Movement Of Air Masses Research Articles

A digital, inquiry-based lesson on the rain shadow effect for middle school

This article introduces a middle-school level, NGSS-aligned, inquiry-based approach to teaching weather and climate concepts in grades six through eight using free online resources including Google Earth. Inquiry-based learning has been shown to improve student achievement, but Earth’s climate systems are complex and macroscopic, making inquiry-based teaching difficult. This tends to result in a teacher-centric approach to teaching climate in middle school, where lectures and authoritative videos predominate. Unfortunately, in this educational setting, many people develop climate misconceptions and tend to view climate change as a minor issue or a matter of personal belief. This lesson offers an alternative approach in which technology provides a scaffold to inquiry-based learning. After an unusual weather phenomenon such as a snowman in the desert is introduced, students use Google Earth to explore the contrasting forest and desert found on opposite sides of some mountain ranges. With Nullschool Earth, students explore daily historical wind data to model prevailing winds and develop an understanding of how patterns in the motion of air masses create the rain shadow effect. This lesson helps students begin to model the complex Earth systems that create climate and to understand the distinction between weather and climate.

Heatwave events and concurrent ozone concentrations between 2006 and 2022 at two sites in southern and northern Spain.

Hotter-than-usual days are becoming more common, such that heat waves are expected to increase in intensity, frequency, duration, and spatial extent in Spain. Within this framework, this paper looks at the combined effects of extreme temperatures and air pollution in two cities in Spain, Córdoba and Valladolid, over the period 2006-2022. Synoptic patterns and air mass movement were analysed during the eleven coincident heat waves at both locations in order to study what impact orography and local meteorology have on ozone concentrations. Weak flow conditions were the most frequent synoptic pattern in the Iberian Peninsula during heat waves. Moreover, west and local circulations characterised the main air trajectories at low levels (500m agl), while southwest maritime advections and African air mass transport were more frequent at higher levels (1500 and 3000m agl) in Córdoba and Valladolid, respectively. On average, maximum ozone values were higher in Córdoba (105.1µgm-3) than in Valladolid (80µgm-3) and were strongly correlated with extreme temperatures at both locations (r up to 0.8, p-value < 0.05). Mean temperature in Córdoba was 31.9°C, with the maximum value reaching 43.7°C, while temperatures in Valladolid were lower (28.3°C and 37.3°C, respectively). Calculation and assessment of some indices helped to understand the impact of extreme events. Caution actions based on the Heat Index characterised heat wave periods. Moderate risk was the general Air Quality Health Index feature recorded and reached a very high risk of unhealthy air quality in the June 2022 event in Córdoba.

Physical-statistical model for forecasting maximum snowmelt-induced stages (the Ob river near the city of Barnaul as a case study)

For the regions with a long-term snow cover, the amount of solid precipitation is one of the driving factors in the formation of floods. The article considers the possibility of using the orographic correction to the velocity of vertical movements of air masses due to the relief in estimating winter precipitation and forecasting maximum snowmelt-induced stages. The significant influence of autumn freezing on the floodplain inundation and, accordingly, maximum water levels of the Ob River near the city of Barnaul is shown.

A novel energy harvesting technology from the movements of air masses

The displacement of air masses caused by the movement of objects or vehicles is often characterized by considerable energy content, which, with appropriate technologies, can be partially recovered. In this sense, numerous scientific works consider rail transport as a possible context for application. However, the literature in the sector highlights how using existing wind technologies in these areas involves many difficulties, mainly related to the turbulent and impulsive nature of the airflows generated. This work presents the architecture and general aspects of an innovative technology for obtaining electrical energy from variable and impulsive airflows, such as those due to the rapid transit of railway trains in tunnels, without precluding its use in other similar fields. The innovative aspect mainly concerns the independent control of two distinct typologies of bladed elements, which can also have translational movement and drag-based and lift-based aerodynamic behavior to improve the adaptability of the embodiment to the site’s fluid dynamic and geometric characteristics. Furthermore, the structural simplification of the apparatus, shifting some of the technological complexity to the control systems, brings further advantages in terms of construction cost, robustness, maintenance, reuse, and transferability to different contexts. Of course, the counterpart of these benefits lies in the software and hardware of the control devices. Analytical models to determine the non-dimensional performance coefficients of the two basic types have been reported as has the architectural model of the control system. The technology shown in this work is protected by an EP and US Patent.

