Groundwater Samples Research Articles

Cost‐effective amperometric sensor for monitoring levofloxacin in groundwater

AbstractThe presence of water micropollutants, such as antibiotics, has proved the necessity to develop novel and cost‐effective devices for their identification and quantification. These devices aim to save time, reagent usage, and costs associated with conventional analytical methods. In this work, we introduce poly(methylene blue) based screen‐printed electrodes (SPE‐PMB) as electrochemical sensors designed for the quantification of levofloxacin (LVX), given its current prevalence as a micropollutant. Integrating the fabrication and measurement processes into a single electrochemical device is a significant step in creating affordable detection tools. The proposed sensor was assessed using LVX solutions prepared in real groundwater samples, demonstrating its selectivity and achieving a detection limit of 3.3 μM. Finally, we compared the SPE‐PMB sensor and high‐performance liquid chromatography (HPLC) to validate its operation and performance. Consequently, our results suggest that the sensor can be a viable alternative to chromatographic methods for identifying and quantifying micropollutants at very low concentrations in complex matrices.

Factors Affecting Distribution and Ecological Risk Assessment of Volatile Organic Compounds (VOCs) in Groundwater of the Huazhou District in Northwestern China

Volatile organic compounds (VOCs) pollution in groundwater is a significant global concern. In this study, 26 groundwater samples were collected from the unconfined aquifers in Huazhou District, northwestern China, to assess their distribution characteristics, influencing factors, and ecological risks across various geomorphological settings. The findings revealed 35 VOCs in collected groundwater samples, with aromatic hydrocarbons having the highest detection rate (100%), and the VOCs distribution exhibited significant spatial variations, with the highest VOCs concentration near a chemical plant on the inclined pluvial plain. The lithology and groundwater flow influenced the vertical and lateral transport of VOCs, with concentrations decreasing as the aquifer permeability decreases along the groundwater flow from the inclined pluvial plain to the river. The Mantel test was used to analyze the correlation between VOCs and environmental factors, geochemical analyses indicated that nitrate (NO3-) and sulfate (SO42-) served as electron acceptors in the anaerobic biodegradation of organic pollutants, with bicarbonate (HCO3-) levels increasing as a result of this biodegradation. Additionally, the curved streamline searchlight shaped model (CS-SLM) was applied to identify the primary land use types affecting VOCs content, construction land and cropland were primary land use types affecting VOCs distribution. Finally, the ecological risk assessment indicated the highest risk quotient (RQ) for styrene (0.21), suggesting a manageable risk level. The study emphasizes the complexity of VOCs contamination in groundwater, providing a foundation for targeted mitigation strategies.

Highly Sensitive Electrochemical Detection of Chlorpromazine Using Broccoli‐Like Copper–Aluminum‐Layered Double Hydroxide‐Modified Platinum Electrode

AbstractChlorpromazine (CPZ), an antipsychotic drug derived from phenothiazine, can cause a range of adverse effects in humans, notably visual problems and hematological disorders upon consumption of chlorpromazine‐contaminated water. In this regard, a novel electrochemical sensing platform based on a copper–aluminum‐layered double hydroxide (Cu–Al LDH)‐modified platinum electrode for the highly sensitive and selective detection of chlorpromazine in groundwater samples has been developed. The immobilized Cu–Al LDH showed an electrocatalytic effect on chlorpromazine reduction and oxidation. Among the employed electroanalytical techniques, only the square‐wave voltammetry‐assisted Pt/Cu–Al LDH electrode could detect chlorpromazine with a remarkable sensitivity of 0.065 µA µM−1 over a broad linear detection range of 0.01–760 µM, with low detection and quantification limits of 4.86 and 16.18 nM, respectively. Furthermore, the developed electrode can rapidly detect chlorpromazine within less than 10 s. In addition, the diffusion profiles of steady‐state concentrations of oxidized and reduced chlorpromazine within the immobilized Cu–Al were studied using the Legendre wavelet method. Moreover, the developed Pt/Cu–Al LDH electrode demonstrated satisfactory rates in the quantification of chlorpromazine in groundwater samples, yielding satisfactory recovery rates (97.63–102.57%), confirming the practicability of the fabricated electrode in real‐time monitoring of chlorpromazine levels in groundwater without requiring any sample pretreatment.

