Assessing Air Pollution and Determining the Composition of Airborne Dust in Urbanized Areas: Granulometric Characteristics

Abstract

The article focuses on the problem of atmospheric pollution in urban areas caused by particulate matter, which is a problem for most industrial cities. The work aims to assess air pollution by particulate matter PM₁₀ and PM_2.5; determine the composition of airborne dust in a zone free of any industrial activity; obtain statistical characteristics of dust distribution in the atmospheric air of urbanized areas according to granulometric characteristics. The issues of PM₁₀ and PM_2.5 presence in the atmospheric air of urban and industrial centers in major European cities were analyzed. The degree of air pollution by PM₁₀ and PM_2.5 in the autumn-winter season 2020–2021 in Chelyabinsk city was assessed by gravimetry, considering the air quality standards valid in Russia and the European Union. It was found that the average concentration of particulate matter in the air of the urbanized areas of Chelyabinsk in the six months of the autumn-winter period 2020–2021 was 83 µg/m³ and exceeded the MPC (maximum permissible concentration) 2.1 times. The average value of the concentration of fine dust fractions for six months of the study period was 67 µg/m³, exceeding the MPC by 2.7 times. The obtained results indicate that there is a big problem of pollution, therefore it is important to apply the necessary actions to restore the state of air quality standards, which do not cause health risks to the population exposed to ultrafine particulate matter.

1. Introduction

Atmospheric particulate matter (PM) pollution is a pressing issue in most industrial cities [1,2]. Urban air pollution sources include emissions from the municipal, industrial, and transportation sectors. Numerous epidemiological studies have shown that exposure to air pollution containing fine dust particles with an aerodynamic diameter of fewer than 2.5 μm may present a risk to human health. Thus, a continued increase in vehicle traffic intensity on roads is closely associated with increased human exposure to the adverse effects of dust aerosols, including its carbon fraction [3]. This fact explains why the disease incidence due to dust pollution has not been reduced or even increased despite the significant reduction in dust emissions from industrial sources during the last quarter of a century [4]. Global environmental threats undoubtedly include dust pollutants. Air conditions that facilitate pollution in large areas due to transboundary extent represent a threat to the health of the affected population, which adds importance to the research done [5].

Particulates in the air are a complex mixture of solid, liquid, and gaseous phases that may remain in the atmosphere in a dispersed state for extended timeframes due to their high dispersibility. As part of the health risk assessment, the relevant parameter for PM is generally classified according to the particle’s aerodynamic diameter. According to air quality monitoring in urban areas, there are two main types of dust in the Russian Federation and Europe. These are PM₁₀ (coarsely dispersed particles) standing for coarse dust particles with an aerodynamic particle diameter smaller than 10 µm, and PM_2.5 (ultrafine particles), standing for the fine dust particles with an aerodynamic diameter smaller than 2.5 µm. In cities, sources of dust in gaseous air pollutants include anthropogenic emissions from housing and public services, industry, and transportation. As numerous studies show, increasing the concentration of fine dust in the air with aerodynamic particle diameter up to 2 µm is dangerous for the health of urban dwellers [6,7].

To prevent an increase in air pollution levels in unfavorable weather conditions for the dispersion of harmful substances, the use of a mathematical apparatus to model and predict these conditions is necessary. Forecasts of adverse weather conditions can cover the city as a whole, source groups, and particular sources. Fine aerosols, composed of particles smaller than 2.5 µm in diameter, appear in the atmosphere as a product of fuel oxidation. These mixtures form smog and contain sulfur dioxide (SO₂), nitrogen oxides (NOx), ammonia (NH₃), volatile organic compounds (VOCs), and water [8]. This fraction contains the largest group of chemicals known to be carcinogenic, mutagenic, and cytotoxic, including polycyclic aromatic hydrocarbons (PAHs), among others [5,9]. Since the second half of the last century, environmental epidemiological studies have highlighted the significant impact of air quality on public health. Health effects relate mainly to all respiratory and cardiovascular diseases associated with increased disease incidence and reduced life expectancy [10,11].

Studies conducted in winter 2013–2014 in various European countries revealed elevated concentrations of PM₁₀ particles in densely populated urban areas [12]. In the Russian Federation, the level of atmospheric air pollution by particulate matter is regulated by the Russian Federation Government Decree No. 1316-r of 8 July 2015, “On approval of the list of pollutants, for which state regulatory measures in the area of environmental protection are applied (as amended and complemented)” [11,12,13].

