Microplastics distribution in the Eurasian Arctic is affected by Atlantic waters and Siberian rivers

Microplastics (1 µm–5 mm) pose ecological risks due to their bioavailability and occurrence throughout marine food webs. Although Arctic environments were once considered largely free of plastic pollution, recent studies report microplastics in Arctic waters, sea ice, sediments, and biota. Key knowledge gaps remain regarding sources, pathways, drivers, and interactions with biota, particularly for the Eurasian Arctic (Kara, Laptev, and East-Siberian Seas), which is underreported. The Arctic Ocean receives substantial freshwater input from major Siberian rivers (Ob, Yenisei, Lena), forming extensive freshened surface plumes across the shelves. The Barents Sea surface is dominated by warm, saline Atlantic inflow. Long-range transport via the thermohaline circulation, local sea/coastal sources, and microplastics trapped and released by sea ice during melt are all potential contributors. However, river-borne microplastics delivery to the Eurasian Arctic has not been quantified in situ. This study addresses these gaps by sampling surface and subsurface waters across the Eurasian Arctic and relating microplastic characteristics to principal surface water masses: Atlantic surface water, Polar surface water, and the Great Siberian River plumes. The goals were to: (i) evaluate microplastic pollution levels in different water masses; (ii) assess spatial distribution, abundance, weight, size, morphology, and polymer types; and (iii) identify potential sources of microplastics to the Eurasian Arctic.

Previous research has documented microplastics across the Arctic system, including surface and subsurface waters, sea ice, deep-sea sediments, and organisms. The North Atlantic drift and thermohaline circulation can transport plastics to the Arctic, with sea ice acting as a temporal sink and transport medium, releasing particles during melt. Reported abundances vary widely depending on methodologies, size cutoffs, and confirmation techniques. Riverine inputs are recognized as major global plastic vectors, but delivery and fate of river-borne microplastics in the Eurasian Arctic had not been quantified with in situ observations. Atlantic waters dominate the Barents Sea surface, whereas the Kara, Laptev, and East-Siberian shelves are influenced by large buoyant plumes from the Ob–Yenisei and Lena rivers, whose seasonal and interannual variability likely affects microplastic distribution. This study builds on these insights by directly linking microplastics properties to identified Eurasian Arctic water masses.

Study area and timeframe: Sampling was conducted during the 78th cruise of R/V Akademik Mstislav Keldysh in September–October 2019 across the Barents, Kara, Laptev, and East-Siberian Seas. Continuous measurements of subsurface salinity and temperature (SBE 21 SeaCAT), and meteorological parameters (air temperature, wind speed, atmospheric pressure) were recorded along the ship track. Water masses: Four water masses were identified along the track: Atlantic surface water (Barents and western Kara), the Ob–Yenisei plume, the Lena plume, and Polar surface water (between plumes). Due to similar characteristics, the Ob–Yenisei and Lena plumes were sub-divided into low-salinity inner (0–16 psu) and more saline outer (16–28 psu) plume regions. Sampling design: 48 surface neuston net tows and 60 subsurface pump samples were collected. Surface water sampling: A neuston net (200 µm mesh; 40 × 60 cm mouth) was towed at ~20 cm depth for 30 min at 2 knots per sample. Towing distances varied ~5%. Filtered volume per tow was 220 ± 11 m³ (based on GPS track). The net was rinsed on deck; the cod-end contents were reduced into a 200 µm metal sieve using pre-filtered Milli-Q water, covered to minimize airborne contamination, and stored in sealed, pre-rinsed glass petri dishes for onshore analysis (target size 0.2–5 mm). Subsurface water sampling: An underway pump-through system with intake at 3 m depth and a 900 W pump supplied flow through sequential stainless steel meshes (1.5 mm and 100 µm). Food-grade PVC plumbing and a Decast Metronic BKCM-15 flow meter recorded sample volumes (2–5 m³ per sample). After each sampling, retained material was back-flushed and collected onto 25 mm stainless steel mesh filters (80 µm), sealed in pre-rinsed glass jars, then digested with 10% KOH in the same jar in a clean lab. The digest was filtered onto 47 mm GF/A filters (1.6 µm) and dried for analysis. Contamination control: All equipment and jars were rinsed with 0.45 µm-filtered Milli-Q water; filters were pre-checked microscopically. Samples/equipment were covered (foil or glass) when possible. Personnel wore cotton lab coats and gloves. All lab steps were conducted in a clean airflow cabinet. Field blanks (1 per 20) and procedural blanks (3 per 20; 10% KOH) were processed identically to subsurface samples and analyzed after filtration onto GF/A paper. No field/procedural blanks were run for surface samples. Particle identification and measurements: For surface samples, particles were visually inspected and photographed onboard; morphology (fragment or fibre), size (mm; longest dimension), and surface area (mm²) were recorded. In the onshore lab, particles were weighed (mg) and analyzed by FT-IR (PerkinElmer Spotlight 400 FTIR, Frontier ATR; 4000–600 cm⁻1; 4 cm⁻1 resolution). Spectra were matched against multiple libraries (PerkinElmer ATR Polymers, STJapan ATR, BASEMAN, and in-house references) and manually validated. For subsurface samples, potential particles on GF/A filters were imaged under a dissecting microscope (Nikon SMZ745T with camera). Size and surface area were measured (Image software); morphology classified (fibres vs fragments) following visual criteria. Chemical composition was determined by micro-FT-IR (PerkinElmer Spotlight 400, transmission µFT-IR). Subsurface particle mass was estimated from polymer density and particle volume (fibres as cylinders; fragment thickness estimated by comparison to nearby fibres). Terminology and metrics: Microplastics were defined as particles <5 mm; detection limits were >200 µm (surface) and >100 µm (subsurface). Metrics included abundance (items/m³; items/km²), particle surface area (mm²), weight concentration (µg/m³), morphology, and polymer type. Statistical analysis: Data (particle characteristics and sampling metadata) were processed in Python (SciPy, Pandas, Matplotlib, Basemap, QGIS). Pearson correlations evaluated relationships between environmental/sampling conditions and microplastic metrics. Pairwise Student’s t-tests with Holm correction assessed differences among water masses for numerical parameters; Friedman and post-hoc Conover tests compared polymer-type distributions; Fisher’s exact test evaluated binary morphology differences. Significance was set at p < 0.05.

