Levels Of Atmospheric Pollution Research Articles

Assessing the impact of meteorological factors and air pollution on respiratory disease mortality rates: a random forest model analysis (2017-2021).

Air pollution poses a significant threat to the health of all living beings on our planet. It has been scientifically established as a crucial factor affecting mortality rates, respiratory illnesses, mental well-being, and overall health. This study aimed to investigate the impact of air pollution and meteorological factors on respiratory disease mortality rates in Mashhad in 2017-2021 using a Random Forest (RF) model. At first, the daily statistics of meteorological parameters (pressure, humidity, temperature, solar radiation) during 2017-2021 were collected. The information related to pollutants pollutants such as PM2.5 (which is defined as particulate matter with less than 2.5 micrometer diameter and potentially harmful to humans), PM10 (Particles with a diameter of 10 micrometers or less that can negatively impact both human health and environmental conditions.), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) was collected. the mortality statistics from respiratory diseases were collected from the Health system registaration (Sina). Then we used the RF regression model in Excel and Python software to investigate the interaction between the mentioned variables. The escalating trend of air pollution in Mashhad has led to an expected increase in respiratory-related hospitalizations. This necessitates urgent air pollution control measures. Concurrently, the study of pollutants and climatic elements, as substantiated by global epidemiological studies, is crucial. In Mashhad, the second most polluted city in Iran, climatic factors like humidity, sunshine duration, temperature, pressure, and sunlight intensity exacerbate atmospheric pollution levels, impacting human health and ecosystems. The R2, RSME, and MAE of RF model are 0.73, 2.52, and 2 which indicate that the model has successfully identified the relationship between input variables and the target variable, and it will exhibit high accuracy in predictions. In this study, the most influential factor was identified when the Variance Inflation (VI) factor reached a value of 0.548. This indicates a strong correlation between this factor and the death rate of patients during the specified period. Furthermore, we analyzed by excluding the day and month plans from our model. The results showed that the factor with the highest coefficient in the executive model was related to pressure, with a VI value of 0.049. This suggests that pressure plays a significant role in our model and has a substantial effect on the death rate of patients. In the study of various pollutants, it was found that PM10 had the most significant impact on the mortality rate of patients with respiratory conditions, with a VI of 0.039. Following PM10, the pollutants with the next highest coefficients of importance were NO2 (VI = 0.034), SO2 (VI = 0.033), PM2.5 (VI = 0.029), and CO (VI = 0.025), respectively. Furthermore, the study observed a notable increase in the mortality rate of respiratory patients over time. Specifically, for every five days, the death rate increased by 35.5%. Indeed, climate change and air pollution significantly contribute to the mortality rate from respiratory diseases. Therefore, it is crucial for individuals, particularly those with respiratory conditions, to heed meteorological warnings.

A systematic scrutiny of artificial intelligence-based air pollution prediction techniques, challenges, and viable solutions

Air is an essential human necessity, and inhaling filthy air poses a significant health risk. One of the most severe hazards to people’s health is air pollution, and appropriate precautions should be taken to monitor and anticipate its quality in advance. Among all the countries, the air quality in India is decreasing daily, which is a matter of concern to the health department. Many studies use machine learning and Deep learning methods to predict atmospheric pollutant levels, prioritizing accuracy over interpretability. Many research studies confuse researchers and readers about how to proceed with further research. This paper aims to give every detail of the considered air pollutants and brief about the techniques used, their advantages, and challenges faced during pollutant prediction, which leads to a better understanding of the techniques before starting any research related to air pollutant prediction. This paper has given numerous prospective questions on air pollution that piqued the study’s interest. This study discussed various machine and deep learning methods and optimization techniques. Despite all the discussed machine learning and deep learning techniques, the paper concluded that more datasets, better learning techniques, and a variety of suggestions would enhance interpretability while maintaining high accuracy for air pollution prediction. The purpose of this review is also to reveal how a family of neural network algorithms has helped researchers across the globe to predict air pollutant(s).