The most industrialized and urbanized zone in Europe is Silesia and the agglomeration of Upper Silesia in Poland, emitting 21.4% of dust and 20% of gas pollutants into the atmosphere [13,14]. Ecological balance disruption in this area has led to high levels of suspended dust over the years. In 2010, the mean annual concentrations of PM₁₀ and PM_2.5 were among the highest in any agglomeration of Poland, amounting to 50.5 µg/m³ and 42.5 µg/m³, respectively [15].

Since 2008, Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008, on Ambient Air Quality and Cleaner Air for Europe (the “CAFE” Directive) [16] has come into force, being an essential legislative text in Europe. In 2004, trials in tunnels allowed concluding that coal accounted for the majority of the dust collected in this zone. Therefore, it is evident that vehicle emissions would typically increase the concentration of carbon in the air, especially elemental carbon. This phenomenon is already well studied and documented for different dust fractions in other areas of the world [17,18].

Forecasts of urban air pollution should be drafted for each season of the year and each half of the day separately. With a rolling schedule of air sampling, samples are taken at 7, 10 and 13 h in the first half of the day and at 15, 18, and 21 h in the second half. For triple sampling, samples are taken at 7 am and 1 pm in the first half of the day and 3 pm and 7 pm in the second half. For the first half of the day, weather forecasts are taken for 6 h, and radio probe data for 3 h. For the second half of the day, weather parameters are considered predictors for the 15 h period. The operational forecast of air pollution is intended to reduce emissions of harmful substances into the air in the short term during adverse weather conditions [19,20]. If necessary, two types of forecasts of atmospheric air pollution in the city can be made: preliminary (for the day ahead) and precise (for 6–8 h ahead, including morning for the current day, afternoon, evening, and night) [21,22]. Differences in levels of PM pollution from natural and anthropogenic sources on a smaller scale and with different parameters are identified and qualified to understand better the nature of their distribution and impact on the environment and human health [23].

This work aims to evaluate air pollution by PM₁₀ and PM_2.5, determine air dust content in a zone free from any industrial activity during the autumn-winter period from October 2020 till March 2021, and obtain statistical characteristics of dust distribution in the atmospheric air of urbanized territories by granulometry.

2. Materials and Methods

2.1. City Features

Chelyabinsk was selected as a typical industrial city in Russia. The Chelyabinsk industry concentrates on metallurgy, machine construction, coal mining, chemical industry, and electricity generation in thermal power plants. These businesses contribute to air pollution with some substances, including particulates from the ultrafine dust fraction.

2.2. Air Sampling Parameters

Air sampling was carried out at 12-h intervals, from 9:00 to 21:00 and from 21:00 to 9:00. The surveys were conducted in the autumn-winter period from October 2020 to March 2021. Information on temperature, relative humidity, and wind speed was derived from the Hydrometeorological Research Center of Russian Federation (Hydrometcentre) data. During the air sampling period, the microclimatic conditions were typical for the city. The concentration of particulate matter in the air was determined by gravimetry using a mass of filter dust samples. All concurrent results were averaged, followed by an estimation of the standard error.

2.3. Measuring Station, Air Sampling Technique

The dust sampling station was located in the southwestern part of Chelyabinsk (point coordinates: 50.279° N, 19.120° E). The PM₁₀ and PM_2.5 suspended dust sampling station was located in the southwestern part of Chelyabinsk (point coordinates: 55°09′00.00″ N, 61°24′00.00″ E). A link to a georeferenced map: https://www.google.com/maps/place/55%C2%B009’00.0%22N+61%C2%B024’00.0%22E/@55.150003,61.3978113,17z/data=!3m1!4b1!4m5!3m4!1s0x0:0x212811f61c00d32a!8m2!3d55.15!4d61.4 (accessed on 18 October 2022).

Measurements were taken according to the criteria specified in the decree of the Minister of Environment on the assessment of substances in the environment [18]. For air sampling, Harvard low-flow pumps equipped with PM₁₀ and PM_2.5 aspiration heads (manufactured by Air Diagnostic and Engineering Inc., Naples, FL, USA) were used [19]. The aspiration head design allows collecting particles with an aerodynamic diameter of 10 and 2.5 μm with 50% efficiency. Dust samples were collected continuously (daily) at a constant airflow rate of 0.009 m³/min. Before and after the measurement, the conformity of the airflow was checked with a calibrated rotameter of type TG06 (VEB Prüfgeräte-Werk Medinge, Berlin, Germany).

