Sources, Contamination and Risk Assessment of Heavy Metals in Riparian Soils of the Weihe River Based on a Receptor Model and Monte Carlo Simulation DOI Open Access

Wen Dong,

Bohan Niu,

Huaien Li

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10779 - 10779

Published: Dec. 9, 2024

The riparian ecosystem is highly susceptible to pollution, particularly heavy metals (HMs), due its unique spatial position and landscape characteristics. Therefore, assessing the risks of HM pollution identifying potential sources are crucial for formulating effective prevention control measures. This study investigates characteristics HMs (Ni, Cr, Zn, Cd, Cu, Pb) in Weihe River zone, identifies their sources, assesses associated ecological human health risks. results indicate that Ni, Cd primary pollutants soil, with average concentration being 5.64 times higher than background value, indicating a high risk. Spatially, concentrations middle upper reaches lower reaches. Vertically, as distance from increases, content exhibits “U”-shaped pattern (increase-decrease-increase). Absolute principal components multiple regression (APCS-MLR) receptor model identified four sources: traffic sources; agricultural industrial natural sources. Additionally, Monte Carlo simulation-based risk assessment indicates non-carcinogenic indices all within acceptable ranges. For carcinogenic indices, there 1.14% probability children. However, vast majority fall or no-risk categories.

Language: Английский

Z-Pythagorean adjusted fuzzy cloud-asymmetric regret decision-making model for environmental pollution assessment DOI
Sidong Xian, Nuo Xu,

Xichun Lan

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127309 - 127309

Published: March 1, 2025

Language: Английский

Citations

0
Sources, Contamination and Risk Assessment of Heavy Metals in Riparian Soils of the Weihe River Based on a Receptor Model and Monte Carlo Simulation DOI Open Access

Wen Dong,

Bohan Niu,

Huaien Li

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10779 - 10779

Published: Dec. 9, 2024

The riparian ecosystem is highly susceptible to pollution, particularly heavy metals (HMs), due its unique spatial position and landscape characteristics. Therefore, assessing the risks of HM pollution identifying potential sources are crucial for formulating effective prevention control measures. This study investigates characteristics HMs (Ni, Cr, Zn, Cd, Cu, Pb) in Weihe River zone, identifies their sources, assesses associated ecological human health risks. results indicate that Ni, Cd primary pollutants soil, with average concentration being 5.64 times higher than background value, indicating a high risk. Spatially, concentrations middle upper reaches lower reaches. Vertically, as distance from increases, content exhibits “U”-shaped pattern (increase-decrease-increase). Absolute principal components multiple regression (APCS-MLR) receptor model identified four sources: traffic sources; agricultural industrial natural sources. Additionally, Monte Carlo simulation-based risk assessment indicates non-carcinogenic indices all within acceptable ranges. For carcinogenic indices, there 1.14% probability children. However, vast majority fall or no-risk categories.

Language: Английский

Citations

0