# Fluvial carbon dioxide emissions peak at the permafrost thawing front in the Western Siberia Lowland

Ivan V. Krickov, Artem G. Lim, Liudmila S. Shirokova, Mikhail . Korets, Oleg S. Pokrovsky

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Ivan V. Krickov, Artem G. Lim, Liudmila S. Shirokova, Mikhail . Korets, Oleg S. Pokrovsky. Fluvial carbon dioxide emissions peak at the permafrost thawing front in the Western Siberia Lowland. Science of the Total Environment, 2024, 936, pp.173491. 10.1016/j.scitotenv.2024.173491. insu-04831466

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# Fluvial carbon dioxide emissions peak at the permafrost thawing front in the Western Siberia Lowland

Ivan V. Krickov<sup>a</sup>, Artem G. Lim<sup>a</sup>, Liudmila S. Shirokova<sup>b,c</sup>, Mikhail A. Korets<sup>d</sup>, Oleg S. Pokrovsky<sup>b,*</sup>

<figure><img src="image_3.png" /></figure>

## HIGHLIGHTS

* Maximal CO₂ emissions from rivers of the discontinuous/sporadic permafrost zone

* Peak of C emission: export ratio at the permafrost thawing front

* Dissolved and particulate organic carbon as potential controllers of CO₂ emissions

* Possible priming effect from DOM of peat ice in C evasion from rivers

* Future two-fold increase in C emissions from rivers of continuous permafrost zone

## GRAPHICAL ABSTRACT

<figure><img src="image_4.png" /></figure>

## ARTICLE INFO

Editor: Pavlos Kassomenos

**Keywords:**

CO₂

CH₄

Flux

Arctic

River

Organic carbon

Landscape

## ABSTRACT

In order to foresee the impact of permafrost thaw on CO₂ emissions by high-latitude rivers, in-situ measurements across a permafrost and climate/vegetation gradient, coupled with assessment of possible physico-chemical and landscape controlling factors are necessary. Here we chose 34 catchments of variable stream order (1 to 9) and watershed size (1 to >10⁵ km²) located across a permafrost and biome gradient in the Western Siberian Lowland (WSL), from the permafrost-free southern taiga to the continuous permafrost zone of tundra. Across the south-north transect, maximal CO₂ emissions (2.2 ± 1.1 g C-CO₂ m⁻² d⁻¹) occurred from rivers of the discontinuous/sporadic permafrost zone, i.e., geographical permafrost thawing boundary. In this transitional zone, fluvial C emission to downstream export ratio was as high as 8.0, which greatly (x 10) exceeded the ratio in the permafrost free and continuous permafrost zones. Such a high evasion at the permafrost thawing front can stem from an optimal combination of multiple environmental factors: maximal active layer thickness, sizable C stock in soils, and mobilization of labile organic nutrients from dispersed peat ice that enhanced DOC and POC processing in the water column, likely due to priming effect. Via a substituting space for time approach, we foresee an increase in CO₂ and CH₄ fluvial evasion in the continuous and discontinuous permafrost zone, which is

<footnote><sup>a</sup> BIO-GEO-CLIM Laboratory, Tomsk State University, Tomsk 634050, Russia</footnote>

<footnote><sup>b</sup> Geosciences and Environment Toulouse, UMR 5563 CNRS, Univeristy of Toulouse, 14 Avenue Edouard Belin, 31400 Toulouse, France</footnote>

<footnote><sup>c</sup> N. Laverov Federal Center for Integrated Arctic Research, Russian Academy of Sciences, Arkhangelsk 163000, Russia</footnote>

<footnote><sup>d</sup> V.N. Sukachev Institute of Forest, Siberian Branch of Russian Academy of Sciences, Krasnoyarsk 660036, Russia</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: oleg.pokrovsky@get.omp.eu (O.S. Pokrovsky).</footnote>
notably linked to the greening of tundra increases in biomass of the riparian vegetation, river water warming and thermokarst lake formation on the watershed.

# 1. Introduction

Fluvial systems in high latitude regions are important drivers of the greenhouse gas (GHG) emissions to the atmosphere (Koprivnjak et al., 2010; Campeau and del Giorgio, 2014; Chadburn et al., 2017; Stackpoole et al., 2017; Tranvik et al., 2018; Vonk et al., 2019; Karlsson et al., 2021; Vachon et al., 2021). Although currently, the northern systems represent a much lower proportion of overall water surface emissions compared to the tropical belt (Liu et al., 2022; Battin et al., 2023), ongoing climate warming, which is mostly pronounced in higher latitudes (Mack et al., 2021), is likely to change the spatial distribution of inland water GHG emissions via increasing the relative contribution of northern aquatic ecosystems (Liu et al., 2022; Miner et al., 2022), notably due to their large and highly vulnerable soil C pool (Turetsky et al., 2020). Among the main factors capable of increasing the importance of arctic and subarctic regions in overall aquatic - atmospheric C balance are: permafrost thaw and liberation of labile organic matter and nutrients (Mann et al., 2012; Spencer et al., 2015; Vonk et al., 2015), heating of water and soil (Chen et al., 2021), increased frequency and intensity of plankton blooms (Carey et al., 2012; Payandi-Rolland et al., 2023), change in hydrological connectivity between rivers and inorganic C-rich groundwaters (Bring et al., 2016), increase in terrestrial (Yang et al., 2023) and aquatic (Terhaar et al., 2021; Saros et al., 2023) primary productivity and northward shifting of biomes (Rosbakh et al., 2021). However, little is known as to which degree the permafrost thaw per se influences fluvial CO₂ evasion at the scale of river watershed. Although several studies demonstrated elevated CO₂ concentrations in aquatic sites of abrupt permafrost thaw (Loiko et al., 2017), most studies were focused on terrestrial (Knoblauch et al., 2021) or small water bodies (Shirokova et al., 2013) subjected to permafrost thaw. In contrast, assessment of thaw impact at the entire catchment scale was not possible due to lack of long-term monitoring of fluvial systems, notably with in-situ CO₂ measurements.