Applied Machine Learning to Study the Movement of Air Masses in the Wind Farm Area

Modeling the atmospheric boundary layer (ABL) in the area of a wind farm using computational fluid dynamics (CFD) methods allows us to study the characteristics of air movement, the shading effect, the influence of relief, etc., and can be actively used in studies of local territories where powerful wind farms are planned to be located. The operating modes of a wind farm largely depend on meteorological phenomena, the intensity and duration of which cause suboptimal operating modes of wind farms, which require the use of modern tools for forecasting and classifying precipitation. The methods and approaches used to predict meteorological phenomena are well known. However, for designed and operated wind farms, the influence of meteorological phenomena on the operating modes, such as freezing rain and hail, remains an urgent problem. This study presents a multi-layered neural network for the classification of precipitation zones, designed to identify adverse meteorological phenomena for wind farms according to weather stations. The neural network receives ten inputs and has direct signal propagation between six hidden layers. During the training of the neural network, an overall accuracy of 81.78%, macro-average memorization of 81.07%, and macro-average memorization of 75.05% were achieved. The neural network is part of an analytical module for making decisions on the application of control actions (control of the boundary layer of the atmosphere by injection of silver iodide, ionization, etc.) and the formation of the initial conditions for CFD modeling. Using the example of the Ulyanovsk wind farm, a study on the movement of air masses in the area of the wind farm was conducted using the initial conditions of the neural network. Digital models of wind turbines and terrain were created in the Simcenter STAR-CCM+ software package, version 2022.1; an approach based on a LES model using an actuating drive disk model (ADM) was implemented for modeling, allowing calculation with an error not exceeding 5%. According to the results of the modeling of the current layout of the wind turbines of the Ulyanovsk wind farm, a significant overlap of the turbulent wake of the wind turbines and an increase in the speed deficit in the area of the wind farm were noted, which significantly reduced its efficiency. A shortage of speed in the near and far tracks was determined for special cases of group placement of wind turbines.

Семенная продуктивность и качество семян Pinus sylvestris L. в лесных культурах на крымских яйлах

The seed production and quality of Pinus sylvestris seeds in forest plantations on the Crimean yaylas has been studied. The dynamics of biometric indicators of cones and seeds by year and in connection with the peculiarities of growing conditions has been characterized. Significant differences in the quality of seeds of P. sylvestris trees have been revealed in terms of the level of germination energy. It has been shown that, along with the temperature regime, a significant impact on the effectiveness of P. sylvestris reproduction processes is exerted by air humidity and the nature of precipitation, as well as the dynamics of air mass movement, since the success of pollination is determined by the quantity and quality of pollen that has reached the female reproductive structures. Based on the analysis of weather phenomena and the dynamics of seed quality, it has been found that the level of seed germination is best reflected by an integrated index that takes into account the combined effect of several factors – the dryness index. In addition, the results of the analysis allowed us to conclude that the efficiency of the pollination process of female cones of P. sylvestris under yayla conditions is most likely influenced by the number of hours of sunshine. The germination energy and seed germination differ not only within the studied plantations, but also depending on the year of study. During the observation period, the forest plantations of the Ai-Petrinskaya Yayla have produced the highest quality seeds. In 2014, in the plantations with a density of 0.5, the seed germination rate was 74.5±2.2 %. The lowest level of germination energy and seed germination has been noted in artificial plantations of P. sylvestris on the Tirke Yayla; in 2012, these indicators here amounted to 15.2±0.7 and 46.2±2.1 %, respectively. In general, the development of the generative sphere of P. sylvestris in artificial plantations on the Crimean yaylas is quite effective. Based on this, a conclusion has been made that the growing conditions on the yaylas are favourable for the implementation of the initial stages of the ontogenesis of the species.

