Development of enhanced method of geospatial electrical intelligence of near-surface soil layers in Northern Kazakhstan for detecting pollution sources
DOI:
https://doi.org/10.15587/1729-4061.2025.322818Keywords:
soil electrical conductivity, digital processing, experimental data, coal dust, transport and logistics flows, rail transportationAbstract
This study focuses on the near-surface soil layers in suburban areas of Astana, Northern Kazakhstan, to address the critical issue of soil pollution caused by anthropogenic activities, particularly coal dust dispersion from open railway freight transportation. Existing geophysical methods for soil conductivity measurement lack precision due to interference from upper soil layers and seasonal moisture variations, limiting reliable pollution source identification.
To enhance the precision of measurements, researchers modified the measuring probes. This improvement, combined with geophysical studies and Global Positioning System topographic referencing, allowed for identifying new patterns in pollutant behavior. A strong correlation was established between electromagnetic anomalies and human activities, including transportation, logistics, and urbanization.
The study revealed that soil electrical conductivity near railway tracks was three times higher due to coal dust, with peak values reaching 4.8 mS/m in spring. Modified probes improved measurement accuracy by 28–32 % depending on the season, enabling precise detection of subsurface pollution patterns.
The findings provide insights into urban pollution dynamics and its long-term effects.
Based on experimental data, recommendations were developed such as transition to renewable energy will reduce coal dependency and pollution.
In conclusion, the study highlights key issues surrounding soil pollution and provides recommendations to mitigate its effects. This approach supports sustainable land management, regulatory enforcement, and pollution mitigation strategies in urban-suburban interfaces worldwide
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