Water storage is one of the key components of terrestrial water balance, therefore its accurate assessment is necessary for a sufficient description of hydrological processes within river basins. Here we compare terrestrial water storage using calibrated hydrological model ECOMAG forced by gauge observations, uncalibrated INM RAS–MSU land surface model forced by reanalysis and GRACE satellite-based data over Northern Dvina and Pechora River basins. To clearly identify differences between the datasets long-term, seasonal and residual components were derived. Results show a predominance of the seasonal component variability over the region (~64% of the total) by all datasets but INM RAS–MSU shows a substantial percentage of long-term component variability as well (~31%), while GRACE and ECOMAG demonstrate the magnitude around 18%. Moreover, INM RAS–MSU shows lowest magnitude of annual range. ECOMAG and INM RAS–MSU is distinguished by earliest begin of TWS decline in spring, while GRACE demonstrates latest dates. Overall, ECOMAG has shown the lowest magnitude of random error from 9 mm for Northern Dvina basin to 10 mm for Pechora basin, while INM RAS–MSU has shown largest one.

Mangroves are one of the most important types of wetlands in coastal areas and perform many different functions. Assessing the structure and function of mangroves is a premise for the management, monitoring and development of this most diverse and vulnerable ecosystem. In this study, the unmanned aerial vehicle (UAV) Phantom 4 Multispectral was used to analyse the structure of a mangrove forest area of approximately 50 hectares in Dong Rui commune, Tien Yen district, Quang Ninh Province – one of the most diverse wetland ecosystems in northern Vietnam. Based on the visual classification method combined with the results of field taxonomic sampling, a mangrove tree classification map was established for UAV with three species, Bruguiera gymnorrhiza, Rhizophora stylosa, and Kandelia obovata, achieving an overall accuracy = 86.28%, corresponding to a Kappa coefficient =0.84. From the images obtained from the UAV, we estimated and developed maps and assessed the difference in tree height and four vegetation indices, including the normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), enhanced vegetation index (EVI), and green chlorophyll index (GCI), for three mangrove plant species in the flying area. Bruguiera gymnorrhiza and Rhizophora stylosa reach an average height of 4 to 5 m and are distributed mainly in high tide areas. Meanwhile, Kandelia obovata has a lower height (ranging from 2 to 4 m), distributed in low-tide areas, near frequent flows. This study confirms the superiority of UAV with red edge and near-infrared wave bands in classifying and studying mangrove structures in small-scale areas.

The land use change has affected nearly 32% of the global landscape from 1960 to 2019. Several studies have examined the impacts of land use land cover (LULC) on the surface temperature. Still, the spatiotemporal variation of LULC and LST with altitude is a less researched area. In the current study, we assess the LULC dynamics and its relation to altitudinal LST in the Himalayan Satluj River basin in Himachal Pradesh across the altitudinal range of 332 to 6558 meters. LULC, LST, NDVI, and NDMI were derived from Landsat data for 1980-2020. The spatial pattern was analyzed using Support Vector Machine (SVM) and a mono-window algorithm. The results of LULC denote that snow covered area (SCA) have decreased by nearly 56.19% since 1980 and vegetation cover has increased. However, a decline in vegetation density is pronounced at the same time. The mean surface temperature of the Satluj basin has amplified by 6°C (0.25°C/year) from 1996 to 2020. Mostly Zone 3 and 4 are under high hilly and temperate dry regions in Lahaul Spiti and Kinnaur district of Himachal Pradesh. The most important sign is that the mean surface temperature for Zone 3 (3000m-4500m) and Zone 4 (above 4500m) was the highest increase to 6°C (0.26°C/year) and 8°C (0.31°C/year) from 1996 to 2020. The increase in LST values is attributed to land cover dynamics precisely the decline of snow cover area and the emergence of vegetation zone at higher above the 4500 altitudes. Our study facilitates regional analysis.