2.4. Conditioning and Gravimetric Analysis of Filters

PTFE (fluorinated hydrocarbon) coated glass filters with a pore diameter of 2 µm (produced by SKC Inc., Eighty Four, PA, USA) were used for air sampling. The material from which they were manufactured is the complete chemical inertia compared to the compounds contained in the filtered air and the high efficiency of particulate retention. Filter conditioning, before and after sampling, and air sampling were conducted under low humidity conditions of 45% and 22 °C. The filters were placed in moisture absorbers filled with anhydrous calcium chloride (CaCl₂) with high hygroscopic properties for a minimum of 24 h. The prepared specimens were subsequently weighed. The mass of clean filters and selected air was determined using analytical scales of Sartorius-Genius ME 215S brand (manufactured by Sartorius AG, Göttingen, Germany) with a weighing accuracy of 10 µg. The scales provided high accuracy in determining the mass using the isoCAL automatic calibration system and electrostatic discharge system (air deionization function). The dust concentration expressed in µg/m³ was determined as the ratio of the dust mass collected on the filter to the volume of drawn-in air.

2.5. Statistical Analysis

Statistical analysis of the variables was undertaken using Statistica for Windows, version 7.1. Major statistical indicators have been identified. The arithmetical, minimum, maximum, median, and quartile averages were calculated [24]. The Shapiro-Wilk test was used to determine the type of distribution of particulate matter concentration in urbanized areas in selected months of the year. When comparing the statistical relationship between variables during the study period, Pearson’s χ² criterion was used. Differences were considered statistically significant at p ≤ 0.05.

2.6. Mathematical Modeling of Particulate Matter Dispersion in the Air of Urbanized Areas

The primary direction of the impurity distribution study is to model the dispersion of pollutants in the environment according to the atmospheric diffusion theory using the turbulent diffusion Equation (1). It enables studying the distribution of impurities from sources of different types to different environmental features.

In general, the air pollution forecasting problem can be described mathematically using a differential equation under some initial conditions and limitations:

$$\frac{\partial C}{\partial t}+w_x\frac{\partial C}{\partial x}+w_e\frac{\partial C}{\partial y}+w_z\frac{\partial C}{\partial z}=D_x\frac{{\partial }^{2}C}{\partial x^2}+D_y\frac{{\partial }^{2}C}{\partial y^2}+D_z\frac{{\partial }^{2}C}{\partial z^2}-kC$$

(1)

where t is time; x, y, z are coordinates; w_x, w_y, w_z are components of the average impurity movement rate; D_x, D_y, D_z are components of the exchange coefficient; k is the coefficient determining the concentration change due to impurity conversion. The reaction rate constant is a first-order reaction on the condition that the impurity degrades. If a complex chemical reaction involving pollutants takes place, the final summand will be another entry.

When it comes to solving practical problems, the form of the equation is more uncomplicated. If the x-axis is oriented in the direction of the average wind speed, the amplitude of the velocity projected on the y-axis is zero (w_y = 0).

Vertical motions in the atmosphere on a homogeneous horizontal surface are small, so w_z = 0 can be assumed if the impurity is light and has no intrinsic motion velocity. If a heavy impurity is considered, gradually deposited in the atmosphere by gravitational forces, then w_z is the deposition velocity entering the equation with the minus sign.

Under the windy conditions, the term with D_x (spread along the x-axis) can be neglected since the diffusive flux of impurity in this direction is much smaller than the convective one.

Subsequent changes in atmospheric concentrations are generally quasi-stationary and can therefore be regarded as:

$$\frac{\partial C}{\partial t}=0$$

(2)

Hence, the equation can be reduced to the form:

$$D_x\frac{{\partial }^{2}C}{\partial x^2}+D_y\frac{{\partial }^{2}C}{\partial y^2}+D_z\frac{{\partial }^{2}C}{\partial z^2}-w_x\frac{\partial C}{\partial x}-kC=0$$

(3)

in the case of light impurities and heavy impurities:

$$D_x\frac{{\partial }^{2}C}{\partial x^2}+D_y\frac{{\partial }^{2}C}{\partial y^2}+D_z\frac{{\partial }^{2}C}{\partial z^2}-w_x\frac{\partial C}{\partial x}-w_z\frac{\partial C}{\partial z}-kC=0$$