Characterization of microplastics in soil, leachate and groundwater at a municipal landfill in Rayong Province, Thailand

Recent years have witnessed a dramatic increase in global plastic production, leading to heightened concerns over microplastics (MPs) contamination as a significant environmental challenge. MP particles are ubiquitously distributed across both continental and marine ecosystems. Given the paucity of research on MPs in Thailand, particularly regarding MPs contamination in terrestrial environments, this study focused on investigating the distribution and characteristics of MPs in a landfill area. We collected 15 soil samples, 2 leachate samples, and 5 groundwater samples from both inside and outside a municipal landfill situated in the urbanized coastal region of Rayong Province. Our findings revealed variability in MPs concentration across different sample types. In soil, the MP count ranged from 240 to 26,100 pieces per kg of dry soil, 58.71 % of all sample sizes are lower than 0.5 mm. Similarly, the size found in the leachate sample, and the average MP in the leachate samples was 139 pieces per liter of MPs. The groundwater samples showed a fluctuation in MPs count from 26 to 94 pieces per liter, and the size of MPs ranged mostly from 0.5 to 1 mm. The predominant forms of MPs identified were sheets, followed by fragments, fibers, and granules. According to μ-FTIR analysis, the majority of the MPs were composed of polyethylene and polypropylene, commonly used in plastic packaging and ropes. The observed high concentrations and extensive distribution of MP contamination underscore the urgency for further studies and effective management strategies to mitigate the adverse impacts of this pollution on various organisms and ecosystems.

Assessment of heavy metal contamination in groundwater and its implications for dental and public health

Groundwater contamination with heavy metals is a critical environmental issue, especially in regions heavily reliant on groundwater for drinking purpose. These metals can seep into groundwater from soil and rock weathering or through improper disposal of industrial waste and effluents. Access to safe drinking water is essential for maintaining public health. This study aimed to assess heavy metal contamination in groundwater and its implications for dental and public health. The objective of the study was to measure the concentration of the heavy metals in the dentine of extracted tooth of the study population. The study concurrently measured heavy metal concentrations in groundwater and tooth dentine samples, analyzing demographic profiles, heavy metal correlations, and underlying structures using Principal Component Analysis (PCA). The average level of heavy metals in the groundwater samples varied from 9.763 ± 3.362 μg/L for Cd to 3426.204 ± 875.264 μg/L for Fe. The mean concentrations (μg/g) in teeth dentine showed significant variations, with iron (Fe) ranging from 0.149 ± 0.03 μg/g in water purifiers to 4.62 ± 0.578 μg/g in local water sources. Similar variations were observed for other heavy metals across different water sources. Principal component analysis (PCA) revealed seven principal components, with the first two components explaining 96.1% of the total variance. The findings revealed varied concentrations of heavy metals across all water sources. Statistical analyses underscored the complex relationship between water sources and heavy metal contamination levels, highlighting the need for targeted interventions to improve water quality and mitigate health risks. The study highlights the urgent need for monitoring and mitigation efforts to ensure safe drinking water and mitigate health risks associated with heavy metal contamination.

Multivariate statistical and hydrogeochemical analysis of seasonal groundwater quality variations in coastal villages of Trivandrum district, south India

This study attempts a detailed assessment of the quality of groundwater in the coastal region of Trivandrum District, Kerala where groundwater is the main source of drinking water. Forty groundwater samples were collected during the pre-monsoon and post-monsoon periods. The collected samples were analyzed for physical properties such as electrical conductivity (EC), pH, total dissolved solids (TDS), and total hardness, along with chemical properties, including major cations (Ca2⁺, Mg2⁺, Na⁺, K⁺) and anions (Cl⁻, SO₄2⁻, HCO₃⁻, NO₃⁻). The analysis of groundwater quality reveals significant spatial and seasonal variations caused by both natural and manmade influences. Water Quality Index (WQI), hydrogeochemical plots, and Principal Component Analysis (PCA) were used to analyses the data. The results show that Vakkom, Kazhakottam, Veli-Attipara, and Pozhiyoor show significant deterioration, and areas such as Varkala, Ayroor, and Edava generally maintain good water quality. The Water Quality Index (WQI) assessment indicates that approximately 22.5% of the studied area falls under excellent quality, while 17.5% is classified as poor. The WHO standard and BSI standards were used to derive the WQI. Principal Component Analysis (PCA) identified electrical conductivity, total dissolved solids, and total hardness as the primary factors affecting groundwater quality, explaining 65.17% and 61.03% of the total variance in the pre-monsoon and post-monsoon periods, respectively. Hydrochemical plots collaborate these results, emphasize the influence of rock-water interactions as the main geochemical process, further compounded by pollution from agricultural runoff and urban development. These findings highlight the need for sustainable groundwater management strategies in coastal communities. Effective measures, including pollution mitigation, sustainable agricultural practice, proper waste management, and preservation of freshwater ecosystems, are essential for ensuring the sustainability of groundwater resources.