The landscape cartography assesses the functional, dynamic, structural and morphological aspects of landscapes, regardless of their taxonomic scale. It seeks to use these units to support environmental and territorial planning and management. Thus, the present study sought to apply this line of analysis to the Pindaré River Basin, precisely in its lower course, located in the Brazilian state of Maranhão. The objective was to identify, classify, map and analyze the landscapes of the lower course through the correlation of variables related to geology, relief, soils, land use and land cover providing data to support and promote preservationist and conservationist public policies and actions in the area. The methodology identified four levels of landscape analysis, from morphometric aspects, geoforms and upper units to reaching the final landscape map, using field output, digital elevation models and satellite images to validate information. The procedures allowed to identify the landscape heterogeneity in a unique environment of saturated and periodically flooded soils contrasting with extensive pastures and little native vegetation. As a result, seven first-level landscape units were identified, coming up to fifty-eight sub-units in the final map. The work aims to apply the methodology in an area of the Maranhão State where few studies on landscape cartography have occurred. The target is to comprehend possible relationships between the functional and structural potential of landscapes and their relationship with the current intensity of land use, contributing to physical- territorial planning permeating geoecological sustainability.

Arsenic is ranked as a significant global health hazard associated with potable water. The present study assesses the arsenic pollution of the surface waters in the mountainous regions of the central part of the North Caucasus due to the presence of geochemical anomalies and the potential health risk by its consumption for the residents. The studies were carried out from 2016 to 2022. The surface waters of 5 main rivers of the region (Kuban, Malka, Baksan, Chegem and Cherek) with their main tributaries have been studied. Samples were taken during the period of intensive melting of glaciers (summer). The determination of the soluble form of arsenic was carried out using the method of atomic absorption spectrometry. In general, arsenic concentrations in this region are lower than Clark values for river waters. Along with this, watercourses with high and very high concentrations of arsenic have been identified. Elevated concentrations of arsenic in surface waters spatially coincide with the location of geochemical anomalies. The most polluted is the Baksan River. The levels of surface waters pollution from natural and anthropogenic sources are almost the same (up to 100 µg/dm3). In this regard, an assessment of the health hazard was carried out. For residents receiving drinking water from wells located at the southern foot of Elbrus, the carcinogenic risk for adults was 4.51×10-4, which is unacceptable for the general population. The non–carcinogenic risk was 1.00 - the maximum permissible risk causing concern.

There could be many environmental and biological impacts such as edaphic, geographic, climatic, age, tree structure and population on morphological, physiological and genetically seed quality in plant species. Gene diversity is an important mirror of genetically seed quality. Gene diversity in seed crops were estimated based on female and male strobili productions of fifty trees (N) randomly chosen from each population sampled over an altitudinal range as low (1200-400 meters ≤ altitude), middle (1400 m < altitude ≤ 1600 m), high (1600 m < altitude ≤ 1800 m), and very high (1800 m < altitude) in Taurus cedar also known as cedar of Lebanon (Cedrus libani A. Rich.) for two consecutive years (2021&2022). The variation in strobilus production was subjected to estimation of female and male fertility variation. The total fertility variation (Ψ) was estimated from the female and male fertility variation. Impacts of some growth characteristics (tree height and diameter at breast height) on strobili productions were also investigated. Strobili productions varied among the populations and individuals within population, and between years. The differences for populations and years were also found for coefficient of variations which were mirror of fertility variation of the strobili productions. Tree height and diameter at breast height seemed more reasonable predictor than age for number of strobili. Fertility variations of female parents were generally higher than that of male in both years. First year showed generally higher parental variations in individual populations. Gene diversity (GD=1-0.5Ψ/N) ranged from 0.967 to 0.974 for the populations and years. The loss of highest gene diversity was 0.004 in low population (0.967 & 0.971) between years. Results of the study indicated that altitudinal gene diversity of seed crop could be used to produce genetically quality seed and their grading. Moreover, data sets can be used to fill the Forest Landscape Restoration library (FLR-Library).