Study of patterns of PM2.5 and PM10 changes in the atmospheric air of Ivano-Frankivsk region

The purpose of this research is to analyse the temporal patterns of changes in concentrations of dust particles – aerosols, regression modeling of the interdependence of PM2.5 and PM10 at the level of instantaneous, average hourly, average daily and average weekly concentrations, and assessment of the impact of the anthropogenic component of dust pollution of atmospheric air in the Ivano-Frankivsk region on regularities of the temporal distribution of these shares.The database for the study included measurements of the concentration of PM10, PM2.5 every hour at four Ecocity public monitoring stations: in the central part of the city of Ivano-Frankivsk, in the village of Bovshiv within the influence of the Burshtyn TPP, in the village of Broshniv-Osada within the influence of the woodworking enterprise "SVISS KRONO" and within the recreational territory of the village of Mykulychyn, Nadvirnyan district. The general regularity of the temporal distribution of PM10, PM2.5 was established for all posts for daily fluctuations – the highest concentrations are observed at night, the lowest – during the period of maximum daily temperatures. It has been proven by actual data that the greater the level of atmospheric air pollution (the greater the anthropogenic component of PM), the higher the daily concentrations of PM10, PM2.5 and the more often the one-time standards of solid suspended particles are exceeded.According to the data of monitoring stations from the territories with different anthropogenic influence, functional dependences of PM2.5 content on PM10 content were obtained for instantaneous values, hourly average values, daily average values, and weekly average values. The scientific novelty of the conducted research consists in the establishment of identical functional interdependence of temporal changes in concentrations of PM2.5 and PM10 dust particles within a conditionally clean area and within the limits of the influence of stationary sources of pollution with a high level of direct regression dependence and a coefficient of determination greater than 0.9 in all cases. This allows us to conclude that the temporal patterns of changes in both PM2.5 and PM10 will not differ in clean and polluted air conditions for the Ivano-Frankivsk region. In conditions of incomplete data on the temporal distribution of the concentration of PM10, the obtained equations can be used to forecast the temporal distribution of the concentration of PM2.5.

Polycyclic aromatic hydrocarbons (PAHs) in black crusts on stone monuments in Milan: detection, quantification, distributions, and source assessment

In the field of conservation of cultural heritage, one must always consider the environmental conditions in which the works of art are located and the level of atmospheric pollution to which they are exposed, especially in the case of monuments stored outdoors. The present study is focused on the detection and the quantification of polycyclic aromatic hydrocarbons (PAHs) in black crust samples from the Monumental Cemetery of Milan (Italy), and the assessment of their sources through the analysis of the distributions of the different compounds in the samples, together with the use of diagnostic ratios. Six black crust samples taken from funerary monuments were analyzed. Fourteen polycyclic aromatic hydrocarbons were identified (naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, indeno[1,2,3-cd]pyrene) by high-performance liquid chromatography with a diode-array detector (HPLC–DAD), with a total concentration from 0.72 to 3.81 μg/g (mean of 1.87 μg/g). The known carcinogenic benzo[a]pyrene accounted for 5–10% of the total polycyclic aromatic hydrocarbons in the samples analyzed, with concentrations up to 0.20 μg/g. Moreover, the study of the distribution and diagnostic ratios allowed us to confirm that anthropogenic sources such as traffic and the proximity of the train station are the major causes of the degradation of the monuments contained in this Cemetery.

Assessment of the Atmospheric Deposition of Potentially Toxic Elements Using Moss Pleurozium schreberi in an Urban Area: The Perm (Perm Region, Russia) Case Study.

Assessment of air quality in urban areas is very important because pollutants affect both the environment and human health. In Perm (Russia), a moss biomonitoring method was used to assess the level of air pollution. The concentrations of 15 elements in 87 samples of moss Pleurozium schreberi in the city territory were determined using a direct mercury analyzer and an inductively coupled plasma atomic emission spectroscopy. Using factor and correlation analyses, the grouping of elements and their relationship with emission sources were established. The main sources of emissions of potentially toxic elements are the transportation (road and rail), metallurgical, and chemical industries. The level of atmospheric air pollution was assessed by calculating the environmental risk index, pollutant load index, and pollution coefficient. Based on the values of the pollution index, the level of atmospheric air pollution in Perm varies from unpolluted to highly polluted, with moderate environmental risk.