Mineral pollutants and coliform contamination in groundwater pose health risks to consumers: a spatiotemporal study in a mining-impacted area

The presence of mineral pollutants, combined with bacterial contamination, has significantly impacted groundwater quality and led to various health-related issues in mining-impacted areas. Therefore, we measured the concentration of fluoride (F-), phosphate (PO43-), sulphate (SO42-), ammonium (NH4+), nitrate (NO3-), the total coliforms (TCs), and physiochemical characteristics in groundwater samples of South Khorasan, Eastern Iran. For this, we collected water samples from 100 wells in spring and autumn across this mining-impacted area. We then measured the concentrations of mineral pollutants and assessed their associated health risks to children and adults using the Environmental Protection Agency (EPA) models and spatiotemporal zoning maps in ArcGIS. The concentrations of PO43-, NH4+, SO42-, NO3-, and F- were 0.70 ± 0.34, 0.82 ± 0.9, 175.45 ± 123, 15.26 ± 9.41, and 0.53 ± 0.68 mg/L in spring, and 0.71 ± 3.18, 4.68 ± 31, 306.72 ± 615.80, 19.30 ± 15.61, and 0.72 ± 0.65 mg/L in autumn, respectively. PO43-, NH4+, and SO42- exceeded both the World Health Organization (WHO) and EPA, but NO3- exceeded only EPA standards. TCs in both seasons exceeded the standards set by the EPA and WHO. The hazard quotient (HQ) values indicated non-carcinogenic risks for F⁻ and NO3⁻, while posing no risks NH4⁺ and PO43⁻ in both adults and children during autumn and spring.Hazard index (HI) was greater than 1 for all minerals in both children and adults in autumn and spring. No correlation was observed between mineral compounds and TCs in the study area, yet the water samples were highly contaminated by coliform with a significant risk to adults and children. In essence, both mineral pollutants and TCs potentially pose serious risks to human, and more efforts are required to improve the quality of water in this area.

Application of geospatial and machine learning algorithms to predict (under certain limitations) the quality of groundwater used for irrigation purposes

ABSTRACT The main objective of the present study is to evaluate groundwater quality for irrigation purposes in the central-western part of Haryana state (India). For this, 272 groundwater samples were collected during the pre- and post-monsoon periods in 2022. Several indices, including SAR, PI, Na%, KR, magnesium adsorption ratio (MAR), and IWQI were derived. The results of SAR, Na%, and KR values indicate that the groundwater is generally suitable for irrigation. On the other hand, PI and MAR exceeded the established limits, primarily showing issues related to salinity and magnesium content in the groundwater. Furthermore, according to the IWQI classification, 47.06 and 25% of the total collected samples fell under the ‘severe restriction for irrigation’ category during the pre-monsoon and post-monsoon periods, respectively. Spatial variation maps indicate that water quality in the western portion of the study area is unsuitable for irrigation during both periods. Three ML algorithms, namely RF, SVM, and XGBoost were integrated and validated to predict the IWQI. The results revealed that the XGBoost with random search achieves the best prediction performances. The approaches established in this study have been confirmed to be cost-effective and feasible for groundwater quality, using hydrochemical parameters as input variables, and highly beneficial for water resource planning and management.

