Multivariate statistical approach and water quality assessment of natural springs and other drinking water sources in Southeastern Nigeria

Risk assessment of potentially toxic elements and mapping of groundwater pollution indices using soft computer models in an agricultural area, Northeast Algeria

Groundwater (GW) quality and contamination by potentially toxic elements (PTEs) are major concerns for environmental sustainability, particularly in arid regions. The aim of this study was to assess the human health risks associated with GW contamination by PTEs in the Terminal Complex (TC) aquifer of the Tolga oasis, located in northeastern Algeria. Seventeen GW samples were analyzed using standard methods to determine contamination levels and associated health risks. Results showed that GW was generally contaminated with lead (Pb), which exceeded the WHO permissible limit of 0.01 mg/L in 76.47 % of the samples. Although some samples were rich in Cr and Mn, their levels were below WHO guidelines. Pollution indices, including Contamination Factor (CF), Heavy Metal Pollution Index (HMI), and Nemerow Pollution Index (NPI), indicated that over 50 % of the samples had medium to high pollution levels. These indices were further estimated using artificial neural network (ANN) and Multiple Linear Regression (MLR) machine learning models, whose performances were validated by Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Nash-Sutcliffe Efficiency Coefficient (NSE). The Taylor diagram analysis showed that MLR models were more accurate than ANN models in estimating GW pollution indices. Mapping these indices using support vector machine (SVM) algorithms and applying chemometric statistical techniques, including principal component analysis (PCA), revealed that alteration of geological formations and anthropogenic activities significantly affected GW contamination by PTEs in the study area. The assessment of health risks associated with heavy metals revealed a significant non-carcinogenic risk, particularly for children, with 41.17 % of samples exceeding the hazard index threshold of 1 due to Pb exposure, while carcinogenic risks were low. This study establishes predictive models based on heavy metal pollution indices, providing crucial information on the spatial distribution of GW contamination. The results support the development of targeted mitigation strategies and intervention plans to safeguard GW resources and public health in the region.

Local residents' perception on factors affecting the willingness to pay for improved urban canal water: a case study in Can Tho city of Vietnam

Urbanization and economic development cause water pollution in the inner-city canals and rivers globally. Bung Xang canal in Can Tho city of Vietnam is facing problems with water pollution due to the lack of centralized wastewater treatment plants and low public awareness on environmental protection. Perception of local residents was collected using structured questionnaires including both qualitative and quantitative information. Regression analysis was employed to evaluate the factors affecting the decision of respondents on the willingness to pay (WTP) to improve water quality in the Bung Xang canal. Knowledge about the environmental protection fee for domestic wastewater (10% of the VAT-excluded from the selling price of 1 m3 of tap water purchased), age of the respondents and their education levels affected the WTP positively, while respondents' perception on water quality affected the WTP negatively. There was 58.33% of the respondents showed the WTP for improved water quality in the canal. They agreed to pay a small fee of VND 10,000 to 15,000 (equivalent to USD 0.42-0.63)/month (1 US$= 23,700 VND). The result indicates that environmental education is the only way forward for a successful sustainable urban city.

Groundwater quality evaluation of the weathering mantle in crystalline basement aquifer system, southern Brazil

Groundwater is the main source of water for more than 2 billion people worldwide. In southern Brazil, the Crystalline Basement Aquifer System is composed of strategic groundwater reservoirs. Groundwater is mostly taken from shallow wells, and it is often used without any treatment, which poses a risk to public health. The present study aims to evaluate shallow groundwater quality and the geochemistry of shallow and deep groundwater located in the municipality of Canguçu, southern Brazil. The physicochemical and microbiological parameters of groundwater samples collected from shallow wells were monitored and analyzed using ANOVA variance analysis and water quality index (CCME WQI) approaches. Also, the results were compared with secondary data from deep wells. The monitored shallow wells had thermotolerant coliforms, Escherichia coli, pH, potassium, manganese, iron, and nitrate in disagreement with the guidelines of the World Health Organization. Moreover, variance analysis showed that the parameters temperature, dissolved oxygen, pH, chloride, and magnesium were the most influenced by seasonal variations. According to the CCME WQI, most samples had good quality (60%), 28% had fair quality, and 12% had poor quality. In addition, the field campaigns with higher precipitation rates also presented fair quality. Therefore, most of the shallow groundwater quality is affected by surface pollutants from the urban area, aggravated in rainy periods. Whereas deep groundwater is influenced by geochemistry mechanisms. The results revealed the risk of water consumption for public health and the urgent need for better maintenance of these wells and water treatment implementation.