In the XXI century, the factors of the development of megacities are changing rapidly, the competitiveness of which increasingly depends on their image in different social environments. The purpose of the study is to identify main common features of the current image of the leading global cities (London, Paris, New York and Tokyo) in the Russian–language segment of the Internet (Runet). The research was based on a combination of methods of socio-economic geography, quantitative and qualitative methods of sociology. To reflect the objective reality of megacities, international statistics were used; to assess the role of Internet information resources influencing the formation of the image, the number of search queries in Runet and the context of publications about cities in social media were analyzed; to identify the configuration of the image, the data of a sociological survey were studied. It was revealed that the perception of megacities in Runet is based on a comparable volume of information flow in social networks (the number of published messages is 20 thousand per day for Paris and London, 15 thousand for New York, 4 thousand for Tokyo) and on similarity of publications’ context (2/5 are in the categories “entertainment” and “personality”). Despite certain limitations of the methods used and the relevance of the digital artifacts obtained, the image structure of the centers under consideration is characterized by the predominance of objective over subjective and cognitive (knowledge and ideas about “physical” givens) over affective (emotions, feelings, sensations) components with the key role of four collective categories: common features of large cities, idealized imagery of the country, prestigious urban locations and world architectural brands; as well as high stability in time and space. The continuation of research based on the proposed principles, while improving the methodology and involving cities of different classes, will contribute to the adaptation of foreign experience in designing of images of ambitious Russian cities in the face of new global challenges.

Increased number of extreme weather events is one of the most serious hazards of climate change over the territory of Russia. However, there is a lack of comprehensive analysis of the number of extreme weather events that caused social and economic damage in the country and its regions. This paper analyzes changes in the total number of events with damage (meteorological for the period 1991-2019 and agrometeorological – for 2004-2019), disaggregated by their types and by regions. The Mann-Kendall test is applied to detect statistical significance (0.05 level of significance, normal distribution). The results show an increase in the number of meteorological extreme events with damage for 1990-2019 in Russia from 130 to 257 events per year on average for the 1990s and 2010s, respectively, while the proportion of events with damage in relation to the total number of extreme events decreased over this period. We found statistically significant trends only for a few types of extreme events: hot and cold temperature, strong wind, heavy rain and droughts (increase by 0.9, 9.4, 11.4, 25.9 and 13.3 events/10 years, respectively). Number of heavy rain precipitation events is the only unidirectional stable growth trend. Unusual increasing trend in cold extreme events with damage in Russia can be attributed to the greater damage to the economy and population from cold extremes than hot ones. The regional distribution of trends across the territory of the Russian Federation is heterogeneous. However, significant changes in the number of extreme events of strong winds, heavy rains and soil drought by regions are statistically positive and observed mostly in some southern and central regions of European part and the Western Siberia. The development of adaptation plans to the negative effects of climate change is a first priority for these regions. A system for monitoring economic and non-economic damage from extreme events must be developed in Russia.

Reconstruction of the dispersal history and formation of modern ranges of various taxa is one of the actual problems of modern biogeography. Molecular genetic biogeography based on the analysis of phylogenetic relationships of taxa of different levels began to develop actively at the end of the XX century. Currently, this method is the most objective and represents the basis for reconstruction of scenarios of the origin and dispersal of various groups of plants. Due to recent transformation of views on the phylogenetic relationships of Pandanales, the reconstruction of tracks and modes of dispersal of representatives of the order Pandanales becomes an actual task. Representatives of all 5 families of Pandanales sensu APG IV were selected for the study and two cladograms were constructed. Based on the molecular-genetic cladistic method the region of hypothetical origin and probable dispersal scenarios of the families of the order Pandanales were determined. The order Pandanales is treated as originated in Laurasia and its differentiation began on the territory of Tibet. Dispersal of the representatives of the basal family Velloziaceae took place by long-distance transport via the Bering Land Bridge to South America (approximately 115 Mya). Velloziaceae dispersed in the New World vicariously in South America, then it was distributed to sub-Atlantic Africa by long-distance transport, and finally also vicariously to the east, south and north of the continent. It is shown, that the modern range of the representatives of rest Pandanales is the result of both types of dispersal – vicariously and long-distance transport.

