012 (0.00034±0.00030)</td><td>0.00083±0.001 (0.00054±0.00049)</td><td>0.0009±0.0011 (0.00054±0.00053)</td></tr></tbody></table>

<footnote>* maximal concentration, corresponding to the quantification limit by Shimadzy instrument. In case if the s.d. of mean (or IQR of median) for a given element exceeds the difference between the values in different fractions, this means non-measurable amount of this element in the 3 kDa - 50 kDa fraction or the 50 kDa - 0.22 µm fraction.</footnote>
<table><caption>**Table 2.** Spearman Rank Order Correlations between the percentage of colloidal forms (3 kDa - 0.22 µm) of major and trace elements and the concentration of main potential colloidal carriers (DOC, SO₄, Al and Fe in the 0.22 µm filtrate). Marked correlations (*) are significant at p < 0.05.</caption><thead><tr><th>Colloids</th><th>pH</th><th>Ca (0.22 µm)</th><th>DOC (0.22 µm)</th><th>SO₄ (0.22 µm)</th><th>Al (0.22 µm)</th><th>Fe (0.22 µm)</th></tr></thead><tbody><tr><td>Cl</td><td>0.12</td><td>-0.34*</td><td>-0.22</td><td>-0.43*</td><td>-0.43*</td><td>-0.44*</td></tr><tr><td>SO₄</td><td>-0.24</td><td>-0.20</td><td>0.08</td><td>-0.06</td><td>-0.13</td><td>0.02</td></tr><tr><td>B</td><td>-0.02</td><td>0.01</td><td>0.08</td><td>-0.25</td><td>-0.23</td><td>-0.19</td></tr><tr><td>Na</td><td>0.02</td><td>0.72*</td><td>0.63*</td><td>0.50*</td><td>0.68*</td><td>0.38*</td></tr><tr><td>Mg</td><td>0.06</td><td>0.52*</td><td>0.36*</td><td>0.34</td><td>0.50*</td><td>0.21</td></tr><tr><td>Al</td><td>0.28</td><td>-0.17</td><td>-0.25</td><td>-0.15</td><td>-0.24</td><td>-0.38*</td></tr><tr><td>Si</td><td>-0.10</td><td>0.49*</td><td>0.42*</td><td>0.46*</td><td>0.54*</td><td>0.27</td></tr><tr><td>P</td><td>-0.29</td><td>0.32</td><td>0.31</td><td>0.22</td><td>0.32</td><td>0.15</td></tr><tr><td>K</td><td>0.33</td><td>0.21</td><td>0.11</td><td>0.01</td><td>0.17</td><td>-0.05</td></tr><tr><td>Ca</td><td>0.28</td><td>0.57*</td><td>0.37*</td><td>0.35*</td><td>0.37*</td><td>0.37*</td></tr><tr><td>V</td><td>-0.25</td><td>0.13</td><td>0.31</td><td>-0.01</td><td>0.01</td><td>-0.12</td></tr><tr><td>Cr</td><td>-0.16</td><td>0.26</td><td>0.25</td><td>0.15</td><td>0.18</td><td>-0.06</td></tr><tr><td>Mn</td><td>0.10</td><td>0.22</td><td>0.23</td><td>0.19</td><td>0.16</td><td>0.19</td></tr><tr><td>Fe</td><td>0.06</td><td>0.09</td><td>0.08</td><td>0.07</td><td>-0.05</td><td>-0.11</td></tr><tr><td>Co</td><td>0.18</td><td>-0.01</td><td>-0.02</td><td>-0.07</td><td>-0.07</td><td>-0.11</td></tr><tr><td>Ni</td><td>0.28</td><td>0.29</td><td>-0.01</td><td>0.25</td><td>0.12</td><td>0.33</td></tr><tr><td>Cu</td><td>0.25</td><td>0.25</td><td>0.28</td><td>0.19</td><td>0.30</td><td>0.11</td></tr><tr><td>Zn</td><td>0.08</td><td>0.40*</td><td>0.29</td><td>0.41*</td><td>0.29</td><td>0.48*</td></tr><tr><td>Ga</td><td>0.19</td><td>0.36*</td><td>-0.17</td><td>0.21</td><td>0.17</td><td>0.03</td></tr><tr><td>As</td><td>-0.22</td><td>-0.29</td><td>0.11</td><td>-0.38*</td><td>-0.29</td><td>-0.32</td></tr><tr><td>Rb</td><td>0.13</td><td>0.30</td><td>0.14</td><td>0.32</td><td>0.16</td><td>0.37*</td></tr><tr><td>Sr</td><td>-0.03</td><td>0.54*</td><td>0.68*</td><td>0.36*</td><td>0.51*</td><td>0.22</td></tr><tr><td>Y</td><td>-0.09</td><td>0.11</td><td>0.13</td><td>0.06</td><td>-0.03</td><td>-0.09</td></tr><tr><td>Zr</td><td>-0.23</td><td>0.54*</td><td>0.60*</td><td>0.66*</td><td>0.60*</td><td>0.49*</td></tr><tr><td>Mo</td><td>0.28</td><td>0.34</td><td>0.32</td><td>-0.03</td><td>0.22</td><td>-0.17</td></tr><tr><td>Cd</td><td>0.10</td><td>0.12</td><td>0.17</td><td>0.01</td><td>-0.02</td><td>0.07</td></tr><tr><td>Sb</td><td>-0.14</td><td>-0.44*</td><td>0.00</td><td>-0.39*</td><td>-0.35*</td><td>-0.27</td></tr><tr><td>Cs</td><td>0.00</td><td>0.31</td><td>0.32</td><td>0.35*</td><td>0.39*</td><td>0.25</td></tr><tr><td>Ba</td><td>-0.05</td><td>0.38*</td><td>0.37*</td><td>0.42*</td><td>0.31</td><td>0.43*</td></tr><tr><td>La</td><td>0.21</td><td>0.11</td><td>0.20</td><td>0.04</td><td>-0.03</td><td>-0.16</td></tr><tr><td>Ce</td><td>0.10</td><td>0.15</td><td>0.31</td><td>0.05</td><td>-0.01</td><td>-0.17</td></tr><tr><td>Yb</td><td>0.15</td><td>0.24</td><td>0.33</td><td>0.14</td><td>0.14</td><td>0.05</td></tr><tr><td>Pb</td><td>0.08</td><td>0.02</td><td>0.06</td><td>-0.12</td><td>-0.16</td><td>-0.07</td></tr><tr><td>U</td><td>0.22</td><td>0.07</td><td>0.04</td><td>0.01</td><td>-0.03</td><td>-0.21</td></tr></tbody></table>