Atmospheric C fluxes from river surfaces were extensively investigated in European and North American boreal zones (Teodoru et al., 2009; Butman and Raymond, 2011; Wallin et al., 2013; Campeau et al., 2014; Casas-Ruiz et al., 2021) and some Arctic and subarctic rivers of Alaska (Striegl et al., 2012; Crawford et al., 2013; Stackpoole et al., 2017). Although recently, sizable research efforts have been devoted to previously significantly understudied Siberian lotic waters (Serikova et al., 2018; Vorobyev et al., 2021, 2022; Krickov et al., 2021, 2023; Castro-Morales et al., 2022; Lim et al., 2022a), there is a clear lack of understanding of the main governing factors for both large and small scale watersheds, and, more importantly, lack of assessments for potential hot spots of both regional and local CO₂ emissions. For example, small and headwater streams, notably those of 1st and 2nd order, are often considered as important hot spots for C emissions (Battin et al., 2009; Hotchkiss et al., 2015; Vonk et al., 2015; Stanley et al., 2016; Attermeyer et al., 2018; Rocher-Ros et al., 2023; Song et al., 2023), by virtue of the most labile, freshly dissolved and particular terrestrial organic matter carried by these streams, their stronger turbulence, and large, but still poorly quantified, areal water surfaces. While the role of small headwater streams has been recently assessed in the permafrost-free zone of western Siberia (Lim et al., 2022a; Krickov et al., 2023), their role in C evasion relative to larger rivers in permafrost-affected territories remains virtually unknown, with just a few occasional measurements for the Kolyma River system (Denfeld et al., 2013), the Tabetan region (Song et al., 2023) and small tributaries of the Taz and Lena Rivers (Vorobyev et al., 2021, 2022). Towards filling this knowledge gap, here we selected a large range of watershed sizes and stream orders in permafrost peatlands in order to quantify the relative role of low order

streams in overall C emissions across the entire permafrost gradient. We also accounted for possible variations between day and night variations in C concentration and emission, because ignoring the diel pattern, both in rivers (Rocher-Ros et al., 2019a; Gómez-Gener et al., 2021b; Attermeyer et al., 2021) and lakes (Shirokova et al., 2020) can lead to sizable underestimation of real fluxes when dealing with only single day-time measurements. We assessed a large suite of water column parameters, including dissolved and particulate organic carbon, macro- and micro-nutrients and total bacterial number in order to identify possible drivers of CO₂ and CH₄ production in the water column. Finally, we related field-measured emissions to land cover parameters of river watersheds to assess potential landscape control on C evasion from river surfaces.

We hypothesized that: 1) given the elevated POC concentrations observed at the boundary of discontinuous and sporadic permafrost zone (Krickov et al., 2018), elevated C emissions at the southern permafrost boundary (maximal ALT) reported in some former measurements for medium sized rivers of the WSL (Serikova et al., 2018) may largely stem from enhanced biodegradation of riverine POC (Attermeyer et al., 2018; Keskitalo et al., 2022); 2) there exist much higher emissions in the first order streams (headwater catchments) compared to medium and larger rivers in all permafrost zones; 3) there are diel CO₂ variations in permafrost-affected rivers, similar to recent studies undertaken in Sweden (Rocher-Ros et al., 2019a; Gómez-Gener et al., 2021b) and Eastern Siberia (Castro-Morales et al., 2022) and 4) there is a straightforward landscape control (watershed land cover parameters such as wetland, forest biomass and soil OC stock) on CO₂ emissions from the river waters, as is known for large Siberian rivers such as the Lena River (Vorobyev et al., 2021) and generally across the subarctic zone (Hutchins et al., 2019, 2020). Through verifying these hypotheses, we aimed to assess the fluxes and mechanisms of C emissions from permafrost peatland lotic waters across a sizable gradient of permafrost and river sizes in order to provide a background for upscale fluvial emissions from the large territory of northern Eurasia. We also compared the total C emission flux with the lateral export (yield) of dissolved and particulate carbon in rivers across the permafrost gradient to reveal a spatial pattern in the emission to export ratio, which allows quantifying the degree to which terrestrial C is lost in the fluvial network or exported to downstream coastal areas (i.e., Striegl et al., 2012).

# 2. Study site, materials and methods

## 2.1. Small and medium size WSL rivers across a permafrost gradient and sampling strategy

We selected several representative rivers in each permafrost zone across four main biomes of the western Siberia Lowland (11 in southern taiga, 8 in northern taiga, 10 in forest-tundra and 5 in southern tundra) as illustrated in Fig. 1 with further details for each permafrost zone in Fig. S1 of the supplement. Stream order ranged from 1 to 9 and catchment size ranged from 1 km² to 113,000 km². General physiographical, climatic and lithological characteristics of the WSL and four biomes focused on during this study have previously been described in detail elsewhere (Krickov et al., 2018; Pokrovsky et al., 2022b; Raudina et al., 2021) and are listed in Table S1 of the Supplement. In brief, permafrost peatlands and taiga forests of the WSL developed on Quaternary clays, sands, and silts of alluvial, lake-alluvial and, rarely, aeolian origin south of 60°N and fluvio-glacial and lake-glacial deposits north of 60°N. Paleogene and Neogene deposits include sands, siltstones and clays, and in the southern, permafrost-free zone, these deposits contain carbonate concretions. The mean annual air temperature (MAAT) decreases from -0.5 °C in the south (Tomsk region) to -9.5 °C
in the north (Tazovsky). Annual precipitation is fairly constant ranging between 550 mm in the south to 600 mm in the north. Due to a decrease in evapo-transpiration northward, the river runoff increases from 190 mm y⁻¹ in the south to 300 mm y⁻¹ in the north. The distribution of permafrost reflects the south-north MAAT gradient and changes from isolated and sporadic in the south to discontinuous and continuous in the north. The dominant soils are podzols in forested areas and histosols in paludal regions.

There is no industry, big cities, and arable land of any agricultural use within the watersheds of studied rivers. These rivers are not impacted by oil extraction sites in the south and the gas stations in the north have minimal impact on the environment, other than pipelines and local roads. The latter allowed for unprecedented ground access to

all catchment sampling sites visited during the study. All rivers were studied during summer baseflow (5–26 August 2020, 2021 and 2022). The 11 rivers of the southern taiga, permafrost-free zone of the WSL, were extensively studied in 2020 across different seasons (Krickov et al., 2023). The other rivers from discontinuous/sporadic, discontinuous and continuous permafrost zone were sampled for the first time in 2020–2022 for this study. For sampling, we moved 500 m upstream of the river bridge, where we collected surface water samples from the middle of the river (using waders or a small motor boat) for determination of hydrochemical parameters and performing floating chamber measurements as presented below.

<figure><img src="image_5.png" /><figcaption>**Fig. 1.** Map of the sampling points of the rivers and their position in the permafrost transect of the western Siberia. The sampling sites 1, 2, 3 and 4 correspond to Tazovsky (continuous permafrost, tundra biome), Nadym (discontinuous permafrost, forest-tundra biome), Khanymey (sporadic/discontinuous permafrost, northern taiga) and Tomskaya region (no permafrost, southern taiga). See parameters of the rivers in Table S1 of the Supplement and detailed map of each site in Fig. S1.</figcaption></figure>
## 2.2. GHG concentrations and fluxes

Surface water CO₂ concentration was measured in-situ at 0.3–0.5 m depth by submersing a portable infrared gas analyzer (IRGA, GMT222 CARBOCAP® probe, Vaisala®; accuracy ±1.5 %) as described elsewhere (Vorobyev et al., 2021, 2022; Lim et al., 2022a). The CO₂ fluxes (FCO₂) were measured using floating chamber method adapted for low velocity western Siberian rivers (Krickov et al., 2023). Typically, three 10-L replicate chambers equipped with non-dispersive infrared CO₂ loggers (SenseAir) were deployed in non-anchored (freely drifting) mode at each river, which is the most efficient method for flux measurement (i.e., Lorke et al., 2015). Based on measured FCO₂ and CO₂ concentration in the river water, we obtained the gas transfer coefficient K_T using Fick's law (Eq. (1)):

$$FCO_2 = K_H \times K_T (C_{water} - C_{air}) \quad (1)$$

where K_H is Henry's constant corrected for temperature and pressure (mol L⁻¹ atm⁻¹) which also incorporates a pH-dependent chemical enhancement factor, Cₗwater is the water CO₂ concentration (ppmv), and Cₗair is the CO₂ concentration in the ambient air (ppmv). The CH₄ analysis was performed by gas chromatography, after sample preservation with saturated KCl solution and headspace creation in the as described previously (Serikova et al., 2019; Krickov et al., 2021, 2023). The instantaneous diffusive CH₄ fluxes were calculated using chamber-specific gas transfer velocity (K_T) for CO₂ measured via non-anchored floating chambers, following standard approach for rivers and lakes of the WSL (Serikova et al., 2019).