Multi-model exploration of groundwater quality and potential health risk assessment in Jajpur district, Eastern India

The presence of fluoride and nitrate is a serious groundwater quality issue in India impacting human health. In the present study, 14 different hydrochemical parameters for 76 groundwater samples collected from the Jajpur district of Odisha, India, were evaluated. Entropy-weighted water quality index (EWQI), fixed-weight groundwater quality index (GWQI), principal component analysis (PCA), and rotated factor loading-based water quality index (PCWQI) were employed to assess groundwater quality. About 65.79 ± 4.68%, 33.55 ± 3.95%, and 0.66 ± 0.76% of the samples were rated as "excellent," "good," or "medium" quality, respectively, across the four different water quality indices, with a nominal rating discrepancy of 13.15%. Though 86% of samples consistently received excellent or good ratings across all WQI frameworks, concentrations of F- and NO3- in 36.8% and 11.84% of the samples exceeded the WHO permissible limit. In health risk assessment, about 38.15% of samples surpassed the F- hazard quotient (HQ > 1) posing non-carcinogenic health risks for children. The non-carcinogenic health risks due to NO3- were evident in 55.26% and 11.84% of samples for children and adults, respectively. The higher concentration of NO3- in some of the water samples, together with its positive correlation with HCO3-, may worsen groundwater pollution. The moderate correlation between Ca2+ and HCO3- (r = 0.410) and the insignificant correlation between Mg2+ and HCO3- (r = 0.234) suggests calcite dissolution is far more common than dolomite.

A GIS approach for groundwater quality evaluation with entropy method and fluoride exposure with health risk assessment

This study used the entropy water quality index to analyse the suitability of groundwater for human consumption as well as the hazard index to identify the probable non-carcinogenic dangers among children, women, and men in Nawada, Bihar (India). A total of 75 groundwater samples were taken from hand pumps and tube/bore wells in the pre-monsoon of 2017, and they were evaluated for various physicochemical characteristics. The region's groundwater major cations and anions are dominated by Ca2+ > Mg2+ and [Formula: see text] > Cl- > [Formula: see text]  > NO3- > F > [Formula: see text]. Fluoride, chloride, and hardness exceeded WHO and BIS safe standards. Calcium, sodium, magnesium, sulphate, and chloride showed positive correlations, indicating water-rock interactions and mineral leaching and dissolution. Ionic cross-plots reveal that the dissolution of carbonate minerals was the primary source of calcium and magnesium in the groundwater. Also, silicate weathering contributed to these ions in the groundwater. The entropy water quality index (EWQI) found that 79% of groundwater samples were drinkable, whereas 21% were not consumable. The eastern, western, and some southern study areas have the worst drinking water quality. The main source of fluoride toxicity in people is groundwater. For all sampling locations, the HQ fluoride was calculated to be in the ranges of 0.04-3.69 (male), 0.04-3.27 (female), and 0.05-4 (children), indicating a considerably greater risk than the permissible levels (> 1). The fluoride-based non-carcinogenic risks are 27%, 20%, and 21% for children, women, and men, respectively. Children have higher risks from polluted water than adults, according to the non-carcinogenic health risk assessment. This study establishes a standard for regional and global scientific studies that help decision-makers and planners determine the quality of groundwater and fluoride risk and management.

Impact of pharmaceutical industry wastewater on stress physiological responses of Spirodela polyrhiza (L.) Schleiden

Impact of pharmaceutical wastewater collected from aeration tank on aquatic macrophyte Spirodela polyrhiza (L.) Schleiden was studied in the present study. Various plant parameters such as chlorophyll, protein, and proline content of wastewater-exposed plants were examined to determine the toxic impacts of pharmaceutical wastewater. In addition to these parameters, electrolyte leakage (EL) and catalase (CAT) activities in S. polyrhiza were assessed for each day of exposure to the wastewater. S. polyrhiza was exposed to four different wastewater concentrations (25%, 50%, 75%, and 100%) under laboratory conditions for 7 days. The plants experienced severe toxicity as revealed by the reduction in photosynthetic pigments, increase in electrolyte leakage, and enhancement of antioxidant enzyme (CAT) activity in S. polyrhiza with an increase in concentration and time of exposure to pharmaceutical effluent.

Modeling, quality assessment, and Sobol sensitivity of water resources and distribution system in Shiraz: A probabilistic human health risk assessment

Given water's vital role in supporting life and ecosystems, global climate change and human activities have significantly diminished its availability and quality. This study explores the health risks of drinking water consumption in the shiraz county water resources and distribution system. The result showed that the water was slightly alkaline. However, the average pH values during the study were within the permissible range. The area's abundance of total hardness and calcium was due to the high concentration of minerals in rocks and soils. The nitrate and fluoride concentrations in drinking groundwater varied from 0.02 to 116.70 mg/L and 0.10-1.85 mg/L, respectively. Although the water quality index indicated that 52.63, 45.03, and 20.3 percent of samples were of excellent, good, and poor quality in 2020, those percentages obtained 46.05, 52.09, and 14.0 percent in 2021. The regression values of training, testing, validation, and the proposed artificial neural network model were 0.93, 0.92, 0.85, and 0.92. The maximum levels of hazard quotient of nitrate and fluoride (except for adults) were higher than 1 in all age groups, indicating a high non-carcinogenic risk by exposure to nitrate. Furthermore, according to the Monte Carlo simulation, the 95th percentile hazard index in all groups was more than 1. Children and infants were more inclined towards risk than teens and adults based on the intake of nitrate and fluoride from drinking water. The Sobol sensitivity reflected that the nitrate concentration and ingestion rate are vital parameters that influence the outcome of the oral exposure model for all age groups. The interaction of ingestion rate with a concentration of nitrate and fluoride is an important parameter affecting the health risk assessment. In conclusion, these findings suggest that precise measures can reduce health risks and guarantee safe drinking water for residents of Shiraz County.