Mapping air quality variations in industrial and agricultural zones: Understanding spatial and temporal patterns of selected air pollutants

With the escalating threat of air pollution on the biota, the need for research on pollutants has become imperative in industrial, urbanized and heavily populated cities. This study aimed to determine the level of major outdoor atmospheric pollutants (PM10, PM2.5, TVOCs, and HCHO) in specific locations including industrial and agricultural zones. Field measurements for this research, spanning 52 locations, were collected in the spring season using a portable instrument, and spatial variation maps were developed using ArcGIS software. The study measured PM10 concentrations ranging from 31 μg/m3 to 267 μg/m3 and PM2.5 concentrations ranging from 27 μg/m3 to 253 μg/m3. PM2.5 levels at most sites exceeded USEPA, WHO, and PEQS standards, while PM10 levels generally met these standards. The highest values of coarse and fine particulate matter were observed in areas dominated by emissions from the textile industry. Furthermore, particulate matter concentrations showed spatial variations, increasing towards the North and East directions. The Total Volatile Organic Compounds (TVOCs) concentrations, ranging from 0 mg/m3 to 4.019 mg/m3, exceeded Hong Kong SAR standards at five locations, thereby elevating health risks for residents in these areas. Similarly, formaldehyde levels, ranging from 0 mg/m3 to 0.754 mg/m3, surpassed the Hong Kong SAR standard at seven locations, indicating a substantial threat of exposure for the local population. In general, air quality at most field sampling sites was registered as UNQUALIFIED but was also observed to be FRESH at a few locations. This research is significant for understanding the levels of major pollutants so that the concerned authorities can take appropriate measures to tackle air pollution by introducing pollution control technologies in industries, switching to renewable energy options, and managing road dust.

Assessment of atmospheric air pollution in Dnipro city as a result of dust entrainment from the ash-disposal areasof Prydniprovsk TPP

Purpose. The purpose of this work is to assess the pollution of atmospheric air in Dnipro city as a result of dust entrainment from the ash-disposal areas of Prydniprovsk TPP. The methods. Assessment of atmospheric air pollution in the city of Dnipro as a result of dust entrainment from the ash-disposal areas of Prydniprovska TPP was carried out as follows: physical and chemical characteristics of the stored fly ash were determined; specific dust entrainment from the surface of dry beaches of ash-disposal areas under the most favorable conditions was determined; mathematical modeling of the spread of atmospheric air pollution of Dnipro city by suspended particles was carried out using UPCAP "ECO Center"program; a comparative assessment of dust entrainment reduction due to the gradual processing of the deposited fly ash was carried out. Findings. Almost 100% of the total mass of ash consists of particles smaller than 80 μm, the content of particles smaller than 10 and 2.5 μm is 27.7 and 8.2%, respectively. The main chemical compounds contained in ash are silicon dioxide, aluminum oxide, iron (III) oxide and carbon. The gross entrainment of substances in the form of suspended fine-grained solid particles from the surface of the dry beaches of the Prydniprovska TPP ash-disposal facilities is 18,654 tons per year. The area of atmospheric air pollution of Dnipro city by suspended particles is about 850 km2 and covers Samarskyi, Sobornyi, partly Industrialnyi and Shevchenkivskyi Districts. As a result of the implementation of a waste-free technology for the processing of fly ash with the utilization of the iron-containing fraction, the area of pollution can be reduced by 13.5 times up to 63 km2, the contamination zone in this case will cover underpopulated part of Samarskyi District of the city of Dnipro. Scientific novelty. A refined dependence of the particle size distribution of the mature Prydniprovsk TPP fly ash particles was determined for the further assessment of potential dust entrainment. For the first time, modeling of the distribution of fine-grained particles of fly ash of the Prydniprovsk TPP in the atmospheric air of the city of Dnipro was carried out, taking into account meteorological conditions, conditions of dust formation and particle size distribution. Practical implementation. The results of the research can contribute to reducing the level of atmospheric air pollution in the city of Dnipro. This will improve the quality of life of the local population and protect the natural environment from negative impacts. Research results can also be a basis for the development and implementation of technological solutions for the waste-free processing of stored fly ash with marketable products obtaining.

