GIS Mapping of Atmospheric Pollution Using Solid Residue Analysis in Snow Geochemical Surveys: A Case Study of Irkutsk City and the Southern Baikal Region

Kachor Ol'ga Leonidovna Doctor of Technical Science Head of the Department of Geoecology; Siberian School of Geosciences; Irkutsk National Research Technical University 3 Akademika Kurchatov str., Irkutsk, Sverdlovsk region, 664074, Russia olgakachor@geo.istu.edu Ikramov Ziyoviddin Lutfiddin ugli Postgraduate student; Institute of Siberian School of Geosciences; Irkutsk National Research Technical University 3 Akademika Kurchatov str., Irkutsk, Sverdlovsk region, 664074, Russia ziyoviddin.ikramov1992@gmail.com Goryachev Ivan Nikolaevich Head of the Department of Ore Geology; Siberian School of Geosciences; Irkutsk National Research Technical University 3 Akademika Kurchatov str., Irkutsk, Sverdlovsk region, 664074, Russia ivan.goryachev@geo.istu.edu Trusova Valentina Valer'evna PhD in Technical Science Senior Researcher; Siberian School of Geosciences; Irkutsk National Research Technical University 3 Akademika Kurchatov str., Irkutsk, Sverdlovsk region, 664074, Russia vvtrusova@geo.istu.edu

Parshin Alexander Vadimovich ORCID: 0000-0003-3733-2140 PhD in Geology and Mineralogy Director; Institute of Siberian School of Geosciences; Irkutsk National Research Technical University Senior Researcher; Institute of Geochemistry SB RAS 3 Akademika Kurchatov str., Irkutsk, Sverdlovsk region, 664074, Russia sarhin@geo.istu.edu Other publications by this author

Introduction

The state of the snow cover in economically developed regions reflects the features of the natural atmogeochemical processes of the area studied and the degree of impact from man-made factors. The snow cover accumulates pollutants during both dry and wet leaching of contaminants from the atmospheric air ^[1]. Dry washout refers to the direct deposition of pollutants onto already fallen snow cover. In contrast, wet washout involves leaching pollutants from the atmosphere during the formation or precipitation of snow cover. As a result of these processes, the concentration of pollutants in the snow cover of the studied area can be several orders of magnitude higher than in atmospheric air, which in natural environments represents a relatively low percentage of pollution—about 10–30%—with the majority of total pollution in snow cover originating high above the earth's surface during their leaching from air masses brought by precipitation. However, in anthropogenic-altered areas, the situation changes: the presence of pollution sources (often permanent) creates a consistent likelihood of pollutants settling near their source of formation, leading to dry deposition accounting for 70 to 90% of the total pollution ^[2].

Thus, by examining the presence and degree of manifestation of various pollutants in the snow cover, it is possible to study the peculiarities of the influence of different industrial facilities on air quality in the area. In regions with long winters, studies of atmospheric pollution through seasonal snow sampling and analyzing its chemical parameters are the most informative way to assess air quality ^[3]. This method can provide high spatial detail of the obtained data, determined by the density of the sampling network, while simultaneously obtaining a considerable number of indicators of anthropogenic impact by applying various methods to study the chemical composition, physical properties, or mineralogical features of the solid or liquid phases of snow. In current geoecological research practices, studies of the chemical composition of soluble forms in snow water and its physical properties (i.e., those formed due to wet leaching) have become the most widespread [4–7]. However, the analysis of solid sediment can also provide significant information; as a result, the number of new methods is continually increasing, allowing for the acquisition of additional parameters and information—the chemical composition of the solid residue, mineral forms, and integral physical characteristics are investigated using various methods [8–12].