(4)

Considering an inert impurity (for a substance that does not undergo the transformation k = 0), it follows:

$$D_y\frac{{\partial }^{2}C}{\partial y^2}+D_z\frac{{\partial }^{2}C}{\partial z^2}-w_x\frac{\partial C}{\partial x}=0$$

(5)

When forecasting air pollution, the primary objective is to determine the expected concentrations in the soil layer at a height relative to the soil surface h = 1.5–2 m. As studies have shown, in the near-ground atmospheric layer up to z = h, the turbulent diffusion coefficient increases in proportion to height D ~ z, and the velocity is a logarithmic function of height w_x~ ln (z). At z = 0 (at the soil surface level), the molecular diffusion coefficient of air can be approximately taken as the limit D value (z = D). The analytic calculation of the convective diffusion can be written for the case when w_x and D are given by power functions on z (w_x = w_0x · zn; D = D_zzl) for light conservative admixture (w_z = w_y = 0, k = 0).

Ground concentration (at z = 0):

$$C=\frac{M}{2\left(n-1\right)D_z\sqrt{\pi D{x}^3}}\mathit{exp}\left(\frac{w_x{H}^{1+n}}{{\left(1+n\right)}^3{D}_{z}x}-\frac{y^2}{4Dx}\right)$$

(6)

where M is the emission of the substance from the source per unit time mg/s; H is a height of the emission source, m.

A feature of the ground C-concentration distribution along the x-axis is the presence of its maximum (C_max) at the distance x_max from the source.

To calculate the distribution of particle concentrations in air as a function of particle diameter, the mass of particles will be represented as $M=\frac{\pi d^3}{6}\rho$.

Then (6) will take the form of:

$$C=\frac{\pi d^3\rho }{12\left(n-1\right)D_z\sqrt{\pi D{x}^3}}\mathit{exp}\left(\frac{w_x{H}^{1+n}}{{\left(1+n\right)}^3{D}_{z}x}-\frac{y^2}{4Dx}\right)$$

(7)

3. Results

The urgent problems of the Chelyabinsk region for several decades have included the metallurgical industry, machine building, power generation, disposal, and recycling of various types of waste. The ecology and the natural environment of the Chelyabinsk region are considered the most unfavorable among the regions of Russia. Atmospheric air, soil, and water in large industrial centers often contain large amounts of toxic substances, the concentration of which exceeds the maximum allowable. Environmental problems of the Chelyabinsk region will always be at the forefront of all crisis situations in the region, so it is necessary to rethink the attitude and approach to solving the problem.

The study found the distribution of daily concentrations of PM₁₀ and PM_2.5 in Chelyabinsk city over selected months in 2020–2021 (Figure 1 and Figure 2).

The RF regulatory documents specifying permissible levels of certain substances in the air (Government of the Russian Federation, 2015), taking into account the requirements of the MEP, determine two levels of PM₁₀ dust. These are 50 µg/m³ as averaged over 24 h and 40 µg/m³ over a calendar year on average (

Table 1. Statistical characteristic of daily dust concentrations of PM₁₀ and PM_2.5 (μg/m³) in Chelyabinsk city between 1 October 2020, and 31 March 2021.

	N	PM10					PM2.5
Experiment Date		$\overline{x}$	>50	Min	Max	s	$\overline{x}$	>50	Min	Max	s
October	31	70	22	31	162	31	53	29	22	119	24
November	30	56	15	19	148	31	41	20	11	81	21
December	31	126	24	21	318	81	105	27	20	229	57
January	31	81	20	31	180	44	71	31	28	161	37
February	28	82	21	28	174	36	67	26	22	150	33
March	31	80	24	31	224	40	63	30	25	182	31

($\overline{x}$ —mean value, >50—number of results above 50 μg/m³, s—standard deviation).

