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Soil contamination with potentially toxic elements (PTEs) in the Malwa region belt of Punjab, India, can be a serious concern as a result of intensive agricultural practices and overuse of agrochemicals. The main objectives of the present study were to evaluate the spatial distribution, geochemical signature, and contamination level/health risk of PTEs in 76 soil samples (0–10 cm) collected from the three districts viz. Muktar, Faridkot, and Moga of Punjab, India. The result shows that PTEs concentrations vary widely in the region, with Fe and Mn distribution patterns being mostly coherent with each other. When compared to the Indian natural soil background values, the average concentration of Pb and Zn were higher than the limit, only Pb exceeded the average values of the world background and upper continental crust (UCC). Spatial autocorrelation plotted with a local indicator of spatial association (LISA) in GeoDa software version 1.18 was used to identify hotspots. A positive spatial autocorrelation (>0.2) was indicated with Moran's I values for Pb, V, Mn, Cu, and Cr, being highest for Pb. A principal component analysis (PCA) identified the major geo-chemical patterns of Fe-Al-V-Cr and TOC-Mn-Zn-HCO3−, which were positively loaded on PC1. This indicates that Fe/Al-oxyhydroxides and organic matter play a dominant role in controlling metal mobility in soils. This can be further substantiated with the Spearman's rank correlation values. The contamination factor (CF) indicates that only Pb and Zn (15.7% and 3.9% samples, respectively) were under high risk. This could be due to the excessive application of chemical fertilizers. The large range of degree of contamination (Cdeg) values suggests that there are variations in the degree of soil pollution due to PTEs. A little over 3.9% of samples had significant contamination, compared to 72.3% of samples with low contamination and 23.6% of samples with moderate contamination. Human non-carcinogenic and carcinogenic risk levels were investigated. The hazard index (HI) values for adult ranged from 0.00 to 0.2, and values for children ranged from 0.009 to 1.2. These findings suggest that both children and adults are not at potential risk, except in a few locations. Overall, the results of this study provide the current baseline status of toxic elements in agricultural soil. This would be helpful for developing strategies for sustainable management of the soil resources in the region, as well as for future monitoring programs of the soil quality in the Malwa region as a whole, to track any changes in the contamination levels over time. [ABSTRACT FROM AUTHOR]

Soil degradation in Odisha poses a significant conservation concern for the local environment. The present research focused on a region in central Odisha State, India, affected by drought conditions. Several models have emerged to assess soil loss, with the Revised Universal Soil Loss Equation (RUSLE) standing out as the most suitable option. The erosion computation process entails utilizing the digital elevation model (DEM), Landsat-9 imagery, and soil data from several sources accessible in different forms and scales. The present analysis took into account various elements, namely, crop management factor (C), practice management factor (P), slope length factor (LS), steepness factor of the slope (S), and rainfall factor (R). Multiplying these factors yielded the average rate of soil erosion. Areas with a high slope length factor, such as those in Kandhamal, Kalahandi, and Nuapada, have a high erosion rate. The study reveals that 57% of the land in the study area experiences very low to moderate soil erosion at a rate of 2–10 tons per hectare per year, while 43% faces moderately to very severe erosion at a rate of 10–25 tons per hectare per year. Erosion hotspots, covering 32,205 square kilometers, are mainly identified in agricultural and forested hilly areas where slopes exceed 10°, such as those in Kandhamal, Kalahandi, and Nuapada, which have a high erosion rate. These districts are especially vulnerable to soil loss and resulting climate action (Sustainable Development Goals-13) because of frequent and severe rainfall, shifting agricultural practices, a thin surface soil covering, natural erosion, and barren hills. The research emphasizes the urgent need for implementing conservation and management measures to protect high-risk areas from further degradation. In conclusion, the study underscores the effectiveness of the RUSLE-GIS model in conducting quantitative and spatial assessments of soil erosion on a river watershed scale. The model is deemed crucial in formulating conservation strategies to address the identified erosion issues in the tropical highlands of the area. [ABSTRACT FROM AUTHOR]

Trace element pollution of soils surrounding coal-mining areas affects the health of local communities. The increasing coal-mining and associated activities in the Raniganj basin (east India) have led to increased soil concentration of certain trace elements. To quantify the elevated trace element (TE) concentrations in the soil surrounding coal-mining areas, 83 surface soil, coal, and shale samples were collected from open-cast mining areas of the eastern Raniganj basin. The soils present are sandy silt, silty sand, and silty in nature, but almost no clay. They are acidic (pH = 4.3) to slightly alkaline (pH = 7.9) with a mean electrical conductivity (EC) of 340.45 µS/cm and a mean total organic carbon (TOC) of 1.80%. The northern and western parts of the study area were found to be highly polluted by certain metallic trace elements. The relevant environmental indices, geoaccumulation index (Igeo), contamination factors (CF), enrichment factors (EF), and pollution load index (PLI) were calculated and assessed. Analysis revealed that Cr was highly enriched in these soil samples, followed by Pb, Co, Cu, Cd, Fe, Ni, Mn, Zn, As, and Al. Geostatistical analyses (correlation coefficients and principal component analysis) indicated that the occurrence of some trace elements (Al, Cd, Co, Cu, Fe, Mn, Ni, and Zn) is most likely linked to the various coal-mining operations in the study area. However, the anomalous Cr and Pb distributions are likely influenced by other anthropogenic, mainly industrial, inputs besides coal mining. These results justify the adoption of rigorous soil monitoring programs in the vicinity of coal-mining areas, to identify pollution hotspots and to develop strategies to reduce or mitigate such environmentally damaging pollution. [ABSTRACT FROM AUTHOR]