In this paper, the authors draw attention to the fact that obtaining a correctly interpreted and reliable result of a geoecological assessment of air pollution is influenced by the sampling or laboratory research methodology and the approach to geostatistical processing and mapping of the results obtained. Of course, cartographic representations—maps, diagrams, cartograms—are the most biologically convenient geodata representation for analysis. At the same time, the standard approach to cartographic visualization of the results of snow and geochemical studies, particularly regarding the analysis of solid sediment, contains several problematic points. The usual mapping outcome is maps of concentrations of various chemical elements or their compounds. However, such maps do not reflect the actual amount of the pollutant that enters a particular area per unit of time, potentially causing environmental damage; they only record its concentration in volume (melt water) or mass (solid residue on the filter) of the substance. While, in the case of meltwater, this approach may be quite acceptable since the volume of water at different points tends to be roughly the same due to the relatively even distribution of snow cover within the studied local area, leading to high concentrations correlating with locations of significant pollutant introduction during the season, the mass of solid residue may vary significantly. Consequently, the final information materials may present a reality far removed from the mapped degree of man-made load from a specific element. If the atmospheric air is clean, filtering samples of melted snow through a filter may leave almost no insoluble particles on the filtering surface, or very few. In this scenario, even a minimal amount of a pollutant attributed to a small sample volume can yield a very high concentration at a point, which does not accurately reflect the real ecological state of the atmosphere. Conversely, if the atmosphere is heavily polluted with dust containing substances other than the studied pollutant, the results will also be distorted; even a significant amount of the studied pollutant, attributed to a large volume of solid residue on the filters, will appear low, suggesting that its degree of influence is minimal. Thus, concentration maps constructed for natural and anthropogenic environments with complex anthropogenic loads and significantly varying dust loads within the studied area may lead to incorrect interpretations.

In this paper, the authors analyze the problem of informative cartographic visualization of the results of studies on the solid phase of snow cover to improve the most rapid approach to the atmogeochemical assessment of territories based on the study of the chemical composition of the solid residue using non-destructive X-ray analysis. This approach is fast and cost-effective, does not require an expensive laboratory setup or complex sample preparation, and simultaneously allows for obtaining informative results that reflect the complex nature of impacts from several sources ^{[8, 10, 13]}. To demonstrate the aforementioned problems and the proposed approach, an illustrative and typical case was selected: previously, based on the results of a snow and geochemical survey ^[10], the authors assessed the state of atmospheric air in the Irkutsk-2 micro district of Irkutsk and the adjacent village of Bokovo, which are subjects of complex anthropogenic impact and constant attention from residents and environmentalists. Chemical and analytical studies of snowmelt using the ICP-AES method and solid residue on filters with the XRF method made it possible to identify areas with the most significant anomalies and potential sources of their formation. Traditional maps of concentrations of substances in water and solid sediment were constructed and interpreted. However, it became evident that the complete set of distortions described above is present in this case due to the presence of areas with a very high dust load. Consequently, this paper provides a comparative analysis of three mapping strategies for the results of chemical and analytical studies of solid residues. It discusses the advantages and disadvantages of the resulting cartographic representations and offers an expanded interpretation of the results of atmospheric and biochemical analyses of the Baikal region under consideration.

Objects and methods of research

Seasonal snow sampling was conducted using the standard approach established by the Institute of Siberian School of Geosciences of IRNTU for implementing basic educational programs based on the principle of "knowledge through activity"^[14]. In this program, first-year students are organized into several groups to conduct research in late February to early March, a period marked by the maximum accumulation of snow cover. They carry out a complete cycle of snow and geochemical studies in any area of the Baikal region, concluding with presentations of the final materials at scientific conferences. In 2024, a separate residential district of Irkutsk and the nearby village of Bokovo became the focus of such research. Approximately 60 people reside in this area, which is under the complicated influence of various sources of mechanical engineering, thermal energy, construction, transport, and more. Residents of the district and environmental authorities frequently report serious air pollution issues ^[10].

Sampling is performed according to a standard procedure, considering the requirements of GOST R 70282-2022 "Environmental protection. Surface and groundwater. General requirements for ice and precipitation sampling." Samples were collected from open areas located at a distance from obvious sources of local impacts using plastic blades and placed in plastic bags. The volume of snow collected was recorded (the depth of the snow cover and the area of the hole were measured). After sampling, the snow samples were transported to the Chemical Analysis Laboratory of the Siberian School of Geosciences, accredited by the established procedure, where, following snowmelt and filtration, a chemical analysis of the solid residue on the filters and filtered meltwater was conducted. The volume of meltwater before filtration and the mass of the solid residue on the filters were also measured; the solid residue was dried at room temperature and weighed using Analytical XP204 laboratory scales with a sensitivity of ± 0.1 mg. The solid residue was analyzed through X-ray fluorescence analysis ^[15].

