Land cover changes and wildfires have had an increasing impact on the Ogan Komering Ilir Peatland ecosystems in South Sumatra, Indonesia. This study aims to understand the peatland land cover and burn severity dynamics from 2015 to 2023. The random forest method was applied to classify land cover, while the differenced Normalized Burn Ratio (dNBR) was used for mapping fire severity. We combined various satellite data to classify land cover, consisting of Landsat-8, Sentinel-1, and Sentinel-2. Landsat-8 or Sentinel-2 images were also used for the dNBR calculation. We revealed complex climate, human, and restoration interactions in land cover and burn severity fluctuations over 273,799 hectares of the study area from 2015 to 2023. The 2015 El Niño-induced drought led to 21,754 fire hotspots and 2.01% of the area in high-severity burns. In 2016, it reduced tree cover by 10.18% and increased bare/sparse vegetation by 6.11%. The 2019 El Niño event led to 7,893 fire hotspots, lessening unburned areas and worsening burns. Due to the extreme effects of the 2015 drought, restoration efforts between 2016 and 2020 significantly decreased fire hotspots in 2016. Tree cover stabilized, reaching 48.46% by 2020, whereas unburned areas rose to 69.46% in 2018, showing good recovery and lower fire severity. In 2021-2023, fire hotspots were modest relative to El Niño years but increased in 2023. After 2020, tree cover decreased, but other land cover classes fluctuated. Therefore, continual monitoring and adaptive management are critical for reducing negative consequences and increasing ecosystem resilience.

The high carbon monoxide content in the urban atmosphere is one of the most important indicators of poor air quality in megacities such as Moscow. This study is to evaluate the importance of wind speed, air temperature, and relative air humidity for predicting the concentrations of carbon monoxide for the day ahead using a simplified one-dimensional quasistationary statistical model. It is shown that the concentration of carbon monoxide in the Moscow atmosphere is determined by a combination of internal (previous days CO concentration) and external (meteorological conditions) factors. The variation of carbon monoxide concentration at one station differs from the variation at another station due to the differences in local conditions. Taking into account wind speed and air temperature increases the predictive value of the onedimensional quasi-stationary statistical model for most of the stations. In contrast to wind, relative air humidity decreases the predictive value of the model for most of the stations. This means that meteorological factors considered in this study could have different effects on predicting carbon monoxide concentration in the case of Moscow. The data from the Balchug weather station, located in the city center, offers a more accurate CO concentration forecast for most Moscow stations compared to the VDNKh weather station. For a more complete description of the influence of meteorological conditions on the predicted low concentration of gases, it is useful to take into account the model wind direction, surface air pressure, and the intensity of mixing in the urban boundary layer.

The geographical position of the region, ethnic composition, acceleration of the process of polarization among rural settlements, and other factors increase the relevance of the research. The subject of the research is the study of rural settlement problems, and the object of the research is the villages and ethnic minorities of the Balakan district. The study aims to reveal the modern problems of the settlement of ethnic minorities and the formation of rural agglomerations, to study the causes of the emptying of some villages, and to prepare a rural development model to prevent the problems. To conduct research, the literature and statistical materials were analyzed, as well as cartographic, comparative analysis, SWOT, and modelling methods were used. Moreover, a field investigation was conducted in the research area. It was revealed that although a majority of the rural population settles in villages with a high demographic potential, villages with a weak demographic potential, due to their higher number, play a major role in the settlement system. Moreover, some villages form rural agglomerations, while some of them lose their population due to socioeconomic challenges. Due to the intense migration processes, some villages have turned into endangered villages (Mazimustu, Goyrujuluk), and even some villages are on the brink of extinction (Bayrambina, Mazimchay, Abjit). Studying the regulation of rural settlement in the region is of practical importance in terms of ensuring the equal development of the region, ensuring the security of the borders, and protecting ethnic minorities. However, there is still a need for serious research in this field.

