Appraising drinking water quality in Ikem rural area (Nigeria) based on chemometrics and multiple indexical methods

Trace element pollution tracking in the complex multi-aquifer groundwater system of Al-Hassa oasis (Saudi Arabia) using spatial, chemometric and index-based techniques

In a global context, trace element pollution assessment in complex multi-aquifer groundwater systems is important, considering the growing concerns about water resource quality and sustainability worldwide. This research addresses multiple objectives by integrating spatial, chemometric, and indexical study approaches, for assessing trace element pollution in the multi-aquifer groundwater system of the Al-Hassa Oasis, Saudi Arabia. Groundwater sampling and analysis followed standard methods. For this purpose, the research employed internationally recognized protocols for groundwater sampling and analysis, including standardized techniques outlined by regulatory bodies such as the United States Environmental Protection Agency (USEPA) and the World Health Organization (WHO). Average values revealed that Cr (0.041) and Fe (2.312) concentrations surpassed the recommended limits for drinking water quality, posing serious threats to groundwater usability by humans. The trace elemental concentrations were ranked as: Li < Mn < Co < As < Mo < Zn < Al < Ba < Se < V < Ni < Cr < Cu < B < Fe < Sr. Various metal(loid) pollution indices, including degree of contamination, heavy metal evaluation index, heavy metal pollution index, and modified heavy metal index, indicated low levels of groundwater pollution. Similarly, low values of water pollution index and weighted arithmetic water quality index were observed for all groundwater points, signifying excellent groundwater quality for drinking and domestic purposes. Spatial distribution analysis showed diverse groundwater quality across the study area, with the eastern and western parts displaying a less desirable quality, while the northern has the best, making water users in the former more vulnerable to potential pollution effects. Thus, the zonation maps hinted the necessity for groundwater quality enhancement from the western to the northern parts. Chemometric analysis identified both human activities and geogenic factors as contributors to groundwater pollution, with human activities found to have more significant impacts. This research provides the scientific basis and insights for protecting the groundwater system and ensuring efficient water management.

Soil heavy metal pollution from waste electrical and electronic equipment of repair and junk shops in southern Thailand and their ecological risk

The waste electrical and electronic equipment (WEEE) stream in Thailand shifted from exporting WEEE to recycling them in domestic enterprises after China's import restrictions on e-waste in 2018. This study aims to investigate the pollution status, pollution sources, and ecological risk of heavy metals from manual WEEE dismantling facilities (12 repair shops and 8 junk shops) in the Nakhon Si Thammarat province of southern Thailand by examining the concentrations of As, Cd, Ni, and Pb in the topsoil (0-15 cm) during the wet and dry seasons. The results revealed that the mean concentrations of all heavy metals were higher during the dry season than in the wet season. The concentrations of analyzed soil heavy metals decreased as the intensity of e-waste dismantling activities increased, with recycling sites > repair sites > control sites (no e-waste recycling activities). Only 10% of WEEE processing workshops (junk shops) had soil Pb and As concentrations that exceeded Thailand's residential soil quality standards. However, ecological indexing models based on the geo-accumulation index found that 75% of electric repair shops were contaminated with the analyzed heavy metals, particularly Pb. Moreover, the Nemerow integrated pollution index indicated that 16.7% of electric repair shops were on the pollution warning line. Our findings suggest that policymakers should promote ecological risk assessment as a method for mitigating the negative environmental impact of electronic repair businesses, which are widely dispersed in residential areas and tend to dominate the WEEE stream because of the circular economy concept of "right to repair", and highlight the decline of junk shops and e-waste dismantling villages for waste export resulting from China's ban.

Human exposures to multiple water sources in the southwestern coastal region of Bangladesh: water quality, pollution sources, and preliminary health risks appraisals

