Examinando por Materia "Ecological risk assessment"

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Ecological and carcinogenic risk assessment of potentially toxic elements in rangelands and croplands around Lake Junin (Peru): Integrating remote sensing, machine learning, and land cover segmentation
(Elsevier, 2025-08-27) Pizarro Carcausto, Samuel Edwin; Requena Rojas, Edilson Jimmy; Barboza, Elgar; Peña Elme, Eunice Dorcas; Arias Arredondo, Alberto Gilmer; Ccopi Trucios, Dennis
The Junín Lake basin, a critical high-altitude ecosystem in the central Peruvian Andes, faces severe contamination from potentially toxic elements (PTEs) driven by mining activities, agriculture, and urbanization. This study evaluates the spatial distribution, ecological risk, and human health implications of 14 heavy metals, metalloids, and trace elements in surface soils surrounding the lake. Using 211 soil samples, we integrated remote sensing, land cover classification, and Random Forest machine learning models with spectral, edaphic, topographic, and proximity-based environmental covariates to predict contamination patterns and assess risk. Results reveal extreme contamination, with arsenic (As), lead (Pb), cadmium (Cd), and zinc (Zn) concentrations exceeding ecological thresholds by over 100-fold in agricultural zones. Ecological risk assessments using contamination degree (mCD), pollution load index (PLI), and risk index (RI) indicated that over 99 % of the study area exhibits very high to ultra-high contamination levels. Human health risk analysis identified unacceptable carcinogenic risks from As, Pb, and Cr across adult and pediatric populations, with arsenic presenting the greatest concern. The integration of geospatial tools and machine learning enabled precise identification of contamination hotspots and vulnerable land cover types, demonstrating the value of AI approaches for monitoring contaminated territories. These findings underscore the urgent need for coordinated environmental management, targeted remediation strategies, and community-based monitoring to protect public health and preserve Andean ecosystem integrity.
Ecological risk associated with potentially toxic elements in agricultural soils across coastal and highland valleys
(Elsevier Ltd., 2026-05-06) Pérez Porras, Wendy Elizabeth; Ccopi Trucios, Dennis; Flores Marquez, Ricardo; Carbajal Llosa, Carlos Miguel; Pizarro Carcausto, Samuel Edwin
Soil elemental composition in heterogeneous agroecosystems is shaped by interacting environmental and anthropogenic controls. This study evaluated the spatial variability of potentially toxic elements (PTEs: Cu, Cr, Fe, Mn, Mo, Ni, Pb, V, Zn, As, and Cd) across coastal (Chancay and Pativilca) and highland (Mantaro and Tarma) agricultural valleys of Peru. A stratified sampling design was combined with multivariate analyses (PCA, PERMANOVA, PERMDISP, and variance partitioning) and ecological risk assessment using integrated indices (PLI, mCd, SRI, and Nemerow index). The first two principal components explained 50.2% of total variance (PC1 = 36.8%; PC2 = 13.4%), reflecting distinct soil–geochemical and climatic–spatial gradients. The Valley × Zone interaction significantly structured elemental composition (R² = 0.049, p = 0.011), whereas crop type showed no significant effect (p = 0.838). Variance partitioning indicated that soil physicochemical, climatic, and spatial/topographic predictors jointly explained 60% of total variation (adjusted R² = 0.597), with the three-way shared fraction accounting for 28%, highlighting strong coupling among pedogenic, climatic, and topographic drivers. Ecological risk indices revealed clear spatial differentiation between systems. Highland valleys exhibited greater contamination intensity, spatial heterogeneity, and more frequent high-risk categories according to PLI, mCd, and SRI. In contrast, coastal valleys showed more homogeneous and diffuse accumulation patterns associated with long-term agricultural intensification. These findings underscore the need for regionally adapted soil monitoring frameworks that incorporate environmental gradients in the assessment and management of PTE-related ecological risk in agricultural landscapes.