Results and discussion

Based on the parameters of the volume of the snow sample, including the area of the pit and the mass of the solid residue, the amount of dust that fell during the entire snow season per 1 m² area was calculated. Using this data, a map of the dust load in the studied area was constructed following the standard methodology (Fig.1) from the moment of stable snow cover formation (November 1, 2023) to the date of sampling (March 11, 2024).

As can be seen from Fig. 1 and noted in the article ^[10], two areas with a high level of seasonal dust accumulation stand out sharply within the studied area: the territory near Stroyproektservice in the northern part of the map and the territory of Komsomolsky Park.

The dust deposition rate per unit time and area was also calculated ^{[6, 16, 17]}, i.e., the amount of dust in mg accumulated per 1 m² of snow per day.

Fig. 1. Map of dust load in Irkutsk-2 microdistrict and Bokovo settlement in winter:

1 – sampling points; 2 – new buildings; 3 – industrial facilities; 4 – roads; 5 – boiler house,

fuel oil–fired boiler house; 6 – coal-fired boiler house; 7 - boundary of the investigated area

The amount of dust load is calculated using the formula:

– the amount of dust load, mg/(^m2*day);

– the mass of the residue on the filter after filtration of snow water, mg;

– the area of the snow pit, ^m2;

– the number of days from the beginning of stable snow cover to the day of sampling, day.

Based on the data obtained, a map of the daily dust load was also constructed (Fig. 2). The anomalies present (Fig. 2) certainly reflect the anomalies from the dust load map for the season (Fig. 1); however, with this data, we can objectively identify areas with an increased level of dust pollution in the snow cover.

These calculations are necessary for us to identify areas with high and low levels of dust load. By themselves, they are standard and have a gradation of dust levels approved by the "Methodological Recommendations for assessing the degree of atmospheric air pollution in populated areas by metals based on their content in snow cover and soil ^[16].":

Low level – _PP < 250 mg / (^m2 * day);

The average level is 251 < R _p < 450 mg/(^m2*day)

High level - 451 < R _p < 850 mg/(^m2*day)

Very high - Ph > 850 mg/(^m2 *day).

Fig. 2. Map of dust load in Irkutsk-2 microdistrict and Bokovo settlement per day:

green color – low dust load; yellow color – medium dust load; red color – high dust load.

According to the presented gradation, the two designated zones (the territory of Stroyproektservice and the territory of Komsomolsky Park) are categorized as areas with high atmospheric air pollution due to dust. It is important to note that in the industrial site of Stroyproektservice, the dust load measures 773 mg/(^m2 * day), while in the park, it is only 482 mg/(^m2 * day). Figures 1 and 2 illustrate that the dust distribution aligns closely with the wind rose. Concerning the first anomaly (StroyProytsErvice), pollution impacts the industrial site of the aircraft factory, the Angara River, and the northwestern part of the village of Bokovo, all of which experience high dust pollution. The second anomaly (Komsomolsky Park) also faces an increased dust load. Within the Irkutsk-2 microdistrict, several apparent non-terrestrial sources of atmospheric pollution exist, including the boiler houses of the Aircraft Factory: those fueled by oil and coal, located in the central territory, and the coal-fired boiler house situated in the southeastern part of the village. According to the wind rose, these sources can significantly influence pollution dispersion. Meanwhile, Komsomolsky Park, positioned in the pathway of boiler emissions, features a well-developed green zone, richly planted with tall trees with broad crowns, serving as a natural barrier and storage for gas and dust flow.

After that, based on data regarding the concentrations and areas of the pits, the intake of heavy metals and arsenic with dust particles per season was calculated. To do this, we multiply the seasonal accumulation of dust (g/^m²) by the content of a specific element recorded in the solid residue on the filter (mg/kg). The values obtained show how much of a specific substance fell on 1 m² of the studied area during the snow season (the 2023–2024 season lasted 132 days). For visual analysis and perception convenience, maps of the distribution of pollutants with the mass of the substance per unit area were constructed (Figs. 3–8). According to the "Methodological Recommendations", such a geostatistical construction can also be classified ^[4] (Fig. 3-8):

Low level of pollution due to precipitation of pollutants < 1000 mg/(^km2*day) (white and green on maps);

The average level of pollution during precipitation of pollutants is from 1000 to 5000 mg/(km² *day) (yellow shade on maps);

High level of pollution during precipitation of pollutants from 5000 to 10000 mg/(km² * day) (red shade on maps);

Very high level of pollution with precipitation of pollutants > 10000 mg/(^km2*day) (purple shade on maps).