An integrated approach of support vector machine (SVM) and weight of evidence (WOE) techniques to map groundwater potential and assess water quality

This study addresses the critical need for effective groundwater (GW) management in Muzaffarabad, Pakistan, amidst challenges posed by rapid urbanization and population growth. By integrating Support Vector Machine (SVM) and Weight of Evidence (WOE) techniques, this study aimed to delineate GW potential zones and assess water quality. This study fills the gap in applying advanced machine learning and geostatistical methods for accurate GW potential mapping. Eight thematic layers based on topography, hydrology, geology, and ecology were utilized to compute the GW potential model. Additionally, water quality analysis was performed on collected samples. The findings indicate that flat and gently sloping terrains, areas with an elevation range of 611 –687 m, and concave slope geometries are associated with higher GW potential. Additionally, proximity to drainage and high-density lineament zones contribute to increased GW potential. The results showed that 31.1% of the area had excellent GW potential according to the WOE model, whereas the SVM model indicated that only 20.3% fell in the excellent potential zone. Results showed that both models performed well in the delineating GW potential zones. Nevertheless, the application of the SVM method is highly recommended which will be benefited in GW resources management related to urban planning. The study also evaluates the spatial distribution of GW quality, with a focus on physical and chemical parameters, including electrical conductivity, pH, turbidity, total dissolved solids, calcium, magnesium, chloride, nitrate, and sulphate. Bacterial contamination assessment reveals that 76% of spring water samples (30 out of 39 samples) are contaminated with E.coli, raising public health concerns. Based on the chemical analysis of GW samples the study identified exceedances of WHO guidelines for calcium in two samples, magnesium in seven samples, sulphate in ten samples, and nitrate levels were below the WHO guideline across all samples. These results highlight localized chemical contamination issues that require targeted remediation efforts to safeguard water quality for public health.

Analysis of Groundwater Quality in Semi-arid Region of Eastern - South Rajasthan on the Basis of Water Quality Index (WQI)

Abstract: The present study was conducted to evaluate the groundwater quality for drinking purposes in selected locations of the Eastern- South Rajasthan of India. Total eight sights groundwater samples were collected during 2022 and the samples were analyzed for physicochemical parameters i.e., pH, total hardness, total dissolved solids, Nitrate, Sulphate, fluoride, Chloride, and alkalinity were calculated. The results of the study are illustrated with the help of descriptive statistics, diagrams, and the water quality index (WQI). The focus of this research was to assess the current state of groundwater quality and the spatial distribution of characteristics in order to determine the quality of drinkable water. The WQI was used to categorize the samples into categories based on its acceptability for consumption. It is observed that most of the samples fall in the water unsuitable for drinking purposes category and a few samples are in the very poor water category.

Assessment of Groundwater Quality for Irrigation Suitability in Rajangaon Shenpunji and Surrounding Area, Aurangabad, Maharashtra, India.

The quality of irrigation water available to farmers has a significant impact on crop yield. Hence, it is need to better understand irrigation water quality. The present study mainly emphasizes the assessment of the suitability of 30 water samples from dug wells, bore wells and surface water bodies in Rajangaon Shenpunji and surrounding areas, Aurangabad, Maharashtra, India. The groundwater sample datasets of post-monsoon 2013 season were collected. The water quality parameters, viz. sodium adsorption ratio (SAR), percent sodium (%Na), residual sodium carbonate (RSC), residual sodium bicarbonate (RSBC), Kelly’s ratio (KR), magnesium adsorption ratio (MAR), permeability index (PI) have been calculated. Based on these calculated parameter results, prepared spatial distribution maps in Arc GIS 10.3 software. These parameters were correlated with standard permissible/desirable limits for irrigation use for the prevailing crops. Based on these factors, most of the samples fall into the category of water suitable for irrigation. A few samples that exceeded permissible limits were discovered in various geological and anthropogenic activities near the water samples in the study area. A complete investigation of groundwater quality may be suitable remedial action. Artificial recharge techniques are developed to increase the chemical concentrations in groundwater or suitable crops are working to continue the present water quality.

Spatial Distribution of Water Quality Parameters in a Mineralized Region of Rajasthan

Water quality parameters, anionic concentrations and uranium levels were measured in groundwater samples collected from Rohil, Sikar District, Rajasthan as a part of radiological baseline survey. This region hosts disseminated uranium deposits. The uranium concentration in water samples showed a mean value of 107 ± 141 μg/L and more than 40% samples crossed the AERB limit. The mean conductivity and TDS of samples were 2221 ± 1513 μS/cm and 1583 ± 1085 ppm, respectively. The mean value of fluoride, chloride, nitrate and sulphate were 2.4 ± 1.4 ppm, 414 ± 466 ppm, 33.70 ± 37.2 ppm and 140 ±133 ppm, respectively. Measured parameters in many samples were above the respective limits set by BIS, AERB and WHO. No particular trend was observed for any of the parameters with increasing distance from the proposed site and no correlation was evident in the measured parameters.

