No abstract

The concentration of heavy metals such as Ba, Co, Cr, Cu, Ni, Pb, Rb, Sr, V, Y, Zn, Zr were studied in soils of Balanagar industrial area, Hyderabad to understand heavy metal contamination due to industrialization and urbanization. This area is affected by the industrial activities like steel, petrochemicals, automobiles, refineries, and battery manufacturing generating hazardous wastes. The assessment of the contamination of the soils was based on the geoaccumulation index, enrichment factor (EF), contamination factor, and degree of contamination. Soil samples were collected from Balanagar industrial area from top 10-50 cm layer of soil. The samples were analyzed using X-ray fluorescence spectrometer for heavy metals. The data revealed that the soils in the study area are significantly contaminated, showing high level of toxic elements than normal distribution. The ranges of concentration of Cr (82.2-2,264 mg/kg), Cu (31.3-1,040 mg/kg), Ni (34.3-289.4 mg/kg), Pb (57.5-1,274 mg/kg), Zn (67.5-5819.5 mg/kg), Co (8.6-54.8 mg/kg), and V (66.6-297 mg/kg). The concentration of abovementioned other elements was similar to the levels in the earth's crust pointed to metal depletion in the soil as the EF was \1. Some heavy metals showed high EF in the soil samples indicating that there is a considerable heavy metal pollution, which could be correlated with the industries in the area. A contamination site poses significant environmental hazards for terrestrial and aquatic ecosystems. They are important sources of pollution and may results in ecotoxicological effects on terrestrial, groundwater and aquatic ecosystems.

In a case history from the Mahanadi basin (India), we demonstrate the use of resistivity data from electric-log soundings and from borehole logs to discriminate between saltwater and freshwater aquifers. We use interpreted data from eight surface-based vertical electrical soundings (VES) and electric well logs from three boreholes in this study. We establish a quantitative relation among longitudinal unit conductance S (obtained from VES), water resistivity [Formula: see text], and layer thickness h. We show that ambiguities in resistivity data interpretation limit its ability to distinguish between freshwater and saltwater aquifers. Electric well-log data interpretation is much more accurate but requires boreholes, which are not cost effective when exploring for groundwater. Integrating well-log-based estimates of [Formula: see text] into resistivity interpretation of surface-based soundings improves its ability to discriminate freshwater aquifers while maintaining cost-effective exploration.