To move to the required dimension, the total accumulation of dust per unit area per unit time (mg/(^m2*day)) is multiplied by the concentration of a specific element (mg/kg) in the solid residue on the filter, resulting in the amount of pollutant received per day along with snow precipitation per unit surface area—square kilometer (mg/(^km2 * day)).

In Figs. 3, 4, 5, 6, 7, and 8, maps are presented for all elements based on their concentration in dust (mg/kg), their specific accumulated load per unit area per season (g/^m²), and the zoning of the territory according to the level of pollution per unit area (mg/(km²·day)).

From Fig. 3a, it follows that in the larger territory of the Irkutsk-2 microdistrict and the village of Bokovo, the level of arsenic contamination, when it falls with dust, corresponds to the average, ranging from 1,000 to 5,000 mg/(km²*day). High levels of pollution are found in the area of the Stroyproektservice industrial site, as well as from trial sites in Komsomolsky Park, low-rise buildings near the Zavodskaya railway station, and the industrial site area of the territory-two Aircraft Factory "Object," from the boiler house to the southeastern outskirts of the village. Due to the lack of sampling in the closed area-2 Aircraft factories in Fig. 3a, the interpolation features divided this common area into two adjacent local zones. The seasonal supply of arsenic has the same character (Fig. 3b).

Fig. 3. Map of the anthropogenic arsenic load in the Irkutsk-2 microdistrict and the village of Bokovo: (A) the level of pollution resulting from the deposition of pollutants along with dust particles, (mg/(^km²·day)); (B) the concentration of pollutants in the dust (mg/kg); (C) the specific accumulated pollutant load per unit area per season (g/^m²).

When comparing Figures 3a and 3b, the inversion of anomalies is immediately noticeable. That is, when the concentrations are converted to the specific accumulated load, the picture changes to the opposite: those points where the concentration of substances is minimal exhibit the maximum absolute accumulation of pollutants. At the same time, the highest concentrations of arsenic in the residue after filtration are found in the private sector near Motorny Proezd and Rechnaya streets (about seven times relative to the background). Concentrations are also high in the southwest, likely associated with railway tracks, and in the southeast, regarding the additional territory of the 2 Aircraft Factory, the "Facility."

Fig. 4 shows that areoles for lead and anomalies for all types of assessment of anthropogenic load (Fig. 4a, b, and c) repeat the areoles for arsenic.

Fig. 4. Map of the anthropogenic load of lead on the territory of the Irkutsk-2 microdistrict and the village of Bokovo: (A) - the level of pollution caused by precipitation of pollutants along with dust particles, (mg/(^km2*day)); (B) is the concentration of pollutants in the dust (mg/kg); (C) is the specific accumulated pollutant load per unit area per season (g/^m2).

However, the level of pollution (Fig.4a) in the anomalies is very high, in the rest of the studied area it is high. Just like arsenic, there is clearly an inversion of anomalies (Figs. 4b and c). At the same time, the lead concentrations in the sample are quite low – in abnormal areas, the background is up to 3 times higher.

Figures 5 (a and b) show that the main localization zones of increased daily and seasonal chromium loads are associated with man-made sources: the industrial site of Stroyproektservice, as well as the industrial site of the territory-2 Aircraft Factory "Object" with a boiler room and various workshops, and are distributed in accordance with the wind rose.

Fig. 5. Map of technogenic chromium load on the territory of the Irkutsk-2 microdistrict and Bokovo village: (A) the level of pollution caused by the precipitation of pollutants along with dust particles (mg/(^km²·day)); (B) the concentration of pollutants in the dust (mg/kg); (C) the specific accumulated pollutant load per unit area per season (g/^m²).