Trace Metal Elements (TMEs) in Groundwater Around the Former Industrial Gold Mine of Poura in Burkina Faso – West Africa

The objective of this study is to assess the quality of groundwater around the first industrial mine in Burkina Faso, whose activities have been closed since 1999. The diagnosis of pollution by trace metal elements of groundwater around the old Poura gold mine was carried out through the determination of the contents of Trace Metal Elements (TME) at MP-AES and the measurements of the physicochemical parameters in situ on 38 samples of borehole water. These data made it possible to calculate the pollution risk index, to establish correlations between the different physicochemical parameters on the one hand and with the trace metal elements on the other hand, from the Pearson matrix and to carry out a multivariate statistical analysis, in particular that in principal components (PCA), with a view to determining the origin of the polluting elements. The results obtained made it possible to identify four samples of groundwater with an acidic pH (GWF18 (6.44), GWF19 (6.39), GWF23 (6.1) and GWP01 (5.99)) and 34 samples of groundwater whose Cd, Al, Fe, As, Pb, or Hg contents are higher than the standards in force in Burkina Faso. The Pollution risk Index (PI) indicates that 35 groundwater samples are slightly polluted and 3 groundwater samples are very heavily polluted (GWP01 (PI = 456%), GWF06 (PI = 132.5%), GWF03 (PI = 105.1%)). The Pearson correlation matrix and the principal component analysis (PCA) show that the origin and mobilization of the trace metal elements involved (Al, As, Cd, Cr, Fe, Hg and Pb) are linked to natural mineralization and anthropogenic activities such as mining and agricultural activities, favored by the infiltration of water into the subsoil through geological structures such as fractures and faults.

Thoron, radon and microbial community as supportive indicators of seismic activity in groundwater

Earthquakes have a significant impact on groundwater environments as well as human life. However, identifying active and affected zones from seismic events using isotopic and microbial diversity indicators remains a challenging frontier. To validate the applicability of this coupled method for real-time analysis, we analyzed thoron (220Rn), radon (222Rn), microbial community compositions, and hydrochemistry in groundwater samples during the 2017 Pohang earthquake for the first time. We observed the detection of 220Rn in groundwater right before the aftershocks, with a high correlation to 222Rn concentrations. This indicates that 220Rn and 222Rn can serve as reliable seismic indicators for real-time analysis. The microbial data can assist in identifying affected groundwater zones, particularly when real-time detection of 220Rn is not feasible. At the phylum level, Peregrinibacteria and Firmicutes were only found in samples with detected thoron. At the genus level, hydrogen-oxidizing or sulfur-oxidizing bacteria could serve as indicators of active zones. Two statistical analyses, self-organizing map (SOM) and principal component analysis (PCA) using hydrochemical parameters, also correlated with the results from these coupled indicators. This study demonstrates the theoretical and practical applicability of 220Rn, 222Rn, and microbial community compositions as new multi-faceted ecological indicators, whether for real-time analysis or otherwise.

Assessment of the Quality of Borehole Water Collected Around Unlined Solid Waste Dumpsites within Awka Metropolis

Groundwater is an important natural resource that is essential to man and other living things. However, it can become polluted resulting from natural and anthropogenic conditions. The quality of selected groundwater samples collected from boreholes around abandoned and active dumpsites in Awka metropolis, Nigeria between January and March 2023, was assessed using water quality index (WQI) method. The samples were analyzed for their physico-chemical properties and some selected heavy metals using atomic absorption spectroscopy. The results of the physico-chemical analysis showed that the mean pH ranged from 5.75 – 6.71 in January as compared to 5.92 – 6.98 in February and 5.94 – 6.84 in March indicating slight acidity. Calcium and magnesium content ranged from 8 – 20mg/l of Ca2+ and 96 – 314 mg/l of Mg2+ ion. The concentration of heavy metals in the samples were all seen to be within the standard limits for potable water (Fe (0.057 – 2.384 ppm), Cu(0.00 – 0.185 ppm) except for mercury, lead and cadmium(Hg (0.00 – 0.248 ppm), Pb (0.00 – 0.051 ppm), Cd (0.006 – 0.39 ppm) for the month of February whereas heavy metal concentration for the month of March ranged from Fe (1.432 – 2.908 ppm), Cu (0.00 – 0.008 ppm), Hg (0.00 – 0.016 ppm), Pb (0.00 – 0.003 ppm), Cd (0.00 – 0.01ppm). Pollution Index of the sampled borehole water from the different locations shows that some were potable and can be consumed without treatment. The study shows that solid wastes contribute to the level of contamination caused by Heavy metals and some physico-chemical parameters in groundwater matrix.