Spring water quality monitoring using multiple bioindicators from multiple collection sites

The aim of this study was to examine the water quality of the Extrema River spring in a Brazilian Cerrado area. Three collection sites (P1 - P3) were sampled in the dry and rainy seasons, which are close to industries from different sectors. In the physicochemical analysis, a decrease in dissolved oxygen levels (<5 mg/L) and pH (< 6) at P3 was detected. An increase in heterotrophic bacteria count was recorded at all sites (> 500 colonies/ml). In ecotoxicological analyses, P2 and P3 exhibited toxicity using Vibrio fischeri (> 20%). In evaluating toxicity, the reduction in seed germination was significant utilizing Lactuca sativa at all locations and with Allium cepa only at P2; rootlet length was decreased at P3 on L. sativa and at all sites with A. cepa. In contrast, loss of membrane integrity and mitochondrial function of meristems was adversely affected at all locations using both L. sativa and A. cepa assays. Principal components analysis (PCA) approach indicated that seasonality apparently did not markedly interfere with the obtained data, but it is important to include more collection locations to be evaluated with multiple bioindicators in the spring region. Our data indicate the urgent need for more rigorous programs to monitor the discharge of effluents into water springs.

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.

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.

Statistical assessment of seasonal variations in water quality for different regions in Lake Van (Türkiye)

On earth, surface water bodies interact and change with the natural ecosystems. These surface waters and water quality may be adversely affected due to different factors. To analyze the effects, parameters indicating water pollution and quality and the possible causes of these parameters should be examined. In addition, environmental pollution issues should be controlled by taking measures. The most important surface water body in the province of Van, located in the east of Türkiye, is the biggest soda Lake Van. The population density around the lake, human polluting factors, unconscious beach use, inadequate wastewater treatment, agriculture and livestock activities, small-scale industrial areas, and chemicals used create a pollution effect. In the study, data were obtained during year of 2018 from six important sampling points around Lake Van and from the middle of the lake. Twenty-seven water quality parameters were analyzed separately and together. These variables' yearly values were evaluated with Turkish Surface Water Quality Regulation (TSWQR, 2015). As a result, these points were determined to have class I in terms of water parameters according to the seasonal data. The basic descriptive statistics were compared with the regulation, and max, mean, and min values were examined. Data analyzed were done with probability-normality, trend analysis, correlation, and regression methods. The results of this study are that general parameters were normal and the quality of the six points continued to be similar. Na⁺, Cl^-, salinity, and TDS were highly correlated, while DO and F were high matrix value parameters. EC, TDS, and SS regression equations provided high correlation parameters.

Spatial water quality assessment of a mountain stream in northwestern India using multivariate statistical techniques

The water quality of Himalayan rivers and streams is deteriorating due to multitude of anthropogenic and natural influences and the changes are more pronounced in smaller hill basins with high human influx. Inadequate data and lack of monitoring further exacerbate the situation. The surface water quality of one such hill stream, Neeru was evaluated for potability and irrigation quality. The water quality parameters were analysed at 25 sampling stations over a stretch of 30 km across four seasons during a 2-year study from January 2014 to December 2015. The CCME Water Quality Index (WQI) indicated excellent water quality in upstream stations, while the midstream and a few downstream stations revealed varying degrees of impaired water quality. Although the irrigation quality of the stream was excellent, pollution levels near urban areas were rather high, necessitating considerable treatment for human consumption. The factor analysis yielded seven components with Eigenvalues greater than one that accounted for 83.656% of the variance and enabled the grouping of selected parameters based on comparable characteristics. The hydrogeochemical characteristics of the water samples indicated that they lie within the zone of rock dominance, while the trilinear diagram depicted the Ca-bicarbonate rich stream water. The study concluded that the upstream stations revealed pristine water quality, which significantly degraded towards human settlements. It thus calls for regular and long-term monitoring of the surface water quality to ensure the continuous and sustainable use of this important water body.

