This paper describes a five-month experiment (February – July 2021) measuring the gradual thaw diffusion of radon-222 (further in the article – radon) from a frozen environment in NW Russia (i.e. Arhangelsk region). Red clay substrate containting a high content of 226Ra filled the bottom insides of 200-liter barrel holding the source of radon and buried at 1.6 m depth (e.g., the radium source zone), then covered with native soil, filled with water and frozen under in-situ conditions. Radon measurements were carried out from soil surface above the container (disturbed soil layer) and at background location (undisturbed soil layer). Several periods of increased radon flux density were observed, which was related to radium source zone thawing. It was shown that in 1-2 days after thawing of the radium source zone and drying of the upper soil layer, the radon flux increases sharply – more than 8 times compared to background values. These results show a strong relationship between radon flux density and soil temperature profiles at different depths. The calculations of radon sourced from frozen and thawed zones show how temperature phase of substrate (e.g. clays) control the barrier influence of radon migration. It reduced them by 10-20 times (according to the results of a theoretical calculation), depending on the characteristics of frozen rocks (density, porosity). Thus, the barrier function of permafrost is related to the physical properties of ice and frozen rocks. These temperture phases controls radon emanation coefficients and significantly influences the migration of radon to the earth’s surface.

Широко используемые официальные региональные символы позволяют повысить осведомленность о животных, что необходимо для их эффективного сохранения и развития экотуризма. Оценивалось наличие животных на гербах регионов России. Выяснилось, что на 49 % из них изображены фигуры животных, а эти районы составляют 76,3 % территории страны. На проанализированных гербах изображено около двадцати животных, из которых 63% млекопитающие. Наиболее распространены медведи (в том числе полярные), орлы и куницы. Также показаны некоторые редкие и находящиеся под угрозой исчезновения виды, такие как амурский (сибирский) тигр и кавказский леопард. На большинстве региональных гербов изображено только одно животное, а две или три фигуры животных встречаются вместе только в нескольких случаях. Географическое распространение животных, изображенных на региональных гербах, лишь отчасти совпадает с истинными зоогеографическими закономерностями. Это ожидаемый вывод, потому что гербы являются элементами культурного пространства, даже если они представляют собой природные объекты. Хотя региональные гербы отражают небольшую часть совокупности животных России и выбор животных не всегда соответствует истинным потребностям сохранения, этот вспомогательный «канал» продвижения знаний о животных представляется ценным.

Motor vehicle emissions are the primary air pollution source in cities worldwide. Changes in traffic flow in a city can drastically change overall levels of air pollution. The level of air pollution may vary significantly in some street segments compared to others, and a small number of stationary ambient air pollution monitors may not capture this variation. This study aimed to evaluate air pollution before and during a new traffic plan established in March 2019 in the city of Kandy, Sri Lanka, using smart sensor technology. Street level air pollution data (PM2.5 and NO2 ) was acquired using a mobile air quality sensor unit before and during the implementation of the new traffic plan. The sensor unit was mounted on a police traffic motorcycle that travelled through the city four times per day. Air pollution in selected road segments was compared before and during the new traffic plan, and the trends at different times of the day were compared using data from a stationary smart sensor. Both PM2.5 and NO2 levels were well above the World Health Organization (WHO) 24-hour guidelines during the monitoring period, regardless of the traffic plan period. Most of the road segments had comparatively higher air pollution levels during compared to before the new traffic plan. For any given time (morning, midday, afternoon, evening), day of the week, and period (before or during the new traffic plan), the highest PM2.5 and NO2 concentrations were observed at the road segment from Girls High School to Kandy Railway Station. The mobile air pollution monitoring data provided evidence that the mean concentration of PM2.5 during the new traffic plan (116.7 µg m-3) was significantly higher than before the new traffic plan (92.3 µg m-3) (p < 0.007). Increasing spatial coverage can provide much better information on human exposure to air pollutants, which is essential to control traffic related air pollution. Before implementing a new traffic plan, careful planning and improvement of road network infrastructure could reduce air pollution in urban areas.

Information regarding land use and land cover is an important for formulating decision making for land information system. The easiest and most effective way to gather such information is via using Earth observation remote sensing satellites supported by ground data. Synthetic Aperture Radar (SAR), due to its additional unique intrinsic characteristics is favoured over the optical systems for procuring land information. An innovative and effective technique for land feature detection is the use of polarimetric capabilities of SAR. Generally applicable for quad polarized data, this study investigates the polarimetric capabilities of a dual polarized data obtained from ALOS PALSAR, which is not a general notion. The approach applied in the study shows accurate results for detection of land features using polarimetric decomposition of dual polarized ALOS PALSAR data over an area of Munger in the state of Bihar, India. Twelve distinct land cover features are identified in the study area using this approach. The polarimetric products are also investigated for deriving the biomass information for the vegetation cover in the study area. The relation between in-situ biomass generated from floral species-specific volumetric equations and SAR polarimetric products showed a moderate correlation of 0.56 with RMSE=29.13 t/ha and data agreement of 0.62 based on exponential regression model for predicting biomass. The decomposition parameters revealed more evidences for forest structure and feature identification rather than biomass information. The method adopted in the study can be well utilized for land resource information and mapping; hence, natural and man-made resource monitoring and management.