Assessment of heavy metal contamination in groundwater of rural areas of Kurdistan Province Iran: A comprehensive study

This study focuses on the contamination of groundwater by heavy metals (HMs) in the Kurdistan Province of Iran, an area heavily reliant on these water resources, especially in rural regions. This research aimed to quantify the concentrations of 20 HMs in groundwater sources and assess the associated health risks, including both carcinogenic and non-carcinogenic effects, for different age groups. The study was conducted in 2024. We collected 155 groundwater samples from water resources of the villages in Kurdistan Province, west of Iran. The study encompassed comprehensive sampling of groundwater from various wells and springs throughout the province, which was subsequently subjected to thorough laboratory analysis utilizing Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) for the quantification of heavy metal (HM) concentrations. The highest concentrations of As, Co, Cu, and Mo were 7.90, 0.22, 2.48, and 1.68 μg/l, respectively. It was related to the cities of Qorveh, Sanandaj, Baneh, and Qorveh respectively. A Health Risk Assessment (HRA) was performed, indicating that, while the concentrations of most HMs were within the thresholds established by national and international standards, certain metals, such as arsenic and lithium, presented notable non-carcinogenic risks, especially to children. These metals were responsible for over 48 % of the cumulative hazard index (HI) across all ten cities evaluated. Furthermore, the HI for the adult demographic exceeded 1.0 (specifically 1.23) exclusively in Qorwe city. The study also identified a high carcinogenic risk associated with lead across the province, which has a carcinogenic risk of 7.3 × 10−03 in 10 studied cities, which is more than the guideline value of 10−04. The findings underscore the urgent need for continuous monitoring and the implementation of preventive measures to safeguard public health. The results provide crucial insights for policymakers and health authorities, facilitating informed decisions to mitigate the health risks posed by HM contamination in the region's groundwater.

Geoenvironmental and geophysical methods applied to identify natural attenuation process on a complex hydrogeological environment contaminated by hydrocarbons

Environmental contamination found in urban areas generally has a chemical composition that favors the generation of a variety of physical, chemical and biological processes that differ from natural soil parameters. Thus, understanding natural attenuation processes in tropical environments is still a challenge, as is understanding how biogeochemical processes can influence and modify natural soil characteristics. The study aimed to apply methods that are not commonly used in investigations of contaminated areas, in order to assess the applicability of non-invasive methodology for detailed stratigraphic characterization and biogeochemical changes resulting from contamination by hydrocarbons in a complex hydrogeological environment site. To date, few studies have presented results obtained using non-invasive techniques to understand biochemical processes. The research was based on the interpretation of results obtained by high-resolution physical environment characterization techniques (such as gamma geophysical profiling and electrical conductivity surveys) and chemical analysis of groundwater. The data was interpreted to obtain a detailed characterization of the study area and evidence of the occurrence of natural attenuation of creosote contamination. The results indicated that the combination of geoenvironmental and geophysical methods is an interesting alternative for obtaining data and understanding the mineralogical and stratigraphic variation of the contaminated area. The physical parameters variations obtained by the methods suggested the presence of local geochemical alterations resulting from natural processes of attenuation of contamination by aliphatic and aromatic hydrocarbons in a tropical environment. The natural attenuation processes were confirmed through groundwater samples, biological analysis and metagenomic classification.

Spatial analysis and soft computational modeling for hazard assessment of potential toxic elements in potable groundwater