Assessment of groundwater geochemistry using multivariate water quality index and potential health risk in industrial belt of central Odisha, India

Groundwater in India has been shown to have a variety of water quality issues, including fluoride, nitrate, and uranium pollution, all of which pose a health risk to humans. In the present study, a total of 106 groundwater samples from the Angul district of Odisha, an industrialized region in India, were analyzed for 14 different hydrochemical parameters. In almost 30%, 34.9%, and 4.7% of the groundwater samples, the concentrations of F-, NO^3- and uranium, respectively, exceeded the permissible limit set by WHO. In addition to the fixed-weight groundwater quality index (GWQI), the entropy-weighted water quality index (EWQI), the principal component analysis (PCA) factor (or rotated factor) loading based water quality index (PCWQI) and human health risk assessment were used. Depending on the models, about 19.1 ± 0.9%, 70.5 ± 1.9% and 10.38 ± 1.9% of water samples were classified as "Excellent", "Good" and "Medium" quality, respectively, across four water quality indexes with a nominal rating disagreement of 11.3%. More than 90% of samples are unanimously classified as excellent or good across the WQI rating. For children and adults, approximately 54.7% and 24.5% of samples exceeded the permitted limit for F^-, (hazard quotient HQ > 1), posing non-carcinogenic health hazards, respectively. In contrast, 71.7% and 34.9% of NO₃^- samples respectively, surpassed the allowed limit and caused non-carcinogenic health concerns for children and adults. In terms of carcinogenic HQ values, about 13.2% and 7.5% of samples exhibit an uranium related carcinogenic health risk in children and adults, respectively. The existence of significant amounts of Cl ^-, NO₃^-, and especially HCO₃^- ions in groundwater in some samples, as well as their positive interdependence, may increase uranium pollution in the future through uranium dissolution.

Potable water quality assessment of traditionally used springs in a hilly town of Bhaderwah, Jammu and Kashmir, India

The quality of spring water and its suitability for human consumption is determined by examining its physicochemical and microbiological characteristics. Preliminary investigations were conducted to determine the potability of seven traditionally used springs in the highly populated hill town of Bhaderwah in Union Territory of Jammu and Kashmir, India. The water analysis was performed for various physico-chemical and microbial parameters during April 2019-March 2020. Water temperature, TDS, EC, pH, DO, free CO₂, total alkalinity, total hardness, Ca²⁺, Mg²⁺, Na⁺, K⁺, CO₃^2-, HCOֿ₃, Cl‾, NOֿ_3, PO₄^3-, SO₄^2-, total coliforms, and thermotolerant coliforms were all measured. Eleven physical and chemical characteristics were used to generate the Water Quality Index. The Piper diagram demonstrated the predominance of Ca²⁺-HCOֿ₃ water types, whereas the Schoeller diagram indicated that all springs had a similar lithological origin. The chemical composition of springs tested met the required criteria for drinking water quality. The microbiological indicators, on the other hand, did not satisfy the criteria except for Eidgah spring, which lacked thermotolerant coliforms. Our results on spring water potability indicate that the town's most dependable springs are susceptible to anthropogenic contamination and therefore need treatment prior to use. Apart from frequent monitoring, the responsible municipal corporation is expected to develop comprehensive plans to rehabilitate and revitalise these vulnerable drinking water sources.

Pharmaceuticals, pesticides and metals/metalloids in Lake Guaíba in Southern Brazil: Spatial and temporal evaluation and a chemometrics approach

Compiling and reporting data related to the presence of pharmaceuticals and pesticides are crucial means of assessing the risk those chemicals pose to human health and environment. Data sets from different sources were combined using a data fusion approach to produce a spatial and temporal variation of contaminants presents in water from Lake Guaíba (29°55'-30°24' S; 51°01'-51°20' W). Lake Guaíba is a 496 km² water body situated in the geological depression of Rio Grande do Sul State, Brazil; that is fed by several rivers from the metropolitan area, the 5th largest metro area in Brazil, with approximately 5 million inhabitants. Analytical methodology to quantify pharmaceuticals and pesticides by LC-QTOF-MS and GC-MS/MS was validated for 41 pharmaceutical and 62 pesticides. Furthermore, 27 chemical elements were analyzed by ICP-MS, and physical chemical parameters were determined using established methodologies. All validation parameters were in accordance with the National Institute of Metrology, Standardization, and Industrial Quality. Thirty-five water samples were analyzed from January to August 2019, and 15 pharmaceuticals and 25 pesticides were present in concentrations ranging from 6.00 ng L^-1 to 580.00 ng L^-1. Twenty-seven elements were analyzed during the same period, and 18 were present in concentrations ranging from 0.2 μg L^-1 to 7060 μg L^-1. Samples were tagged according to the points and months of collection to identify temporal and spatial patterns. The main findings show that the compounds are distributed throughout the studied area without an apparent regular pattern, suggesting that events in a specific point affect the entire ecosystem. Conversely, temporal variations were well defined, as samples were grouped according to the climatic conditions of the months of collection. Considering the calculated quotient risks, atrazine, cyproconazole, diuron, and simazine showed the highest risk levels for algae; acetaminophen, diclofenac, and ibuprofen showed the highest risk levels for aquatics invertebrates.

