Anton V. Silaev

Methodological approaches to the identification of hydrologically sensitive landscapes have been developed and implemented in the Selenga River basin. The topographic wetness index (TWI) is calculated to detect accumulative landscapes using the digital relief model of the region under study. Areas with TWI ranges of 12–15 and 15–18 are recognized as areas with the most likely runoff zones. To assess the possibility of their influence on the formation of the river runoff composition, a map of the total runoff is created using the flow accumulation (FA) model. Hydrologically sensitive areas (HSAs) in a watershed are determined by superimposing a spatial distribution map of areas with maximum total runoff values on the TWI differentiation map. Areas with contours located within the territories of maximum values of total runoff are identified as true hydrologically sensitive landscapes. Model polygons are selected to test the methodology for mapping hydrologically sensitive areas and primary pollution sources. Studies are carried out on the model territory of the city of Ulan-Ude, which is one of the main pollutants of the waters of the Selenga River and Lake Baikal. The main condition for the formation of secondary sources of pollution (accumulative landscapes) is the correspondence of the pollution source coverage area with HSA. The resulting map of production facilities is superimposed on the HSA spatial distribution map, fragments of which within industrial zones are identified as possible secondary sources of pollution (critical sources areas (CSAs)). The accuracy of the CSA allocation has been confirmed by the results of assessing the level of soil pollution in the city of Ulan-Ude.

This study was the first attempt to identify the sources of total oxidized nitrogen (TON) and inorganic phosphorus (IP) in the water of the Selenga River—the main tributary of Lake Baikal. To identify TON and IP sources, the data on nutrient concentrations in water of Selenga River and its tributaries as well as the data on river runoff were collected and mapped. On the basis of the obtained data, the values of TON and IP exported from different parts of Selenga watershed were evaluated and mapped using geospatial techniques. In addition, critical source areas (CSAs) which accumulate soil pollutants from nonpoint pollution sources and release them into the surface water during storm events were identified in most polluted watershed areas. It was found that the values of TON exports in most parts of the Selenga watershed varied in the range 0–50 kg/km²/yr, whereas the values of IP exports varied in the range 0–5 kg/km²/yr. Obtained data on TON export were in agreement with those obtained earlier by foreign researchers using global models of nutrient export, whereas data on IP exports were two times higher than those previously modelled.

The aim of this study was the systematization and generalization of data obtained by authors during the last decade and the comparison of these data with those obtained by other authors. Gas chromatography (GC-MS) was used for the determination of PAHs and the positive matrix factorization (PMF) model and principal component analysis (PCA) were used for source apportionment of PAHs. It was found that the total concentration of 16 priority PAHs in surface waters varied from 5 to 200 ng/L, whereas the concentration of 16 PAHs in bottom sediments varied from 50 to 700 ng/g. The 2–3-ring PAHs were dominant in water, whereas the 4–6-ring PAHs were dominant in sediments. That was due to PAHs fractionation in the soil–water system. The source apportionment results showed that the PAHs in both water and sediments mostly originated from the combustion of biomass and fossil fuels. In contrast to sediments, there was a PAH fraction in water that did not originate from a single source. The pollution of freshwater ecosystems manifested itself in the lack of correlation between values of octanol/water partitioning coefficients and sediment/water partitioning coefficients of PAHs.

The influence of anthropogenic and natural factors in the trends and mechanisms of development at various topological levels is determined based on relevant information on the structure and dynamics of fluvial systems in the south of Eastern Siberia in various geodynamic settings. This article considers the current spatial and temporal dynamics of the hydrological conditions of the vast territory of the Angara River and its influence on channel deformations and the manifestation of dangerous processes. An analysis of fluctuations in the maximum runoff using differential integral curves resulted in the identification of six periods of water content according to the maximum annual discharges for the period spanning from the beginning of observations to 2020 for the rivers under consideration. The dynamics and intensity of manifestation of hydrological and geological hazardous processes are demonstrated using a series of studies conducted under various geodynamic conditions. Catastrophic floods brought on by enhanced cyclonic activity are accompanied by the destruction of the bank. The highest rate of bank erosion in the plains is 1.5 to 2 m per year, and for rivers in mountains and piedmonts it is 2 to 6 m per year. An analysis of the dynamics of the development of floodplain–channel complexes in the Upper Angara region makes it possible to distinguish two zones of actively developing floodplain–channel complexes: piedmont and estuarine, separated by a relatively stable plain zone.