Seasonal Variation in Short-Term Ambient Air Pollutants and ST-Elevation Myocardial Infarction Admissions: An Innovative Exploration of Air Pollution’s Health Consequences

Cardiovascular diseases (CVDs) persist as a significant contributor to global morbidity and mortality despite advances in medical technology. Air pollution has emerged as a significant contemporary challenge due to increased energy consumption and rapid economic development. The study utilized multivariable Poisson regression and Distributed Lag Models (DLM) to assess the link between brief exposure to outdoor air pollutants (PM10—particulate matter with a diameter ≤ 10 μm, NO2—nitrogen dioxide, and O3—ozone) and the risk of acute myocardial infarction with ST-segment elevation (STEMI) hospitalization, stratified by season. The research was conducted from January 2019 to December 2021 at the University Hospital in Timisoara, Romania, and daily records were collected for STEMI admissions, atmospheric pollutant levels, and meteorological parameters. The most pronounced impacts were observed with each 10 μg/m3 increase at lag 07 for PM10 during summer, leading to a 2% increase in STEMI admissions, and for NO2 during spring at lag 07, resulting in a 0.9% rise in CVD incidence. Men, middle-aged adults, and older adults exhibited greater susceptibility to elevated NO2 and PM10 concentrations than women and younger individuals. Brief exposure to diverse air pollutants heightens the likelihood of hospitalization due to STEMI, particularly among men and adults over 45. Effective measures must be implemented to mitigate these impacts, especially for vulnerable populations.

INFORMATION SUPPORT IN ENVIRONMENTAL PROTECTION TECHNOLOGIES

The information support in environmental protection technologies includes forecasting and information analysis. The informational component is a necessary tool for assessing the level of environmental impact of the activities of industrial enterprises, with the aim of applying the necessary methods and means of protection. In this study, the information support for a metallurgical enterprise is considered, which is based on forecasting the level of atmospheric air pollution by gas emissions of the enterprise. The analysis of the concentration fields makes it possible to single out the areas of the city that fall into the zone of influence of pollutants depending on the direction and speed of the wind, to compare them with the maximum permissible concentration. The informational component regarding the enterprise's impact on the environment is important for the enterprise itself, from the point of view of adjusting its activities regarding environmental safety. At the same time, the information support is important for people who live directly outside the sanitary zone, but are exposed to harmful factors that spread in the environment according to the state of the atmosphere.

THE POSSIBILITIES OF USING BIG DATA TECHNOLOGIES IN SOLVING PROBLEMS OF PROCESSING DATA ON ATMOSPHERIC AIR POLLUTION

The main objective of the article is to substantiate the possibility of using Big Data technologies in the field of atmospheric air monitoring. In the form of a diagram, a model for processing big data obtained from measuring meteorological gas analysis stations using the PySpark library for further experimental studies is presented. The factors accompanying the use of Big Data in the field of atmospheric air monitoring are derived, and the performance of the Pandas and PySpark libraries is compared. The obtained results will allow us to further rely on the derived factors and use the most optimal data processing technologies to build predictive machine learning models in the field of analyzing the level of atmospheric air pollution. Consistent use of big data and machine learning methods will ensure clean and healthy air for future generations through more effective predictive analytics. This article is valuable for students and specialists in the field of information technology, in particular, in the field of data processing and machine learning.

ASSESSMENT OF THE INFLUENCE OF THE INTENSITY OF TRAFFIC FLOWS ON THE STATE OF THE STREET AND ROAD NETWORK OF THE CITY

The article is devoted to the assessment and forecasting of the level of atmospheric air pollution in street canyons in Kyiv by controlling the parameters of traffic flow. Today, road transport is the main anthropogenic source of environmental pollution. The specificity of air pollution by traffic flows lies in their ground location, close proximity to people's homes, which leads to the accumulation of pollutants near the ground surface - in the breathing zone of people. The article analyzes the main approaches to modeling the dispersion of pollutants in the atmosphere from motor vehicles. It is advisable to assess the level of urban air pollution in homogeneous elements of the urban area - street canyons. Based on the urban street canyons model (OSPM), the level of pollution in the street canyons of the Pechersk district of Kyiv by the main harmful substances contained in car exhaust gases is determined. The critical intensity of traffic flows for each of the street canyons at which the level of pollution by the corresponding harmful substance reaches the maximum permissible value was determined. Thus, the obtained results of the study allow us to quickly predict the level of air pollution in the roadside space of cities and prevent environmentally hazardous situations by controlling the parameters of the traffic flow.