Urban Green Spaces (UGS) curtails all environmental issues and ensure an eco-friendly locale. Similarly, the emergence of UGS is very helpful to cope with emerging urban flooding in cities by setting up the world standard of green space ratio (20 to 25 percent of the area) and green per capita (9m2 ) in a geographical area. Therefore, the present study is conducted to evaluate the causal effect relation of UGS with the frequency of urban flooding. For this purpose, 69 selected union councils are taken as a study area in District Lahore, Pakistan. The relation between UGS and the occurrence of floods is evaluated using geo-statistical and geospatial analysis techniques during the monsoon rainfalls from 2013 to 2019. Furthermore, the data sets of sore points (inundated areas), occurrences of urban flooding (number of event occurrences), green per capita, and green ratio are used. Results revealed that selected union councils in Lahore don’t have enough urban green spaces. There is only a 51 sq km area with adequate UGS that accounts for only 18 percent of the study area. The rest of the area does not meet the world standards of green area. There are some areas including Ravi town, Gulberg town, and Samanabad town with green per capita more than 4 green per capita. On the other hand, there are only 02 union councils including Race Course and Model Town that are comprised of a 20 percent green area. The findings of the study will be helpful for proper urban planning and strategies i.e. with greener structures.

Zinc is an essential nutrient for humans, animals, and plants. Zinc uptake by crops is dictated by zinc availability in the soil, which in turn may be dictated, at least in part, by soil mineralogy. Little is known about the phytoavailability of Zn in Andisols, which are important agricultural soils in volcanic regions, such as Japan, New Zealand, and southern Chile. In this study, we assessed the vegetative growth response of perennial ryegrass (Lolium perenne, L.) to Zn fertilization in an Andisol from southern Chile. Ryegrass was grown in a greenhouse pot experiment with twelve rates of Zn application from 0 to 6075 mg Zn/kg soil. After 63 days, shoot length, specific leaf area, and biomass were measured. Foliar Zn concentrations were measured and correlated with plant-available Zn as measured by a diethylenetriaminepentaacetic acid (DTPA)-soil extraction (DTPA-Zn hereafter). Zinc toxicity to ryegrass was assessed using the Toxicity Relationship Analysis Program. This study demonstrated that a DTPA-Zn level of 1 mg Zn/kg soil was not limiting for ryegrass growth. Although Zn fertilization did not improve ryegrass growth in the studied Andisol, this study still has practical implications. Zinc deficiency in humans is a global problem and increasing Zn in staple food and forage crops may require Zn fertilization. This study suggests that Andisols can be fertilized with high doses of Zn without a risk of causing Zn toxicity to crops. However, a DTPA-Zn level of >489 mg Zn/kg soil decreased shoot length, indicating a toxicity response.

Lakes are features found in Brazil’s northern region, commonly formed in sandy-clay layers of the Plio-Pleistocene, in a setting of the extensive flat surface, and under a high precipitation rate. Our goal in this work is to understand the sediment transport dynamic and its relation to the hydrological behavior of the regional lacustrine system. Two lakes were selected, Lago do Italiano (LIT) and Lago do Bicho (LB), situated in the municipality of Bonfim in the state of Roraima, Brazil. The lakes differ in hydrological regime, depth, and vegetation. The methodology involved bibliographical and remote sensor data and field surveys followed by laboratory processing. The results revealed that the lakes are composed of sandy materials, with layers what reach 95% of sand. The grains is medium to fine texture, with morphology angular (0 a 50%) and subangular (18% a 43%) grains, disposed at different depths. The grains’ morphology suggests that their sediment provider source is near and, at the same time, indicates a low energy environment. Concerning the mineralogical attributes, the sediments are of a quartzose nature, which permits their correlation with the arenites of the Boa Vista Formation, a sub-cropping unit. The sediment input is controlled by the seasonal oscillation of the groundwater level and inundation pulses that reach the fluviolacustrine plain of the Tacutu River in which the lakes are inserted.

The Covid-19 pandemic affects many areas of life, including the tourism sector. Furthermore, it significantly reduced the number of people visiting tourist destinations, and the reduction has helped to improve the environment in the National Park. Therefore, this study aims to present a satellite image classification method using Support Vector Machine to identify changes in the vegetation area of Komodo National Park. The satellite image used was created with Google Earth Pro with a resolution of 1920 x 1280 pixels using data collected in 2019 and 2020 before and during the pandemic. This study focuses on six tourist destinations in Komodo National Park: Loh Liang, Loh Buaya, Padar Island, Kanawa Island, Pink Beach, and Loh Sebita. The image was pre-processed using radiometric calibration, atmospheric correction, and contrast enhancement. The results of the pre-processing showed that segmentation will be performed to distinguish the area between one class and another. Furthermore, the image will be classified into five classes using the Support Vector Machine, including Soil, Vegetation, Built-Up Area, Deep Water, and Shallow Water. The measurement of the area of vegetation from 2019 and 2020 using Otsu’s thresholding showed environmental changes. Meanwhile, environmental improvements occurred in seven areas in the vegetation area category, with a 31.86% rise from 2019 to 2020. The increase in the area of green areas in the Komodo National Park all because tourist restriction and there is no climate fluctuations during the time of study.