Lateral downstream export fluxes of dissolved and particulate carbon during open water period (May to October) were calculated based on hydrological approaches as described in Pokrovsky et al. (2020). In brief, the runoff was modelled based on average altitude of the watershed using the parameters obtained for gauged rivers. Note that the contribution of winter time export in large rivers typically does not exceed 10%; moreover, small (< 1000–10,000 km² watershed) WSL rivers freeze solid in winter (Pokrovsky et al., 2015). In order to calculate element export fluxes of 32 WSL rivers (Pokrovsky et al., 2020), we first defined six bins of latitude (56–58°N, 58–60°N, 60–62°N, 62–64°N, 64–66°N and 66–68°N). These latitude class bins were selected based on: i) the permafrost map of the WSL, where the permafrost zones roughly follow the latitude, and ii) necessity to integrate sufficient number of rivers in each latitudinal grid in order to provide robust statistics. The number of rivers used for the latitudinal-average flux calculation ranged from 6 to 16. We finally defined one permafrost-free and three major permafrost zones for which we calculated average open-water period yields of dissolved and particulate C.

## 2.3. Analyses of river water

The dissolved oxygen, pH, specific conductivity, and water temperature were measured in-situ at 20 cm depth using a WTW 3320 Multi-meter. The water was sampled in pre-cleaned polypropylene bottles from 20 to 30 cm depth in the middle of the river and then immediately filtered through disposable sterile Sartorius filter units (0.45 µm pore size). The first 50 mL of filtrate was discarded. The DOC and Dissolved Inorganic Carbon (DIC) were determined by a Shimadzu TOC-VSCN Analyzer with an uncertainty of 3 % and a detection limit of 0.1 mg L⁻¹. Blanks of Milli-Q water passed through the filters demonstrated negligible release of DOC from the filter material. The SUVA₂₅₄, which is an indicator of aromaticity of DOM and its allochthonous (terrestrial) origin, was measured at 254 nm using a 10-mm quartz cuvette on a Bruker CARY-50 UV-VIS spectrophotometer.

To preserve the filtered samples for nutrient and organic acid analyses, we used portable cryoconservator filled by liquid nitrogen, into which the polypropylene vials (2.5 mL) were immersed immediately after on-site filtration. Main inorganic anions, including nutrients, were

measured by high-performance ionic chromatography (Dionex Ics-5000+) with an uncertainty of 2 %. The certified reference materials Ion-915 and Ion-964 were used to verify the accuracy of analyses; the reference material measured concentrations were within 10 % of certified values.

The concentrations of Particulate Organic C and N (POC and PON, respectively) in total suspended solids (TSS) were determined via filtration of freshly collected river water (1–2L) on-site (at the river bank or in the boat) with pre-weighted GFF filters (47 mm) using a manual vacuum pump. The C and N concentrations were measured using catalytic combustion with an uncertainty of ≤0.5 % using Thermo Flash 2000 CN Analyzer. Total bacterial cell concentration (TBC) was measured by a flow cytometry after sample fixation in glutaraldehyde following standard procedures (Marie et al., 1999; Krickov et al., 2023).

## 2.4. Land cover parameters and data treatment

The physio-geographical characteristics of the river watersheds were determined from digital elevation model (DEM GMTED2010), soil, vegetation and lithological maps following the methodology elaborated for northern Eurasia (Krickov et al., 2023; Vorobyev et al., 2022), based on the TerraNorte Database of Land Cover of Russia (Bartalev et al., 2011, http://terranorte.iki.rssi.ru), climate data (Harris et al., 2014) and the biomass and soil OC content (Santoro et al., 2010; Hugelius et al., 2013). The lithology of the watersheds was assessed from Geological map of the region (scale 1: 5000000, http://www.geolkarta.ru/). River water surface area was quantified using the global Sustainable Development Goal (SDG) database with 30 m² resolution (Pekel et al., 2016) together with a more recent Global River Width from Landsat (GRWL) database (Allen and Pavelsky, 2018).

GHG concentrations and fluxes and solute concentrations for all datasets were tested for normality using a Shapiro-Wilk test. Because data were not normally distributed, we used non-parametric statistics. Thus, the median and interquartile range (IQR) were used to represent C concentration and fluxes in sampled rivers. Comparisons of GHG concentration and CO₂ fluxes between different permafrost zones were conducted using a non-parametric Mann Whitney U test at a significance level of 0.05. The Pearson rank order correlation coefficient was used to determine the relationship between CO₂ concentrations and emission fluxes and main landscape parameters of the river watersheds, as well as hydrochemical parameters of the watercolumn.

# 3. Results

## 3.1. Spatial variation of GHG concentration, CO₂ fluxes and hydrochemical parameters

Full dataset of river hydrochemical parameters, GHG concentrations and fluxes and land cover parameters is presented in Mendeley Data portal (Krickov et al., 2024). Neither the watershed size nor the stream order exhibited significant control on CO₂ concentration and fluxes (Fig. 2 A-D). This was true for rivers in each individual zones as well as for the entire set of rivers. Similarly to CO₂, aqueous CH₄ concentration did not relate to stream order or catchment area. This result allowed calculating the mean values of C pattern and other hydrochemical parameters for all rivers in each permafrost zone. A Mann-Whitney test demonstrated significant differences in FCO₂ and CH₄ concentrations between the continuous permafrost zone of the southern tundra and other biomes (Table S2 of the Supplement). The concentrations on DOC, POC, and total bacteria were also different between most permafrost zones.

Mean values of measured hydrochemical parameters and CO₂ emissions for each permafrost zone are listed in Table 1. Across the permafrost gradient, CO₂ concentrations were highest in the southern taiga biome, and remained rather similar for all permafrost-affected regions (Fig. 3 A). Dissolved methane concentration was highest in the
<figure><img src="image_6.png" /><figcaption>**Fig. 2.** Concentration of dissolved CO2 and emission flux of CO2 as a function of watershed size (A, B) and stream order (C, D) in the WSL rivers across permafrost zones (median and IQR).</figcaption></figure>

<caption>**Table 1**</caption>

Mean (± SD) physical, chemical and biological characteristics of the water column for the WSL rivers.