Irrigated agriculture is the major determinant of economic growth potential as it accounts for 20% of the Gross Domestic Product (GDP) of the country. The current study focuses on the qualitative and quantitative assessment of groundwater in three districts i.e., Okara, Sahiwal and Khanewal of the Punjab province of Pakistan, which are considered highly fertile for agriculture production. The data were acquired from the Punjab Irrigation Department (PID) for 10 years (2010-2020) to assess the spatio-temporal patterns. The spatiotemporal mapping and variability of depth to the water table, electrical conductivity (EC), sodium absorption ratio (SAR), and residual sodium carbonate (RSC) were done as per the standards of the World Health Organization (WHO) and Punjab Irrigation Department using inverse distance weighting (IDW) statistical approach of GIS Techniques. The finding of the study revealed that overall water quality in the study area was reported as “fit” by following the WHO standards, whereas as per Punjab Irrigation Department standards, it was observed, as “Moderately fit”. Moreover, in Sahiwal, Okara, and Khanewal districts, the average depth of the water table declined from 2010 to 2015 by 0.619, 1.286, and 0.164 metres and then increased from 2016 to 2020 by 1.698, 1.421 and 0.830 metres, respectively. Although currently the quality and quantity of groundwater were not in critical condition, with continued carelessness and the release of additional water from aquifers, these conditions could deteriorate in the near future. So, developing a suitable mechanism for supplying surface water to farmers, and adapting environmentally acceptable methods of recharging aquifers is much needed.

This study aims to examine the impact of climate change on the water storage across the East European Plain, utilizing archived digital materials from several remote sensing satellites, including the Terra/Aqua (MODIS), the Global Precipitation Climatology Project, GRACE, and GRACE FO satellites, as well as data from digital maps of Selyaninov hydrothermal coefficients. The spatial resolution of the analyzed data ranged from 1x1 km to 250x250 km. Aiming to enhance the spatial resolution of Selyaninov coefficient maps, a new version of the Selyaninov hydrothermal coefficient was suggested, leveraging satellite remote sensing data. Both visual and computer analyses of these materials reveal a consistent reduction in water storage in the southern regions of the East European Plain, accompanied by a slight increase in the Novgorod Oblast. This information suggests that the non-chernozem region of the East European Plain will play a crucial role in supplying agricultural products to the population in the next decades. The observed stable water storage in the northern part of the East European Plain, encompassing the Komi Republic and the Novgorod Oblast, hints at the potential of increased agricultural production in these areas. However, achieving sustainable growth in agricultural production in these regions necessitates a focused investment policy.

Mitigating yield-scaled greenhouse gas emissions (YSE) is beneficial for enhancing crop yield, reducing greenhouse gas (GHG) emissions, and advancing climate-smart agronomic management practices. This study aims to evaluate the impact of different crop residue rates– 100% (R100), 50% (R50), and residue removal (R0) – on the YSE indicator within a maize-wheat cropping rotation under both conventional tillage (CT) and no-tillage (NT) systems in a semi-arid region. In the NT system, crop residues had a notable effect on the YSE indicator for wheat. Specifically, R0 exhibited a 39% and 20% decrease in YSE for wheat compared to R100 and R50, respectively. Interestingly, crop residue did not significantly influence YSE for maize under the NT system. On the other hand, in the CT system, YSE for maize in R0 was 33% and 25% lower than that in R100 and R50, respectively. Additionally, compared to R0, there were observed increases of 28% and 20% in YSE for wheat in R100 and R50 under the CT system, respectively. Our findings show that crop residue removal decreases YSE under both CT and NT systems. However, given that this practice degrades soil quality and results in lower yields, it is not considered a sustainable management practice compared to residue retention options. This research highlights the importance of evaluating GHG mitigation strategies by concurrently considering both emissions and crop production. Nevertheless, it is essential to conduct off-site assessments of GHG emissions from crop residue application and also engage in long-term studies to comprehend the full potential of crop residue management on YSE.

