Wind erosion is one of the most significant forms of land degradation which occurs in arid and semi-arid regions. Agricultural land is significantly affected by wind erosion, which leads to soil quality reduction, and consequently to economic losses. This research was conducted in the autonomous province (AP) of Vojvodina (a region dominated by agriculture), which represents one of the most important economic regions in the Republic of Serbia. The aim of this research was to identify areas sensitive to wind erosion (in the month of March) in the AP Vojvodina by using fuzzy logic, remote sensing data, and geographical information systems (GIS). The data of prior research on erosion sediment were used for results validation. The results show that the hazardous sensitivity category covers approximately 60.41% of the research area, while the medium sensitive category accounts for 36% of the area. These findings are primarily a result of the lack of vegetation in almost the entire area, particularly in wind-exposed agricultural areas with no vegetation, which are being prepared for sowing. Another factor putting such a large area at risk is the unfavorable climate (especially in southeastern parts of the area), and slightly less favorable soil properties in the north. The results of this research could be used in decision-making at the regional level, along with the development and implementation of programs aimed at mitigating the effects of wind erosion.
Conserving clean and safe freshwater is a global challenge, with nitrogen (N) and phosphorus (P) as frequent limiting factors affecting water quality due to eutrophication. This paper provides a critical overview of the spatiotemporal variability in both nutrient concentrations and their total mass ratio (TN:TP) in the canal network of the Hydro system Danube–Tisza–Danube at 21 measuring locations monitored by the Environmental Protection Agency of the Republic of Serbia over a length of almost 1000 km, collected once a month during the last decade. A spatiotemporal variation in nutrient concentrations in the tested surface water samples was confirmed by correlations and cluster analyses. The highest TN concentrations were found in winter and early spring (non-vegetation season), and the highest TP concentrations in the middle of the year (vegetation season). The TN:TP mass ratio as an indicator of the eutrophication pointed out N and P co-limitation (TN:TP 8–24) in 64% of samples, N limitation (TN:TP < 8) was detected in 27% and P limitation (TN:TP > 24) in the remaining 9% of water samples. Such observations indicate slow-flowing, lowland water courses exposed to the effects of non-point and point contamination sources as nutrient runoff from the surrounding farmlands and/or urban and industrial zones, but further investigation is needed for clarification. These results are an important starting point for reducing N and P runoff loads and controlling source pollution to improve water quality and underpin recovery from eutrophication in the studied watershed.
Land degradation is a complex issue caused by diverse drivers, each of which should be considered in the analysis of land sensitivity to degradation. This study identifies the areas most sensitive to land degradation in the Grdelica Gorge and Vranjska Valley, which are unique in terms of natural and socioeconomic conditions. Land-use changes and inappropriate land management have led to serious degradation in this region. The flexible and multifactorial approach of the Mediterranean Desertification and Land Use (MEDALUS) model allowed comprehensive land degradation sensitivity analysis in the study area. The main factors driving soil degradation were assessed by estimating climate quality index, soil quality index, and vegetation quality index, and the main socioeconomic indicators by management quality index and social quality index. The results showed that forest cover is the main factor to contrast land degradation, and even minor adverse changes in forest characteristics, such as structure, canopy cover, health, and quality, could trigger degradation processes. The vegetation quality index was defined in terms of the current vegetation's capacity to protect soil from erosion, drought resistance, and fire risk. Detailed data on forest vegetation cover was obtained from the National Forest Inventory (NFI). The environmentally sensitive area (ESA) index generated through the analysis classified 26.11% of the total study area as critical, 69.53% as fragile, and 2.70% as either prone to or unaffected by degradation processes. According to the ESA index, the areas covered by forests with optimal species composition and high canopy cover were the least susceptible to degradation. The areas under intensive agricultural production without any application of conservation measures were the most susceptible to degradation. Future strategies for optimal land-use patterns are discussed, such as the intergration of woody species in croplands to protect soil against degradation and meet human needs in the areas prone to degradation.
Background: Anthropogenic activities have clearly affected the environment, with irreversible and destructive consequences. Mining activities have a significant negative impact, primarily on soil, and then on human health. The negative impact of the first mining activities is represented even today in the soils of those localities. Research shows that, for different types of mines, the concentrations of potentially toxic elements (PTEs) are high, especially in antimony, multi-metal and lead–zinc mines, which have adverse effects on the environment and then on human health and the economy. A large flood in 2014 in Western Serbia resulted in the breaking of the dam of the processed antimony ore dump of the former antimony mine, causing toxic tailings to spill and pollute the downstream area. Due to this accident, tailings material flooded the area downstream of the dump, and severely affected the local agriculture and population. Methods: Potentially toxic elements content, pollution indices and health indices were determined in soil samples from the flooded area, using referenced methodologies. The sources and routes of pollutants and risks were determined and quantified using statistical principal component analysis, positive matrix factorisation, and a Monte Carlo simulation. Results: The main source of As, Cd, Hg, Pb, Sb and Zn in the upper part of the study area was the tailing material. Based on the pollution indices, about 72% of the studied samples show a high risk of contamination and are mainly distributed immediately downstream of the tailings dump that was spilled due to heavy rainfall. Conclusions: Although the content of the PTEs is high, there is no non-carcinogenic risk for any PTEs except As, for which a threshold risk was determined. There is no carcinogenic risk in the study area.
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