System for delivering radio interference transmitters to receiving devices of ground-based radio electronic means of satellite radio communication and radio navigation systems

Formulation of the problem. The method of delivering radio jamming transmitters to the area where a radio-electronic device is located, based on dropping transmitters from an unmanned aerial vehicle, is characterized by a number of disadvantages: high complexity of the equipment and, accordingly, the high cost of the UAV; low efficiency of radio interference transmitters in suppressing ground-based radio electronics of satellite radio communication and radio navigation systems. Purpose. Consider the possibility of increasing the efficiency of radio-electronic suppression of ground-based radio electronics of satellite radio communication and radio navigation systems by autonomous radio jamming transmitters delivered to the work area using UAVs, while reducing the complexity of the equipment and the cost of UAVs - carriers of radio jamming transmitters. Results. A delivery system for radio interference transmitters is proposed. The system uses an uncontrolled free aerostat (balloon) filled with gas as a UAV. The volume of gas depends on the given flight altitude. The balloon, together with the transmitter and battery, is launched from a starting position placed on the earth's surface, taking into account the known direction of the wind and the known location of the suppressed weapon. The balloon is delivered to the electronic jamming work zone by moving air masses. The calculations showed that the use of the proposed system provides a gain in the required transmitter EIRP of at least 7 dB compared to a ground-based transmitter. To suppress a Starlink user terminal at a range of up to 4 km, a transmitter with an EIRP of no more than 13 dBW (20 W) is required. Practical significance. The results obtained can be used to increase the efficiency of electronic jamming of ground-based satellite radio communication and radio navigation systems.

The recent increasing frequency of strong cooling event in Southwest China in February

AbstractA strong cooling event refers to a sharp change in the average temperature over a short period. The rapid change of temperature has important effect on human health and is highly concerned recent years. Based on the observed temperature data set from stations in Southwest China (SWC) from 1979 to 2017, this paper analyses the characteristics of the strong cooling event (SCE). The result shows that SCE occurs with the highest frequency during the time from February to May. Among them, the frequency of SCE in February exhibits an abrupt change before and after 2005 with a significant increase. Further study reveals that the change of SCE frequency in February is associated with the large‐scale background circulation patterns. After 2005, there is a cyclonic circulation anomaly in Northeast Asia and an anticyclonic circulation anomaly in the Tibet Plateau (TP). This pattern provides a favourable condition for the southward movement of cold air mass, thereby increasing the frequency of SCE in SWC. Furthermore, it is revealed that there is a strong correlation between the variation of SCE frequency in February and sea surface temperatures (SST) in the Northwest Pacific in January before 2005. The cold SST anomaly could favour the occurrence of extreme TD events in SWC through vertical circulation. After 2005, the correlation between SCE and Northwest Pacific SST is not significant. The sea ice in the northern Barents Sea and Kara Sea becomes the dominant impact factor. The abnormally low sea ice concentration is conducive to strengthen the meridional circulation over East Asia, leading to an increasing frequency of SCE in SWC.

Aerosol-PM2.5 Dynamics: In-situ and satellite observations under the influence of regional crop residue burning in post-monsoon over Delhi-NCR, India

The increasing air pollution in the urban atmosphere is adversely impacts the environment, climate and human health. The alarming degradation of air quality, atmospheric conditions, economy and human life due to air pollution needs significant in-depth studies to ascertain causes, contributions and impacts for developing and implementing an effective policy to combat these issues. This work lies in its multifaceted approach towards comprehensive understanding and mitigating severe pollution episodes in Delhi and its surrounding areas. We investigated the aerosol dynamics in the post-monsoon season (PMS) from 2019 to 2022 under the influence of both crop residue burning and meteorological conditions. The study involves a broad spectrum of factors, including PM2.5 concentrations, active fire events, and meteorological parameters, shedding light on previously unexplored studies. The average AOD550 (0.79) and PM2.5 concentration (140.12 μg/m³) were the highest in 2019. PM2.5 was higher from mid-October to mid-November each year, exceeding the WHO guideline of 15 μg/m³ (24 h) by 27–34 times, signifying a public health emergency. A moderate to strong correlation between PM2.5 and AOD was found (r = 0.65) in 2021. The hotspot region accounts for almost 50% (2019), 47.51% (2020), 57.91% (2021) and 36.61% (2022) of the total fire events. A statistically significant negative non-linear correlation (r) was observed between wind speed (WS) and both AOD and PM2.5 concentration, influencing air quality over the region. HYSPLIT model and Windrose result show the movement of air masses predominated from the North and North-West direction during PMS. This study suggest to promotes strategies such as alternative waste management, encouraging modern agricultural practices in hot-spot regions, and enforcing strict emission norms for industries and vehicles to reducing air pollution and its detrimental effects on public health in the region and also highlights the need for future possibilities of research to attract the global attention.