Quality control: No microplastics were detected in subsurface field (n=3) or procedural (n=9) blanks; a few cellulose fibres were found in blanks, indicating low contamination risk. No blanks were run for surface samples. No significant correlations were found between microplastic metrics and wind speed or ship velocity; moderate relationships appeared between particle size and salinity/temperature (R² ≈ 0.52–0.53). Overall abundances: Across the study area, surface abundance averaged 0.004 items/m³ (800 items/km²), and subsurface abundance averaged 0.8 items/m³. These levels are on the low end of previously reported Arctic/Atlantic ranges. Surface layer (neuston; 48 stations; total filtered volume 10,670 m³): 258 particles were collected visually; 41 (15.9%) were confirmed plastics, found at 12 stations (25%). Abundance ranged 0–0.045 items/m³ (0–9,000 items/km²), mean 0.004 ± 0.009 items/m³ (800 ± 2,000 items/km²). Among seas: Laptev lowest (0.002 items/m³), East-Siberian highest (0.010 items/m³). Mean particle size 2.5 ± 1.5 mm; mean surface area 3.2 ± 4.1 mm² (Laptev 1.2 ± 2.1; Barents 6.1 ± 6.6). Mean weight concentration 3.7 ± 11.5 µg/m³ (0–71), highest in Barents (12.5 µg/m³). Morphology: 80.5% fragments (incl. 3 films), 19.5% fibres. Polymer types: PE 36.6%, PUR 17.1%, PVC 14.6%, Polyester 14.6%, PA 9.8%, PS 4.9%, PP 2.4%. Three larger PP fragments (10–30 mm) were excluded from analyses. Subsurface layer (pump; 60 samples; total filtered volume 159 m³): 665 visually selected particles; 111 (16.7%) confirmed plastics (0–7 items per sample). Two PTFE fragments (6–9 mm) and three polyester fibres (7–20 mm) were excluded as >5 mm. Sizes 0.1–3.6 mm (mean 0.7 ± 0.7 mm); surface area 0.0001–0.7 mm² (mean 0.04 ± 0.09 mm²). Abundance ranged 0–2.4 items/m³; mean 0.8 ± 0.6 items/m³; similar across seas (Laptev 0.7; Kara 1.0 items/m³). Morphology: fibres 55%, fragments 45% (incl. 9 films). Fourteen polymers identified; most common: Polyester 39%, Acryl 18%, PE 8.1%, PP/PS/PTFE 5.4% each, PA 3.6%, PUR 2.7%, PVC 2%, others (NBR, SAN, POM, PPPO, phenoxy) 1–2% each. Subsurface particle surface area was larger in Barents (0.2 mm²) than other seas (0.01–0.03 mm²; p < 0.05). Weight concentration decreased from Barents toward East-Siberian Sea. Water mass differences and sources: Surface plumes (inner vs outer) showed smaller particles and higher fibre proportion in inner plumes (0–16 psu), and larger particles, higher weight concentration, and greater polymer diversity in outer plumes (16–28 psu). Surface abundance was similar between inner and outer plumes (~0.0045–0.0051 items/m³), but weight concentration was higher in the outer plume (2.9 vs 1.6 µg/m³). No floating microplastics were detected in Polar surface water. In Atlantic surface water, surface abundance (0.0045 items/m³) matched plume values, but particle surface area (p < 0.05), morphology (fibre/fragment ratio; p < 0.05), and polymer types differed from plumes. In subsurface samples, fragments increased and surface area/weight concentration rose from inner plumes to outer plume and to open sea. Inner plumes had abundant fibres and lacked fragments. Atlantic surface water vs plumes showed statistically different fragment abundance (t-test, p < 0.05) and fibre/fragment ratios (Fisher test, p < 0.05). Despite similar subsurface abundances (0.8–1.0 items/m³), weight concentration differed by an order of magnitude between Atlantic water and river plumes (3.8 vs 0.3 µg/m³). Polar surface water subsurface microplastics resembled Atlantic water in abundance and characteristics. Identification of two main sources: Statistical differences in surface area, morphology, polymer composition (p < 0.05) across water masses indicate two dominant sources: (1) Atlantic-origin microplastics advected from the North Atlantic, and (2) river-borne microplastics from Ob, Yenisei, and Lena discharges. Highest weight concentrations occurred in Atlantic-influenced waters; rivers contributed a second, distinct source dominated by fibres (notably polyester) within buoyant plumes.

