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Atmospheric waves on a planetary scale play the main role in the formation of the atmosphere regime, and a polar vortex forms in the stratosphere in winter. A striking example of the interannual variability of the stratospheric polar vortex caused by stationary planetary waves is sudden stratospheric warming (SSW). The internal dynamics of major sudden stratospheric warming accompanied by displacement and splitting of the stratospheric polar vortex (SPV) was studied based on the MERRA-2 reanalysis data from the point of view of explicitly calculating nonlinear interactions of planetary waves with each other and with the mean flow to identify similar trends in the formation of SSW of various types. In particular, it is shown that the formation of a SSW with SPV splitting is not always accompanied by dominant variations in the wave activity of stationary planetary wave with zonal wavenumber 2 (SPW2), but is determined by the maximum interactions of SPW2 with the mean flow. It was obtained that the wave-wave interactions during the generation of secondary stationary planetary wave with zonal wavenumber 1 (SPW1) are maximal 1-2 weeks before, and during the generation of secondary SPW2, 5-10 days before a SSW with SPV displacement. The results aimed at identifying predictors of SSW formation are important due to the fact that SSW significantly affects the entire middle atmosphere, ionosphere, as well as weather conditions in the troposphere and the formation of extreme weather events.

Solar thermal tides have a significant impact on global atmospheric circulation, making it important to study the various external factors that can influence their generation and propagation throughout the atmosphere. Using the mechanistic nonlinear numerical general circulation model of the middle and upper atmosphere (MUAM), this paper examines the influence of solar activity (SA) variations on the spatiotemporal structure of tides. Two ensembles of MUAM simulations of the global atmospheric circulation in January are considered, each consisting of 16 runs, corresponding to high and low SA. It is shown that with increasing solar forcing at high SA, the diurnal migrating tide (DW1) weakens in the altitude range 100-150 km and intensifies at higher altitudes. The analysis of the Eliassen-Palm (EP) fluxes demonstrates a significant correlation between changes in the vertical propagation of wave activity and the amplitude of DW1: downward flux increments generally correspond to tide weakening in the range 110-150 km, while upward flux increments correspond to strengthening of the tide above 150 km. The semidiurnal migrating tide (SW2) weakens at high SA at altitudes of up to 140 km in the Southern Hemisphere and 190 km in the Northern Hemisphere in the mid- and high-latitude thermosphere. This is accompanied by mainly weakening of the ascending EP fluxes. Above 200 km, SW2 amplitude in the Northern Hemisphere increases by a factor of 2-3 at high SA. Above 150 km in the thermosphere, the amplitude of the stationary planetary wave with zonal number 1 (SPW1) decreases at high SA, while the amplitude of the migrating tides increases. Taken together, this leads to a complex structure of changes in the amplitudes of non-migrating tides. As an important link in the dynamic relationship between atmospheric layers, tides, in particular, provide the distribution of the effect of changing solar forcing during varying solar activity across all atmospheric layers. Understanding the complex mechanisms of dynamic interactions between tides and atmospheric circulation is important for improving numerical forecasts of changes in atmospheric processes on various time scales, from days to decades.

A detailed study of the spatial distribution of aerosol sources is essential for understanding their impact on air quality and public health. The source fields of various atmospheric aerosol types arriving to the Middle Urals were estimated with the use of the analysis of the potential source contribution function. The initial data comprised information on the aerosol type obtained through the classification of aerosol particles based on the spectral values of atmospheric aerosol optical depth. The results demonstrate a clear spatial differentiation of atmospheric aerosol sources for the classes “dust” and “elevated smoke”. The proposed approach can significantly enhance the information provided by spectral ground-based photometric measurements, thus improving the accuracy of air quality assessments.

During disturbances in near-Earth space, disruptions in ground-based and satellite technological systems, including catastrophic failures, occur. Therefore, the problem of developing methods for real-time analysis and monitoring of the natural environment with acceptable accuracy is particularly pressing. This article explores a new automated method for detecting anomalies in neutron monitor (NM) observations. This method is based on the synthesis of wavelet decompositions with the rules of statistical decision theory; it enables the detection of anomalies in NM observations and the assessment of their intensity. Discrete wavelet decompositions with adaptive threshold functions are used to detect anomalies. The parameters of the threshold functions are automatically estimated (as data entered the processing system) using the rules of statistical decision theory. The application of these rules yielded a solution with an error not exceeding an a priori specified value. The intensity of anomalies in NM observations is then calculated by summing the amplitudes of wavelet coefficients exceeding the estimated thresholds. The paper studies periods of strong and extreme geomagnetic storms in 2024-2025. Correlations between Dst index and the intensity of anomalies in NM observations are analyzed. The results showed a significant increase in the correlation between the Dst index and the intensity of anomalies in neutron monitor observations during geomagnetic storms. The obtained correlations reached their maxima with a delay of several hours, demonstrating the importance of neutron monitor observations and their consideration when solving space weather problems. The results of the work can be used in space weather forecasting for the early detection of sporadic variations in the cosmic ray flux.