At the same time, the highest concentration of chromium (Fig. 5b), four and a half times higher than the background, is observed in the residential area at the intersection of Muravyova Street with streets from Mira to Pochtamskaya and only on one of the aforementioned industrial sites: the territory-two the Aircraft Factory. The chromium concentration per unit volume in the gas and dust flows of StroyProektService is obviously low.

For cobalt in the studied area, the level of anthropogenic load is quite acceptable (Fig. 6a ­—low and medium, with only one test site in the park showing a high level (Fig. 6a, c). There were also no significant excess concentrations in the cobalt samples; the maximum is 3–9 times, located along Novatorov Street between Aviastroiteley and Leningradskaya streets, as well as to the southeast of the territory-two of the Aircraft Factory.

Fig. 6. Map of the anthropogenic load of cobalt in the Irkutsk-2 microdistrict and the village of Bokovo: (A) the level of pollution caused by the deposition of pollutants along with dust particles (mg/(^km2*day)); (B) the concentration of pollutants in the dust (mg/kg); (C) the specific accumulated pollutant load per unit area per season (g/^m2).

According to the amount of copper deposited along with dust particles each day, the entire studied area is classified as very highly polluted (Fig. 7a). In Fig. 7b, two anomalies are more clearly identified, which are also confined to the StroyProytsErvice industrial site and the central part of the microdistrict, situated in the zone of influence of two Aircraft Factory sites: territory-1 in the west and territory-two in the southeast. Meanwhile, the greatest seasonal accumulation of copper is observed at one of the test sites of this anomaly, in Komsomolsky Park. In this case, it is possible that the trees in the park act as an air filter, contributing to the deposition of suspended dust. However, the highest concentration of copper in the samples is found in the solid residue after filtering snow collected from the private sector in the area of Motorny Proezd and Rechnaya streets in the northeast of the neighborhood. The maps (Figs. 7b and c) illustrating the distribution of concentrations and seasonal anthropogenic loads on copper clearly show an inversion of the identified anomalies.

Fig. 7. Map of man-made copper load in the territory of the Irkutsk-2 microdistrict and Bokovo village: (A) the pollution level caused by the precipitation of pollutants and dust particles (mg/(^km²·day)); (B) the concentration of pollutants in the dust (mg/kg); (C) the specific accumulated pollutant load per unit area per season (g/^m²).

According to the daily load of nickel, pollution levels in most of the surveyed territory are very high (Fig. 8a).

Fig. 8. Map of man-made nickel load on the territory of the Irkutsk-2 microdistrict and Bokovo village: (A) the level of pollution caused by the precipitation of pollutants along with dust particles (mg/(^km2*day)); (B) the concentration of pollutants in the dust (mg/kg); (C) the specific accumulated pollutant load per unit area per season (g/^m2).

There is a narrow zone with a high pollution level between two sources of negative impact: the Stroyproektservice industrial site and the territory-two Aircraft Factory, where the amount of nickel transported with dust is slightly lower than in the rest of the area. On the maps (Fig. 8b and c), the inversion of anomalies is highlighted only for the territory of the Stroyproektservice industrial site – the concentration in the sample is low, but the amount of dust is very large, leading to a significant seasonal supply of nickel. In the central part of the neighborhood, the situation is somewhat different: an increased concentration of nickel is documented from the area of the Zavodskaya railway station between Shpachek and Muravyov streets to their intersection with Sibirskikh Partizan Street, as well as in the non-residential area in the northeast of the neighborhood. An additional zone of increased specific seasonal load (excluding the territory of the StroyProektService) is situated in two green areas: Komsomolsky Park and the square at the intersection of Muravyova St. and Sibirskie Partizan. At the same time, the square falls into the anomalies in Figures 8b and 8c, indicating that it is in this zone where dust flows containing nickel accumulate.