The spatial accessibility of educational services is important in planning and managing educational services. This study seeks to evaluate the spatial distribution of basic schools, find the optimal location for the distribution of those schools, and develop solutions and proposals to improve accessibility by creating new schools. p-median models were applied to allocate sites. After analysing the locations of schools and demand points (residential buildings) in the city of Mafraq, where this model tries to provide recommendations regarding the area that service should cover, the standards of the Ministry of Education were adopted; they stipulate that the distance between the site of the basic school and the residential building should range 750 m. Accordingly, two models were applied: The first scenario was applied to evaluate the current school sites, whereas the second suggested the establishment of new schools in underserved areas and the evaluation of the effectiveness of accessibility after the construction of new schools. The results of the study showed that the number of unserviced demand points according to the optimal criterion for distance of access is approximately 58.9%, while it decreased to 38% after proposing the establishment of 10 schools in new locations. The study concluded that the analysis of site allocation using p-median models is an effective method in the spatial planning of schools. It can assist decisionmakers and urban planners in improving accessibility to primary schools by establishing new schools and upgrading access to existing schools in underserviced areas..

The aim of this study is to provide a tool to assess sediment production in an urban area. The urban environment is affected by a variety of anthropogenic and natural factors that, in particular, lead to the sediment production. The storage of sediments in the urban landscape negatively affects the quality of the urban environment. The model was developed on the basis of landscape studies conducted in residential areas of six Russian cities. The model takes into account (1) the influence of precipitation, spring snowmelt, and vehicles, (2) the influence of erosion factors for two seasons: warm (t>5°C) and cold (t<5°C), and (3) the presence of disturbed surfaces. The application of the developed model to Ekaterinburg city conditions returned sediment production equal to 1.2 kg/m2/y. A comparison of seasonal values shows that sediment production in cold season is 2.5 times higher than in the warm season. In the absence of the disturbed surfaces, sediment production decreases to 0.44 kg/m2/y. Modeling showed a correlation between sediment production in Russian cities and duration of the cold season. The efficiency of various urban area maintenance practices and cleaning measures were evaluated in terms of sediment production and storage. The developed model presented in this paper is based on research in Russian cities, but can be applied to assess the formation of sediment and measures to reduce the value of its accumulation in the urban environment in different regions of the world.

The results of lidar sensing of aerosol pollution in St. Petersburg (Russia) were compared with ones located in Minsk (Belarus) and Kuopio (Finland) to assess the impact of large cities on atmospheric pollution by aerosol particles. For comparison, aerosol optical depth (AOD) data obtained at the three stations from 2014 to 2021 were used. Lidar sounding of atmospheric aerosols was carried out using aerosol Nd:YAG lasers operating at three wavelengths: 355, 532 and 1064 nm. Due to differences in the lidar station equipment characteristics and, consequently, in the lower limit for determining aerosols, the aerosol optical depth was compared in the range of heights from 800 to 1600 m at 355 and 532 nm. Since the compared stations do not have data for all years, the period from 2014 to 2016 was analyzed separately. The average annual AOD 355 in Minsk in the period 2014-2016 is almost the same as the average annual AOD in St. Petersburg. When comparing data in St. Petersburg and Minsk for the period 2014-2020, AOD 355 in St. Petersburg exceeds AOD 355 in Minsk by 1.46 times. AOD 532 nm in Minsk is larger than in St. Petersburg, regardless of the chosen comparison period. The average annual AOT 355 in Kuopio is lower than in Minsk and St. Petersburg by 2.1 times, while at a wavelength of 532 nm they are 3.6 times lower than in Minsk and 2.6 times in St. Petersburg. The calculated Angstrom exponent coefficient shows that the coarse mode in Minsk is higher than in St. Petersburg. The atmosphere over Kuopio has a lower content of aerosol particles. Since 2017, there was a steady excess of aerosol content over St. Petersburg compared to Minsk. Additionally, a comparison of the lidar data with the total AOD of AERONET stations located in Kuopio, Minsk and Peterhof (25 km from the lidar station in St. Petersburg) was carried out. The AOD obtained by lidar and AERONET method is in good agreement.

The aim of this article evaluate the long-term air quality in China based on the air quality index (AQI) and the air quality composite index (AQCI) though the multinomial logistic regression method. The two developed models employ different dependent variables, AQI and AQCI, while maintaining the same controlled variables gross domestic product (GDP), and a primary pollutant. Explicitly, the primary impurity is associated with one or more contaminants among six pollutant factors: O3, PM2.5, PM10, NO2, SO2, and CO. Model quality verification is an integral part of our analysis. The results are illustrate d using real air quality data from China. The developed models were applied to predict AQI and ACQI for the 31 capital cities in China from 2013 to 2019 annually. All calculations and tests are conducted using R-studio. In summary, both models are able to predict China’s long-term air quality. A comparison of the AQI and AQCI models using the ROC curve reveals that the AQCI model exhibits greater significance than the AQI model.