<table><thead><tr><th rowspan="2">Permafrost</th><th>Tomsk<br>(Southern taiga)<br>n = 11</th><th>Khanymey<br>(Northern taiga)<br>n = 8</th><th>Nadym<br>(Forest-tundra)<br>n = 10</th><th>Tazovsky<br>(Southern tundra)<br>n = 5</th><th>Nadym diel dynamics<br>(Forest-tundra)</th></tr><tr><th>Absent</th><th>Sporadic/<br>Discontinuous</th><th>Discontinuous</th><th>Continuous</th><th>Discontinuous</th></tr></thead><tbody><tr><td>pH</td><td>6.91 ± 0.991</td><td>6.94 ± 0.841</td><td>7.84 ± 0.988</td><td>6.81 ± 0.576</td><td>6.69 ± 0.39</td></tr><tr><td>T<sub>water</sub>, °C</td><td>16.7 ± 2.4</td><td>17.9 ± 1.4</td><td>15.2 ± 4.5</td><td>10.9 ± 0.9</td><td>10.1 ± 2.3</td></tr><tr><td>E.C., µS cm<sup>-1</sup></td><td>134 ± 74.7</td><td>35.4 ± 17.4</td><td>69.4 ± 24.1</td><td>46.3 ± 20.5</td><td>67.6 ± 3.59</td></tr><tr><td>O<sub>2</sub>, mg L<sup>-1</sup></td><td>7.55 ± 1.39</td><td>8.23 ± 1.07</td><td>10.9 ± 0.391</td><td>10.5 ± 0.532</td><td>10.5 ± 0.399</td></tr><tr><td>pCO<sub>2</sub>, µatm</td><td>4450 ± 3640</td><td>2250 ± 1060</td><td>2052 ± 800</td><td>1920 ± 530</td><td>1838 ± 333</td></tr><tr><td>CH<sub>4</sub>, µmol L<sup>-1</sup></td><td>3.3 ± 5.2</td><td>2.3 ± 1.9</td><td>1.4 ± 0.39</td><td>0.093 ± 0.033</td><td>1.36 ± 0.63</td></tr><tr><td>pH</td><td>6.91 ± 0.991</td><td>6.94 ± 0.841</td><td>7.84 ± 0.988</td><td>6.81 ± 0.576</td><td>6.69 ± 0.39</td></tr><tr><td>T<sub>water</sub>, °C</td><td>16.7 ± 2.37</td><td>17.9 ± 1.39</td><td>15.2 ± 4.53</td><td>10.9 ± 0.9</td><td>10.1 ± 2.29</td></tr><tr><td>RSM, mg L<sup>-1</sup></td><td>13.2 ± 6.44</td><td>12.7 ± 4.38</td><td>6.76 ± 2.58</td><td>12.1 ± 6.55</td><td>n.d.</td></tr><tr><td>FCO<sub>2</sub>, g C m<sup>-2</sup> d<sup>-1</sup></td><td>1.72 ± 0.913</td><td>2.23 ± 1.09</td><td>1.25 ± 0.523</td><td>0.628 ± 0.286</td><td>1.92 ± 0.859</td></tr><tr><td>K<sub>T</sub>, m d<sup>-1</sup></td><td>1.91 ± 1.29</td><td>0.686 ± 0.341</td><td>1.21 ± 0.395</td><td>0.674 ± 0.338</td><td>1.94 ± 0.638</td></tr><tr><td>FCH<sub>4</sub>, mmol m<sup>-2</sup>d<sup>-1</sup></td><td>35 ± 74</td><td>7.28 ± 8.3</td><td>7.7 ± 4.2</td><td>0.0463 ± 0.074</td><td>11.8 ± 7.7</td></tr><tr><td>POC, mg L<sup>-1</sup></td><td>1.37 ± 0.713</td><td>2.48 ± 0.748</td><td>1.2 ± 0.441</td><td>1.83 ± 0.483</td><td>0.940 ± 0.250</td></tr><tr><td>PON, mg L<sup>-1</sup></td><td>0.104 ± 0.0520</td><td>0.186 ± 0.0640</td><td>0.134 ± 0.0656</td><td>0.229 ± 0.0556</td><td>0.099 ± 0.0139</td></tr><tr><td>DIC, mg L<sup>-1</sup></td><td>19.1 ± 13.8</td><td>2.72 ± 1.18</td><td>6.84 ± 2.03</td><td>3.61 ± 2.03</td><td>6.82 ± 0.172</td></tr><tr><td>DOC, mg L<sup>-1</sup></td><td>11.0 ± 3.67</td><td>7.87 ± 1.88</td><td>3.3 ± 1.11</td><td>18.3 ± 5.36</td><td>3.05 ± 0.314</td></tr><tr><td>SUVA<sub>254</sub></td><td>3.55 ± 0.474</td><td>3.96 ± 0.291</td><td>3.89 ± 0.334</td><td>4.05 ± 0.189</td><td>4.13 ± 0.478</td></tr><tr><td>Cl, mg L<sup>-1</sup></td><td>0.323 ± 0.33</td><td>2.07 ± 2.94</td><td>0.291 ± 0.375</td><td>n.d.</td><td>0.191 ± 0.0305</td></tr><tr><td>SO<sub>4</sub>, mg L<sup>-1</sup></td><td>1.46 ± 2.38</td><td>0.72 ± 0.117</td><td>1.6 ± 1.74</td><td>n.d.</td><td>1.34 ± 0.841</td></tr><tr><td>P-PO<sub>4</sub>, µg L<sup>-1</sup></td><td>20.5 ± 13.2</td><td>11.9 ± 4.68</td><td>14.4 ± 8.49</td><td>n.d.</td><td>19.9 ± 5.14</td></tr><tr><td>P<sub>total</sub>, µg L<sup>-1</sup></td><td>44.1 ± 11.5</td><td>38.1 ± 6.73</td><td>n.d.</td><td>n.d.</td><td>n.d.</td></tr><tr><td>N-NO<sub>2</sub>, µg L<sup>-1</sup></td><td>6.9 ± 2.6</td><td>5.9 ± 1.4</td><td>26.3 ± 0.80</td><td>n.d.</td><td>26.5 ± 0.08</td></tr><tr><td>N-NO<sub>3</sub>, µg L<sup>-1</sup></td><td>127 ± 21</td><td>82 ± 25</td><td>64 ± 60</td><td>n.d.</td><td>73 ± 4.6</td></tr><tr><td>N-NH<sub>4</sub>, µg L<sup>-1</sup></td><td>45 ± 38</td><td>31.4 ± 13.6</td><td>n.d.</td><td>n.d.</td><td>n.d.</td></tr><tr><td>N<sub>total</sub>, µg L<sup>-1</sup></td><td>489 ± 99</td><td>356 ± 98</td><td>n.d.</td><td>n.d.</td><td>n.d.</td></tr><tr><td>total bacteria,<br>cell mL<sup>-1</sup></td><td>1,710,000±<br>1,190,000</td><td>2,140,000±<br>2,680,000</td><td>105,200±<br>43,800</td><td>345,000±<br>63,300</td><td>98,380±<br>37,700</td></tr></tbody></table>