The article presents a comprehensive analysis of the impact of global and regional events on the dynamics of tourist flows. The primary reasons for the decrease in inbound tourist flows have been identified and categorized into three main groups: military-political class, economic class, and natural-technological class. Additionally, a hybrid class was identified, to which COVID-19 was assigned. The article is based on causal and comparative analysis, utilizing statistical data on tourist flows provided by the World Bank and UNWTO, as well as an assessment of similar patterns among countries worldwide. The main characteristics of tourist flows from 1995 to 2022 have been identified, pinpointing leaders among countries in increasing and decreasing the number of tourists per year. During the study, countries with similar patterns of tourist flow dynamics were identified. It was concluded that relying solely on quantitative analysis has limited applicability in identifying these patterns. Therefore, it is recommended that quantitative analysis be complemented with expert assessments for a more comprehensive understanding. The basic strategies for responding to the identified classes of causes were outlined. The research will benefit tourism professionals, governmental authorities, and researchers in socio-economic and political disciplines.

The level of pollution of lake sediments located in the city of Murmansk (Russia) with petroleum hydrocarbons was studied. The most urban lakes can be classified as slightly polluted, representing the maximum acceptable risk for human health and ecosystems; Lake Yuzhnoe – as moderately polluted with a negative impact on the aquatic environment, and Lake Ledovoe located near the highway, gas station, and car service, – as dangerously polluted, posing a threat to human health and requiring remediation. The background content of organic compounds identified as petroleum hydrocarbons in the sediments of Murmansk lakes ranges from 76 to 307 mg TPH/kg. High background concentrations of hydrocarbons can be associated with a large amount of organic matter in the sediments of lakes. The standards for the content of hydrocarbons in sediments, developed for other regions, give an ambiguous assessment of their content in the sediments of lakes in Murmansk. It is not entirely correct to use the background content of hydrocarbons in the sediments of lakes in other regions, which differ in particle size distribution, content of organic matter, and chemical composition, to assess the degree of pollution. Additional research is needed to determine the content of hydrocarbons in the sediments of background lakes in the Murmansk region and to develop standards for the content of hydrocarbons in the bottom sediments of Arctic cities.

Atmospheric precipitation acts as a significant pathway for pollutants from the atmosphere to the Earth’s surface, and analyzing urban precipitation data on intensity, fallout regime, transfer patterns, and solid particle content helps identify pollution sources. For the first time in the Moscow megacity, the levels of soluble forms of potentially hazardous elements (PHEs) in atmospheric precipitation were studied during the whole summer season of May–September 2019. The concentrations of Al, As, B, Ba, Be, Bi, Cd, Ce, Co, Cu, Fe, La, Li, Mn, Ni, P, Pb, Rb, Sb, Sn, Sr, and Zn were determined using inductively coupled plasma mass spectrometry and atomic emission spectroscopy methods. The research underscores the crucial role of atmospheric precipitation in washing PHEs out of the atmosphere. In May and September, concentrations of PHEs surpass the warm-season average. Notable contamination in May stems from elevated traffic during vacations, extensive burning of plant debris and wood, and pollen transport. Summer months are characterized by reduced forest and agricultural fires, traffic, and increased vegetation, leading to lower PHE concentrations, especially in July, with typical amount of precipitation contributing to pollutant dispersion. Elevated PHE levels in September are observed due to increased traffic load, biomass burning, and the expansion of unvegetated soil areas. Rainwater is enriched with Sb, Pb, Cd, Zn, Cu, B, Bi, P, and Sr, sourced from vehicle emissions, soil particles, industry, construction dust, biomass burning, and forest fires. Moderate enrichment with Ba, Mn, Ni, Co, and Sn also occurs episodically. Regression analysis highlights solid particles’ role as a major PHE source in rainwater, with the longer antecedent dry periods and the higher acidity level of rain intensifying the accumulation of PHEs. Long-range transport plays a lesser role, with Southern and Northern Europe, Western Siberia, and the central part of European Russia contributing meaningfully.