The coastal areas of Bangladesh have poor accessibility to fresh drinking water and the groundwater is not suitable for drinking, cooking, and other domestic uses due to high levels of salinity and potentially toxic elements. The current study focuses on understanding of the distribution of some physicochemical parameters (temperature, pH, EC, TDS, and salinity) and chemical elements (Fe, Mn, Zn, Ca, Mg, Na, K, Cu, Co, Pb, As, Cr, Cd, and Ni) with health perspective in drinking water from the southwestern coastal area of Bangladesh. The physicochemical properties of the water samples were examined with a multiparameter meter, while the elemental concentrations were analyzed using atomic absorption spectrometer. Water quality index (WQI) and irrigation indices were utilized to determine the drinking water quality and irrigation feasibility, respectively, whereas hazard quotients (HQs) and hazard index (HI) were used to assess the probable pathways and the associated potential risks to human health. The concentrations of some toxic elements in measured samples were relatively higher compared to drinking water guidelines, indicating that ground and surface water are not apt for drinking and/or domestic uses. The multivariate statistical approaches linked the source of the pollutants in the studied water body mostly to the geogenic origin including saline water intrusion. WQI values ranged from 18 to 430, reflecting excellent to unsuitable categories of water quality. The assessment of human health risks due to exposure to contaminated water demonstrated both carcinogenic and non-carcinogenic health risks in the exposed residents of the study area. Therefore, appropriate long-term coastal area management strategies should be adopted in the study region for environmental sustainability. The findings of this research will be supportive in understanding the actual situation of fresh drinking water in the area for policymakers, planners, and environmentalists to take effective necessary measures to ensure safe drinking water in the study area.

Assessment of Bacteriological Quality and Physiochemical Parameters of Domestic Water Sources in Jenin Governorate: A Case Study

Water quality of drinking water is a concern in Palestine due to possible pollution sources. There is a demand for investigating the quality of municipal water supply. This study aimed to assess the quality of domestic water in Jenin Governorate located in the north of the West Bank. The methodology of this research was based on field sampling and laboratory standard testing. The tested parameters included (1) physicochemical parameters of electrical conductivity, turbidity, total hardness, salinity, pH, and total alkalinity, (2) chemical contents including the contents of nitrate, nitrite, sulfate, chloride, sodium, potassium, aluminum, and fluoride, and (3) biological contents including total coliforms and fecal coliforms. The water quality parameters were compared with the acceptable limits set by local and international standards. The findings confirm that most of the values of the investigated parameters are within the acceptable standard limits. No pollution of heavy metals is detectable. On the other hand, there are limited pollution contents in terms of the total dissolved solid (TDS), total hardness, and calcium. Furthermore, the biological parameters indicate that there are low to very high risks in a fraction of the water quality samples in terms of total coliforms and fecal coliforms. This is believed to be due to the presence of septic tanks in the neighborhoods of the sampling locations. For these cases, biological disinfection treatments are recommended before human use with an essential need for the construction of urban sewer systems. Furthermore, water treatment for harness removal may be required.

Multi-pollutants (organic and inorganic) removal potential of scenedesmus species on municipal sewage water and analyzed their phycoremediation mechanisms

Municipal sledge water is a combination of residential wastewater, industrial effluent, and precipitation water. The water quality parameters analyses results demonstrated that most of the parameters (pH: 5.6 ± 0.3, Turbidity: 102.31 ± 2.8 mg L^-1, TH: 946.38 ± 3.7 mg L^-1, BOD: 295.63 ± 5.4 mg L^-1, COD: 482.41 ± 4.9 mg L^-1, Ca: 278.74 ± 1.8 mg L^-1, SO₄^2-: 559.64 ± 11.4 mg L^-1, Cd: 18.56 ± 1.37 mg L^-1, Cr: 31.25 ± 1.49 mg L^-1, Pb: 21.45 ± 1.12 mg L^-1, and Zn: 48.65 ± 1.56 mg L^-1) were considerably increased in quantities with slightly acidic in condition. The in-vitro phycoremediation study was carried out for two weeks with pre-identified Scenedesmus sp. Biomass in different groups of treatments (A, B, C, and D). Interestingly, most of the physicochemical parameters were significantly reduced in group C (4 × 10³ cells mL^-1) treated municipal sledge water in a shorter treatment period than in the other treatment groups. The phycoremediation percentage of group C were found as pH: 32.85%, EC:52.81%, TDS: 31.32%, TH: 25.58%, BOD:34.02%, COD:26.47%, Ni: 58.94%, Ca:44.75%, K: 42.74%, Mg:39.52%, Na: 36.55%, Fe: 68%, Cl: 37.03%, SO₄^2-: 16.77%, PO₄^3-: 43.15%, F: 55.55%, Cd:44.88%, Cr:37.21%, Pb:43.8%, and Zn:33.17%. These findings suggest that increased biomass from Scenedesmus sp. Can be used to significantly remediate municipal sledge water and that the obtained biomass and treated sledge can be used as feedstock's for bio fuel as well as bio fertilizer, respectively.