An appraisal of data collection, analysis, and reporting adopted for water quality assessment: A case of Nigeria water quality research

The appropriate acquisition and processing of water quality data are crucial for water resource management. As such, published articles on water quality monitoring and assessment are meant to convey essential and reliable information to water quality experts, decision-makers, researchers, students, and the public. The implication is that such information must emanate from data obtained and analysed in an up-to-date, scientifically sound manner. Thus, inappropriate data analysis and reporting techniques could yield misleading results and mar the endeavours of achieving error-free conclusions. This study utilises the findings on water quality assessment in Nigeria over the last 20 years to reveal the likely trends in water quality research regarding data collection, data analysis, and reporting for physicochemical, bacteriological parameters, and trace organics. A total of 123 Web of Science and quartile ranked (Q1-Q4) published articles involving water quality assessment in Nigeria were analysed. Results indicated shortcomings in various aspects of data analysis and reporting. Consequently, we use simulated heatmaps and graphs to illustrate preferred ways of analysing, reporting, and visualising some regularly used descriptive and inferential statistics of water quality variables. Finally, we highlight alternative approaches to the customarily applied water quality assessment methods in Nigeria and emphasise other areas of deficiency that need attention for improved water quality research.

GIS, Multivariate Statistics Analysis and Health Risk Assessment of Water Supply Quality for Human Use in Central Mexico

The spatial assessments of water supply quality from wells, springs, and surface bodies were performed during the dry and rainy seasons in six municipalities in the eastern regions of Michoacán (Central Mexico). Different physicochemical parameters were used to determine the supplies’ Water Quality Index (WQI); all of the communities presented good quality. The analysis indicates that many water quality parameters were within limits set by the international standards, showing levels of “excellent and good quality” according to WQI, mainly during the dry season (except at San Pedro Jácuaro and Irimbo communities in the rainy season). However, some sites showed “poor quality” and “unsuitable drinking water” related to low pH levels (<5) and high levels of turbidity, color, Fe, Al, Mn, and arsenic. Multivariate statistical analysis techniques (Principal Component and Hierarchical Cluster) and geographic information system (GIS) identify potential sources of water pollution and estimate the geographic extension of parameters with negative effects on human health (mainly in communities without sampling). According to multivariate analysis, the Na+/K+ ratio and water temperature (22–42 °C) in various sites suggest that the WQI values were affected by geological and geothermal conditions and physical changes between seasons, but were not from anthropogenic activity. The GIS established predictions about the probable spatial distribution of arsenic levels, pH, temperature, acidity, and hardness in the study area, which provides valuable information on these parameters in the communities where the sampling was not carried out. The health risk assessment for dermal contact and ingestion showed that the noncancer risk level exceeded the recommended criteria (HQ > 1) in the rainy season for three target groups. At the same time, the carcinogenic risk (1 × 10−3) exceeded the acceptability criterion in the rainy season, which suggests that the As mainly represents a threat to the health of adults, children, and infants.

WITHDRAWN: Investigation of drinking water quality and population health risk assessment in a poor rural area

Ahead of Print article withdrawn by publisher.

Impact of some beverage industries on the physicochemical characteristics of Ajali River in Enugu, Nigeria

Ajali River near some beverage industries was assessed. Eleven physicochemical parameters and six heavy metals (copper, zinc, iron, cadmium, chromium, and lead) were analyzed on water and sediment collected from different locations near three beverage industries. Standard methods were used to determine the physicochemical parameters while heavy metals were determined with atomic absorption spectrophotometer. The health risk assessment of the water samples were estimated by calculating the hazard quotient (HQ), total hazard index (THI), and the probability cancer risk (PCR) of the heavy metals. Results showed that the concentrations of some heavy metal and physicochemical properties were slightly impaired compared to permissible standards. However, cadmium in water (0.56-11.34 mg/L) and sediments (2.81-481.40 mg/kg) samples were above the recommended limit, indicating possible cadmium pollution in the study area. The water quality index values showed that some of the sampled locations had poor (53.43-134.90%) water quality. The risk assessment of the water samples revealed that HQ for Cu, Zn, Fe, and Cr were of no probable risk (HQ < 1) while Cd (HQ = 173-438) were of probable risk. THI of the water samples showed probable risk (THI > 1) resulting from the high percentage contribution of Cd (94.13 to 99.95%). The probability carcinogenic risk assessment for adults (Cd-7.14 × 10^-2, Cr-1.43 × 10^-4) and children (Cd-1.66 × 10^-1 and Cr-3.34 × 10^-4) were significantly harmful. Even though the presence of these industries could encourage more economic activities in the area, there is need for the relevant agencies to enforce effective treatment and proper management of wastes especially cadmium, to safeguard this water source for the rural dwellers.