Monitoring and analysing the dynamics of ionospheric parameters allow one to detect disturbances that negatively impact technical systems. Problems of the timely detection of ionospheric disturbances are associated with a high degree of uncertainty in our prior knowledge about the dynamics of ionospheric processes during disturbed periods and the influence of interference and uneven observation network in certain areas. These issues necessitate the development of data recording and analysis methods that guarantee high accuracy and efficiency. The paper presents a new automated method for estimating the state of the ionosphere using ground-based vertical radiosonde data. This method combines elements of statistical decision theory and threshold estimation with wavelet transform. Numerical solutions constructed using this method are used in the Aurora interactive system (https://lsaoperanalysis.ikir.ru/lsaoperanalysis.html), which was developed at the Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch, Russian Academy of Sciences. The results of the implemented algorithms provide data on the state of the ionosphere over Kamchatka (calm or perturbed) and the parameters of ionospheric inhomogeneities in perturbed state. The algorithms are adaptive and do not require preliminary training. Data from the Paratunka (Russia, Kamchatka Region) and Wakkanai (Japan) stations were used to evaluate the method. The behaviour of the ionosphere during periods of strong geomagnetic storms in 2023-2024 was studied. The study confirmed the method efficiency in analysing ionospheric data and detecting inhomogeneities. Prior to the analysed events, signs of an anomalous increase in electron density in the ionosphere were identified. This is of significant practical importance. The suggested method can be used in ionospheric data analysis techniques for monitoring and forecasting space weather conditions, with the aim of timely detection of ionospheric disturbances.

The results of parasitologic and metagenomic study of two nests of the long-tailed gopher obtained in the Tuva mountain plague focus (Mongun-Taiga kozhun of the Tyva Republic) are presented. The fauna of blood-sucking arthropods of both nests was formed by fleas Citellophilus tesquorum Wagn., Frontopsylla elatoides Wagn., Rhadinopsylla li transbaikalica Ioff et Tifl., Oropsylla alaskensis Baker, Neopsylla mana Wagn. and ticks Haemogamasus mandschuricus Vitzthum and Hg. hodosi Goncharova et Buyakova. F. hetera Wagn., F. frontalis baikal Ioff were sporadically present in nest No. 1. According to the size, depth of occurrence, length of passage to the nest chamber, species composition and physiological state of ectoparasites, nests were defined as wintering nest No. 1 and reserve nest No. 2. According to the results of metagenomic analysis, nest community No. 1 contained 64.2 % of Proteobacteria phyla (Allorhizobium - 22.8 %, Aureimonas - 9.71 % and Methylobacterium - 7.68 %), 35 % of Actinobacteria (including Brachybacterium - 3.8 %, Amycolatopsis - 3.33 %, Brevibacterium - 1.76 %), 0.8 % of Firmicutes (Staphylococcus). In the sample from nest No. 2, 87.1 % of sequenced sequences belonged to Actinobacteria phyla (Brachybacterium - 51.0 %, Brevibacterium - 19.6 % and Nocardioides - 7.4 %), 12.8 % to Firmicutes (Staphylococcus), 0.08 % to Proteobacteria (Methylobacterium). Possible reasons for the differences in the composition of nest bacterial communities are discussed.

Extreme weather events change the diurnal and seasonal variations in CO₂ fluxes between the forest and the above surface atmosphere. The analysis of interannual variability of net CO₂ exchange (NEE), total ecosystem respiration (TER), gross ecosystem photosynthesis (GEP) and evapotranspiration (ET) in a cowberry-lichen pine forest of the middle taiga subzone was performed under different weather conditions during the 2021-2023 growing season. According to measurements by eddy covariance system, in the pine forest over three years of observations, the total NEE in May-August varied from -653 to -980 g CO₂/m², GEP varied from 1711 to 2360 g CO₂/m², TER - from 913 to 1380 g CO₂/m². The total evapotranspiration corresponded to 137-262 mm, and the GEP/ET ratio varied within 1.8-3.9 mgC/g H₂O. As a result of multi-level statistical analysis, a correlation GEP with gross radiation, temperature and humidity in the growing season was revealed. A relationship between GEP and air temperature and humidity characteristics of the growing season was revealed. GEP and NEE decreased at abnormally high temperatures and a long absence of precipitation in the first half of the 2021 growing season. Maximal effect of air temperature on ecosystem CO₂ exchange was observed in 2023 at increased supply of soil moisture. It was concluded that the water reserve in the soil mitigates the negative effect of atmospheric moisture deficit in the summer on photosynthesis and evapotranspiration and thereby ensures a stable seasonal net sink of CO₂ in the ecosystem of the cowberry-lichen pine forest of the middle taiga subzone.