The lack of planning and feasibility of controlling actions over land use and land cover lead to relationship problems between the support capacity that environmental systems present and their current use. The goal of this study is to figure out how much land can be used based on its natural and physical features and to find problems that come up because of the heavy use in the Formoso River watershed. It is one of the most recognized Brazilian watersheds, due to its turistic, karst, and environmental characteristics. The methodology consists in handling and generating data in a GIS environment by performing a synthesis map, as well as adopting geoprocessing criteria and techniques in the field to validate the collected data. The results indicate that the watershed presents large areas without conflicts due to its numerous conservation units. However, major conflicts are identified in other areas, affecting the balance and dynamics of the landscape and its water resources. Such conflicts arise because soybean crops advance in fragile and karst areas. The highest concentration of confit is only 1.61%, particularly near the Formoso River marsh. Therefore, the present work considers a methodology that assesses the capacity of use through a method that has produced a summary document that is applicable and compatible with the karst system.

The Central Chernozem region of Russia has undergone significant changes in socio-demographic processes over the past half-century. The aim of this study was to establish the impact of metropolization on the demographic transformation of sparsely populated rural settlements for the Central Chernozem region and to develop a demographic forecast for 2030. The study’s goals were to (1) determine the scale of regional metropolises; (2) identify the impact of metropolization on the quantitative indicators of sparsely populated rural settlements; (3) establish trends in their transformation; and (4) compile a medium-term demographic forecast for the Central Chernozem region. The set objectives were achieved by integrating methods for spatial-temporal and comparative geographical analysis, statistical methods, and a combination of official statistics with sociological methods. Analysis of the level of urbanization of the regions in modern conditions (20th and 21st centuries) showed that, although this process was and remained below the national average, it did not prevent the formation of regional metropolises (Belgorod, Stary Oskol, Kursk, Voronezh, Lipetsk, Tambov) as an obvious outcome of urbanization processes. A regional pattern of degradation of the network of rural settlements, mainly the smallest and small in terms of population (1-25, 26-50 people), which make up over one third of all settlements in the Central Chernozem region of Russia, was determined. A stable long-term trend of growth in the number of abandoned villages and hamlets was established. Between the last two All-Russian population censuses (11 years), their number increased by 45%. The forecasting results obtained confirm the established patterns in the medium-term trend of “compression” of rural settlement around regional metropolis (with some exceptions). The medium-term demographic forecast showed that population concentration in metropolitan areas and further socio-demographic desertification in peripheral areas will continue with growing territorial differentiation. The obtained results of the study of the transformation of settlement systems of the Central Chernozem region as a result of the metropolization of regional centers can help government institutions in strategic planning of territorial development.

Overexploitation and climate change have threatened the availability and sustenance of groundwater resources. A proper understanding of the regional distribution of groundwater is crucial to ensure long-term water security. The present study aims to identify the groundwater potential zones in the Lakhimpur district of Assam using the Analytical Hierarchy Process (AHP) in combination with geospatial technologies. The occurrence of groundwater in the region was determined by several factors including geomorphology, lithology, slope, distance from the river, drainage density, lineament density, rainfall, curvature, soil, land use, land cover, Normalized difference vegetation index (NDVI), and topographic wetness index (TWI). These factors organized as thematic layers were utilized to generate a groundwater potential zones (GWPZ) map in the GIS environment. The AHP, an effective decision-making technique, was adopted to assign weights to each thematic layer corresponding to their relative importance in influencing groundwater availability. The GWPZ map prepared using the weighted overlay techniques was categorized into three classes: good, moderate, and poor. The result revealed that the good potential zone comprises 1909.41 km2 (65.12%), moderate 1018.25 km2 (34.72%) and the poor zone comprises 4.22 km2 (0.14%) of the total geographical area. The obtained results of 73.33% (Overall accuracy), 0.708 (ROC-AUC), and 0.50 mbgl (groundwater level fluctuation) between pre-monsoon and post-monsoon prove that the model has performed satisfactorily in identifying groundwater potential zones. The findings provide a framework for the effective exploration and management of groundwater resources, ensuring their future availability in the region.