Nanocomposites for Electrochemical Sensors and Their Applications on the Detection of Trace Metals in Environmental Water Samples

The elevated concentrations of various trace metals beyond existing guideline recommendations in water bodies have promoted research on the development of various electrochemical nanosensors for the trace metals' early detection. Inspired by the exciting physical and chemical properties of nanomaterials, advanced functional nanocomposites with improved sensitivity, sensitivity and stability, amongst other performance parameters, have been synthesized, characterized, and applied on the detection of various trace metals in water matrices. Nanocomposites have been perceived as a solution to address a critical challenge of distinct nanomaterials that are limited by agglomerations, structure stacking leading to aggregations, low conductivity, and limited porous structure for electrolyte access, amongst others. In the past few years, much effort has been dedicated to the development of various nanocomposites such as; electrochemical nanosensors for the detection of trace metals in water matrices. Herein, the recent progress on the development of nanocomposites classified according to their structure as carbon nanocomposites, metallic nanocomposites, and metal oxide/hydroxide nanocomposites is summarized, alongside their application as electrochemical nanosensors for trace metals detection in water matrices. Some perspectives on the development of smart electrochemical nanosensors are also introduced.

A comprehensive review of water quality monitoring and assessment in Nigeria

Nigeria is the most populated black nation in the world with about 199 million people. About 66.3 million Nigerians do not have access to safe drinking water. In this study, research findings on water quality monitoring and assessment in Nigeria over the past two decades were systematically reviewed. There are still grave enforcement issues in Nigeria as quality guidelines are still being contravened at no cost to the infringer due to the corrupt socio-political circumstances of the country. The quality of surface water, groundwater, rainwater and commercially available water was discussed in line with their pollution sources. The quality of surface water was generally poor. Groundwater pollution has come due to landfill leachate, oil and gas exploration and production, sewage and hydrogeological interactions of the groundwater with the base rock. The hydrogeological effect has led to the observation of lead and barium in groundwater in many locations across the country. The main issue with rainwater in Nigeria is the low pH but it was observed to be fairly clean. Commercially available water (bottled or sachet) is currently the best source of drinking water for the Nigerian populace. Bottled water quality is higher than for sachet water and the latter largely influenced by microbe contamination. Future perspectives in water quality monitoring and assessment are suggested in the evaluation of emerging contaminants and micro-pollutants and the utilisation of internet-enabled technologies.

Application of Irrigation Water Quality Indices and Multivariate Statistical Techniques for Surface Water Quality Assessments in the Northern Nile Delta, Egypt

Under sustainable development conditions, the water quality of irrigation systems is a complex issue which involves the combined effects of several surface water management parameters. Therefore, this work aims to enhance the surface water quality assessment and geochemical controlling mechanisms and to assess the validation of surface water networks for irrigation using six Water Quality Indices (WQIs) supported by multivariate modelling techniques, such as Principal Component Regression (PCR), Support Vector Machine Regression (SVMR) and Stepwise Multiple Linear Regression (SMLR). A total of 110 surface water samples from a network of surface water cannels during the summers of 2018 and 2019 were collected for this research and standard analytical techniques were used to measure 21 physical and chemical parameters. The physicochemical properties revealed that the major ions concentrations were reported in the following order: Ca2+ > Na+ > Mg2+ > K+ and alkalinity > SO42− > Cl− > NO3− > F−. The trace elements concentrations were reported in the following order: Fe > Mn > B > Cr > Pb > Ni > Cu > Zn > Cd. The surface water belongs to the Ca2+-Mg2+-HCO3− and Ca2+-Mg2+-Cl−-SO42− water types, under a stress of silicate weathering and reverse ion exchange process. The computation of WQI values across two years revealed that 82% of samples represent a high class and the remaining 18% constitute a medium class of water quality for irrigation use with respect to the Irrigation Water Quality (IWQ) value, while the Sodium Percentage (Na%) values across two years indicated that 96% of samples fell into in a healthy class and 4% fell into in a permissible class for irrigation. In addition, the Sodium Absorption Ratio (SAR), Permeability Index (PI), Kelley Index (KI) and Residual Sodium Carbonate (RSC) values revealed that all surface water samples were appropriate for irrigation use. The PCR and SVMR indicated accurate and robust models that predict the six WQIs in both datasets of the calibration (Cal.) and validation (Val.), with R2 values varying from 0.48 to 0.99. The SMLR presented estimated the six WQIs well, with an R2 value that ranged from 0.66 to 0.99. In conclusion, WQIs and multivariate statistical analyses are effective and applicable for assessing the surface water quality. The PCR, SVMR and SMLR models provided robust and reliable estimates of the different indices and showed the highest R2 and the highest slopes values close to 1.00, as well as minimum values of RMSE in all models.