Source Apportionment of Air Quality Parameters and Noise Levels in the Industrial Zones of Blantyre City

The increase in industrial activities has raised concerns regarding air quality in urban areas within Malawi. To assess the source apportionment of air quality parameters (AQPs) and noise levels, concentrations of AQPs (CO, TSP, PM 2.5, PM10) and noise levels were monitored at 15 sites in Makata, Limbe, Maselema, Chirimba, and Maone during dry and wet seasons, respectively. Active mobile multi-gas monitors and a Dylos DC1100 PRO Laser Particle Counter (2018 model) were used to monitor AQPs, while Integrated Sound Level Meters were used to measure noise levels. Monitoring and analysis were guided by the World Health Organization (WHO) and Malawi Standards (MS). A Positive Matrix Factorization (PMF) model was used to determine source apportionment of AQPs, and matrix trajectories analysed air mass movement. In the wet season, the average concentration values of CO, TSP, PM10, and PM2.5 were 0.49 ± 0.65 mg/m3, 85.03 ± 62.18 µg/m3, 14.65 ± 8.13 µg/m3, and 11.52 ± 7.19 µg/m3, respectively. Dry season average concentration values increased to 1.31 ± 0.81 mg/m3, 99.86± 30.06 µg/m3, 24.35 ± 9.53 µg/m3, and 18.28 ± 7.14 µg/m3. Noise levels remained below public MS and WHO standards (85 dB). Positive correlations between AQPs and noise levels were observed, strengthening from weak in the dry season to moderately strong in the wet season. PMF analysis identified key factors influencing AQPs accumulation, emphasizing the need for periodic sampling to monitor seasonal pollution trends, considering potential impacts on public health and environmental sustainability. Further studies should look at factors affecting the dynamics of PMF in Blantyre City.

Back-trajectory analyses for evaluating the transboundary transport effect to the aerosol pollution in South Korea

This study performed a back-trajectory analysis to determine the influence of transboundary transport on the extent of aerosol pollution in South Korea, based on 5-year PM2.5 measurements (2015–2019) in five cities covering South Korea. A transboundary transport case was selected if a back trajectory passed over a dedicated region (BOX 1 and BOX 2) in the Yellow Sea. First, we found that the frequency of transboundary transport largely increases in the high pollution case, and this pattern is almost consistent for all months and all five cities, indicating the importance of investigating the horizontal direction of air mass movement associated with PM2.5, which has been discussed extensively in previous studies. In this study, we also examined the altitude change and straight moving distance (defined as travel distance) of back trajectories regarding the extent of local PM2.5. Consequently, we found that back trajectories in high aerosol pollution showed much lower altitudes and shorter travel differences, implying a significant contribution of surface emissions and stagnant air conditions to severe aerosol pollution. As a result, the local PM2.5 level was not significantly enhanced when the air mass passed over the Yellow Sea if transboundary transport occurred at high altitudes with rapid movement (i.e., high altitude and long travel distance back-trajectory). Based on these results, we suggest utilizing the combined information of the horizontal direction, altitude variation, and length of back trajectories to better evaluate transboundary transport.