Swiftly increasing population and industrial developments of urban areas has accelerated the worsening of the water quality in recent years. Groundwater samples from different locations of the Doon valley, Garhwal Himalaya were analyzed to measure concentrations of six potential toxic elements (PTEs) viz. chromium (Cr), nickel (Ni), arsenic (As), molybdenum (Mo), cadmium (Cd), and lead (Pb) using Inductively Coupled Plasma Mass Spectrometer (ICP-MS) with the aim to study the spatial distribution and associated hazards. In addition, machine learning algorithms have been used for prediction of water quality and identification of influencing PTEs. The results inferred that the mean values (in the units of µg L−1) of analyzed PTEs were observed in the order of Mo (1.066) > Ni (0.744) > Pb (0.337) > As (0.186) > Cr (0.180) > Cd (0.026). The levels and computed risks of PTEs were found below the safe limits. The radial basis function neural network (RBF-NN) algorithms showed high level of accuracy in the predictions of heavy metal pollution index (HPI), heavy metal evaluation index (HEI), non-carcinogenic (N-CR) and carcinogenic (CR) parameters with determination coefficient values ranged from 0.912 to 0.976. However, the modified heavy metal pollution index (m-HPI) and contamination index (CI) predictions showed comparatively lower coefficient values as 0.753 and 0.657, respectively. The multilayer perceptron neural network (MLP-NN) demonstrated fluctuation in precision with determination coefficient between 0.167 and 0.954 for the prediction of computed indices (HPI, HEI, CI, m-HPI). In contrast, the proficiency in forecasting of non-carcinogenic and carcinogenic hazards for both sub-groups showcased coefficient values ranged from 0.887 to 0.995. As compared to each other, the radial basis function (RBF) model indicated closer alignments between predicted and actual values for pollution indices, while multilayer perceptron (MLP) model portrayed greater precision in prediction of health risk indices.

Chlorine dioxide is a broad-spectrum disinfectant against Shiga toxin-producing Escherichia coli and Listeria monocytogenes in agricultural water

Agricultural water is commonly treated with chlorine-based disinfectants, which are impacted by water quality. Understanding how water quality influences disinfectants such as chlorine dioxide (ClO2) against pathogenic bacteria is important for creating efficacious sanitation regimens. In this study, the minimum inhibitory concentration (MIC) of ClO2 needed to achieve a 3-Log reduction against Shiga toxin-producing Escherichia coli (STEC) and Listeria monocytogenes was compared across agricultural water samples. Sterile ddH2O served as a control to compare with environmental samples from Salinas Valley, CA, and laboratory standards. To test different dosages and water qualities, stock ClO2 was diluted in 24-well plates with target concentrations of 10, 5, 2.5, and 1.25 mg/L. Well plates were inoculated with pathogens and treated with sanitizer for 5 min. Following treatment, surviving pathogens were enumerated using viable cell counts. The results demonstrate that groundwater samples had the highest water quality of the environmental samples and required the lowest concentration of disinfectant to achieve 3-Log reduction against both bacteria, with MIC between 1.4 and 2.0 mg/L. Open-source samples had lower water quality and required a higher concentration of ClO2 for 3-Log reduction, with MIC between 2.8 and 5.8 mg/L for both pathogens. There was no correlation between pH, turbidity, or conductivity/TDS and reduction for either STEC or L. monocytogenes, suggesting no individual water metric was driving reduction. A lower dosage was required to achieve 3-Log reduction against STEC, while L. monocytogenes required greater concentrations to achieve the same level of reduction. Overall, these results help guide growers in using ClO2 as a broad-spectrum disinfectant and demonstrate its efficacy in reaching 3-Log reduction across agricultural water samples.

Treatment of fluoride-contaminated water in a prototype adsorption unit using zirconium-activated carbon nanocomposites

ABSTRACT Zirconium-activated carbon nanocomposites (ZANC) are found to have high fluoride removal capacity and thus used as an adsorbent to perform column studies. The adsorbent was characterised using SEM-EDS and FTIR before and after the adsorption of fluoride. A packed bed adsorber prototype of 1 m length was fabricated to carry out defluoridation studies. The effect of varying initial fluoride concentration (2.5–10 ppm) and bed height (6–14 cm) was studied. The maximum fluoride removal was found to be 29.4% and uptake capacity was 4.72 mg/g at an initial fluoride concentration of 10 ppm, flow rate of 2 LPM, and bed height of 14 cm for synthetic samples. The Thomas, Yoon–Nelson and Bed Depth Service Time (BDST) models were employed and their results confirmed the experimental findings. The maximum fluoride adsorption capacities obtained from the Thomas model are 1.9 mg/g and from the BDST model, the N value was 20.979 mg/cm3. Regeneration studies were performed and found that the adsorbent can be regenerated for three cycles. Column studies were also performed using real-field groundwater samples collected from Pavagada of Tumakuru district. All the tested parameters of the treated water were found to be within the permissible limit.