Аңдатпа
Introduction Urban soils in long-established mining and metallurgical cities represent persistent reservoirs of potentially toxic elements (PTEs), posing long-term ecological and human health risks. Ust-Kamenogorsk (Oskemen), one of Kazakhstan’s major non-ferrous metallurgical centers, has experienced more than seven decades of intensive ore processing and smelting. Although previous studies reported elevated concentrations of Cd, Pb, Zn, and Cu, a comprehensive assessment integrating contamination status, ecological risk, spatial variability, and environmental controls has remained limited. Methods Surface soils from 29 sampling sites representing industrial, urban, and background functional zones were analyzed for Zn, Cu, Cd, and Pb. Contamination was evaluated using the contamination factor (CF), geoaccumulation index (Igeo), pollution index (PI), Nemerow pollution index (PN), ecological risk factor (Er), and potential ecological risk index (RI). Spatial patterns were mapped using inverse distance weighting (IDW), while Spearman correlation analysis, principal component analysis (PCA), and non-metric multidimensional scaling (NMDS) were used to evaluate relationships among heavy metals, soil properties, and contamination patterns. Results Heavy metal concentrations ranged from 5.2-1675.0 mg kg - ¹ (Zn), 0.3-57.8 mg kg - ¹ (Cu), 0.8-39.0 mg kg - ¹ (Cd), and 0.7-59.5 mg kg - ¹ (Pb). Industrial soils exhibited pronounced polymetallic contamination, with Zn dominating overall enrichment and Cd contributing most to ecological risk. The maximum RI reached 2188.9, while the mean RI (674.9) indicated a generally very high ecological risk. Spatial analyses identified contamination hotspots surrounding major metallurgical facilities. Significant correlations among Zn, Cd, and Pb (ρ = 0.68-0.90, p < 0.001), together with PCA and NMDS, were consistent with a strong anthropogenic influence, whereas pH, organic carbon, carbonate content, and soil texture significantly influenced metal accumulation. Discussion The integrated assessment demonstrates that combining pollution indices, ecological risk metrics, spatial modeling, and multivariate statistics provides a robust framework for identifying contamination hotspots and environmental drivers of legacy pollution. These findings provide a scientific basis for environmental monitoring, risk-based remediation, and sustainable urban land management in long-established metallurgical cities.