). For both PM₁₀ and PM_2.5, statistically significant differences (p ≤ 0.05) were recorded between the values of atmospheric dust particle concentrations in urbanized areas of Chelyabinsk obtained in autumn (October–November) and winter (December–March) months. The highest concentrations of PM₁₀ fractions were observed in December, with the concentration ranging between 22 and 319 µg/m³ (115 µg/m³, on average). From January to February, PM₁₀ dust concentrations were lower. However, the daily variation in dust concentrations was large relative to the recommended allowable values, and the median values were 85 µg/m³ and 106 µg/m³, respectively. The lowest average atmospheric dust concentrations (median 70 µg/m³ and 56 µg/m³) and the lowest maximum values (162 µg/m³ and 149 µg/m³) were observed in October. During the period analyzed, there were 126 days (70% of the study period) when the prescriptive value for the 24-h averaging period was exceeded. However, according to the methodological recommendations, the frequency of exceedances for the whole calendar year cannot exceed 35 times (Table 1). Moreover, the alarming level of the substance concentration (200 µg/m³) as the threshold value for informing the population about the risk of adverse health effects for three consecutive days was exceeded 6-fold [25].

For six months of the reviewed period, the average value of particulate matter concentration in the air of urbanized Chelyabinsk city areas was 83 µg/m³, exceeding the recommended level by 2.1 times. This specific value of permissible PM_2.5 concentration for a 24-averaging period of one hour is different in the Polish legislation. According to the CAFE Directive, the average limit value of particulate matter concentration in the air has been set at 25 µg/m³ per year [14]. The highest PM_2.5 fine dust concentration level was recorded in December, ranging between 20–230 µg/m³ (97 µg/m³, on average). In other winter months, the values were as follows: in January, the average concentration was 55 µg/m³, and the concentration range was 28–161 µg/m³; in February, the average concentration was 71 µg/m 3, and the concentration range was 22–151 µg/m³, and in March, the average concentration was 55 µg/m³, and the concentration range was 25–182 µg/m³. For the autumn months from October to November, generally lower dust concentrations were recorded. Median concentrations were 47 µg/m³ (concentration range: 22–119 µg/m³) in October and 43 µg/m³ (concentration range: 11–82 µg/m³) in November. Statistical analysis of air pollution with fine PM_2.5 showed that during 164 days of the analyzed period, there were splashes in concentrations above 25 µg/m³, which is up to 90% over the entire measurement period. The average concentration value for six months of the study period was 67 µg/m³, exceeding the recommended permissible level by 2.7 times.

Table 2. Statistical characteristics of the PM_2.5 to PM₁₀ mass ratio in Chelyabinsk in the autumn-winter season 2020–2021.

Experiment Date	PM10	PM2.5	PM2.5/PM10
October	69.41	46.14	0.66
November	60.09	41.67	0.69
December	41.10	96.58	2.35
January	115.47	55.72	0.48
February	70.02	70.41	1.01
March	69.40	53.48	0.77

shows the proportion of PM_2.5 dust in total particulate matter compared to PM₁₀ in particular months. The average PM₁₀ to PM_2.5 ratio over the entire study period was 0.81 (from 0.75 in November to 0.88 in January). The frequency of a factor greater than 0.6 occurred in over 92% of days within the study period (Figure 2).

The results of estimating PM_2.5 and PM₁₀ concentration distributions from a single point source can be illustrated graphically (Figure 3).

Figure 3 shows the percentage content dependence of dust particles D (%) for PM_2.5 and PM₁₀ in the air of urban areas on the particle diameter. The following statistical parameters were calculated for the presented data: Pearson criterion χ² = 1 × 10⁻⁵, the standard deviation is 0.2…0.001, and the statistical significance of the results is p < 0.005.

4. Discussion

The city of Chelyabinsk presents atmospheric pollution conditions typical of urban areas. Air pollution due to anthropogenic emissions is associated with housing and utilities, industry, and transportation. The area is subject to advection of pollutants from the neighboring highly industrial centers. Chelyabinsk is among the cities that pose major environmental risks due to emissions of a wide range of pollutants [13]. As a consequence, the air quality in industrial areas of the city deteriorates. This is compounded by the increased use of solid fuels in local power stations and home heating during the heating season. A study of road dust near metallurgical plants in Chelyabinsk using inductively coupled plasma mass spectroscopy (ICP-MS) showed the presence of such substances like As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Sr, and Zn. Besides, As, Hg, and Sb were indicators of emissions from coal-fired electricity plants. It has also been found that the risk of cancer disease in the Chelyabinsk population due to exposure to As, Cd, Cr, and Pb is acceptable or tolerable [26]. Dust testing of PM₁₀ and PM_2.5 daily concentrations in specific months of the autumn-winter measuring season in the air of urbanized areas showed no significant differences. The latest report on air quality assessment in zones and urban agglomerations until 2020 also confirmed these results, prepared under the State Environmental Monitoring and Measurement of air pollutant concentrations. The classification of zones based on PM₁₀ dust concentration showed that 91% have the lowest C-category due to the frequency of exceeding the PM₁₀ daily concentration values [23]. The same goes for the countries of Europe. Modern literature sources do not provide data on the environmental situation in Silesia Province (Poland), where significant environmental pressure specifies a high level of atmospheric air pollution with suspended dust particles. This is reflected in the fact that all parts of the province are included in category C since the average annual and daily norms for PM₁₀ dust are exceeded. Relevant criteria for the concentration of harmful substances in the air were established by the Regulations of the Minister of the Environment on 24 August 2012 [20] (Figure 4).

