Heavy metal(loid)s contamination and potential risk assessment via groundwater consumption in the district of Hangu, Pakistan

Appraisal of groundwater suitability for drinking and irrigation purposes in highly vulnerable coastal area of Bangladesh

Groundwater contamination is a significant threat to water security in Bangladesh, especially in coastal areas influenced by salinity intrusion and geogenic pollutants. The study has collected 48 groundwater samples and analyzed 16 water quality parameters to assess the suitability of groundwater for drinking and irrigation purposes in a highly vulnerable coastal area of Bangladesh. The Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI), Metal Index (MI), and Heavy Metal Pollution Index (HPI) were used to assess drinking water quality. In contrast, irrigation water suitability was evaluated using indices like Sodium Absorption Ratio (SAR), Sodium Percentage (Na%), Magnesium Absorption Ratio (MAR), and Kelly Ratio (KR). The results show that 72.92 % of the samples were above WHO drinking water guidelines for EC, which indicated high salinity risks. The CCME WQI classified 25 % of the samples as marginal or poor, and MI and HPI both showed significant contamination, mainly due to high Fe and As concentrations. The MAR indicated that 25 % of the samples were unsuitable for irrigation, mainly because of high salinity and sodium. Spatial analysis proved that severe deterioration of groundwater quality has been taking place in the southern area of Pirojpur severely, which requires urgent intervention, and continuous monitoring for safeguarding water resources in this vulnerable area.

Assessment of health risk and identification of pollution sources of heavy metals in water in Chongqing's wastewater treatment plants based on ICP-MS

Chongqing is located upstream of the Yangtze River and within the Three Gorges Reservoir Area. Boasting a dense hydrological network comprising interconnected rivers, tributaries, and reservoirs, the condition of the natural environment in Chongqing is intrinsically linked to drinking water safety. To evaluate the regional distribution, pollution levels, health risks, and sources of 12 heavy metals, a total of 90 water samples (30 influent sewage, 30 effluent sewage, and 30 tap water samples) were systematically collected from 30 wastewater treatment plants (WWTPs) across Chongqing. Heavy metal pollution index (HPI), heavy metal evaluation index (HEI), degree of contamination (CD), and health risk assessment were utilized in this study to present the findings of a thorough assessment of heavy metal contamination in the region. Meanwhile positive matrices factorization (PMF) was applied to ascertain sources of heavy metals in influent sewage. The results showed that sewage treatment diminished pollutant concentrations. After treatment, Zn, Hg, Pb, and Cr were the primary contaminants in the effluent sewage, significantly surpassing the Class I standard limit for surface water in China. The primary sources of sewage contamination were anthropogenic activities, including agriculture, industry, and transportation. The cumulative health risk from carcinogenic heavy metals surpassed the permissible danger threshold. Cr was responsible for majority of health hazards. These findings indicate the priority control requirements for various heavy metals and establish a scientific foundation for the hierarchical management strategy of heavy metals, optimization of wastewater treatment processes, and the assurance system for drinking water safety.

Mobilization mechanisms and spatial distribution of arsenic in groundwater of western Bangladesh: Evaluating water quality and health risk using EWQI and Monte Carlo simulation

Arsenic (As) contamination in groundwater is emerging as a significant global concern, posing serious risks to the safety of drinking water and public health. To understand the release mechanisms, mobilization processes, spatial distribution, and probabilistic health risks of As in western Bangladesh, forty-seven samples were collected and analyzed using an atomic absorption spectrometer (AAS). The As concentrations in groundwater ranged from 1.97 to 697.4 μg L⁻1 (mean: 229.9), significantly exceeding recommended levels. The dominant hydrochemistry of As-enriched groundwater was Ca-Mg-HCO₃, with the primary sources of arsenic in groundwater being the dissolution of arsenic-bearing minerals in sediment and the recharge of aquifers from the Ganges River Basin. The assessment using the Entropy Water Quality Index revealed that the groundwater is unsuitable for drinking, with 89.36% (n = 42) of the samples surpassing the WHO's limit for arsenic. Rock-water interactions, including calcite dissolution and silicate weathering within the confined aquifer, predominantly influenced hydrochemical properties. The significant relationships among Fe, Mn, and As indicate that the reductive dissolution of FeOOH and/or MnOOH considerably contributes to the release of As from sediment into groundwater. Geochemical modeling analysis revealed that siderite and rhodochrosite precipitate into aquifer solids, suggesting a weak to moderate relationship among As, Fe, and Mn. The long residence time of groundwater, combined with the presence of a clayey aquitard, likely controls the mobilization of arsenic in the aquifer. For the first time, Monte Carlo simulations have been used in arsenic-prone areas to assess the severity of arsenic contamination in western Bangladesh. The analysis indicates that out of 100,000 people, 10 may develop cancer as a result of drinking arsenic-contaminated water, with children being more susceptible than adults.

