Issue |
E3S Web Conf.
Volume 548, 2024
X International Conference on Advanced Agritechnologies, Environmental Engineering and Sustainable Development (AGRITECH-X 2024)
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Article Number | 01018 | |
Number of page(s) | 8 | |
Section | Agritechnologies and Agritech Engineering for Sustainable Environmental Health | |
DOI | https://doi.org/10.1051/e3sconf/202454801018 | |
Published online | 12 July 2024 |
Ecological assessment of bottom sediments for conditions of an agro-industrial region with high anthropogenic load
Belgorod State National Research University, Institute of Earth Sciences, 85 Pobeda Street, Belgorod, 308015, Russia
* Corresponding author: fnliset@mail.ru
Areas of active farming undergo significant soil erosion atcatchments and pollution of surface waters and bottom sediments. Whenthese issues in mining regions are coupled with the effects of drainage waterand dust emissions from open-pit mining, it becomes critical to evaluate andmonitor contamination of water bodies and bottom sediments. The aim ofthis work was to compare the ecological and geochemical characteristics ofsediments in water bodies within the Kursk Magnetic Anomaly (KMA),which has open-pit mining, with rivers and ponds affected by agro-industrialeffluents, excluding the impact of drainage water. The concentrations ofseveral heavy metals (Pb, Zn, Cu) and organic matter content in bottomsediments were greater in the Belgorod Oblast than the iron ore district.When using indicators of regional background for KMA water bodies, theman-made impact on sediment pollution was determined, which is reflectedin excess concentrations of Mn, Zn, Cu (from 1.5 to 2.8 times). Research ofsurface and groundwater transformations, their interactions, and thepeculiarities of pollutant migration provide the foundation for developing amonitoring system for water bodies affected by mining operations to supportmanagement decision-making.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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