Hydrogeochemical assessment and health-related risks due to toxic element ingestion and dermal contact within the Nnewi-Awka urban areas, Nigeria

Awka and Nnewi metropolises are known for intensive socioeconomic activities that could predispose the available groundwater to pollution. In this paper, an integrated investigation of the drinking water quality and associated human health risks of contaminated groundwater was carried out using geochemical models, numerical water quality models, and the HHRISK code. Physicochemical analysis revealed that the groundwater pH is acidic. Predicted results from PHREEQC model showed that most of the major chemical and trace elements occurred as free mobile ions while a few were bounded to their various hydrated, oxides and carbonate phases. This may have limited their concentration in the groundwater; implying that apart from anthropogenic influx, the metals and their species also occur in the groundwater as a result of geogenic processes. The PHREEQC-based insights were also supported by joint multivariate statistical analyses. Groundwater quality index, pollution index of groundwater, heavy metal toxicity load, and heavy metal evaluation index revealed that 60-70% of the groundwater samples within the two metropolises are unsuitable for drinking as a result of anthropogenic influx, with Pb and Cd identified as the priority elements influencing the water quality. The HHRISK code evaluated the ingestion and dermal exposure pathway of the consumption of contaminated water for children and adult. Results revealed that groundwater from both areas poses a very high chronic and carcinogenic risk from ingestion than dermal contact with the children population showing greater vulnerability. Aggregated and cumulative HHRISK coefficients identified Cd, Pb, and Cu, to have the highest health impact on the groundwater quality of both areas; with residents around Awka appearing to be at greater risks. There is, therefore, an urgent need for the adoption of a state-of-the-art waste management and water treatment strategies to ensure safe drinking water for the public.

Metal(loid)s in tap-water from schools in central Bangladesh (Mirpur): Source apportionment, water quality, and health risks appraisals

Considering the health risks originating from the exposure of metal(loid)s in tap-water and the concomitant vulnerability of school-going students, 25 composite tap water samples from different schools and colleges of central Bangladesh (Mirpur, Dhaka) were analyzed by atomic absorption spectroscopic technique. Elemental abundances of Na, Mg, K, Ca, Cr, Mn, Fe, Co, Ni, Zn, As, Cd, and Pb in the studied tap water samples varied from 4520 to 62250, 2760-29580, 210-3000, 15780-78130, 1.54-5.32, 7.00-196, 2.00-450, 0.04-1.45, 8.23-24.4, 0.10-813, 0.10-10.5, 0.002-0.212, and 1.55-15.8 μgL^-1, respectively. Dissolved metal(loid)s' concentrations were mostly within the national and international threshold values with few exceptions which were also consistent with the entropy-based water quality assessment. Multivariate statistical approaches demonstrated that hydro-geochemical processes like water-rock interactions mostly govern the major elemental (Na, Mg, K, Ca) compositions in tap water. However, anthropogenic processes typically control the trace elemental compositions where supply pipeline scaling was identified as the major source. Cluster analysis on sampling sites separated two groups of schools and colleges depending on their establishment years where tap water from older schools and colleges possesses relatively higher levels of metal(loid)s. Hence, gradual pipeline scaling on a temporal scale augmented the metal(loid)s' concentrations in tap-water. In terms of non-carcinogenic health risks estimation, studied tap-water seems to be safe, whereas elemental abundances of Pb and As can cause carcinogenic risks to school-going people. However, progressive deterioration of water quality by pipeline scaling will be supposed to cause significant health risks in the future, for which preventative measures should be adopted.

Inconsistency of PCA-based water quality index - Does it reflect the quality?

The formalization of a stable water quality index (WQI) from measured hydrogeochemical parameters is essential for the identification and classification of water resources. In the principal component analysis (PCA) based WQI approach, the parameter weight is derived using either PC loading or rotated factor loading from a large number of samples pooled for WQI measurement. The PCA-based approach is paradoxical, as the calculated WQI rating of a sample would rather be dependent on the size, and composition of the population. Though this issue is well anticipated, no attempt has been made to regularize or measure the extent of WQI disagreement. In the present study, the WQI of 106 groundwater samples analyzed for 12 different hydrochemical parameters were modelled using PC loading or rotated factor loading (referred to as PCQ-1, PCQ-2, respectively) approach. Analysis reveals PCQ-1 to be positively biased in 78 % of samples and rating disagreements were evident in 9.43 % of samples. WQI of the data set was estimated using repeated (1000) random non-overlapping 2 to 5-fold data partitioning (containing 21 to 83 samples in each fold) adopting either an in-sample (test set) or out-sample (train set) modelling approach. The mean of WQI deviations in repeated resampling from the reference (i.e., using the entire dataset) has been positive in most of the samples using the PCQ-1 model, irrespective of the fold partition size. The median root mean square deviation values of the data set increased with the number of fold partitioning for in-sample calibration for both PCQ-1 and PCQ-2 approaches. The exclusion of a single water quality parameter from the PCA model can cause up to a 60 % deviation of the WQI score in some water samples. The cross-validation and Monte Carlo resampling approach can serve as a framework to test the stability of PCA-based WQI.