INVINMENTAL PROBLEMS OF REGIONAL ECONOMY OF SOME TERRITORIES OF THE RUSSIAN FEDERATION

The article discusses the most pressing problems of reducing the quality of some components of the environment (natural) in federal districts — macroregions of the Russian Federation, which require their solution. An analysis of the level of atmospheric air pollution by emissions of harmful and polluting substances from stationary sources, based on data from annual state statistical reporting, showed that over the previous 11 years, the minimum volume of emissions was noted in the North Caucasus macroregion, and the maximum in the Siberian macroregion. The next one is the problem of pollution of the seas of the Arctic Ocean with wastewater from Russian rivers flowing into these seas, containing such a substance that pollutes the water basin of the entire planet as microplastic. The largest volume of such polluted waters was noted in the Arkhangelsk region (Northwestern macroregion), Krasnoyarsk region and Tomsk region (Siberian macroregion), and the smallest in the Kostroma region (Central macroregion) and the Republic of Tyva (Siberian macroregion). The problem of preserving and restoring such a component of the natural environment as forests, including in the protected zone of Lake Baikal and the volcanoes of the Kamchatka Peninsula, is debatable. An analysis of plans for the construction of several waste processing complexes and waste processing plants in the North-Western macroregion is aimed at identifying possibilities for solving the problem of a future reduction in the volume of such a component of the natural environment as anthropogenic waste. To solve some problems, the authors propose specific measures.

Cellulose Nanofiber-Based Triboelectric Nanogenerators for Efficient Air Filtration in Harsh Environments.

Advanced portable healthcare devices with high efficiencies, small pressure drops, and high-temperature resistance are urgently desired in harsh environments with high temperatures, high humidities, and high levels of atmospheric pollution. Triboelectric nanogenerators (TENGs), which serve as energy converters in a revolutionary self-powered sensor device, present a sustainable solution for meeting these requirements. In this work, we developed a porous negative triboelectric material by synthesizing ZIF-8 on the surface of a cellulose/graphene oxide aerogel, grafting it with trimethoxy(1H,1H,2H,2H-heptadecafluorodecyl)silane, and adding a negative corona treatment, and it was combined with a positive triboelectric material to create a cellulose nanofiber-based TENG self-powered filter. The devices achieved a balance between a small pressure drop (53 Pa) and high filtration efficiency (98.97%, 99.65%, and 99.93% for PM0.3, PM0.5, and PM1, respectively), demonstrating robust filtration properties at high temperatures and high humidities. Our work provides a new approach for developing self-powered wearable healthcare devices with excellent air filtration properties.

The impact of restriction measures implementation due to COVID-19 on particulate atmospheric pollution in Greek urban areas

In this work, the variation on the levels of suspended particulates, in Greek urban areas, was examined, for the period of the restrictive measures implementation (period 1: March to May 2020 and period 2: November 2020 to January 2021) due to the pandemic caused by the COVID-19 virus. The PM10 and PM2.5 concentrations are measured by the National Air Pollution Monitoring Network of Greece monitored by the Energy/Environment Ministry. In particular, a comparison of the PM10 and PM2.5 concentration levels was made, concerning the above time periods, with the corresponding atmospheric pollution levels during the periods 2001-2009 (period before the Greek economic crisis), 2010-2019 (period during the Greek economic crisis), as well as with the entire time period 2001-2019. The assessment showed a significant reduction in the levels of both PM10 concentrations, which ranged from 8% to 45%, and PM2.5 concentrations, which ranged from 13% to 48%, thus demonstrating the effectiveness of the control measures in improving air quality in Greek urban areas. The above findings show that with appropriate emission control strategies, vital improvements in the air environment of urban areas can be achieved.

Transport ecology in the context of the coronavirus pandemic

The work is devoted to the analysis of the latest data on the study of socio-hygienic and environmental consequences, a pandemic in conditions of a high level of atmospheric air pollution, the effect of solid and gaseous components of exhaust gases from automobiles and industry on human health and the environment.The object of the study is the atmospheric air polluted by the viral infection COVID-19. Action to tackle air pollution is particularly relevant in the wake of the outbreak of the coronavirus pandemic, according to research from the Harvard School of Public Health (USA), which Bellona has already written about, as well as reports from European scientists at the University of Siena School of Medicine (Italy). The dependence of health and mortality rates on air quality is a fact repeatedly confirmed. According to the World Health Organization (WHO), currently 9 out of 10 people in the world breathe polluted air, and this leads to 7 million additional deaths annually. WHO officials say that one third of deaths from stroke, lung cancer and heart disease are due to air pollution: “This death is caused by exposure to fine particulate matter 2.5 microns or less (PM 2.5) in diameter, which leads to the development of cardiovascular, respiratory and oncological diseases".