As can be seen from the figure (Fig. 9a), the daily zinc intake has a very high level of impact on the studied area. The increased zones of specific accumulated zinc load (Fig. 9b) correspond to the zones on the dust load map (Fig. 2): the Stroyproektservice industrial site and the zone of influence of the territory-two Aircraft Factories "Object" in the northwest and southeast directions. On the concentration map (Fig. 9b), the zone of influence of the boiler house partially coincides with the zone of the specific accumulated load for this element during the season. However, there is a low zinc concentration in the dust volume in Komsomolsky Park. That is, the total volume of dust trapped in the snow cover in the park area is very high (Fig. 2). The specific zinc load is also relatively high, but the concentration of zinc in the snow of this territory is low. Most likely, this means that the amount of dust trapped in the park area is caused by different sources, and is concentrated in a much larger volume than in the adjacent territories, which are also in the zone of influence of emissions from the territory-two Aircraft Factory, with a lower density of trees per unit area. At the same time, another green area, the square at the intersection of Muravyov Street and Sibirskikh Partizan, which is also in the zone of influence of territory-two emissions, has anomalies both on the concentration map and on the map of accumulated seasonal specific load (Figs. 9b and c). This most likely means that there are no other sources of dust in this area, and the trees of the park act as a filter and accumulate dust along with the zinc contained in it on their territory, increasing its content relative to neighboring sites. In the StroyProektService area, we again observe an inversion of anomalies on the concentration and specific seasonal load maps (Figs. 9b and c).

Fig. 9. Map of man-made zinc load on the territory of Irkutsk-2 microdistrict and Bokovo village: (A)- the level of pollution caused by precipitation of pollutants along with dust particles, (mg/(^km2*day)); (B) is the concentration of pollutants in the dust (mg/kg); (C) is the specific accumulated pollutant load per unit area per season (g/^m2).

As can be seen from the figure (Fig. 10a), the daily intake of manganese, as well as zinc, has a very high level of impact on the studied area everywhere. The maps of concentration anomalies and specific accumulated seasonal load do not match (Fig. 10b and c), however, the maximum exceedances of the background value are not particularly significant – 1.5-2 times.

Fig. 10. Map of the anthropogenic load of manganese on the territory of the Irkutsk-2 microdistrict and the village of Bokovo: (A) - the level of pollution caused by precipitation of pollutants along with dust particles, (mg/(^km2*day)); (B) is the concentration of pollutants in the dust (mg/kg); (C) is the specific accumulated pollutant load per unit area per season (g/^m2).

Conclusions

A comparative analysis of cartographic materials reflecting the concentrations of pollutants in the solid residue of snow cover and other mapping options based on the same initial data from snow geochemical surveys – maps of daily intake of substances and maps of anthropogenic load per season, convincingly shows that in the case of significantly different dust loads within the studied area, it is better not to build conventional concentration maps and use it. It is shown that the standard mapping option in terms of mg/kg and the like forms a significantly distorted view of the degree of anomaly of the effect of each pollutant on the environment of the studied area, in a series of examples for various elements the effects are shown up to the inversion of anomalies. For example, in situations where there is a high level of pollution in an area with heavily polluted air, due to the large volume of dust in the samples, which includes the content of each pollutant in chemical studies, concentration maps give low estimates of contamination at the points, which distorts the ecological meaning of the data.

Based on additional cartographic materials, atmospheric air pollution in the Irkutsk-2 microdistrict of Irkutsk city and adjacent suburbs has been characterized more fully than in the previous study of the district. It is shown that in this case, the Stroyproektservice construction company, located in the northern part of the studied area, produces in the course of its activities a large amount of inorganic dust with low concentrations, but high absolute amounts of arsenic and heavy metals in it. The territory-2 of the Irkutsk Aviation Plant is also a source of emission of gas and dust mixtures, with higher concentrations of pollutants in it, but a lower total mass. This situation is reflected in various mapping options in the form of prominent anomalies in this area on almost all maps of the distribution of concentrations and the specific accumulated seasonal load of pollutants.

It is shown that the green areas of the Irkutsk-2 microdistrict, located in the areas of influence of sources of negative impact of industrial sites of the Aircraft Factory (Komsomolsky Park, the square at the intersection of Muravyova Street and Sibirskie Partizan), due to the higher density of trees, are natural filters and, accordingly, accumulators of gas and dust flows, increasing the concentration of pollutants within their territories. At the same time, they themselves are not sources of pollution.

Based on the results of the analysis of various types of cartographic materials, it becomes obvious that when assessing snow cover pollution, it is necessary to consider all the characteristics of pollution: the concentration of pollutants in the sample, the daily specific load, and the seasonal accumulated specific load. Only a comparison and analysis of all these characteristics allows us to obtain an objective picture of the distribution and pollution from the identified sources.