Analysis of the qualitative evolution of groundwater in the Abouabou area in the Port-Bouët municipality (Abidjan, Côte d'Ivoire)

The study aimed to analyze the seasonal qualitative evolution of the Quaternary groundwater in the Abouabou area in order to see the capacity of this water to be used as a water supply by the populations. In-situ measurements (temperature, electrical conductivity, dissolved oxygen, turbidity and pH) and chemical parameter analyses (NH₄⁺, Ca²⁺, Mg²⁺, K⁺, Na⁺, NO₃^-, NO₂^-, PO₄^3-, SO₄^2-, Cl⁻ and HCO₃^-) were performed on the 24 samples collected during the four (4) seasons of the year. The use of Kruskal-Wallis and ANOVA tests has allowed the monitoring of seasonal variations in hydro-chemical parameters in well and borehole water. Also, the Piper diagram permit to identify the main hydrochemical facies according to the seasons. Finally, the Kohonen Self Organizing Maps (SOM) method was applied to physico-chemical parameters in order to highlight the spatial distribution of groundwater quality in the Abouabou area. The results show that, based on the physico-chemical parameters analysed, the groundwater is of good quality due to meeting WHO standards for drinking water consumption during all seasons of the year. Significant seasonal variations were recorded in the values of the parameters like turbidity, pH and Cl⁻ for well water and turbidity, PO₄^3-, NO₃^-, NH₄⁺, K⁺, Cl⁻ for borehole water. The hydrochemical facies shows a seasonal variation. Analysis of Abouabou's water reveals the variation of its hydrochemical facies. Thus, bicarbonate, calcium and magnesium facies during the long dry and rainy seasons move towards the chlorine, calcium and magnesium facies during the short dry and rainy seasons. Four water groups have been identified using SOM method, including heterogeneous groups composed mainly of borehole water (I and III) or of well water (II and IV). Borehole and well water acquire most of their mineralization by the infiltration of surface elements. Drinking water from boreholes is of good quality.

Application of Multivariate Statistical Analysis in the Development of a Surrogate Water Quality Index (WQI) for South African Watersheds

Water quality indices (WQIs) are customarily associated with heavy data input demand, making them more rigorous and bulky. Such burdensome attributes are too taxing, time-consuming, and command a significant amount of resources to implement, which discourages their application and directly influences water resource monitoring. It is then imperative to focus on developing compatible, simpler, and less-demanding WQI tools, but with equally matching computational ability. Surrogate models are the best fitting, conforming to the prescribed features and scope. Therefore, this study attempts to provide a surrogate WQI as an alternative water quality monitoring tool that requires fewer inputs, minimal effort, and marginal resources to function. Accordingly, multivariate statistical techniques which include principal component analysis (PCA), hierarchical clustering analysis (HCA) and multiple linear regression (MLR) are applied primarily to determine four proxy variables and establish relevant model coefficients. As a result, chlorophyll-a, electrical conductivity, pondus Hydrogenium and turbidity are the final four proxy variables retained. A vital feature of the proposed surrogate index is that the input parameters qualify for inclusion into remote monitoring systems; henceforth, the model can be applied in remote monitoring programs. Reflecting on the model validation results, the proposed surrogate WQI is considered scientifically stable, with a minimum magnitude of divergence from the ideal water quality values. More importantly, the model displayed a predictive pattern identical to the ideal graph, matching on both index scores and classification values. The established surrogate model is an important milestone with the potential of promoting water resource monitoring and assisting in capturing of spatial and temporal changes in South African river catchments. This paper aims at outlining the methods used in developing the surrogate water quality index and document the results achieved.

Increased health threats from land use change caused by anthropogenic activity in an endemic fluorosis and arsenicosis area

Urbanization is conducive to promoting social development and improving living standards. However, the changing land use attributed to urbanization has placed both the environment and humans at risk. Based on the long-term monitoring and the land use change during 2010-2017, we investigated the exposure of fluoride (F) and arsenic (As) in groundwater. We analyzed the temporal and spatial variation of F and As from different land use changes. The study assessed health risk for children by calculating carcinogenic risk and non-carcinogenic risk. Furthermore, we mapped the distribution pattern of F and As using GIS. For the 768 water samples collected from 2010 to 2017, F concentrations ranged between 0.10 and 5.70 mg L^-1 (M = 0.68 ± 0.02 mg L^-1), As concentrations ranged between 0.50 and 71.50 μg L^-1 (M = 4.28 ± 0.28 μg L^-1). A concerning result showed that 6.77% of F concentrations larger than 1.5  mg L^-1 and 11.46% of As concentrations larger than 10 μg L^-1 based on the recommendation by WHO, respectively. Results proved that land use change caused by human activity increased groundwater pollution and placed human health at risk. High F and As risk were found in southern Taiyuan City. In particular, the groundwater of industrial land suffered from more severe pollution, especially at the frontier of urban and suburban areas in the southern part of Taiyuan City. Land use change attributed to industrial land resulted in major increases in the F and As concentrations in groundwater across 2010-2017. Both carcinogenic risk and non-carcinogenic risk in 2016-2017 were higher than that in 2010-2015. Rational land use planning, strict groundwater protection policies and the regular monitoring of pollution levels are necessary in order to prevent the adverse health of residents.

