Distribution, source apportionment, and assessment of heavy metal pollution in the Yellow River Basin, Northwestern China DOI
Cheng Ma, Menglu Wang, Qian Li

и другие.

Frontiers of Environmental Science & Engineering, Год журнала: 2024, Номер 19(2)

Опубликована: Дек. 12, 2024

Язык: Английский

Nanocapsule decorated reduced graphene oxide/Schiff base functionalized Fe3O4 for effective detection of Cd(II) and anti-interference properties DOI
Yujie Liang, Xiaoqiang Lin, Haiyan Liao

и другие.

Chemical Engineering Journal, Год журнала: 2025, Номер unknown, С. 160606 - 160606

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

2

Identification of the primary pollution sources and dominant influencing factors of soil heavy metals using a random forest model optimized by genetic algorithm coupled with geodetector DOI Creative Commons
Tong Liu,

Mingshi Wang,

Mingya Wang

и другие.

Ecotoxicology and Environmental Safety, Год журнала: 2025, Номер 290, С. 117731 - 117731

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1

Risk assessment and source tracing of heavy metals in major rice-producing provinces of Yangtze River Basin DOI

Haizhen Ding,

Jiwei Liu, Qin Liu

и другие.

Journal of Hazardous Materials, Год журнала: 2024, Номер 480, С. 136206 - 136206

Опубликована: Окт. 18, 2024

Язык: Английский

Процитировано

5

Identification of hydrogeochemical processes in shallow groundwater using multivariate statistical analysis and inverse geochemical modeling DOI
Nan Liu, Meng Chen, Dongdong Gao

и другие.

Environmental Monitoring and Assessment, Год журнала: 2025, Номер 197(2)

Опубликована: Янв. 6, 2025

Язык: Английский

Процитировано

0

Spatial and temporal distribution characteristics and source apportionment of biogenic elements using APCS-MLR model in the main inlet tributary of Danjiangkou Reservoir DOI

Yihang Wu,

Qianzhu Zhang,

Yuan Luo

и другие.

Environmental Science and Pollution Research, Год журнала: 2025, Номер unknown

Опубликована: Янв. 20, 2025

Язык: Английский

Процитировано

0

Assessing technology's influence on cropland green production efficiency in the Yellow River basin, China DOI

Chaoqing Chai,

Ruiting Wen, Huadong Zhu

и другие.

Environmental Impact Assessment Review, Год журнала: 2025, Номер 112, С. 107838 - 107838

Опубликована: Фев. 3, 2025

Язык: Английский

Процитировано

0

Global Perspectives on Lead Contamination and Health Risks in Surface Water, Rice Grains, and Soils DOI Open Access
Amit Kumar, Vinod Kumar, Monika Thakur

и другие.

Land Degradation and Development, Год журнала: 2025, Номер unknown

Опубликована: Фев. 4, 2025

ABSTRACT Lead (Pb), a pervasive and highly toxic metal, poses significant environmental health risks due to its extensive biogeochemical cycling, driven by anthropogenic activities. This review evaluates the hazards allied with Pb contamination in surface water bodies, soils, rice grains, based on comprehensive analysis (2015–2024) of 118, 133, 102 literature studies, respectively. The year‐wise assessment concentration bodies soils frequently exceeded their permissible limits 2015, 2017, 2018, 2019, 2020, 2022. However, mean grains consistently surpassed Codex Alimentarius limit (2.5 μg/g) across analyzed years. Geographically, Bangladesh, India, Pakistan, China for emphasizing regional vulnerabilities. Health risk indicated hazard quotient values exceeding one children adults exhibiting non‐carcinogenic risks. In dermal exposure identified as predominant pathways contributing followed ingestion, while inhalation presented lower risk. These findings emphasize imperative necessitate implementing strict regulatory frameworks preventive measures mitigate environment minimize potential impacts. study advances understanding risks, offering valuable insights targeted mitigation strategies public interventions.

Язык: Английский

Процитировано

0

Assessment of Heavy Metals in Surface Waters of the Santiago–Guadalajara River Basin, Mexico DOI Creative Commons
Rosa Leonor González-Díaz, José de Anda, Harvey Shear

и другие.

Hydrology, Год журнала: 2025, Номер 12(2), С. 37 - 37

Опубликована: Фев. 17, 2025

The Santiago–Guadalajara River Basin has an area of 10,016.46 km2. Metropolitan Area Guadalajara, within the basin, is second-largest city in country, with more than 5 million inhabitants. growth urban population, as well industrial and agricultural activities insufficient infrastructure for sanitation wastewater its reuse, have caused environmental deterioration surface waters gradual depletion groundwater resources. To assess level contamination from presence heavy metals a monthly monitoring campaign was carried out at 25 sampling stations located main tributary streams July 2021 to April 2022. following decreasing sequence found according mean concentration values: Fe > Al Mn B Ba Zn As Cu Cr Ni Pb Cd. Heavy Metal Pollution Index (HPI) method applied risk aquatic life, finding average global HPI value 305.522 which classifies it critical range. results also reflect health risks due As, Cd, some monitored stations. It will be necessary expand network, identify point non-point sources contamination, implement measures pollution control protect life human river.

Язык: Английский

Процитировано

0

Time Series Analysis for the Adaptive Prediction of Total Phosphorus in the Yangtze River: A Machine Learning Approach DOI Open Access
Tianqi Ma,

Xing Chen

Water, Год журнала: 2025, Номер 17(4), С. 603 - 603

Опубликована: Фев. 19, 2025

Accurate prediction of total phosphorus (TP) in water quality is critical for monitoring ecosystem stability and eutrophication status. However, the distribution natural environmental data such as tends to undergo complex changes over time. Stable reliable results not only require a certain degree periodicity but also that TP model be highly adaptable random fluctuations distributional drifts data. Therefore, it challenge adapt models drift In this study, spatial temporal variations Yangtze River from 2019 2023 were described detail. Using mining techniques, time series analyzed generate forecast dataset focusing on fluctuations. By comparing various models, MTS-Mixers was finally selected experimental baseline different modes used prediction. The show after parameter adjustment, can achieve high accuracy (MAE: 0.145; MSE: 0.277), which guarantee at 20 steps. These research comprehensively reliably predicted provided effective methods tools management. They provide scientific basis protection improvement Basin help formulation implementation relevant policies promote sustainable development environment. addition, study confirms applicability machine learning hydrological responding changes.

Язык: Английский

Процитировано

0

Nutrients and metal(loid)s in surface sediments of the Chishui River: A DGT-based assessment of the last natural tributary of the upper Yangtze River (China) DOI
Xia Wei,

Tian-Xin Zhang,

Li Xue

и другие.

Environmental Research, Год журнала: 2025, Номер unknown, С. 121455 - 121455

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0