Critical source areas (CSAs) are the areas prone to generating runoff and are characterized by a high level of soil pollution. CSAs may accumulate and release soil pollutants emitted by primary emission sources (industrial and municipal enterprises) into the surface water during storm events. The aim of this study was to identify CSAs and their pollution sources and to assess the level of soil pollution in CSAs with polycyclic aromatic hydrocarbons (PAH) and trace metals (TM). CSAs were identified using a geospatial data model (GIS), and primary emission sources were identified using a positive matrix factorization (PMF) model. It was found that the soils of CSAs were characterized by higher pollution levels than soils outside the CSAs. Pollution levels were highly variable among the identified CSAs due to the different capacities of the plants located in those areas. Due to high variability of TM concentrations in preindustrial soils, the pollution level of PAHs and the pollution level of TMs in CSA soils did not correlate with each other. The PAH composition of bottom sediments was different from that of soils, whereas the TM compositions of the soils and bottom sediments were similar. It was proved that the main sources of PAHs and TMs in CSA soils were traffic emissions and central heating boilers.

Proceedings of the International conference

The aim of this study was to obtain a detailed picture of the origin of the anthropogenic and natural inorganic solutes in the surface waters of the Lake Baikal watershed using limited data on solute sources. To reveal the origin of solutes, the chemical composition of water was considered as a mixture of solutes from different sources such as rocks and anthropogenic wastes. The end-member mixing approach (EMMA), based on the observation that the element ratios in water uncorrelated with one another are those that exhibit differences in values across the different types of rocks and anthropogenic wastes, was used for source apportionment. According to the results of correlation analysis, two tracers of sources of most abundant ions present in riverine waters were selected. The first tracer was the ratio of combined concentration of calcium and magnesium ions to concentration of potassium ion ((Ca²⁺ + Mg²⁺)/K⁺), and the second tracer was the ratio of sulfate and bicarbonate ion concentrations (SO₄²⁻/HCO₃⁻). Using these tracers, three sources of main ions in water, such as sulfide-bearing silicate rocks, non-sulfide silicate rocks and carbonate rocks, were apportioned. The results of cluster analysis showed the possibility of using the ratios of strontium, iron, manganese, molybdenum, nickel, and vanadium concentrations (Sr/Fe, Sr/Mn, Ni/V, Mo/V) as tracers of the trace element sources. The use of these tracers and the obtained data on sources of main ions showed the possibility of identifying the natural trace element sources and distinguishing between natural and anthropogenic trace element sources.

Proceedings of the International conference

The aim of this study was to select chemical species characterized by distinctly different proportions in natural and anthropogenic particulate matter that could be used as tracers for air pollutant sources. The end-member mixing approach, based on the observation that the chemical species in snow closely correlated with land use are those that exhibit differences in concentrations across the different types of anthropogenic wastes, was used for source apportionment. The concentrations of Si and Fe normalized to Al were used as tracers in the mixing equations. Mixing diagrams showed that the major pollution sources (in descending order) are oil, coal, and wood combustion. The traces of several minor sources, such as aluminum production plants, pulp and paper mills, steel rust, and natural aluminosilicates, were also detected. It was found that the fingerprint of diesel engines on snow is similar to that of oil combustion; thus, future research of the role of diesel engines in air pollution will be needed. The insufficient precision of source apportionment is probably due to different combinations of pollution sources in different areas. Thus, principles for the delineation of areas affected by different source combinations should be the subject of further studies.