Investigation of groundwater quality in the Southern Coast of the Black Sea: application of computational health risk assessment in Giresun, Türkiye

Potentially toxic elements (PTEs), especially arsenic in drinking water, pose significant global health risks, including cancer. This study evaluates the groundwater quality in Giresun province on the Black Sea coast of Türkiye by analyzing twelve groundwater resources. The mean concentrations of macronutrients (mg/L) were: Ca (10.53 ± 6.63), Na (6.81 ± 3.47), Mg (3.39 ± 2.27), and K (2.05 ± 1.10). The mean levels of PTEs (µg/L) were: Al (40.02 ± 15.45), Fe (17.65 ± 14.35), Zn (5.63 ± 2.59), V (4.74 ± 5.85), Cu (1.57 ± 0.81), Mn (1.02 ± 0.76), As (0.93 ± 0.73), Cr (0.75 ± 0.57), Ni (0.41 ± 0.18), Pb (0.36 ± 0.23), and Cd (0.10 ± 0.05). All PTE levels complied with WHO drinking water safety guidelines, and overall water quality was excellent. The heavy metal evaluation index (HEI < 10) and heavy metal pollution index (HPI < 45) indicate low pollution levels across all stations. Irrigation water quality was largely adequate, as shown by the magnesium hazard (MH), sodium adsorption ratio (SAR), Na%, and Kelly's ratio (KR). The total hazard index (THI) values consistently remained below 1, indicating no non-carcinogenic health risks. However, at station 10 (city center), the cancer risk (CR) for adults due to arsenic was slightly above the threshold (1.44E-04). Using principal component analysis (PCA), positive matrix factorization (PMF), and geographic information system (GIS) mapping, the study determined that most PTEs originated from natural geological formations or a combination of natural and human sources, with minimal impact from human activities. These findings highlight the safety and reliability of the groundwater sources studied, emphasizing their potential as a long-term, safe water supply for nearby populations.

DNA damage in inhabitants exposed to heavy metals near Hudiara drain, Lahore, Pakistan

The current study was conducted on the inhabitants living in the area adjacent to the Hudiara drain using bore water and vegetables adjacent to the Hudiara drain. Toxic heavy metals badly affect human health because of industrial environmental contamination. Particularly hundreds of millions of individuals globally have faced the consequences of consuming water and food tainted with pollutants. Concentrations of heavy metals in human blood were elevated in Hudiara drainings in Lahore city, Pakistan, due to highly polluted industrial effluents. The study determined the health effects of high levels of heavy metals (Cd, Cu, Zn, Fe, Pb, Ni, Hg, Cr) on residents of the Hudiara draining area, including serum MDA, 8-Isoprostane, 8-hydroxyguanosine, and creatinine levels. An absorption spectrophotometer was used to determine heavy metals in wate water, drinking water, soil, plants and human beings blood sampleas and ELISA kits were used to assess the level of 8-hydroxyguanosine, MDA, 8-Isoprostane in plasma serum creatinine level. Waste water samples, irrigation water samples, drinking water samples, Soil samples, Plants samples and blood specimens of adult of different weights and ages were collected from the polluted area of the Hudiara drain (Laloo and Mohanwal), and control samples were obtained from the unpolluted site Sheiikhpura, 60 km away from the site. Toxic heavy metals in blood damage the cell membrane and DNA structures, increasing the 8-hydroxyguanosine, MDA, creatinine, and 8-Isoprostane. Toxic metals contaminated bore water and vegetables, resulting in increased levels of creatinine, MDA, Isoprostane, and 8-hydroxy-2-guanosine in the blood of inhabitants from the adjacent area Hudiara drain compared to the control group. In addition,. This study also investigated heavy metal concentrations in meat and milk samples from buffaloes, cows, and goats. In meat, cow samples showed the highest Cd, Cu, Fe and Mn concentrations. In milk also, cows exhibited elevated Cu and Fe levels compared to goats. The results highlight species-specific variations in heavy metal accumulation, emphasizing the need for targeted monitoring to address potential health risks. The significant difference between the two groups i.e., the control group and the affected group, in all traits of the respondents (weight, age, heavy metal values MDA, 8-Isoprostane, 8-hydroxyguaniosine, and serum creatinine level). Pearson's correlation coefficient was calculated. The study has shown that the level of serum MDA, 8-Isoprostane, 8-hydroxyguaniosine, or creatinine has not significantly correlated with age, so it is independent of age. This study has proved that in Pakistan, the selected area of Lahore in the villages of Laloo and Mohanwal, excess of heavy metals in the human body damages the DNA and increases the level of 8-Isoprostane, MDA, creatinine, and 8-hydroxyguaniosine. As a result, National and international cooperation must take major steps to control exposure to heavy metals.