Spatial distribution, water quality, human health risk assessment, and origin of heavy metals in groundwater and seawater around the ship-breaking area of Bangladesh

The concentrations of eleven heavy metals (Pb, Cd, Cr, Fe, Mn, Zn, Cu, Ni, Co, As, and Ag) were assessed in both groundwater and seawater collected from the ship-breaking industrial area of Bangladesh using an atomic absorption spectrometer. The investigation aimed to estimate the water quality and pollution level employing several indices, and its associated health risks for the first time in that area. This study found that Cd, Cr, Fe, Pb, Mn, and Ni were higher in both groundwater and seawater compared with WHO standards. Based on the WQI (water quality index) and EWQI (entropy water quality index) classifications, the quality of most of the groundwater is extremely poor or unsuitable for drinking purposes. Furthermore, the HPI (heavy metal pollution index), HEI (heavy metal evaluation index), and CD (degree of contamination) values of most groundwater and all seawater samples exhibit a higher degree of pollution. In addition, the results of NI (Nemerow pollution index) come to an end that both groundwater and seawater in the study area are mostly polluted by Fe, Mn, Pb, Cr, and Cd. Although the HI (hazard quotient index) values of almost all studied heavy metals in both cases of adults and children are within the safe limit, the HI value of Cr for an adult is near the threshold limit and the maximum HI value of Cr for children exceeds this limit. The carcinogenic risk reveals that Cr, Pb, As, and Cd produce detrimental effects on local people through the direct ingestion of groundwater. The pollution source is identified using principal component analysis and a Pearson correlation matrix as being primarily anthropogenic and attributed to intensive ship-breaking activities or other industries in the area.

Entropy-assisted approach to determine priorities in water quality monitoring process

Effective determination of water quality and water pollution assessment is crucial and challenging processes. Evaluating water quality in rivers, researchers have referred to various statistical, probabilistic and stochastic methods to obtain efficient information from the monitoring network. As data are greatly random, the information content can be obtained by utilizing various methods including but not limited to the "entropy." Monitoring is a difficult process due to high measurement costs, while it is also difficult to optimize the network in terms of time, space, and especially the variable to be monitored. In the presented study, it is aimed to create an effective approach to be used in optimizing the monitoring network by determining the "prior" variables by entropy that measures the uncertainty by using all the data without time difference. The presented study proposes an alternative method to define the water quality variables that should be monitored much more frequently. Study is exemplified for demonstrating its potential use in a case study level, Grand River in Canada, by assessing water quality data obtained from 15 water quality monitoring stations. Results showed that BOD, Cl, and NO₂-N among examined 8 different variables are as the "prior" variables should be monitored. It is being proven that the prior variable that should be monitored for optimization of the network can be easily determined with the information obtained from the data statistically evaluated with entropy, and it can be stated as an effective method for managers to use in the decision-making process.

A green method for removing chromium (VI) from aqueous systems using novel silicon nanoparticles: Adsorption and interaction mechanisms

In the present study, we used the horsetail plant (Equisetum arvense) as a green source to synthesize silicon nanoparticles (GS-SiNPs), considering that it could be an effective adsorbent for removing chromium (Cr (VI)) from aqueous solutions. The characterization of GS-SiNPs was performed via Brunauer-Emmett-Teller (BET), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and X-ray photo electron spectroscopy (XPS) techniques. The batch test results of Cr (VI) adsorption on GS-SiNPs showed a high adsorption capacity, reaching 87.9% of the amount added. The pseudo-second order kinetic model was able to comprehensively explain the adsorption kinetics and provided a maximum Cr (VI) adsorption capacity (Q_e) of 3.28 mg g^-1 (R² = 90.68), indicating fast initial adsorption by the diffusion process. The Langmuir isotherm model fitted the experimental data, and accurately simulated the adsorption of Cr (VI) on GS-SiNPs (R² = 97.79). FTIR and XPS spectroscopy gave further confirmation that the main mechanism was ion exchange with Cr and surface complexation through -OH and -COOH. Overall, the results of the research can be of relevance as regards a green and new alternative for the removal of Cr (VI) pollution from affected environments.