Meeting air quality standards, especially in winter, is a challenge for many European cities. The results obtained in the study are consistent with the studies of other authors [24]. Multicentre studies conducted in five Central and Eastern European countries (Poland, Czech Republic, Bulgaria, Romania, and Slovakia) showed that average concentration of suspended dust PM₁₀ and PM_2.5 measured in winter is twice as high as in summer. The highest pollution level with fine PM_2.5 dust was observed in December (mean concentration: 97 µg/m³, concentration range: 20–230 µg/m³). The distribution in the remaining winter months was as follows: in January (average concentration: 55 µg/m³, concentration range: 28–161 µg/m³), February (average concentration: 71 µg/m³, concentration range: 22–151 µg/m³), and March (average concentration: 55 µg/m³, value range 25–182 µg/m³). Lower dust concentrations generally accompanied autumn months (October-November). The average concentration 47 µg/m³ (concentration range: 22–119 µg/m³) in October and 43 µg/m³ (concentration range: 11–82 µg/m³) in November. Statistical analysis of air pollution by PM_2.5 fine particles showed that during 164 days of the analyzed period, concentrations exceeded 25 µg/m³. That comprised 90% of the results during the entire measurement period (Table 2). During the six-month study period, the concentration was 67 µg/m³, exceeding the MPC values by 2.7 times. In contrast, other authors obtained lower values of suspended dust concentration and the same values of PM₁₀, in particular Diapouli et al. [25], Cesari et al. [27], and Stafoggia et al. [28] in their studies note that the concentration of carbon particles increases significantly during the cold period. These works are based on studies carried out in Italy, Greece, Poland, and other European countries. According to the literature data on PM₁₀ concentrations in winter, the most polluted cities in Europe are Katowice and Krakow in Poland (63 µg/m³ and 52 µg/m³, respectively), Teplice and Prague in the Czech Republic (56 µg/m³ and 50 µg/m³, respectively), and Budapest, Hungary (54 µg/m³). That was likely due to a reduced influence from anthropogenic emissions. In the urban environment, coarse and fine dust particles exist in the atmosphere. However, their proportions vary according to the season and the main sources of ultrafine dust emissions. For Europe as a whole, the average contribution of the PM_2.5 fraction to PM₁₀ dust is 0.65 (overall range is 0.42 to 0.82) [29]. In addition, Japanese scientists, in particular Wada [30] and colleagues, in their scientific works also confirm the increase of pollutants in the air during the winter period. Thus, adjusted for toxic equivalence factors, the concentration of total PAHs determined in the area of Nagasaki City was 2.33 ng/m³. Concentrations of total PAHs and nitrated-PAHs were higher in winter than in summer [30].

Due to high concentrations of particulate matter in the air of Chelyabinsk city, the high values of PM₁₀ to PM_2.5 ratio obtained in this work correlate with studies conducted by other authors on the structure of atmospheric aerosols in various European cities. The morbidity of urban residents and a high share of the dust fraction of PM_2.5 compared to PM₁₀ is considered typical of the winter season since it is an indicator of anthropogenic emissions growth, particularly in areas where low emissions predominate [31,32]. Special weather conditions resulting from unfavorable ventilation conditions can make it a natural and frequent phenomenon, particularly during the winter inversion of extremely high concentrations of particles, defined as “smog elements”. In Zabrze on 29 January 2016, the industrial sector’s emissions of ultrafine particulate matter were 778 µg/m³, exceeding the MPC level by 15 times. In Krakow on 25 January 2006, the concentration of PM₁₀ was 600 µg/m³ and exceeded the accepted permissible level by 12 times [26].

