Gennady Suvorov

Dr. Gennady Suvorov

Institute of Forest Sciences, Uspenskoe, Moscow Region, Russia
orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 November 2021 in Land
Verified
Journal Article
Open access
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Andrey SirinAndrey Sirin
Andrey Sirin
MMMary Medvedeva
Mary Medvedeva
VKVladimir Korotkov
Vladimir Korotkov
Victor Yurevich ItkinVictor Yurevich Itkin
Victor Yurevich Itkin
Tatiana MinayevaTatiana Minayeva
Tatiana Minayeva
HJHans Joosten
Hans Joosten
Rewetting is the most effective way to reduce greenhouse gas (GHG) emissions from drained peatlands and must significantly contribute to the implementation of the Paris Agreement on Climate within the land sector. In 2010–2013, more than 73 thousand hectares of fire-prone peatlands were rewetted in the Moscow Region (the hitherto largest rewetting program in the Northern Hemisphere). As the Russian Federation has no national accounting of rewetted areas yet, this paper presents an approach to detect them based on multispectral satellite data verified by ground truthing. We propose that effectively rewetted areas should minimally include areas with wet grasslands and those covered with water (cf. the IPCC categories “rewetted organic soils” and “flooded lands”). In 2020, these lands amounted in Moscow Region to more than 5.3 and 3.6 thousand hectares, respectively. Assuming that most rewetted areas were former peat extraction sites and using IPCC default GHG emission factors, an overall GHG emission reduction of over 36,000 tCO2-eq year−1 was calculated. We furthermore considered the uncertainty of calculations. With the example of a 1535 ha large rewetted peatland, we illustrate the estimation of GHG emission reductions for the period up to 2050. The approach presented can be used to estimate GHG emission reductions by peatland rewetting on the national, regional, and object level.

1 September 2020 in Geoderma Regional
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Journal Article
Closed access
DKDmitry Karelin
Dmitry Karelin
SGSergey Goryachkin
Sergey Goryachkin
EZElya Zazovskaya
Elya Zazovskaya
VSVasily Shishkov
Vasily Shishkov
APAlex Pochikalov
Alex Pochikalov
Gleb KraevGleb Kraev
Gleb Kraev

10 January 2026 in Sensors
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Journal Article
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VMViacheslav Meshcherinov
Viacheslav Meshcherinov
IGIskander Gazizov
Iskander Gazizov
BPBogdan Pravuk
Bogdan Pravuk
VKViktor Kazakov
Viktor Kazakov
SZSergei Zenevich
Sergei Zenevich
ARAlexander Rodin
Alexander Rodin
We present E-CAHORS—a compact mid-infrared open-path diode-laser spectrometer designed for the simultaneous measurement of carbon dioxide, methane, and water vapor concentrations in the near-surface atmospheric layer. These measurements, combined with simultaneous data from a three-dimensional anemometer, can be used to determine fluxes using the eddy-covariance method. The instrument utilizes two interband cascade lasers operating at 2.78 µm and 3.24 µm within a novel four-pass M-shaped optical cell, which provides high signal power and long-term field operation without requiring active air sampling. Two detection techniques—tunable diode laser absorption spectroscopy (TDLAS) and a simplified wavelength modulation spectroscopy (sWMS)—were implemented and evaluated. Laboratory calibration demonstrated linear responses for all gases (R2 ≈ 0.999) and detection precisions at 10 Hz of 311 ppb for CO2, 8.87 ppb for CH4, and 788 ppb for H2O. Field tests conducted at a grassland site near Moscow showed strong correlations (R = 0.91 for CO2 and H2O, R = 0.74 for CH4) with commercial LI-COR LI-7200 and LI-7700 analyzers. The TDLAS mode demonstrated lower noise and greater stability under outdoor conditions, while sWMS provided baseline-free spectra but was more sensitive to power fluctuations. E-CAHORS combines high precision, multi-species sensing capability with low power consumption (10 W) and a compact design (4.2 kg).

2 November 2019 in Izvestiâ Rossijskoj akademii nauk. Seriâ geografičeskaâ
Verified
Journal Article
Open access
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DKD. V. Karelin
D. V. Karelin
EZE. P. Zazovskaya
E. P. Zazovskaya
VSV. A. Shishkov
V. A. Shishkov
ADA. V. Dolgikh
A. V. Dolgikh
ASA. A. Sirin
A. A. Sirin
NON. I. Osokin
N. I. Osokin
Monitoring of CO2 fluxes on Svalbard: land use alters the gas exchange in the arctic tundra Наблюдения за потоками СО2 на архипелаге Шпицберген: использование территории человеком меняет газообмен арктической тундры

26 September 2021 in Archives of Agronomy and Soil Science
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Journal Article
Closed access
DIDanil Viktorovich Ilyasov
Danil Viktorovich Ilyasov
AMAlexander G. Molchanov
Alexander G. Molchanov
GSGennady Suvorov
Gennady Suvorov
MGMikhail V. Glagolev
Mikhail V. Glagolev
ASAndrey A. Sirin
Andrey A. Sirin
Haylands are the mildest option for the agricultural use of drained peatlands in terms of CO2 emissions. However, CO2 fluxes and their balance may depend on various conditions including the frequency of mowing and amount of phytomass removed. Based on field measurements of CO2 fluxes using the chamber method and monitoring of environmental factors conducted in 2018–2020 on hayland and fallow on drained peatland in central European Russia, a mathematical model of CO2 balance was built. Numerical experiments showed that mowing of hayland, irrespective of the intensity, did not lead to an increase in CO2 emissions compared to fallow. Fallow and hayland after single mowing had closely modelled net ecosystem exchange (NEE) values: 9.9 ± 2.4 and 8.5 ± 2.7 t C ha−1 season−1, respectively. Furthermore, a single mowing turned out 2.8 t ha−1 of hay (0.8 ± 0.1 t C ha−1), and 4.4 (1.4 ± 0.1) after double mowing. The modelled NEE after double mowing increased to 9.4 ± 2.9 t C ha−1 season−1. A single mowing session in early summer is recommended. Compared to other uses, e.g. arable land, mowing on hayland is a compromise between reducing CO2 emissions and gaining economic benefits from drained peatlands.

26 January 2026 in Global Biogeochemical Cycles
Verified
Journal Article
Closed access
VMVadim Mamkin
Vadim Mamkin
VAV. Avilov
V. Avilov
ADA. Dmitrichenko
A. Dmitrichenko
Egor DyukarevEgor Dyukarev
Egor Dyukarev
EEE. Emelianova
E. Emelianova
JKJ. Kurbatova
J. Kurbatova