E.C., electrical conductivity; RSM, river suspended matter; POC, particulate organic carbon; PON, particulate organic nitrogen.

permafrost-free zone and lowest at the Tazovsky site of the continuous permafrost zone (Fig. 3 B). The CO₂ fluxes, however, exhibited a maximum in the Khanymey site (northern taiga) located at the border

between the sporadic and continuous permafrost zone (Fig. 3 C). Measured FCO₂ ranged from 0.63 ± 0.33 g C-CO₂ m⁻² d⁻¹ at the Tazovsky site to 2.2 ± 1.1 g C-CO₂ m⁻² d⁻¹ at the Khanymey site
<figure><img src="image_7.png" /><figcaption>Fig. 3. Median (IQR, range) concentrations of CO₂ (A) and CH₄ (B) and fluxes of CO₂ (C) and CH₄ (D) in WSL rivers across different permafrost zones. The difference in C concentration and emission pattern between different permafrost zones was assessed from Mann-Whitney (U test) and presented in Table S2 of the Supplementary Material.</figcaption></figure>

(Table 1). Calculated diffuse CH₄ fluxes (FCH₄) provided a sizable contribution to total C emissions in the permafrost-free zone (19 %), decreased to 4–7 % in the sporadic and discontinuous zone, and became negligible (0.1 %) in the continuous permafrost zone (Fig. 3 D).

DOC concentration decreased almost three-fold from the permafrost-free to the discontinuous permafrost zone and then increased to 18 mg L⁻¹ in the continuous permafrost zone (Fig. S2 A of the Supplement). DIC concentration was highest in the southern site of the WSL (Fig. S2 B). Particulate organic carbon and nitrogen exhibited a local maximum in the northern taiga (sporadic permafrost) zone and increased ten-fold in the continuous permafrost zone (Fig. S2 C, D). In contrast, total particulate suspended matter did not show any systematic spatial pattern (Fig. S2 E). Finally, total bacteria number was highest in the permafrost-free and sporadic permafrost zone and lowest in the discontinuous permafrost zone (Fig. S2 F).

## 3.2. Diel variations of C concentration and emission pattern

High frequency (each 2 h over 26 h time span) monitoring of all hydrochemical parameters, CO₂ concentration and emissions via floating chambers were performed for two rivers of the discontinuous permafrost zone, the Idayaha and Khabitose rivers (S<sub>watershed</sub> of 184 and 448 km², respectively) as illustrated in Fig. 4. Mean CO₂ concentrations were 2130 ± 90 and 1600 ± 200 vppm in the Idayaha and Khabitose rivers, respectively. There was slight increase (15–20 %) in CO₂ concentrations after sunrise (Fig. 4 A), but overall, the difference in CO₂ concentration between day and night period was not significant (Mann-Whitney *U* test difference, *p* > 0.05). Mean CO₂ flux was equal to 2.74 ± 0.52 and 1.29 ± 0.42 g C-CO₂ m⁻² d⁻¹ for the Idayaha and Khabitose rivers, respectively. For both rivers, emissions were 15–40 % higher in the first half of the day compared to the night, but generally similar between day and night, across the 26-h lapse, considering the uncertainties of replicate chambers (Fig. 4 B). The diel variations of pCO₂ and FCO₂ were not related to those of temperature, pH and O₂ (not shown). The concentrations of DOC, DIC, POC, and nutrients (PO₄, NO₃)

<figure><img src="image_8.png" /><figcaption>Fig. 4. Diel variations of CO₂ concentrations (A) and CO₂ emissions (B) of two small rivers of the discontinuous permafrost zone of the WSL (Idayaha, S<sub>watershed</sub> = 184 km², and Khabitose, S<sub>watershed</sub> = 448 km²) during summer base-flow. Night period is shadowed.</figcaption></figure>
as well as SUVA did not exhibit any systematic diel pattern (Fig. S3 A-H). However, there was a local maximum in total bacterial number during early morning (Fig. S3 F). Although it could be tentatively correlated with local $FCO_2$ maximum after sunrise (Fig. 4 B), the rather limited number of measurements and short period of observation do not allow concluding on any causality linkage.

Overall, although all rivers were sampled during the day (typically, early afternoon), the lack of a diurnal pattern in $CO_2$ concentration and emission and other hydrochemical parameters allowed us testing the environmental controllers of $CO_2$ emission in each permafrost zone and upscale the carbon emission to export ratio over the entire territories of river catchments investigated in this study as described in the two sections below.

### 3.3. Hydrochemical factors and land cover parameters control on C pattern in rivers

Pairwise correlation analysis of the entire data set across all permafrost zones did not reveal significant linkage between $CO_2$ or $CH_4$ concentration and $CO_2$ fluxes with the main physico-chemical parameters of the river waters such as DOC, POC, SUVA, nutrients and bacterial number (Table S3). Exceptions are $pCO_2$, which correlated ($p$ < 0.05) with $NH_4$ and $FCH_4$, which correlated with $N_{tot}$ concentration ($R_p$ = 0.85 and 0.56, respectively). When considering individual biomes, $pCO_2$ was positively related to DOC (sporadic/discontinuous zone), POC and PON (for all zones except continuous permafrost), and to $NH_4$ concentration in the permafrost-free zone (Table S4). Among all parameters of the water column, POC exhibited the highest and significant correlation with $FCO_2$ ($R_p$ = 0.48, $p$ < 0.05) then all permafrost zones are treated together (Table S3), and this correlation was especially pronounced in the sporadic/discontinuous permafrost zone ($R_p$ = 0.68, $p$ < 0.05; Table S4). $FCO_2$ also positively correlated with TSS, suspended N and dissolved $N_{tot}$, although these correlations were not significant.

The $CH_4$ concentration significantly correlated with dissolved P and N in the permafrost-free and sporadic/discontinuous zone, and positively but not significantly correlated with macronutrients. In the continuous permafrost zone, $CH_4$ production in the water column and emission positively correlated with water temperature and $O_2$ concentration (Table S4). However, although the correlations of GHG concentrations and fluxes with water column parameters were more pronounced for individual biomes, the rather small number of sampled rivers ($n$ = 8 to 10) does not allow confirmation of these links with sufficient certainty.

Concerning the control of landscape parameters, when considering all biomes together, we found that aboveground biomass at the watershed positively correlated with $CO_2$ concentration and $FCO_2$ flux, although the latter trend was not significant (Table S5). Positive correlations of $CH_4$ concentration and fluxes with the biomass were also not significant. It is worth noting that SUVA, POC and PON in the rivers positively correlated with soil organic carbon stock. Among individual biomes, the control of land cover factors consisted in positive correlations of $CO_2$ concentrations and fluxes with 1) riparian vegetation of rivers from southern, permafrost-free zone; 2) soil carbon stock in the northern taiga region, and 3) soil carbon stock, peatland and water body coverage in the continuous permafrost zone (Table S5). Methane concentration and emissions were positively linked only to riparian vegetation in the permafrost-free zone.