Lithium in drinking water sources in rural and urban communities in Southeastern Nigeria

There is a dearth of data on lithium content of domestic water sources in Nigeria. This study reported the lithium concentration in ground and surface water sources used for drinking in Southeastern Nigeria. Thirteen (13) natural springs, 24 streams, 7 hand-dug wells and 80 boreholes, making a total of 124 water samples were collected from strategic locations and analysed by ICP-OES. The distribution of lithium according to water sources and lithostratigraphic units as well as dietary contribution of lithium through drinking water was investigated. Average lithium concentrations in water samples from all sources were between 0.09 and 1.54 μg/L (overall mean ± SEM: 1.0 ± 0.2 μg/L). Results according to the geological formations of the areas studied indicated that only water sources located within the Benin Formation and Bende-Ameki Formation contained lithium in the range of <0.21-7.24 and < 0.21-1.97 μg/L respectively, whereas lithium was not detected in samples located within the Nsukka and Mamu lithostratigraphic units. Total intakes of lithium from water consumption (0.64 L for children and 2 L for adults) for all water sources were 79 and 247 μg/day for children and adults respectively, while the average daily intake of lithium from the water sources ranged from 0.004 to 0.066 and 0.002-0.044 μg/kg body weight for children (15 kg) and adults (70 kg) respectively. Drinking water in the study areas contributes only about 0.02-0.47% of the U.S. EPA estimated daily intake (9.3-44.3 μg/kg) of Lithium.

Assessment of spa mineral water quality from Vrnjačka Banja, Serbia: geochemical, bacteriological, and health risk aspects

The goal of this study is to evaluate the quality of seven natural mineral water sources in the Vrnjačka Banja area used in the treatment of various diseases. The 24 macro- and microelements were determined by inductively coupled plasma optical emission spectrometry (ICP-OES). The results show that element content was within allowed limits of concentration, except for B, As, and Se. The evaluated content of these elements can be associated with geological and anthropogenic factors. The sample S6 contains more than twice the concentration of As, meaning that the use of water from this source should be limited due to the negative impact of this element on human health. The calculated values of weekly (EWI) and oral (OI) intakes as well as the acute hazard quotient (HQ_A) of selected toxic and potentially toxic elements indicate no health risks to the consumers. The highest hazard quotient (HQ_L) observed for As in sample S6 (2.0·10^-1) demonstrated a significant risk of carcinogenic diseases in long-term consumption from this source. The estimated non-carcinogenic (DI_A) and carcinogenic (DI_L) dermal intakes with acute (HQ_A) and long-term (HQ_L) hazard quotient values for sample S3 show that there is no health risk to those who use the water from this thermal source for bathing. The presence of aerobic mesophilic bacteria at 22 °C and 37 °C in samples S3, S6, and S7 as well as sulphite-reducing Clostridia species in sample S5 were detected, potentially indicating some non-faecal or faecal contamination.

Expounding the origin of chromium in groundwater of the Sarigkiol basin, Western Macedonia, Greece: a cohesive statistical approach and hydrochemical study

The aim of this paper is to provide a methodology including statistical tools and spatial techniques, in order to identify the various potential sources of chromium (Cr_tot) in the Sarigkiol basin, Western Macedonia, Greece, where elevated concentrations of Cr_tot in groundwater have been recorded since 1996. Integrated hydrochemical approach and statistical analyses including Pearson's correlation coefficient, multivariate statistical analyses (factor analysis and hierarchical cluster analysis), and spatial techniques (Moran's I spatial autocorrelation index and bivariate local indicator spatial association cluster map) were applied to evaluate the chemical analyses of 73 water samples, from irrigation wells, natural springs, and surface water. Both natural and anthropogenic sources of Cr_tot were recorded; the first (ultramafic-dominated environment) is strongly depicted on the natural spring water, in which Cr_tot concentrations as high as ~ 130 μg/L were recorded, whereas the second (agricultural activities) acts synergistically in the irrigation wells of the Sarigkiol basin, in which strong correlations of Cr_tot, P, and NO₃^- were defined. The paper highlights its findings by outlining the potential sources of elevated concentrations of Cr⁶⁺ in the Sarigkiol basin, stressing the need for a closer attention on the role of agricultural activities as an important, though commonly neglected, anthropogenic source of Cr_tot in groundwater.

A multi-class classification system for continuous water quality monitoring

The issue addressed in this exposition is the classification of multivariate data collected through different sensors for water quality monitoring. Multivariate data are sequences that have various attributes in every instance of the sequences. A few endeavours exist to address this issue; however, none of them has given full emphasis on continuous dataset. Another solution for this issue is to reduce the instances to a single attribute while losing significant information. Different arrangements address both the multivariate and the sequential part of the data yet give an un-versatile solution. The proposed algorithm is not only able to monitor continuous water quality, but it also produces a better classification model for other continuous datasets as well. Instead of decreasing the attributes of the dataset, we introduce three additional reference indicators which are dependent on the actual attributes. We compare the classification accuracy of our proposed algorithm with standard classification models. The proposed method gives better classification accuracy compared to existing methods.