CLUSTER ANALYSIS OF INDICATORS CHARACTERIZING DECARBONIZATION PROCESSES IN THE REGIONS OF THE RUSSIAN FEDERATION

The article is devoted to the study of decarbonization processes in the Russian Federation based on cluster analysis using machine learning methods. The purpose of the study is to assess decarbonization processes in the subjects and federal districts of the Russian Federation. Materials and methods. The information basis of the study consists of statistical data from Rosstat for the period 2000-2021 for 82 subjects of the Russian Federation, federal districts, the cities of Moscow, St. Petersburg, Sevastopol and the Russian Federation as a whole. In the process of the proposed study, correlation and cluster analysis was carried out ("k-means" methods and determining the median indicators of each cluster). Estimate indicators of the ratio of GRP to the level of atmospheric air pollution and the level of water bodies’ pollution were used as determining indicators. Results. Based on the analysis, 7 clusters were identified, differing from each other by levels of the main aspects of decarbonization. The first cluster includes 5 subjects (brief description – maximum fresh water per capita, minimum emissions per capita, average carbonisation level), the second – 43 subjects (minimum emissions, minimum discharge and minimum carbonisation of GRP by air), the third – 8 subjects (maximum discharge and maximum carbonisation of GRP by water), in the fourth – 22 subjects (minimum of fresh water), in the fifth – 2 subjects (significant maximum of carbonisation by air and maximum positive balance between capture and emissions), in the sixth – 4 subjects (balance of capture and emissions, minimum carbonisation of GRP by water, minimum discharge and maximum emissions) and the seventh cluster included 12 subjects of the Russian Federation (maximum efficiency of water resources use). Cluster analysis has shown that about half of the subjects of the Russian Federation are characterized by minimum of emissions, minimum of discharge and minimum of GRP carbonisation by air. Conclusions. The conducted cluster analysis of decarbonization processes in the subjects of the Russian Federation makes it possible to conclude that most of the subjects are characterized by efficient use of water resources. There are also subjects with opposite extremes in air and water (maximum emissions and minimum use of fresh water per capita and vice versa). In addition, in the aspect of decarbonization of the Russian economy, it can be concluded that water resources per capita in the subjects of the Russian Federation are used more efficiently than air resources.

Changeability of quantitative and quality signs of pollen of Robinia pseudoacacia L. is in the conditions of megalopolis

The work is aimed at spreading the practice of bioindication, in particular palynoindication of atmospheric air quality in the surface layer. It is possible to continue monitoring the state of the environment in Ukraine under the conditions of the destructive impact of military operations only with the use of methodologically and economically accessible approaches. The obtained results provide an opportunity to make scientifically based conclusions about the state of the environment and recommendations for zoning territories according to environmental risks for the population. Assessment of the state of atmospheric air in the surface layer is important for determining the potential consequences for the ecosystem and for assessing the risk to public health. We believe that the most informative are the results of the study of plants of the shrub layer. Their generative part is exposed to the long-term effects of the main components of air pollution in the zone of maximum impact on the respiratory system of people. Cytogenetic testing was carried out on Robinia pseudoacacia plants, which belong to the group of sensitive phytoindicator species. Monitoring was carried out during 2020–2021 at 7 locations of park, forest-park ecosystems and street landscaping in four administrative districts of Kyiv. The analysis of weather and climate conditions, the differences of the studied territories in terms of the level of atmospheric air pollution, the level of anthropogenic load, the intensity of transport connections, as well as the provision of green spaces as the main factor in reducing the impact of the urban environment on the state of life and health of the population is given. It was noted that the pollen sterility index reflects the influence of non-optimal factors of the growing environment on the reproductive potential of R. pseudoacacia. The variability of the morphometric characteristics of dry grains according to the shape index is also a fairly informative indicator of its quality. In particular, a tendency to decrease in the equatorial diameter and a further prolonged decrease in the length of the polar axis during the flowering phase of plants was observed. A significant increase in the proportion of degenerated and hypertrophied grains of R. pseudoacacia was noted in areas with significant influence of a complex of exogenous factors and year conditions. Intensive inhibition of the microsporogenesis process was noted in plants in areas with active traffic. Minimal violations were observed in plants from large park plantations. A certain improvement in the state of the atmospheric air during the lockdown period also contributed to a decrease in the number of morphologically abnormal grains. The results of cytotesting of the sensitivity of R. pseudoacacia pollen to the influence of factors of the growing environment can serve as an important component of the assessment of the quality of the environment and zoning of the territories of the metropolis.