Groundwater quality evaluation and human health risks assessment using the WQI, NPI and HQnitrate models: case of the Sfax intermediate aquifer, Sahel Tunisia

Groundwater is a vital natural resource required to satisfy the domestic and agricultural needs. In general, human health is linked to the quality of the consumed water. For instance, long-term exposure to high nitrate levels in groundwater may cause problems. Hence, the present study was conducted to assess the nitrate contamination of groundwater as well as its related health risks for the inhabitants of the Sfax region, Sahel Tunisia. Irrigation groundwater suitability has been evaluated with sodium content (%Na), electrical conductivity (EC), magnesium hazard (MH), sodium adsorption ratio (SAR), permeability index (PI), Kelly's ratio (KR) and soluble sodium percent (SSP). The results indicate that the selected groundwater is characterized by low to moderate quality for irrigation. Furthermore, the drinking water quality index (DWQI) was assessed using potential of hydrogen (pH), total dissolved solids (TDS), magnesium (Mg²⁺), calcium (Ca²⁺), sodium (Na⁺), chloride (Cl^-), sulfate (SO₄^2-), potassium (K⁺), bicarbonate (HCO₃^-) and nitrate (NO₃^-). The results indicate that 3.63% of samples have good quality of water, while 41.82% have poor to very poor water quality and the rest (54.55%) are unfit for drinking. The nitrate pollution index (NPI) model revealed that about 42% of the samples present significant to very significant type of pollution. Based on human health risk assessment, the children are at higher risks compared to the other affected groups. The obtained results could be used as a basic document for realistic management of groundwater quality and to provide an overview for decision-making authorities to take necessary actions.

Combining data-intelligent algorithms for the assessment and predictive modeling of groundwater resources quality in parts of southeastern Nigeria

Machine learning algorithms have proven useful in the estimation, classification, and prediction of water quality parameters. Similarly, indexical modeling has enhanced the evaluation and summarization of water quality. In Nigeria, works that have incorporated machine learning modeling in water quality analysis are scarce. Although studies across the globe have utilized overall index of pollution (OIP) and water quality index (WQI), works that have simulated and predicted them using machine learning algorithms seem to be scarce. Studies have not simulated nor predicted OIP. In this paper, several physicochemical parameters were analyzed and used for groundwater quality modeling in southeastern Nigeria based on integrated data-intelligent algorithms. Standard methods were followed in all the analysis and modeling performed in this work. OIP and WQI were computed, and their results revealed that 80% of the groundwater resources are suitable for drinking whereas 20% are highly polluted and unsuitable. Pearson's correlation analysis and R-mode hierarchical clustering revealed the possible sources of contamination. Meanwhile, agglomerative Q-mode hierarchical clustering and K-means (partitional) clustering were used to show the spatial demarcations of water quality in the area. Both clustering algorithms identified two main water quality classes-the suitable and unsuitable classes. Furthermore, multiple linear regression (MLR) model and multilayer perceptron neural networks (MLP-NN) were used for the estimation and prediction of the water quality indices. With low modeling errors, both MLR and MLP-NN showed very strong predictions, as their determination coefficient ranged between 0.999 and 1.000. However, MLR slightly outperformed the MLP-NN in the prediction of OIP. The findings of this paper would enhance sustainable water management in the study region and also contribute great insights to the national and global water quality prediction literatures.