Understanding the relationship between the conditions prevailing in anthropogenic altered soils and the diversity of the soil microbiome can provide important information for assessing the state and solving the problem of maintaining the stability of natural and man-made ecosystems. Using high-throughput Illumina sequencing, the diversity and composition of bacteria, archaea, and fungi in the soils of five different phytocenoses within the Meshcherskaya Lowland (Southern Moscow region), as one of the most industrially saturated regions in the country, were analyzed. The results showed a reduction in taxonomic richness and a decrease in phylogenetic diversity and alignment of microbial communities during the transition from the soil of a conventionally background site to soils of secondary phytocenoses and soils associated with man-made objects - an overgrown phosphogypsum dump and an industrial wastewater discharge site. Representatives of 28 bacterial and 1 archaeal phylum were identified in the prokaryotic component of the microbiomes of the studied soils. The dominant position was occupied by the phylum Actinomycetota (relative abundance 21-30 %) and Pseudomonadota (16-19 %). The taxonomic composition of the fungal component of the communities was dominated by Ascomycota (53-74 %), represented by the classes Dothideomycetes, Sordariomycetes, Eurotiomycetes, and Leotiomycetes. Representatives of Basidiomycota in the soils of different phytocenoses accounted for from 16 to 29 % of all identified fungal taxa. The most numerous among the basidiomycetes were the classes Tremellomycetes, Agaricomycetes, and Microbotryomycetes. Using the FAPROTAX software package for predicting the ecological functions of bacterial and archaeal taxa obtained by sequencing 16S rRNA amplicons, as well as the automatic FUNGuild algorithm for sorting by ecologically significant categories of the fungal taxa identified during ITS amplicon sequencing, the ecological profiles of the studied microbial communities were characterized. The data obtained can be used in the environmental monitoring system of impact zones of industrial enterprises.

Biosorption is a promising method for preventing REE migration in natural environments and for their purification, and microscopic fungi are considered effective biosorbents. The article is devoted to studying the biosorption capacity of soil microscopic fungi in relation to REE in aqueous solutions. The dyna`mics of adsorption was studied using the example of lanthanum by the biomass of micromycetes Penicillium canescens and Talaromyces funiculosus depending on the contact time and its concentration in the solution. It was found that adsorption equilibrium in the fungal biomass - aqueous lanthanum solution system occurs within 24 hours, the T. funiculosus biomass demonstrated a higher sorption capacity. Lanthanum adsorption is more intense at medium acidic pH values of solutions; the maximum lanthanum sorption for 24 hours was noted at pH 3.1 by P. canescens biomass. It was revealed that REE with larger ionic radii are extracted more effectively, they more actively occupy free sorption centers with the formation of complexes. With prolonged interaction of REE with fungal biomass, nanoparticles are formed, the composition of which is close to monazite. According to IR spectroscopy data, the REE sorption centers are amide, carboxyl, amine and phosphate groups of the fungal cell wall. The presence of many ionogenic groups determines the high sorption capacity of the fungal cell wall. Intermolecular modeling of the interaction of lanthanum with amino acid residues of fungal cell wall proteins revealed that proteins form strong complexes by complex formation of REE with amino acid residues, where the active centers are glutamic and aspartic amino acids.

Based on the results of microbial indication for 2023 and 2024, it was established that Avacha Gulf and the southwestern coast of Kamchatka are subject to significant oil pollution. The number of hydrocarbon-oxidizing microorganisms at most of the studied stations was 10³ CFU/ml (g) and higher. The results of molecular genetic analysis identifying marker bacterial genes for the oxidation of alkanes (ALK-1, ALK-2, ALK-3) and PAHs (nah, phn, bphA1, xylE, GN-PAH, GP-PAH) in the environment indicated the dominance of bacteria capable to oxidize short- and medium-chain alkanes in the surface waters of Avacha Gulf in 2023, and bacteria that are potential destructors of medium- and long-chain alkanes in the waters of the southwestern coast of Kamchatka. Also, the waters of both areas were characterized by a significant presence of gram-negative bacteria that oxidize various types of PAHs. In 2024, the proportion of stations with bacteria that degrade phenanthrene and short-chain alkanes sharply decreased in Avacha Gulf, but the proportion of stations with microorganisms that oxidize long-chain alkanes increased. An increase in the proportion of water samples with bacterial biphenyl oxidation genes and PAH oxidation genes of gram-negative microbiota was noted for the southwestern coast of Kamchatka. In bottom sediment samples collected in 2023 from both study areas, the genes responsible for PAH oxidation by gram-positive microbiota and for the degradation of long-chain alkanes were most often detected. Analysis of bottom sediment samples collected in 2024 indicated a decrease in the proportion of stations with microorganisms capable of oxidizing various petroleum hydrocarbons in both study areas.