Also, data obtained by Onat et al. [32] in two urban areas of Istanbul (Yenibosna and Göztepe) indicate that the mean total particle concentrations and standard deviations were respectively: 67.7 ± 17.0 µg/m³ and 82.1 ± 21.2 µg/m³. The higher content of metals in fine and medium-sized PM indicates that the most significant sources of pollution are anthropogenic sources, namely transport, road dust, coal and fuel oil combustion and industrial emissions [32].

Similar values are presented in the works of Isildak [33], according to which in Tokat Province in Turkey, the initial results of chemical analysis showed that the values of concentrations of heavy metals in the observed air particles exceeded the recommended limits of the World Health Organization (WHO). Thus, the concentration of particulate matter was up to 52.43 µg/m³ in the sampling area, this amount of pollutants emitted into the atmosphere is associated with heating, industrial emissions, as well as the general pollution of the city center of Tokat [33].

According to the data of Krupnova et al. [26] in Chelyabinsk, the most common smog cases were recorded in December, when the maximum concentration of solid particles exceeded the allowable concentration by more than 6 times. The carcinogenic effect of dust is due to the content of heavy metals, PAHs, aromatic hydrocarbons, and their derivatives, included in the so-called “active dust” concept. Numerous authors note the biologically active properties of organic constituents of suspended particulate matter [34]. Winter suspended dust is considered to have a mutagenic effect of 1.7 to 2.5 times compared with summer dust. The strong mutagenic effect of dust is undoubtedly influenced by the presence of benzo[a]pyrene in its composition, which is 4–6 times higher than MPC values in the winter period [25]. This fact is confirmed by studies of other authors [24,25] who obtained high values of mutagenicity and cytotoxicity factors of dust taken for tests in the winter season in different cities of Poland (Sosnowiec, Wroclaw) per 1 m³ of air. Research in environmental epidemiology confirms a high degree of air quality influence on the emergence of health problems in the cities of Silesia (Poland). Stafoggia et al. [28] and Parascandola [35] note that high incidence of lung cancer was observed among women and men in Sosnowiec, Chorzów, Ruda Śląska, Zabrze, Bytom, Dąbrowa Górnicza and Powiat Ochota. Due to poor air quality in Chelyabinsk, a further increase in the incidence of lung disease is expected in people who remain in prolonged contact with elevated dust concentrations. Similarly, there is a parallel between high ultrafine concentrations and the risk of lung cancer. These diseases are often recorded when a person is exposed to extreme particulate levels for up to four years less than other contaminants. Such a scenario is highly possible. This is confirmed by an increase in disease incidence in the population exposed to this type of pollution. Also, data obtained by Arden Pope III and Docker [36] provide compelling evidence that exposure to fine particulate air pollution has adverse effects on cardiopulmonary health; these results have important implications for science, medicine, and public health. The result may be a synergistic effect of a high concentration of airborne dust associated with the high toxicity of the accompanying pollutants [27].

The results of research by scientists should be updated to develop new models for estimating the concentration of air pollutants with a high spatial and temporal resolution, which will allow documenting the adverse short-term impact on mortality and morbidity at very low concentrations and developing methods of reducing air pollution to standards.

5. Conclusions

Analysis of the atmospheric air pollution by suspended PM₁₀ and PM_2.5 evicted an unfavorable environmental situation in Chelyabinsk city due to the emission of ultrafine solid particles in the air of urbanized territories. The state of the atmospheric air in Chelyabinsk was monitored during the measuring period.

It was found that the average concentration of particulate matter in the air of Chelyabinsk’s urbanized areas in the six months of the autumn-winter period 2020–2021 was 83 µg/m³ and exceeded the recommended level 2.1 times. The average concentration of fine dust fractions during the six months of the study period was 67 µg/m³, exceeding the recommended permissible level by 2.7 times.

Most of the mass of solid particles in the air of Chelyabinsk proves a high level of anthropogenic emissions associated with the burning of fuel at thermal power plants and metallurgical enterprises, in addition, the sources of solid particles are various combustion processes, heating of premises, during electricity generation, during work of internal combustion engines in cars, etc. Thus, as a result, in the territory of Chelyabinsk, cases of smog occur most often in December, with the maximum concentration of solid particles exceeding the permissible level by more than 6 times. Even more importantly, there is a possible risk of increasing morbidity.

It is required to apply measures to restore the state of air quality that poses no risk to the health of the population exposed to ultrafine particles. Further research might analyze modern practices of urbanized cities with the aim of reducing air pollution.