Linking microplastic metrics to water masses allowed discrimination of sources and pathways across the Eurasian Arctic. Floating microplastics in the western study area (Barents and western Kara) reflect Atlantic advection and are enriched in PE and larger particles, with higher weight concentrations. In contrast, river-borne microplastics consist predominantly of fibres (notably polyester) accumulating within buoyant inner plumes near river mouths; outer plume regions show larger particles and more diverse polymers. The absence of floating microplastics in Polar surface water, coupled with similar subsurface microplastic characteristics to Atlantic waters, suggests seasonal trapping of floating particles in sea ice and subsequent release and sinking upon melt, explaining the prevalence of subsurface fragments in saline waters and their scarcity within river plumes. These findings address the research questions by quantifying microplastics across seas and water masses, identifying Atlantic and Siberian river inputs as key sources, and demonstrating that physical and chemical particle properties can serve as tracers of water mass identity and history. The consistency between independent surface and subsurface sampling methods strengthens the robustness of the source attribution and emphasizes the need to assess multiple layers of the water column to capture the full microplastics inventory.

This study provides a basin-scale assessment of microplastics in the Eurasian Arctic, demonstrating low but consistent abundances in both surface and subsurface layers. It identifies two dominant sources—Atlantic surface waters advecting marine-borne microplastics and the Great Siberian Rivers delivering river-borne microplastics—and shows that particle properties (abundance, size, surface area, morphology, polymer type, and weight concentration) can statistically distinguish these sources and delineate water masses. Atlantic-influenced waters exhibited the highest weight concentrations, while river plumes contributed comparable abundances but lower weight concentrations and fibre-rich compositions. Future research should: (i) quantify microplastic dynamics during the cold season, including trapping in newly formed sea ice, transformation of buoyancy, and release during melt; (ii) intensify spatial sampling within river plumes to resolve fine-scale variability and frontal accumulations; (iii) harmonize methodologies and extend analyses to particles <100–200 µm; (iv) conduct coordinated comparisons of neuston vs pump sampling from identical water volumes; and (v) incorporate atmospheric inputs for the smallest microplastics in the Eurasian Arctic budget.

- No field or procedural blanks were conducted for surface (neuston) samples, preventing direct correction for potential procedural contamination in surface data. - Detection limits excluded smaller particles: >200 µm (surface) and >100 µm (subsurface), potentially underestimating total microplastics, especially the smallest fractions. - Sampling occurred only in late summer to early autumn (September–October 2019), not covering ice formation/melt periods; seasonal processes (e.g., ice trapping and release) were inferred rather than directly observed. - Some water-mass categories had limited sample sizes (e.g., inner plume subsurface N=2), reducing statistical power for certain comparisons. - Subsurface particle mass estimates for fragments relied on approximate thickness assumptions, introducing uncertainty into weight concentration estimates. - Surface and subsurface methods sampled different layers and volumes and were not applied to identical water parcels, limiting direct method intercomparisons. - Potential spatial heterogeneity within plumes is high; more extensive within-plume sampling is needed to solidify statistical inferences.