A metapopulation framework integrating landscape heterogeneity to model an airborne plant pathogen: The case of brown rot of peach in France

Plant disease dynamics are driven by the concurrent interplay of host susceptibility, pathogen presence, and environmental conditions. While host susceptibility and environmental conditions can readily be characterized, the transmission of an airborne pathogen depends on the biotic and abiotic conditions of the surrounding environment. We propose an original metapopulation framework integrating landscape heterogeneity, in terms of climate and host density, where populations of plant hosts are connected via air-masses which allow pathogen dispersal. We explicitly account for climatic drivers affecting pathogen transport while modelling aerial dispersal using Lagrangian simulations, as well as host phenology and infection. We calibrate the model parameters according to the literature and using Approximate Bayesian Computation against observations of brown rot incidence in French peach orchards from 2001 to 2020 across an area of 50,000 km2. We use the model to produce maps of risk, distinguishing site dangerousness (risk of causing secondary infection in other sites) and vulnerability (risk of becoming infected) across the our study area. We demonstrate that airborne transport of Monilinia spores is essential in describing the spread of brown rot in French orchards in the considered period. We find that most dangerous and vulnerable sites are located along the Rhône Valley, due to the concurrence of high density of peach cultivation, a suitable climate and persistent airborne connections. Our work represents a first step to integrate metapopulation theory, epidemiology and air-mass movements to inform plant protection strategies at the national level. Furthermore, it could be adapted to optimize crop protection under future climate projections.

Responses of underground air and drip water geochemistry to meteorological factors: A multi-parameter approach in the Rull Cave (Spain)

Our research aims to assess the complex interactions between the elements that constitute and influence a cave system through the analysis of an extensive dataset of climatic and environmental parameters (222Rn, CO2, drip rates, chemical composition, and environmental isotopes) measured in air, water, and solid in the Rull Cave (southeastern Spain). Of particular importance is understanding the effect of rainfall and temperature on water and gas transport through the epikarst and the involved processes. Our results show that the cave gaseous concentration patterns do not only depend on the temperature-caused movement of air masses, but they can also be affected by abundant rainfall. The δ18O and δD composition of cave water also relies on such precipitations for the effective transfer of the rainfall signal into the cave, which can take between 3 and 7 days. The elemental ratios (Sr/Ca and Mg/Ca) show high responsiveness to the water drip rate, hinting that enhanced prior calcite precipitation (PCP) occurs at slower drip rates. Despite this, and regardless of drip rates, calcite saturation indices follow a seasonal variation pattern inversely proportional to the cave air CO2 concentration, while δ13C-DIC is proportional. Our results show how the interlinkage between these multiple components defines the dynamics of the atmosphere-soil-cave system. Cave monitoring is then essential to understand the karstic vadose zone, which is highly sensitive to climatic influence and its changes.

Synthesis of a measurement procedure for estimating the orientation of a small unmanned aerial vehicle under conditions of changing status of measurement results

The problem of processing measurement information with changing status of measurement results of micromechanical sensors of an intelligent on-board measuring system of a small unmanned aerial vehicle is considered. While vehicle is in the air, the measurement results status changes from confirmed to orienting, for example, due to sensor defects, degradation of the measuring channel, the appearance of false measurement output signals of micromechanical sensors due to vibrations and shocks caused by the movement of air masses. As a result, the probability of stability loss of a small unmanned aerial vehicle increases and it is necessary to raise the accuracy of estimating its orientation in conditions of changing status of measurement results. The measuring procedure of the Kalman structure is considered, the equations of which are determined with accuracy to the parameters of the transition and noise matrices of the state, as well as the perturbation vector, characterizing the measuring process. The parameter values are determined by a mathematical model for converting measuring information based on a dynamic mathematical model, which distinguishes the developed measuring procedure from a measuring procedure with a classical transition matrix. A neural network is used to find unknown parameters. A multilayer perceptron was selected as the basis of a neural network, for which an error back propagation algorithm is used to train. Based on the results of mathematical modeling and measurement experiment, it was found that the accuracy of the synthesized measuring procedure based on a dynamic mathematical model is higher than the accuracy of the measuring procedure of the Kalman structure with a classical transition matrix. The results of the study will be useful in the development of intelligent measurement procedures for on-board measurement systems operating under conditions of changing status of measurement results