Chemometric approach in environmental pollution analysis: A critical review

With the ever-increasing global population and industrialization, it has become a call of the hour to start taking care of the environment to balance the ecosystem. For this, effective monitoring and assessment are required, which involves collecting and measuring environmental details, temporal and spatial readings of environmental data, and parameters. However, assessment of the environment is very tedious as it includes monitoring target analytes, identifying their sources, and reporting, which invariably implies that detailed environmental monitoring would be an intricate and expensive process. The traditional protocols in environmental measures are often manual and time demanding, which makes it further difficult. Moreover, several changes also occur within the environment, which could be chemical, physical, or biological, and since these environmental impacts are often cumulative, it becomes difficult to measure an isolated system. Furthermore, the chances of skipping significant results and trends become high. Also, experimental data obtained from the environmental analysis are usually non-linear and multi-variant due to different associations among various contributing variables. Therefore, it is implied that accurate measurements and environment monitoring are not using traditional analytical protocols. Thus, the need for a chemometric approach in environmental pollution analysis becomes paramount due to the inherent limitations associated with the conventional approach of analyzing environmental datasets. Chemometrics has appeared as a potential technique, which enhances the particulars of the chemical datasets by using statistical and mathematical analysis methods to analyze chemical data beyond univariate analysis. Utilizing chemometrics to study the environmental data is a revolutionary idea as it helps identify the relationship between sources of contaminations, environmental drivers, and their impact on the environment. Hence, this review critically explores the concept of chemometrics and its application in environmental pollution analysis by briefly highlighting the idea of chemometrics, its types, applications, advantages, and limitations in the environmental domain. An attempt is also made to present future trends in applications of chemometrics in environmental pollution analysis.

Data-driven soft computing modeling of groundwater quality parameters in southeast Nigeria: comparing the performances of different algorithms

In recent decades, the simulation and modeling of water quality parameters have been useful for monitoring and assessment of the quality of water resources. Moreover, the use of multiple modeling techniques, rather than a standalone model, tends to provide more robust and reliable insights. In this present paper, several soft computing techniques were integrated and compared for the modeling of groundwater quality parameters (pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), modified heavy metal index (MHMI), pollution load index (PLI), and synthetic pollution index (SPI)) in Ojoto area, SE Nigeria. Standard methods were employed in the physicochemical analysis of the groundwater resources. It was found that anthropogenic and non-anthropogenic activities influenced the concentrations of the water quality parameters. The PLI, MHMI, and SPI revealed that about 20-25% of the groundwater samples are unsuitable for drinking. Simple linear regression indicated that strong agreements exist between the results of the water quality indices. Principal component and Varimax-rotated factor analyses showed that Pb, Ni, and Zn influenced the judgment of the water quality indices most. Q-mode hierarchical and K-means clustering  algorithms grouped the water samples based on their pH, EC, TDS, TH, MHMI, PLI, and SPI values. Multiple linear regression (MLR) and artificial neural network (ANN) algorithms were used for the simulation and prediction of  the pH, EC, TDS, TH, PLI, MHMI, and SPI. The MLR performed better than the ANN model in predicting EC, TH, and TDS. Nevertheless, the ANN model predicted the pH better than the MLR model. Meanwhile, both MLR and ANN performed equally in the prediction of PLI, MHMI, and SPI.

Modeling the impact of potentially harmful elements on the groundwater quality of a mining area (Nigeria) by integrating NSFWQI, HERisk code, and HCs

With excess potentially harmful elements (PHEs), drinking water is marked unsuitable and could pose some health risks when ingested or absorbed by humans. Different age groups are exposed to varied risk levels of PHEs. Analyzing the health risks of PHEs for several age groups could provide detailed insights for effective water resources management. No known study in Ameka Pb-Zn mine province (Nigeria) investigated the health risks of PHEs in water resources for several age groups. Therefore, in this paper, the carcinogenic and non-carcinogenic health risks (due to ingestion and dermal contact) of PHEs in groundwater resources of this area were investigated for nine age groups. To achieve its aim, this study integrated novel HERisk code, NSFWQI (national sanitation foundation water quality index), and hierarchical clusters (HCs) in modeling the groundwater quality. Standard elemental composition analysis revealed that the groundwater is polluted with PHEs. The NSFWQI indicated that 15% of the analyzed water samples have moderate water quality whereas 85% are unsuitable for drinking. The HERisk code, which considered nine age groups (1 to < 2 years, 2 to < 3 years, 3 to < 6 years, 6 to < 11 years, 11 to < 16 years, 16 to < 18 years, 18 to < 21 years, 21 to < 65 years, and > 65 years), revealed that all the samples pose high chronic and cancer risks to all the age groups due to oral ingestion. However, it was realized that age groups 1 to < 16 and > 65 are posed with higher risks than age groups 18 to < 65. Overall, it was realized that all the age groups are far more exposed to ingest or absorb Se, Co, Cd, Se, As, Ni, and Pb than Cu, Fe, and Zn. Nevertheless, the health risks due to dermal absorption are far lower than the risks due to oral ingestion. Conclusively, children and aging people are more predisposed to the health threats than middle-aged populations. HCs and geospatial maps aided the spatiotemporal analysis of the groundwater quality.