### 3.4. Pattern of $CO_2$ emission and export across the permafrost gradient

Considering the mean values of $CO_2$ emissions from river water surfaces in each permafrost zone, we calculated the average land-area normalized riverine evasion flux for 6 months—assuming that summer period (July and August) is representative for the entire open water period (May to October)—as follows from previous works of our group in the southern (Krickov et al., 2023) and northern (Serikova et al.,

2018) part of the WSL and also proven by high-resolution (once to twice a week) sampling for dissolved C river fluxes over the entire year, including spring – autumn period in both permafrost (Pokrovsky et al., 2022a) and permafrost-free (Vorobyev et al., 2019) regions.

We also calculated the land-normalized fluvial emissions solely for July and August period (Table 2). For these calculations, we used a GIS-based total river water surface area for each zone (Table S1), given that the watershed area and stream order did not exert significant impact on GHG emissions (see Section 3.1 and Table S5). The main uncertainties attached to these numbers stem from variation in C emissions among different rivers in each permafrost zone (i.e., typically 30 to 50 %, see Table 1). These allowed for calculation of overall land-normalized fluvial emissions for each permafrost zone, separately for 6- and 2-month open water periods.

The export flux of dissolved (> 90 %) and particulate (< 10 %) organic and inorganic carbon by the WSL rivers across the same permafrost gradient is constrained for three main open-water seasons in previous works of our group (Krickov et al., 2018, 2023; Pokrovsky et al., 2020, 2022a). These lateral DOC and DIC yields (C flux in mass unit per month/period, normalized to land area) were quantified for the permafrost-free and three main permafrost zones of the WSL during spring, summer and autumn, as listed in Table 2. Based on these estimations, we could calculate the ratio of C-$CO_2$ emission to C (DOC and DIC) lateral export across the permafrost zones of western Siberia (Fig. 5). The remarkable result here is that the ratio is a factor of 4 to 10 higher in the sporadic/discontinuous permafrost zone (Khanymey, northern taiga biome) compared to all other biomes and permafrost zones of the WSL.

## 4. Discussion

### 4.1. Spatial variations of C evasion across different permafrost zones and river sizes

Over past decade, the understanding and quantification of C evasion from lotic waters have strongly advanced (Horgby et al., 2019; Schneider et al., 2020; Gómez-Gener et al., 2021a, 2021b; Hao et al., 2021; Li et al., 2021a, 2021b; Xiao et al., 2020; Liu et al., 2022). However, regional variations of $FCO_2$ from rivers and streams are huge due to the strong heterogeneity of water objects and various, often counter-acting, factors controlling emissions (Richey et al., 2002; Humborg et al., 2010; Striegl et al., 2012; Borges et al., 2015; Pearce et al., 2022). The Western Siberia Lowland can help to overcome this heterogeneity because of its relatively homogeneous relief, land cover, soil C stock, river runoff and climate, with permafrost being the sole factor systematically varying for the set of 34 rivers selected in this study.

Our results generally confirmed the first hypothesis on the local regional maximum of $CO_2$ evasion from river waters located at the southern permafrost boundary (northern taiga biome, in the vicinity of Khanymey Research station). Specifically, it is at the border of the sporadic/discontinuous permafrost, where we observe the maximal concentrations and fluxes of POC (Krickov et al., 2018; Fig. S2 C, D of this study) and the maximum of $CO_2$ flux (Fig. 3 C). We designed our study to reveal not only $CO_2$ emissions along the permafrost gradient, but the ratio of emission to export, which is an important ecological parameter, allowing to discern the degree to which terrestrial C is lost in the aquatic network or exported to downstream areas. In the southern permafrost region, we evidenced a much higher ratio of C emission: downstream export (Fig. 5). Such a ratio, achieving eight in July–August, is several times higher than the mean for rivers in western Siberia in general (2; Serikova et al., 2018), Taz and Lena river fluvial systems (2 and 1, respectively; Vorobyev et al., 2021, 2022), mean global value (Raymond et al., 2013; Lauerwald et al., 2015) and that of the Yukon River (Striegl et al., 2012).

Generally speaking, high emission: export ratios, such as those
<table><caption>**Table 2**
Land-normalized fluvial C emissions and downstream C export by the WSL rivers of different permafrost zones over July and August (60 days).</caption><thead><tr><th rowspan="2">Site</th><th>Watershed area</th><th>DOC flux</th><th>DIC flux</th><th>DOC export</th><th>DIC expert</th><th>Total C export</th><th>River water area</th><th>CO<sub>2</sub> Flux</th><th>Emission</th><th>Ratio emission: export</th></tr><tr><th>km<sup>2</sup></th><th>t C/km<sup>2</sup>/day</th><th>t C/km<sup>2</sup>/day</th><th>t C/day</th><th>t C/day</th><th>t C/day</th><th>km<sup>2</sup></th><th>g C m<sup>2</sup>/d</th><th>t C d<sup>-1</sup></th><th></th></tr></thead><tbody><tr><td>South rivers</td><td>186,905</td><td>0.249*</td><td>1.42*</td><td>46,540</td><td>265,400</td><td>311,940</td><td>1435</td><td>1.72</td><td>148,090</td><td>0.48</td></tr><tr><td>Khanymey</td><td>10,690</td><td>0.449*</td><td>0.256*</td><td>4800</td><td>2737</td><td>7536</td><td>457.6</td><td>2.2</td><td>60,403</td><td>8.0</td></tr><tr><td>Nadym</td><td>53,899</td><td>0.577*</td><td>0.157*</td><td>31,100</td><td>8462</td><td>39,560</td><td>1150</td><td>1.25</td><td>86,250</td><td>2.2</td></tr><tr><td>Tazovsky</td><td>1519</td><td>0.318*</td><td>0.477*</td><td>483</td><td>725</td><td>1208</td><td>22</td><td>0.63</td><td>832</td><td>0.69</td></tr></tbody></table>

<figure><img src="image_9.png" /><figcaption>**Fig. 5.** Carbon emission to export ratio across a permafrost gradient in western Siberia Lowland.</figcaption></figure>

discovered in this study, are not common for permafrost-draining rivers, where colder temperatures inhibit efficient mineralization of exported terrestrial OC (i.e., Striegl et al., 2012). Previously, elevated C emission to export ratios in the WSL rivers were attributed to the long travel times of river water, governed by the overall flat topography of the area, which allowed sufficient time for DOM mineralization and C evasion (Serikova et al., 2018). In the present study, we suggest that enhanced CO₂ emissions at the permafrost thawing front correspond to maximal active layer depth, which may lead to involvement of low molecular weight (LMW) organic matter, including carboxylic acids, originated from freshly thawed dispersed peat ice (Lim et al., 2021, 2022b; Kuzmina et al., 2023) into microbial metabolism within the river water column. Note that large pools of organic nutrients are also reported in other permafrost soils (i.e., Fouché et al., 2020), and it is known that ancient LMW organic acids can stimulate CO₂ production upon permafrost thaw (Drake et al., 2015). Fast processing of this labile OM can further enhance overall DOM and POM biodegradation via, for example, priming effect, which refers to the changes in the degradation of stable OM by the addition of labile OM (i.e., Hotchkiss et al., 2014; Ward et al., 2016; Begum et al., 2019; Zhuang et al., 2021). Although priming effect on stream DOM biodegradation has not been evidenced in permafrost-affected mineral soils (Textor et al., 2019), the role of labile DOM from dispersed peat ice on surface DOM processing and CO₂ production is not known and has to be addressed in a separate study.