Exploring Spatial and Temporal Dynamics of Red Sea Air Quality through Multivariate Analysis, Trajectories, and Satellite Observations

The Red Sea, a significant ecoregion and vital marine transportation route, has experienced a consistent rise in air pollution in recent years. Hence, it is imperative to assess the spatial and temporal distribution of air quality parameters across the Red Sea and identify temporal trends. This study concentrates on utilizing multiple satellite observations to gather diverse meteorological data and vertical tropospheric columns of aerosols and trace gases, encompassing carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3). Furthermore, the study employs the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to analyze the backward trajectory of air mass movement, aiding in the identification of significant sources of air pollutants. A principal component analysis (PCA) with varimax rotation is applied to explore the relationship and co-variance between the aerosol index (AI), trace gas concentrations, and meteorological data. The investigation reveals seasonal and regional patterns in the tropospheric columns of trace gases and AI over the Red Sea. The correlation analysis indicates medium-to-low positive correlations (0.2 &lt; r &lt; 0.6) between air pollutants (NO2, SO2, and O3) and meteorological parameters, while negative correlations (−0.3 &lt; r &lt; −0.7) are observed between O3, aerosol index, and wind speed. The results from the HYSPLIT model unveil long-range trajectory patterns. Despite inherent limitations in satellite observations compared to in situ measurements, this study provides an encompassing view of air pollution across the Red Sea, offering valuable insights for future researchers and policymakers.

Enhanced methodology for thermal management area assessment of metro lines

The article analyzes the operation of metro lines with doubletrack and single-track tunnels in the Russian Federation. Simultaneous activation of traffic on single-track and double-track tunnels affects the management of thermal and humidity parameters of the air environment on metro lines. Currently, there is limited experience in using shared lines. The study conducted an analysis of the features in the formation of thermal and ventilation regimes in double-track and single-track subway tunnels. It also examined the temperature regime of the station when mixing air flows from a double-track tunnel between stations and the flow from one of the stations. An algorithm has been defined for controlling the thermal and humidity parameters of the environment in underground structures. Measures are proposed to minimize the consequences of combining air flows and normalize microclimate parameters. The analysis of air mass movement revealed that the air temperature at the station located beyond the junction point of the double-track tunnel section and single-track tunnels is influenced by circulation flows in single-track tunnels, as well as the flow rate and temperature of the air coming from the double-track tunnel.

Role of winds and air masses in the transport of non-local Pinus sp. pollen at an urban location in North India: A statistical perspective

Airborne pollen is not uniformly spread in the urban environment. They are influenced by vegetation, weather parameters (mainly wind speed and direction) and the built environment. Pinus sp. Pollen was reported in the aerobiological load of Chandigarh, a non-native species. Therefore, the study investigates Pinus sp. Pollen potential source and origin. The current study examined the effect of local wind direction and the transboundary air mass movement on the temporal distribution pattern of Pinus sp., which was recorded in a city located in Indo-Gangetic Plains, India. An integrated platform having HYSPLIT, GIS and statistical analysis were used to explain the aerobiological load of Pinus sp. Pollen based on spatial and temporal variability in an urban environment. The comprehensive circular statistical analysis was found to be complementary to cluster trajectories at 10 m height, contrary to regional trajectories. This revealed that Pinus sp. Pollen originated from potential sources close to Chandigarh and were unrelated to the regional air mass transmission scale. One possible source area for Pinus sp. Pollen might be Kasauli and Solan, which is well-documented in the literature. There are also evidence that suggests that long-range transport of allergic pollen sp. Could enhance the exposure and public health risk. Hence, there is a need to understand the dispersal pattern of long-range transport of Pinus sp. Pollen and other allergic pollen sp. Under varying urban meteorological conditions.

