Assessment of Drinking Water Quality and Identifying Pollution Sources in a Chromite Mining Region

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 480, P. 136050 - 136050

Published: Oct. 4, 2024

Language: Английский

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Machine learning and GIS based groundwater quality prediction for agricultural practices - A case study form Arjunanadi River basin of South India

Computers and Electronics in Agriculture, Journal Year: 2025, Volume and Issue: 229, P. 109932 - 109932

Published: Jan. 16, 2025

Language: Английский

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Physicochemical Qualities and Health Risk Assessment of Heavy Metals in Drinking Water From Selected Areas of the Gofa Zone, Ethiopia

Journal of Chemistry, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

Spring and well waters are among the most important sources of drinking water in Gofa Zone rural areas; therefore, it is vital to evaluate quality these sources. Hence, this study aims determine physicochemical parameters metallic mineral concentration with its associated health risks selected areas zone, Ethiopia. The purposive sampling method was used for sample collection. Standard analytical procedures were contents. average values all spring well‐drinking obtained as temperature (20.73°C 20.30°C), pH (7.2 6.07), electrical conductivity (481.13 µS/cm 584.24 µS/cm), dissolved oxygen (4.09 6.07 mg/L), turbidity (1.60 NTU 6.55 NTU), total solids (330.83 338.3 suspended (84.76 89.24 chloride concentrations (58.15 60.47 SO 4 2− ion (68.50 mg/L 5.58 NO 3 + (3.25 2.75 fluoride (0.49 0.37 mg/L). Health risk assessment indicates that Co metal showed high hazard indices compared Fe, Cu, Zn. Additionally, heavy pollution index (MPI) evaluation (HEI) indicate Sawla Kusti (SSW5), Geze Mhirzho Wola (GGSW7), Bulki Guya (BGWW8) considered highly polluted not recommended purposes.

Language: Английский

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Spatial distribution and health risk assessment of heavy metals in drinking water in Nikshahr and Iranshahr cities of Iran

International Journal of Environmental & Analytical Chemistry, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: June 11, 2024

The presence of high concentrations certain heavy metals (HMs) in drinking water poses a serious threat to the health consumers. This work was done investigate concentration such as Arsenic (As) cadmium (Cd), chromium (Cr), iron (Fe), mercury (Hg), nickel (Ni), lead (Pb) and cobalt (Co) resources two cities Iranshahr Nikshahr south Sistan Baluchistan province. For this aim, 24 samples sources were collected determined by inductively coupled plasma-mass spectrometry (ICP-MS). results these networks showed that average Pb (11.25 μg/L), Hg (10.33 As (10.62 μg/L) Cd (3.45 far exceeds standard World Health Organisation. is respectively Fe>Pb>As>Hg>Ni>Cr>Co>Cd Fe>Pb>As> Ni > Cr >Co>Cd> Hg. Potential pollution study are attributed infiltration industrial effluents agricultural runoff, which significant groundwater quality. calculated hazard quotients (HQ(values for non-carcinogenic risk show value less than 1 most metals, but index)HI) children greater 1, evident. HI obtained 5.4 adults 2.6. However, carcinogenics equal 2.66 E-05 and1.3E–6, respectively, increase cancer higher due consumption water. Therefore, it necessary protect sources, treatment monitor more distribution based on safety plan.

Language: Английский

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A comprehensive review on human health hazards due to groundwater contamination: A global perspective

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2024, Volume and Issue: 135, P. 103637 - 103637

Published: May 18, 2024

Language: Английский

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Groundwater quality evaluation for drinking and agricultural purposes. A case study in semi-arid region (Zab El-gharbi SE-Algeria)

Desalination and Water Treatment, Journal Year: 2024, Volume and Issue: 319, P. 100476 - 100476

Published: June 7, 2024

The current research delved into the geochemical attributes of groundwater and assessed compliance with drinking water standards. 35 samples Zab El Gharbi region in province Biskra were analyzed to evaluate physico-chemical quality. obtained results compared World Health Organization standards as well Algerian Standards. It appears that nitrate concentrations all acceptable since they less than 50 mg/L. WQI classification showed values ranged from 95 269; only 3 % had good quality, 80 poor 17.14 very water, indicating need for treatment before use human consumption. Two main hydrochemical facies dominated predominated, Ca-SO4 type Mixed Ca–Mg–Cl-SO4 type, respectively. Q mode hierarchical cluster analysis (HCA) was employed partitioning facies, revealed presence two distinct types based on principal ion concentrations. Hydrochemically, group 1 characterized by primary 90.32 categorized 9.67 Ca-Mg-Cl-SO4 type. While 2 a estimated sodium adsorption ratio (SAR), percent (Na%), permeability index (PI), Kelly's (KR) Magnesium hazard (MH), averages study area is reported be range 0.90 5.60, 4.46 41.26 %, 12.50 44.47 0.10 0.73 9.69 75.06 Parameters such Permeability Index Ratio (KR), Hazard (MH) indicated 37.14 excellent category, while remaining 62.85 making them suitable irrigation across various soil types. They considered exhibits favorable characteristics agricultural applications, ranging good. These findings are encouraging agriculture land-use planning. This lies addressing quality this promontory area, where no prior has been published. We using statistical, geostatistical, cartographic methods estimate unsampled areas. Additionally, we examined how climatic conditions, particularly high evapotranspiration during festive season, affect will help farmers scientists make informed decisions protect natural resources. work meant highlight issues also provide practical solutions optimize management

Language: Английский

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Harnessing Deep Learning for Real-Time Water Quality Assessment: A Sustainable Solution

Water, Journal Year: 2024, Volume and Issue: 16(23), P. 3380 - 3380

Published: Nov. 24, 2024

This study presents an innovative approach utilizing artificial intelligence (AI) for the prediction and classification of water quality parameters based on physico-chemical measurements. The primary objective was to enhance accuracy, speed, accessibility monitoring. Data collected from various samples in Algeria were analyzed determine key such as conductivity, turbidity, pH, total dissolved solids (TDS). These measurements integrated into deep neural networks (DNNs) predict indices sodium adsorption ratio (SAR), magnesium hazard (MH), percentage (SP), Kelley’s (KR), potential salinity (PS), exchangeable (ESP), well Water Quality Index (WQI) Irrigation (IWQI). DNNs model, optimized through selection activation functions hidden layers, demonstrated high precision, with a correlation coefficient (R) 0.9994 low root mean square error (RMSE) 0.0020. AI-driven methodology significantly reduces reliance traditional laboratory analyses, offering real-time assessments that are adaptable local conditions environmentally sustainable. provides practical solution resource managers, particularly resource-limited regions, efficiently monitor make informed decisions public health agricultural applications.

Language: Английский

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Deep learning-based analysis of groundwater pollution sources and health risk evaluation around typical irrigation areas

Human and Ecological Risk Assessment An International Journal, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 24

Published: Jan. 24, 2025

Language: Английский

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Application of multi-indexing approach within a GIS framework to investigate the quality and contamination of ground water in Barisal sadar, Bangladesh

Heliyon, Journal Year: 2025, Volume and Issue: 11(3), P. e42262 - e42262

Published: Jan. 27, 2025

Language: Английский

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Assessment of water quality and health hazards using water quality index and human health risk evaluation in district Talagang Pakistan

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 12, 2025

Language: Английский

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