Appraisal of treated drinking water quality from arsenic removal units in West Bengal, India: Approach on safety, efficiency, sustainability, future health risk and socioeconomics

The present study depicts the true failed scenario of the arsenic (As) removal units (ARU) in West Bengal by evaluating their treated water quality. Annual As removal efficiency of the 12 studied ARUs range between 35.2% and 82.6%. A comprehensive physico-chemical parameters and trace elements analysis find almost 25% and 16.7% of treated drinking water samples with poor water quality index (WQI) and high heavy metal evaluation index (HEI), respectively. The pond-based water treatment plant maintains the production of continuous As-safe water with a range between 60.2% and 66.7% due to its high Fe/As ratio. It's a discontent concluding the treated drinking water of the groundwater based-ARUs were observed with sufficient As mediated cancer risk (3 ×10-3). The non-cancer risk (HQ) of As is safe for the surface water treatment plant (0.38), whereas it is threatening for the groundwater based-ARUs (7.44). However, the drinking water samples are safe in view of HQ from the other trace elements like Hg, Al, Cd, Cr, Pb, F- and NO3-. Small scale ARU could be a feasible mitigation strategy in reducing the As menace in the long run if the plants are maintained correctly. Nevertheless, surface treated water is the most sustainable solution as withdrawal of groundwater for drinking purpose is not a viable practice.

Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area

Combining the results of base models to create a meta-model is one of the ensemble approaches known as stacking. In this study, stacking of five base learners, including eXtreme gradient boosting, random forest, feed-forward neural networks, generalized linear models with Lasso or Elastic Net regularization, and support vector machines, was used to study the spatial variation of Mn, Cd, Pb, and nitrate in Qom-Kahak Aquifers, Iran. The stacking strategy proved to be an effective substitute predictor for existing machine learning approaches due to its high accuracy and stability when compared to individual learners. Contrarily, there was not any best-performing base model for all of the involved parameters. For instance, in the case of cadmium, random forest produced the best results, with adjusted R2 and RMSE of 0.108 and 0.014, as opposed to 0.337 and 0.013 obtained by the stacking method. The Mn and Cd showed a tight link with phosphate by the redundancy analysis (RDA). This demonstrates the effect of phosphate fertilizers on agricultural operations. In order to analyze the causes of groundwater pollution, spatial methodologies can be used with multivariate analytic techniques, such as RDA, to help uncover hidden sources of contamination that would otherwise go undetected. Lead has a larger health risk than nitrate, according to the probabilistic health risk assessment, which found that 34.4% and 6.3% of the simulated values for children and adults, respectively, were higher than HQ = 1. Furthermore, cadmium exposure risk affected 84% of children and 47% of adults in the research area.

Spatial distribution of potentially toxic elements contaminations and risk indices of water and sediments in the Darband and Samana streams, Pakistan

This study examined potentially toxic elements (PTE) of water and sediments in the Darband and Samana streams of Hangu District. Darband and Samana streams are the main fluvial ecosystems of Hangu District, Pakistan, directly or indirectly affecting more than 0.52 Million people. Water and sediment samples were collected and analyzed for PTE utilizing inductively coupled plasma mass spectrometry (ICP-MS). Water characteristics of Darband and Samana streams were noted within the WHO drinking water guidelines, except for Turbidity and sulfate. Most water characteristics showed higher values in the Samana stream than in the Darband stream. Similarly, most of PTE showed higher concentrations in sediments collected from the Samana stream than the Darband stream. For ecological risk evaluation, several pollution indices were employed to assess the eco-toxicological consequences. The highest contamination factor (CF) value of 15 and 20 were exhibited by molybdenum (Mo) in the Samana and Darband streams showing very high contamination. Similarly, the pollution load index (PLI) showed that 24% of the sediment samples were polluted (PLI > 1). Furthermore, a high ecological risk in a range of 160 < ERI < 320 was observed for Mo, while a low ecological risk ERI < 40 was by As for the Darband and Samana streams sediments. Statistical techniques revealed that various anthropogenic sources primarily contaminated in water and sediment. Therefore, this study recommends regular monitoring PTE contaminations in the area to avoid any health hazards in the future.

Assessment of groundwater vulnerability by applying the improved DRASTIC model: a case in Guyuan City, Ningxia, China

Groundwater is the main source of production and living in most arid and semi-arid areas, and it plays an increasingly critical role in achieving local urban development. There is a serious issue regarding the contradiction between urban development and groundwater protection. In this study, we used three different models to assess the groundwater vulnerability of Guyuan City, including DRASTIC model, analytical hierarchy process-DRASTIC model (AHP-DRASTIC) and variable weight theory-DRASTIC model (VW-DRASTIC). The groundwater vulnerability index (GVI) of the study area was calculated in ArcGIS. Based on the magnitude of GVI, the groundwater vulnerability was classified into five classes: very high, high, medium, low, and very low using the natural breakpoint method, and the groundwater vulnerability map (GVM) of the study area was drawn. In order to validate the accuracy of groundwater vulnerability, the Spearman correlation coefficient was used, and the results showed that the VW-DRASTIC model performed best among the three models (ρ=0.83). The improved VW-DRASTIC model shows that the variable weight model effectively improves the accuracy of the DRASTIC model, which is more suitable for the study area. Finally, based on the results of GVM combined with the distribution of F^- and urban development planning, suggestions were proposed for further sustainable groundwater management. This study provides a scientific basis for groundwater management in Guyuan City, which can be an example for similar areas, particularly in arid and semi-arid areas.