Additional factor responsible for elevated CO₂ production in the sporadic/discontinuous permafrost zone could be enhanced terrestrial input of CO₂-rich soil pore waters, delivered to the river via supra-permafrost flow. Unlike in the northern (continuous permafrost) regions, here the active layer is thick and the waters have sufficient residence time in soils (i.e., Ala-aho et al., 2018) to get enriched in CO₂, nutrients and DOC. This also contrasts with southern (permafrost-free) regions, where connectivity is too high, permafrost is absent and most of the labile soil and peat leachates are already processed before they arrive to the river. Therefore, we posit that, at the border between two extreme cases, the presence of some permafrost and sufficiently fast connectivity might lead to optimal conditions of CO₂ enrichment in peat/soil pore waters and its delivery to the river.

Contrary to our second hypothesis, which was initially based on

numerous works in temperate, boreal and subarctic regions (Marx et al., 2017; Li et al., 2021a), we did not evidence significantly (at *p* < 0.05) higher emissions in the first order streams (headwater catchments) compared to medium and larger rivers. Following the explanation developed for the permafrost-free zone of the WSL (Krickov et al., 2023), we suggest that a relatively high and stable SUVA₂₅₄ across the wide range of river sizes (3.8 ± 0.2 L mg⁻¹ m⁻¹) reflects stable input of essentially allochthonous DOM from surrounding peatlands. In contrast, the groundwater regime likely exerts a sub-ordinary influence on the fluvial CO₂ regime in western Siberia. The role of groundwater discharge in driving the CO₂ pattern in the rivers is well established in temperate and boreal regions (i.e. Hope et al., 2001; Finlay, 2003; Johnson et al., 2008; Oquist et al., 2009; Giesler et al., 2013). However, in the WSL, especially in its permafrost-dominated part, the connectivity of small streams to groundwater reservoirs is minimal if not absent at all (Ala-aho et al., 2018; Pokrovsky et al., 2015). As a result, spatial CO₂ concentration and emission patterns across streams and rivers of different sizes are likely to be essentially influenced by soil-derived DOC and POC mineralization in the water column. This findings corroborates previous work in Canadian small boreal streams, which demonstrated the important role of both direct soil CO₂ injection and soil DOC processing, occurring principally in the hyporheic zone of the stream (Rasilo et al., 2017).

## 4.2. Lack of systematic diel variations in C concentrations and emissions

As consistent with previous work of our group on southern (permafrost-free) rivers of the WSL (Krickov et al., 2023), two rivers located in the discontinuous permafrost zone (Nadym site) did not exhibit systematic difference between day and night time CO₂ and CH₄ concentrations and emissions. This finding does not support the third hypothesis of our study. Moreover, short (~2 h) morning-period CO₂ emissions were actually 15 to 40 % higher than the rest of the 24-h time lapse of observations (Fig. 4B), instead of the more common night maximum and the mid-day minimum, as has been documented for continuous pCO₂ measurements and relevant FCO₂ calculations (i.e., Rocher-Ros et al., 2019a, 2019b; Castro-Morales et al., 2022) or via direct floating chambers (Attermeyer et al., 2021). We therefore suggest

<footnote>* Mean multi-annual riverine C yield in each permafrost zone, based on former assessments (Pokrovsky et al., 2020).</footnote>
a negligible role of primary productivity in rivers of the discontinuous permafrost zone during the period of summer baseflow. Among possible factors, riparian shading, which is known to reduce in-stream photosynthesis, can be invoked (i.e., Roberts et al., 2007; Ulseth et al., 2018). Another reason for weak diel variations in CO₂ fluxes could be counteracting CO₂ production via DOM/POM photo mineralization and simultaneous decrease of CO₂ due to photosynthesis of river plankton and periphyton during the day, as also suggested in DOC-rich Siberian Arctic rivers (Castro-Morales et al., 2022). Regardless of the exact mechanisms behind the diurnal pattern, we submit that the uncertainties linked to floating chamber measurements on individual rivers (i.e., standard deviation of replicates) and variations among streams of similar size and land cover are larger than the day / night difference in CO₂ fluxes for the same river. As a result of what is presented above (negligible effect of stream order and period of the day/night), we could average the CO₂ fluxes across rivers of different size, regardless of the exact period of the sampling, and test the effect of land cover parameters controlling fluvial C evasions across the entire permafrost gradient as discussed below.

### 4.3. Landscape factors controlling fluvial C evasions

Our forth hypothesis was that there exists a straightforward landscape control such as wetland coverage, forest biomass and soil OC stock on CO₂ emissions from the river waters, as it is known for large Siberian rivers such as the Lena River (Vorobyev et al., 2021) and generally across the subarctic zone (Hutchins et al., 2019). This hypothesis was only partially confirmed as we found that C stock in soils positively correlated with FCO₂, but only in the sporadic/discontinuous permafrost zone, whereas the wetland coverage was a potential factor of CO₂ emission only in the continuous permafrost zone. Among all land cover factors, solely the aboveground phytomass positively correlated with pCO₂, when considering all the permafrost zones. Most likely, litterfall in the taiga forest on the studied watersheds provided stable allochthonous input of OM, which was subjected to microbial processing in the water column. In western Siberia, that accommodates extremely flat river watersheds, the riparian zones and floodplains of small rivers may turn out to be the main sites of elevated CH₄ generation in the water column and river shore sediments, as supported by a positive correlation (R<sub>Pearson</sub> = 0.89–0.94, *p* < 0.01) between pCH₄ and riparian vegetation of the watershed in the southern, permafrost-free zone (Table S5). However, this mechanism does not operate in permafrost-bearing zones, where none of the landscape factors correlated with CH₄ concentration or fluxes. Here, the water temperature rather than land cover becomes the limiting factor of CH₄ pattern, as follows from a strongly positive (R<sub>Pearson</sub> = 0.98…0.91, *p* < 0.01) correlation between CH₄ concentration or fluxes and water temperature in rivers of the continuous permafrost zone (Table S4). Note that the ebullition, not assessed in the present study, can constitute sizable proportion of total CH₄ flux as it is known for lakes of the Ob River floodplain in western Siberia (Sabrekov et al., 2017). Overall, we admit that the complexity of counteracting factors controlling fluvial methane emissions (Rocher-Ros et al., 2023) does not allow resolving the mechanisms operating in the WSL rivers without further detailed spatially- and seasonally-resolved measurements, including ebullition fluxes whose role in overall C emissions from permafrost rivers can be comparable or exceeding those of CO₂ (i.e., Zhang et al., 2020).