Численное моделирование процессов естественного проветривания карьера при вариации его глубины в условиях инверсионного состояния атмосферы

The research objective is to assess the influence of the background stratification parameter and the depth of an open pit mine on the time of natural ventilation of the mine and the level of atmospheric pollution at the upper side of the pit downwind of blasting operations in conditions of the North. An aerothermodynamic model of the atmosphere was used, in which the equations of dynamics in the approximation of incompressible fluid were supplemented with the heat transfer equation, and the buoyancy and background stratification mechanisms were taken into account. The model was created in a general-purpose COMSOL software package and makes it possible to study aerothermogasodynamics of the atmosphere in its various states. A two-dimensional CFD-model of the open pit atmosphere was tested using the recirculation ventilation process. The background stratification parameter (from 0.0 to +0.025 °С/m with the increment of 0.005 °С/m) and the quarry depth from 300 to 700 m were variated. The wind velocity of 1 m/s at the upper side of the pit, the initial location of the dust and gas cloud (in the center of the pit near its floor) and the slope angle of the pit wall of 45° were recorded. A significant increase in the time of natural ventilation of the open pit is demonstrated at intensifying inversion of the atmosphere. Two formation types of the maximum pollution area with the increasing pit depth are predicted: (1) displacement from the center to the lee side of the pit at neutral stratification; and (2) position in the center of the pit near its floor at positive background stratification. It is shown that increasing of both the pit depth and the background stratification parameter leads to a noticeable increase in the time to reach the maximum concentration at the upper side of the pit and a decrease in the value of this maximum. For the recirculation ventilation scheme, intensification of inversion in the atmosphere increases the time of natural ventilation, but reduces the level of atmospheric contamination at the upper side of the pit downstream.

Evaluation of metal pollution characteristics using water and moss in the Luanchuan molybdenum mining area, China.

Luanchuan is rich in molybdenum resources, and mining activities are frequent, but over-mining can cause serious metal pollution to the local environment. To explore the degree of metal pollution caused by mining activities, the content characteristics and spatial distribution of metals in mining areas were studied by measuring the concentrations of Fe, Mn, Zn, Ba, Mo, Cu, Cr, Co, V, and W in surface water and mosses of mining areas. In addition, the metal pollution index (HPI), contamination factor (CF), and pollution load index (PLI) were used to evaluate metal pollution, and factor analysis was used to analyze the sources of metals. The results of the analysis of surface water at the mine site indicate the most abundant element in surface water, with a maximum concentration of 3713.8 μg/L, and its content far exceeds the water quality standard of Class III of the Environmental Quality Standard for Surface Water. The results of the HPI analysis showed that nearly 90% of the surface water was moderately contaminated (HPI ≥ 15). The results of the analysis of atmospheric deposition at the mine site confirm that the metal elements with a high threat to the atmospheric environment are Mo and W. The results of PLI indicate that the level of atmospheric deposition pollution in the study area is severe (PLI > 4). Factor analysis indicated that rock weathering and mining activities were the main sources of metals. This study provides a theoretical basis for the investigation and control of metal pollution in similar metal mining areas.

Дистанционная оценка качества атмосферного воздуха в населенных пунктах нефтегазовой специализации Ямало-Ненецкого автономного округа

The remote assessment of methane (CH4), nitrogen dioxide (NO2), and sulfur dioxide (SO2) concentrations in the atmosphere of oil-and-gas profile settlements within the Yamalo-Nenets Autonomous Okrug for 2019–2022 was made for the first time. Data analysis from the TROPOMI spectrometer revealed that the highest levels of atmospheric pollution are observed near industrial centers and major cities (Novy Urengoy, Salekhard, Nadym). Increased impurities were identified along gas pipelines (near compressor stations). The highest average values of nitrogen dioxide content were recorded in Novy Urengoy (1,34 mol/m², with contamination peaks occurring in winter months). Excessive concentrations of sulfur dioxide were found in urban-type settlements. The highest average values were recorded in Stary Nadym (20,35 mol/m²). The maximum methane content (1866,2 ppb) was reported in Novy Urengoy. Urban air, in general, has increased methane content. However, focuses of its spread are also observed beyond cities, which may be a consequence of global warming