Rancang Bangun Prototipe Alat Ukur Kecepatan dan Arah Angin Berbasis Arduino Pro Mini Studi Kasus Penerapan pada Olahraga Paralayang di Parangtritis

Wind is a phenomenon observable a mass movement of air the effect and experienced in everyday life due to differences in the air pressure in two separate places so there the airflow from a having the air pressure is higher to a lower have pressure air. Fast slowness wind speed depends on how big a pressure difference of the two it. Essentially any need sports facilities must meet the standard sports itself. Sports paralayang, on the need facilities able to meet a need the related sports development. This study aims to to build a helmet safety to users paralayang on sports paralayang in parangritis. A helmet these were designed based microcontroller to help users paralayang, so users of paralayang would quickly get information that can be used as an effort to safety. The helmet worn by paralayang, which in upon the helmet these there were instrument that serves to measuring wind speed. When the wind is fast , this instrument will sound and paralayang must be down. So risk can minimize accident. The result of this study graphic display the output of a system for conducting the process of wind measurements is expected to measuring changes wind is more precision by means of sensors optocoupler which are cheap and have good qualities.

Spatial patterns of PM2.5-bound heavy metals and analysis of their influencing factors in China

This study investigates the relationship between the spatial distribution patterns of heavy metals (HMs) in atmospheric fine particulate matter (PM2.5) and their influencing factors in China, in order to address air pollution problems. Using HM data from PM2.5 collected from 88 Chinese cities between 2012 and 2020, the study employed a combination of enrichment factor (EF) analysis, standard deviation ellipses and hot spot analysis to assess spatial distribution patterns; geographical detectors to identify influencing factors; and hybrid single-particle Lagrangian integrated trajectory models (HYSPLIT) to determine air mass movement. The results reveal that the spatial distribution of PM2.5-bound HMs in China is characterized by high levels in the north and interior and low levels in the south and along the coast. Anthropogenic activities affect HM levels in China's interior more strongly than on the coast. Moreover, the distribution of PM2.5-bound HMs in China exhibits a northeast-southwest spatial pattern, with significantly higher levels observed in central and northern regions than in eastern regions, particularly along the coast. Industrial waste emissions and energy consumption are key factors contributing to high PM2.5-bound HMs. In central China, the summer air mass movement predominantly follows a southeast direction, while in winter, it follows a northwest direction, originating from inland. In contrast, in eastern China, summer air mass movement predominantly follows a southeast direction, while in winter, it follows a northeast direction, originating from the ocean. Overall, our findings suggest that HMs in PM2.5 display high clustering values in central China, due primarily to industrial waste emissions, energy consumption, and air mass movement.

EXTREME SITUATIONS AT FACILITIES OF THE FUEL AND ENERGY COMPLEX: ASSESSMENT OF THE RISK OF HUMAN INJURY

Problem statement. The task of assessing the zones of human damage in the event of an extreme situation at a gas station located in a crowded place in the city of Dnipro is under consideration. An analysis of the size of thermal air pollution zones and the zone of possible injury to people in the event of flying debris, created in the event of an extreme situation at a gas station, is being carried out. To solve the problems of this class, the development of specialized mathematical models is required. The purpose of the article. Assessment of the risk of injury to a person from the throwing action of debris and in the event of a fire at a gas station in the event of an emergency situation. Methodology. A numerical model based on the integration of Newton's second law for the movement of a material point in the air is used to analyze the damage zones during the flight of fragments. A computer program was created on the basis of this numerical model. Numerical integration of the energy equation is used to analyze thermal pollution zones during a fire at a gas station. This equation takes into account the speed of movement of air masses, coefficients of thermal conductivity, air temperature at the site of the fire. Scientific novelty. An effective numerical model has been developed for the analysis of damage zones from the throwing action of debris, which are formed in the event of an extreme situation at a gas station. Damage zones in the event of a possible fire at a gas station located in the city of Dnipro have been determined. Practical significance. A program has been developed for calculating the dynamics of the movement of debris in the air, which are formed in an extreme situation at a gas station. This makes it possible to determine the damage zones from the throwing action of fragments of different sizes. Zones of thermal air pollution are defined, which allow to assess the risk of thermal damage to people. Conclusions. An effective tool for analyzing the risk of injury to people in the event of flying debris and a fire at a gas station has been developed. The results of computational experiments are presented.