Integrating Unsupervised Machine Learning, Statistical Analysis, and Monte Carlo Simulation to Assess Toxic Metal Contamination and Salinization in Non-Rechargeable Aquifers DOI Creative Commons
Mohamed Hamdy Eid, Omar Saeed, András Székács

и другие.

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104989 - 104989

Опубликована: Апрель 1, 2025

Язык: Английский

Analyzing topsoil heavy metal pollution sources and ecological risks around antimony mine waste sites by a joint methodology DOI Creative Commons
Hao Zou, Bozhi Ren

Ecological Indicators, Год журнала: 2023, Номер 154, С. 110761 - 110761

Опубликована: Авг. 6, 2023

Studies on soil contamination caused by waste sites near antimony mining areas are scarce. For environmental protection, it is critical to investigate the levels, spatial distribution, and ecological risk assessment of heavy metals (HMs) in surface soils different land use types around identify related potential sources. In this study, pollution status, sources risks Hg, Pb, Cd, Cr, As Sb built-up areas, woodlands croplands were resolved for first time combining self-organizing maps (SOM), K-means clustering, geographic information systems (GIS) positive matrix factorization (PMF). According analysis results samples, average abundance order HMs is: > Cd Pb Cr Hg. The cumulative geological index defines as a severe level. shows that all samples above load 67.7% heavily polluted. SOM divided studied elements into three clusters combined with GIS from cluster 1, 2, Hg 3. PMF yielded metals: natural dominated (48.6%), direct accumulation represented (32.9%) mixed human activities transportation (18.5%). Ecological construction area prominent, main contribution element high risk. This study combines multiple methods current status metal environment mine slag sites, providing theoretical basis better research source control, contributing scarcity site research.

Язык: Английский

Процитировано

15

DOM accumulation in the hyporheic zone promotes geogenic Fe mobility: A laboratory column study DOI
Xuelian Xia, Weifeng Yue, Yuanzheng Zhai

и другие.

The Science of The Total Environment, Год журнала: 2023, Номер 896, С. 165140 - 165140

Опубликована: Июнь 28, 2023

Язык: Английский

Процитировано

14

Optimized groundwater quality evaluation using unsupervised machine learning, game theory and Monte-Carlo simulation DOI
Yuting Yan,

Yunhui Zhang,

Shiming Yang

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 371, С. 122902 - 122902

Опубликована: Ноя. 11, 2024

Язык: Английский

Процитировано

6

Groundwater heavy metal(loid)s risk prediction based on topsoil contamination and aquifer vulnerability at a zinc smelting site DOI
Shengguo Xue, Yuanyuan Wang, Jun Jiang

и другие.

Environmental Pollution, Год журнала: 2023, Номер 341, С. 122939 - 122939

Опубликована: Ноя. 17, 2023

Язык: Английский

Процитировано

13

Groundwater suitability assessment for irrigation and drinking purposes by integrating spatial analysis, machine learning, water quality index, and health risk model DOI
Yuting Yan, Yunhui Zhang, Rongwen Yao

и другие.

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(27), С. 39155 - 39176

Опубликована: Май 29, 2024

Язык: Английский

Процитировано

4

Geochemical fingerprints, evolution, and driving forces of groundwater in an alpine basin on Tibetan Plateau: Insights from unsupervised machine learning and objective weight allocation approaches DOI Creative Commons

Hongjie Yang,

Yong Xiao,

Shaokang Yang

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 56, С. 102054 - 102054

Опубликована: Ноя. 5, 2024

Язык: Английский

Процитировано

4

Heavy metal pollution and ecological risk assessment: A study on Linli County soils based on self-organizing map and positive factorization approaches DOI
Hao Zou,

Wu-qing Li,

Bozhi Ren

и другие.

Journal of Central South University, Год журнала: 2024, Номер 31(4), С. 1371 - 1382

Опубликована: Апрель 1, 2024

Язык: Английский

Процитировано

3

Precise management and control around the landfill integrating artificial intelligence and groundwater pollution risks DOI
Xiao Yang, Chao Jia, Yue Yao

и другие.

Chemosphere, Год журнала: 2024, Номер 364, С. 143185 - 143185

Опубликована: Авг. 24, 2024

Язык: Английский

Процитировано

3

Hydrogeochemical mechanisms and health risks of fluoride and nitrate in phreatic groundwater in the Songnen basin: insights from hydrogeochemical zonation DOI
Mingqian Li, He Wang,

Hongbiao Gu

и другие.

Human and Ecological Risk Assessment An International Journal, Год журнала: 2025, Номер unknown, С. 1 - 19

Опубликована: Фев. 12, 2025

Язык: Английский

Процитировано

0

Spatial pattern of groundwater chemistry in a typical piedmont plain of Northern China driven by natural and anthropogenic forces DOI Creative Commons
Qichen Hao, Yong Xiao, Kui Liu

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Март 4, 2025

Groundwater is crucial for human society's development in piedmont plains, yet its hydrogeochemistry often exhibits complex spatial distributions due to the interplay of nature and factors. Ninety-two phreatic groundwater samples were collected from a typical plain northern China analyzed using self-organizing map combined with hydrogeochemical simulation, diagrams, entropy-weighted water quality index. categorized into four clusters, demonstrating gradual facies evolution HCO3-Ca Cl-Mg·Ca Cl-Na, along an increase NO3- content order clusters IV, II, III, I. Natural processes, including silicates weathering reverse cation-exchange, establish natural fundamental framework chemistry, which furtherly sculptured by agricultural substances input. was predominantly excellent or good, index (EWQI) values below 100 at over 92% sampling sites. relatively poorer upstream areas near mountains Hutuo River, where stratum permeability high, but improves downstream lower. Agricultural land use variation aquifer are responsible observed variations chemistry. contaminants warrant attention protection plains that long-term activities, especially mountains. This research understanding distribution chemistry provides scientific guidance related management.

Язык: Английский

Процитировано

0