The article presents the results of study of the application of machine learning methods to the problem of classification and identification of different river water regimes in a large region – the European territory of Russia. An accumulation of hydrological observation data for the 60 – 80 years makes it possible to create an information basis for such studies. The article uses information on the average monthly runoff at 351 hydrological gauges during the period from 1945 to 2018. The most widely used data clustering approaches were used as analysis methods – K-means, EM-method, agglomerative hierarchical clustering, DBSCAN algorithms and the application of gradient boosting methods (CATBUST). Clustering and classification algorithms were given eight parameters as a basis for prediction. It was found that the most distinct and stable clusters are formed with three parameters, and the highest silhouette coefficient (SS = 0,3-0,5) is obtained using the numbers for months of the maximum and minimum runoff and the ratio of the maximum to the minimum water flow. The best result gives DBSCAN (SS = 0,6 – 0,7). Supervised classification models also show high correspondence with the reference classification, with an accuracy of 87%. Both clustering methods and classification methods showed a shift of clusters representing southern water regimes. In the central region these regimes expanded by a 1000 km to the north. Furthermore, results demonstrate that currently available data already makes it possible to apply machine learning methods to the analysis of hydrological data. Clusters corresponding to different types of water regime can be obtained by utilizing contemporary clustering algorithms. The study shows that over the past 40 years, the southern types of water regimes have noticeably shifted to the north.

Floods are increasingly affecting cities around the world. As a result, displacement and resettlement of floodaffected households have become the norm in many parts of the world. While resettlement may be necessary to address flood vulnerabilities, including protecting the lives of those affected, empirical studies on the post-resettlement well-being of the resettled population are scarce. This paper presents empirical findings on the livelihood situation of flood-resettled households in Dar es Salaam. The results are based on key informant and household interviews and focus group discussions with resettled households. The findings show that the resettlement area’s location in the peri-urban of the city resulted in various challenges, including inaccessibility to basic facilities and high transportation costs, with households spending an average of TZS 2,000 (~US$1) to reach a public transportation facility, i.e., a bus stand. Resettled households also have lower income levels ranging from less than TZS 50,000 (12%) to between TZS 50,000 and TZS 500, 000 (75%). While weak social ties, a lack of trust among household members, and the social stress of loss of privacy were typical challenges among resettled households, vulnerable groups, particularly women and children, were exposed to increased vulnerability. The observed post-resettlement livelihood situation is influenced by the pre-resettlement conditions of the households, characterized by large household sizes ranging from 5 to 6 members (55%) to more than seven members (35%), low education levels (77%), and informal employment, largely petty trading (56%). The paper suggests that when resettling flood-affected households, the context-specific characteristics of the affected population, such as demographic and socio-economic characteristics, and their needs, be considered to improve post-resettlement livelihood sustainability.

In this study, we discussed relationship between the vertical and spatial differentiation of 14 chemical elements (total content and three mobile fractions extracted by NH4 Ac, NH4 Ac with 1% EDTA and 1M HNO3 ) and the environmental factors in background Retisols and Stagnosols within a soil catena. In the A soil horizon, the extractability of elements decreased in the series Cd, Mn, Pb> Co, Ni, Cu, Fe> Zn, Bi, As> U, Cr, Mo> Sb. In the O and A horizons, total and exchangeable Mn and Zn were uptaken by plants. In the A horizon, total Bi, Cd, Pb, Sb, Mo, exchangeable As, Bi, Cd, Co, Ni, Mo, as well as As, Cd, Cu, Pb, Zn, Sb bound with Fe-Mn (hydr)oxides were sorbed by soil organic matter; Cr, Fe, Mn formed the organic complexes. In the C horizon, Cd, Fe, Mn, Sb complexes co-precipitated with carbonates. In the Bt horizon, total Cr, Cu, exchangeable Cu, Ni, as well as Cr and U bound with Fe-Mn (hydr)oxides migrated due to the lessivage. On the toeslope’s biogeochemical barrier, exchangeable Zn, Mo bound with complexes, As, Bi, and Fe bound with Fe-Mn (hydr)oxides were accumulated. In the lower part of the catena, peat accumulated the exchangeable compounds of As, Bi, Cr, Fe, Mo, Pb, U. The spatial differentiation of elements became less contrasting from the O and A horizons to the E, B and C horizons.