### 4.4. Foreseeing possible evolution of carbon emission in western Siberia rivers upon climate warming and permafrost thaw

Taking advantage of the sizable permafrost gradient, along which small and medium-size rivers sampled in the present study are located, we can apply a substituting space for time approach (i.e., Blois et al., 2013a, 2013b) in order to foresee possible changes in C emission to export ratio in WSL rivers upon climate warming and permafrost

boundary shift northwards. Overall, the vast and relatively pristine territory of the western Siberia is perfectly suitable for a space-for-time substituting scenario because it exhibits highly homogeneous and flat relief, similar lithology (sedimentary clays and sands), soils (podzols and histosols) and vegetation (taiga and tundra) characteristics. Taken advantage of such a unique physio-geographic setting, our group widely used the substituting space for time approach for predicting evolution of lake (Manasypov et al., 2014, 2020), river (Vorobyev et al., 2017; Krickov et al., 2018), and soil porewaters (Raudina et al., 2021) hydrochemistry, as well as the lake hydrobiology (Pokrovsky et al., 2022b) and GHG regime (Serikova et al., 2019) in western Siberia. When applying this scenario for C emission pattern in WSL rivers across the permafrost gradient, we can expect a progressive and sizable increase in C emission to export ratio in the northern part of the WSL, when the discontinuous/sporadic permafrost boundary shifts northward. The increase in the active layer thickness and mobilization of fresh labile low molecular weight organic matter from previously frozen dispersed ice (Lim et al., 2022b; Kuzmina et al., 2023) in the discontinuous and continuous permafrost zone might bring about an increase in biodegradation of this freshly delivered OM in the river water.

A notable result was a positive impact of water bodies coverage of the watershed on FCO₂ in the continuous permafrost zone (Table S5). This suggests that both on-going thermokarst lake drainage and decrease of lake size in the north (Polishchuk et al., 2018; Polishchuk and Kuprianov, 2022) and overall increase in terrestrial biomass and primary production in Siberia (Yang et al., 2023) may decrease the CO₂ evasion from fluvial systems. Furthermore, despite the positive impact of terrestrial biomass on FCO₂ (Table S5), an increase in land primary production in Siberia (Yang et al., 2023), notably greening of the tundra biome (Berner et al., 2020), should increase atmospheric C uptake on the land and thus decrease the share of C fluvial emissions in the overall C exchange budget of the territory.

The production of methane, which is positively linked to riparian vegetation in the southern taiga (Table S5) and water temperature in the tundra biome (Table S4), will likely be responsive to a lesser amount of environmental factors compared to CO₂ although it is also possible that these factors are not entirely identified in the WSL rivers. However, it is reasonable to expect that, regardless of regional pattern of permafrost thawing, climate warming and increase of summer-time precipitation will increase in riparian zone productivity and overall warming of WSL lotic waters during summer season. This will inevitably increase methane emissions from river water surfaces, across all terrestrial biomes of western Siberia, especially in the continuous permafrost zone.

## 5. Conclusions

A complex biogeochemical study of CO₂ and CH₄ concentration and emission, dissolved and particulate carbon and nutrient dynamics covering 34 western Siberian streams and rivers of different sizes across a latitudinal gradient, ranging from a permafrost-free southern taiga biome to a continuous permafrost zone of northern tundra, allowed for a comprehensive picture of the spatial variability in GHG emissions from river water surfaces. We measured CO₂ emissions by floating chambers, including diel cycle on some rivers, and assessed a suite of parameters for the water column, including dissolved and particulate organic carbon (DOC and POC, respectively), nutrients and total bacterial concentrations. Further, we related measured C pattern to GIS-based land cover parameters (vegetation biomass and productivity, climate, soil C, wetlands) of individual catchments.

The CO₂ concentrations and emissions from water surface were independent of watershed size and stream order and did not exhibit sizable (> 30 %) variations between day and night. Considering all permafrost zones, we have not confirmed the existence of hot spots of C emissions in small headwater streams of 1st order. Diel variations in CO₂ concentration and emissions were not sizably pronounced, and there was no systematic difference in the CO₂ pattern between day and night
period in the discontinuous permafrost zone. We did not observe any straightforward control of landscape parameters of the river watershed on fluvial CO₂ emissions, whereas DOC and POC concentrations positively correlated with CO₂ fluxes, suggesting OC mineralization in the water column as one potential driver of CO₂ evasion from river surfaces. We discovered a strong local maximum of C emission (> 90 % CO₂, < 1–10 % CH₄) to C export (DOC+DIC) ratio, which was as high as 8 during summer baseflow at the border between the sporadic and discontinuous permafrost zones. This maximum likely stemmed from an optimal combination of terrestrial input of shallow (suprapermafrost) C-rich peatland waters. Such waters contain large amounts of labile OM, which, together with maximal delivery of particulate organic matter, led to efficient in-stream OC mineralization and CO₂ production. The allochthonous DOM biodegradation could be further enhanced via the priming effect of labile low molecular weight organic matter from dispersed peat ice. The latter was mostly pronounced at the very edge of permafrost thaw, with maximal ALT but still sizable reservoirs of labile OM-rich permafrost ice. In accord with previous studies in western Siberia, and generally across the boreal and subarctic zone, we identified particulate and dissolved organic carbon as main factors of CO₂ production in the water column. Based on current spatial pattern of C emissions in WSL rivers across a permafrost gradient, and applying a “substitution space for time” scenario, the effect of climate warming and permafrost thaw is not expected to sizably modify the emissions in the sporadic and isolated permafrost zone. In contrast, there could be a two-fold increase in CO₂ emissions from rivers of the continuous and discontinuous permafrost zone, whereas the emissions of CH₄ in the continuous permafrost zone might also strongly increase.

## CRediT authorship contribution statement

**Ivan V. Krickov:** Writing – original draft, Investigation, Data cura-
tion, Conceptualization.
**Artem G. Lim:** Writing – review & editing,
Methodology, Investigation.
**Liudmila S. Shirokova:** Writing – review
& editing, Methodology, Investigation, Data curation.
**Mikhail A. Kores:** Writing – review & editing, Visualization, Software, Investiga-
tion.
**Oleg S. Pokrovsky:** Writing – original draft, Conceptualization.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Data availability

All the data obtained in this work are presented in Supplementary Information.

## Acknowledgements

The work was supported by the TSU Program Priority-2030. Partial support from RSF grant 23-17-00281 is also acknowledged. OP and LS are grateful for funding from project PEACE of PEPR FairCarboN ANR-22-PEXF-0011.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.scitotenv.2024.173491.

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