Assessment of the groundwater quality, physicochemical composition, and human and ecological health risks in a coastal metropolitan: A case study of a residential estate in Lagos, Nigeria

Water is essential for humankind's existence, providing food security, amongst others, as well as promoting industrial and economic development. The physicochemical composition, potentially toxic metals, water quality index, human health, and ecological risks of groundwater in a residential estate in Lagos, Nigeria, were studied to assess their possibility for drinking and domestic purposes. Groundwater samples were collected from twelve designated sites and analysed using standard methods. TDS and pH values of 5.4 ± 1.7-20.8 ± 0.84 and 5.08 ± 0.26-5.56 ± 0.57, respectively, were recorded for the groundwater samples whereas DO and BOD were detected at 4.2 ± 1.2-5.45 ± 0.52 mg O₂/L and 2.6 ± 1.2-24.6 ± 5.7 mg/L, respectively. Additionally, water conductivity ranged from zero to 0.60 ± 0.89 µS/cm. Of the seven PTMs (Pb, Cd, Zn, Cu, Cr, Ni, & Fe) analysed, Pb was present, over the standard limit, in all the samples whereas Fe was detected below the limit in over 83.3% of the groundwater sampled. The hazard index (HI) indicated that 83.3% and 100% of the samples were within the acceptable limits, with no health risks, for the children and adult groups, respectively. WQI showed that 75.0% of the samples was of good quality and suitable for domestic purposes, with low ecological and carcinogenic health risks. The results show that the groundwater samples are good for domestic purposes but require pre-treatment to make them safe for drinking.

Heavy metal concentrations in rivers and drinking water of Esmeraldas (Ecuador) under an intermittent water supply service

Universal access to safe water is a major global goal, but these efforts could be at stake because drinking water sources are becoming polluted in many developing countries. Chlorine, major ions, and heavy metals were measured in rivers and drinking water of Esmeraldas because potential pollution sources raise concerns about the quality of the water supply, and because users have developed strategies to cope with water shortages including collecting river water and water distributed by tankers, storing water at home, and consuming commercial bottled water. We sampled water from the water distribution system (WDS) and the Esmeraldas and Teaone rivers including the intake to the potabilization plant, water distributed by tankers, and commercial bottled water. Most of the samples collected from the Esmeraldas and Teaone rivers, the WDS, and tankers complied with drinking water standards, but higher concentration of cadmium and other metals in the eastern part of the city is an indication of corrosion inside the WDS. Commercial bottled and WDS water showed similar heavy metal concentrations, but regular consumption of some brands may lead to higher exposure to arsenic and mineral deficiencies. Chlorine concentrations in the water supplied by the WDS were below the values required for safe disinfection, and in-house chlorination is uncommon in the city. Strengthening pollution control in the Esmeraldas river, monitoring corrosion of the WDS, and promoting point-use chlorination and better water handling practices are required to secure a safer water supply in the long term.

Discussion on the existing methodology of entropy-weights in water quality indexing and proposal for a modification of the expected conflicts

The present research focuses on addressing various ambiguities in the existing method of integrating information entropy and water quality, thereby presenting a novel approach for an entropy-weighted water quality index. A three-dimensional water quality dataset is considered in the proposed method, the third dimension being the sampling frequency factor. The probability of observed values adhering to desirable limits prescribed by a standard code is estimated, leading to the computation of information entropy and, eventually, entropy weights. These weights are then used for the computation of the Modified Entropy-weight Water Quality Index (MEWQI) values. To verify the proposed method's applicability, the water quality dataset of Deepor Beel, India, was considered. IS 10500: 2012 was used for estimating MEWQI values. Results showed an excellent correlation with the observed dataset and their uncertainties of occurrence. The reliability and correctness of the proposed methodology were finally confirmed through both cluster analysis and sensitivity analysis. The cluster analysis showed remarkable associations with the computed MEWQI values, while the sensitivity analysis proved that no particular parameter was accountable for the contribution of MEWQI values; instead, all parameters exhibited equal contributions. The proposed methodology was thus found to be the most reasonable and reliable as it considered both factors, i.e., measured values concerning standard limits and the uncertainty, necessary for a consistent water quality monitoring program.