Greenhouse gas fluxes (CH4, CO2) from the Kuibyshev Reservoir: an eddy covariance study

Authors

  • Nikitin O.V. 1
  • Stepanova N.Yu. 2
  • Aukhadeev T.R. 2
  • Latypova V.Z. 2
  • 1 Ekoaudit LLC, Sechenov Str., 17, Kazan, 420061, Russia
    2 Kazan Federal University, Kremlyovskaya Str., 18, Kazan, 420008, Russia

DOI:

https://doi.org/10.31951/2658-3518-2025-A-4-995

Keywords:

greenhouse gases, methane, carbon dioxide, eddy covariance, Kuibyshev Reservoir, Volga Carbon Polygon

Abstract

The study presents the results of evaluating greenhouse gas fluxes (methane and carbon dioxide) from the surface of the Kuibyshev Reservoir (Russia) using the eddy covariance method along with the LI-7700 (CH4) and LI-7200RS (CO2/H2O) gas analyzers. Measurements were conducted from August to December 2024 in a shallow section (2–4 m) of the reservoir within the water cluster of the Volga Carbon Polygon (Republic of Tatarstan, Russia). The results showed that the reservoir is a source of methane and carbon dioxide, with maximum emissions observed in August–September (52.84 ± 22.49 and 47.53 ± 27.06 mg CH4 m–2·day–1; 2.32 ± 1.70 and 2.54 ± 1.75 g CO2 m–2·day–1, respectively). At the same time, significant daily CO2 uptake was also recorded in August–September, driven by the photosynthetic activity of phytoplankton. In autumn, alongside emission, occasional methane flux from the atmosphere into the water column was recorded. During winter, gas exchange was minimized due to the ice cover. Seasonal variability of the fluxes is determined by a combination of biological processes (methane production and oxidation, photosynthesis), physical factors (water temperature, concentration gradients, turbulent mixing), and meteorological conditions (wind impact, ice cover formation). The eddy covariance method enables continuous data collection with high temporal resolution and accounts for the spatial heterogeneity of the water surface. The obtained data are important for refining the contribution of reservoirs to the regional carbon balance and global carbon cycle and demonstrate the advantages of using the eddy covariance method in such studies.

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Published

2025-08-31

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Section

Articles