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

Machine learning-driven multi-technique source tracing and source-specific probabilistic ecological risk assessment of heavy metal(loid)s in urban river sediments DOI Creative Commons
Jun Li, Chao Wang,

Xin-Ying Tuo

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 171, P. 113189 - 113189

Published: Feb. 1, 2025

Language: Английский

Citations

0
Antibiotic Source Apportionment in Island Rivers Based on Point-of-Interest Data Coupled with Multimodel Approaches: A Case Study of the Nandu River in Hainan Island​ DOI
Hongwei Yi, Yuyan Liu, Ling Wang

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Deciphering multi-media occurrence and anthropogenic drivers of potentially toxic elements in a rapidly urbanized estuary: A neural network-enhanced source apportionment DOI
Weili Wang, Yi‐Tao Lin, Zhong Pan

et al.

Marine Pollution Bulletin, Journal Year: 2025, Volume and Issue: 218, P. 118178 - 118178

Published: May 20, 2025

Language: Английский

Citations

0
Using PCA-APCS-MLR and Monte-Carlo models to quantify the source and ecological-health risk of soil potentially toxic elements in a typical agricultural area DOI
Ying Wang, Shiming Yang,

Xiao Jiang

et al.

Stochastic Environmental Research and Risk Assessment, Journal Year: 2025, Volume and Issue: unknown

Published: June 5, 2025

Language: Английский

Citations

0
Distribution, ecological risk assessment, and source identification of potential toxic elements (PTEs) in Muttukadu backwater sediments, Southern India DOI

Atchuthan Purushothaman,

Gopal Veeramalai,

Ramamoorthy Ayyamperumal

et al.

Regional Studies in Marine Science, Journal Year: 2024, Volume and Issue: 78, P. 103769 - 103769

Published: Aug. 23, 2024

Language: Английский

Citations

1
Evaluation of urban air pollution by metal contents of woody vegetation leaves in the urban ecosystem DOI Creative Commons

Z. Ali Ben Ali,

Khawar Sultan, Qamar uz Zaman

et al.

International Journal of Applied and Experimental Biology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 11, 2024

Urban air pollution is a major environmental concern, and it should be addressed on priority basis for human health the urban ecosystem. The study was performed to investigate understand spatial distribution contamination levels in leaves of selected plants (Eugenia jambolana, Morus alba, Dalbergia sissoo, Populus deltoides, Ficus religiosa, variegata, Cassia fistula, Eucalyptus camaldulensis, Melia azedarach, Psidium guajava, Pongamia pinnata, Callistemon citrinus, Polyalthia longifolia) exposed polluted areas Canal Road, Lahore. Metal concentrations (Pb, As, Cr, Cd) were analyzed using atomic absorption spectrometry (AAS). level As (Average ~1.03 mg/kg) found moderately low all trees tested except camaldulensis (As~2.11 mg/kg). Lead (Pb) accumulation observed visibly higher almost samples ~ 5.34 than WHO recommended limit (2 Among samples, religiosa have highest Pb. trends Cr high (Average~1.06 non-native species, specifically (3.21 Cd also plant ~1.90 permissible (0.02 plants. Principal Component Analysis (PCA), GIS, Minitab-19 applied data. This work important set baseline future researchers appraise load different light findings this study.

Language: Английский

Citations

1
Spatial Distribution, Source Apportionment, and Pollution Assessment of Toxic Metals Around Agricultural Soils Based on APCS-MLR Receptor Modelling: A Case Study of the Northern Slope of Tianshan Mountains DOI Creative Commons

Buasi Nueraihemaiti,

Halidan Asaiduli,

Abudugheni Abliz

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2067 - 2067

Published: Dec. 1, 2024

To investigate the contamination status and analyze sources of soil toxic metal on northern slopes East Tianshan mountain industrial belt in Xinjiang, northwest China, this study measured contents six common metals such as Zn, Cu, Cr, Pb, Hg As 82 surface (0–20 cm), using ground accumulation index, pollution load improved weighted index assessed characteristics a semi-variance function APCS-MLR model identified potential contamination. The results indicate that average concentrations Hg, are significantly higher than background values Xinjiang. ranking content is follows: Zn > Cr Pb Cu as. A single-factor analysis shows severe, while moderate. moderate lead accounts for 6.1% severe 54.88%; 98.88% arsenic severely contaminated. three main heavy metals: production sources, transportation agricultural activity As, natural mixed sources. This provides solid scientific basis prevention control soils, thus ensuring food security sustainable development region.

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