The results of a comparison of the PM_2.5 aerosol concentration daily variability for the summer and winter seasons at the urban and background monitoring sites in the Middle Urals for 2016–2019 are presented. The cluster analysis method revealed a statistically significant difference between the two groups corresponding to higher and lower concentrations of fine aerosol during the day. Studies of the daily variation of the PM_2.5 particle concentration in the Middle Urals indicate the leading role of meteorological characteristics (in particular, air temperature, pressure and wind speed) in changing the level of aerosol suspension in the air surface layer. Distinctive typical average daily concentrations of PM_2.5 for the Middle Urals region, corresponding to the cluster of lower values, are observed in the summer and are on average ~ 5.2 µg/m³ for the urban area and ~ 3.4 μg/m³ for the background site. In winter, these parameters are 12.8 μg/m³ for urban conditions and 10.5 μg/m³ for background site. The higher content of PM_2.5 particles, corresponding to the cluster of higher values, are identified in winter and are on average ~32.2 µg/m³ in urban conditions and ~ 30.3 µg/m³ in the background area. In summer, these parameters are 13.6 μg/m³ for urban site and 9.6 μg/m³ for background area. Simultaneous analysis of the fine aerosol concentrations and the meteorological parameters in the surface atmospheric layer allowed to define of weather conditions, at which the occurrence of higher PM_2.5 values is possible.

Studies on thermal power plant areas with respect to chemical composition of particulate matter deposited in snow cover are limited. This study aims to monitor (2014–2022) particulate load and trace elements associated with the particulate matter distributed around (0.5-4.5 km) the coal-fired thermal power plant in Karaganda. In this study, snow cover was used as an effective scavenger of atmospheric pollutants. Using instrumental neutron activation analysis and atomic absorption spectrometry, the content of 26 elements and Hg, respectively, was determined in the particulate phase of snow. The results showed that particulate load varied from 26 to 1751, with mean of 427 and a background of 47 mg m-2 d-1. Anthropogenic impact caused a significant increase in content of U, Hg, Ta, Zn, Na, Cr, Co, Sr, Rb, Cs, Sc, Ca, Fe, Nd, Ba (2–30 times) in the samples compared to the background. Metal-bearing phases of Zn, Ba, As, U-Ta-Nb were detected through scanning electron microscope. The highest levels of particulate load (169–1032 mg m-2 d-1) and element contents in the samples were localized up to 0.7 km from the thermal power plant. The changes of particulate load and element composition of snow deposits during the monitoring period were connected with temperature, modernization of dust-collecting equipment, composition of coal and fly ash, long-range transport of emissions from other industries. The element content and metal-bearing phases in the particulate phase of snow can be used as markers for identifying emission sources from coal combustion.

Accurate information on air quality serves as the foundation for making regulatory and legal decisions aimed at reducing air pollution. This study investigates the vertical distribution of dust particle concentration, their elemental composition, and size distribution in the atmospheric surface layer in Yekaterinburg. Over eight days in April 2021, 64 dust samples were collected on filters at heights ranging from 0.5 m to 10 m at a single site using a mobile post. The mass concentration of the dust, characterized by heterogeneous data with a coefficient of variation exceeding 30%, exhibited a weak tendency to decrease with height. The proportion of particles smaller than 1 µm decreased with increasing altitude, except for 10 m, where their proportion increased. Conversely, the concentration of p articles ranging from one to two microns decreased closer to the surface. Dust grains of other sizes were nearly evenly distributed at various heights. Dust particles smaller than PM2.5 accounted for approximately 45% of the total particles. X-ray fluorescence analysis identified 12 elements in dust particles, with S, Ca, and Fe showing the most substantial content. The proportion of most metals and Ca in solid particles decreased with height, while the content of S and As increased. The Cu, Zn, and Sb content in dust particles remained constant at all measured heights.