Arsenic and fluoride exposure in drinking water caused human health risk in coastal groundwater aquifers

Spatial distribution and health risk assessment of fluoride in groundwater in the oasis of the Hotan river basin in Xinjiang, China

High fluoride groundwater is a global environmental and public health issue. To explore the effects of fluoride in groundwater in the oasis of the Hotan River Basin in Xinjiang on human health, this study analyzed the content and spatial distribution of fluoride in groundwater. Moreover, health risk assessment was performed using the Monte Carlo method based on the Unite States Environmental Protection Agency (USEPA) model. The results revealed that the groundwater in the Hotan River Basin oasis has an average F- content of 1.04 mg·L-1, with an exceedance rate of 35.2%. High-fluoride groundwater is typically characterized by a high HCO3- content, low Ca2+ content relative to Mg2+ content, and the presence of hydrochemical types of Cl·HCO3-Na and HCO3-Na. The hazard quotient (HQ) of fluoride in groundwater > 1 for children and adults in Lop County, Karakax County, and Hotan city and for children in Hotan County. In the study area, the 1-95% quantile certainty of HQ is greater for children (58.30-38.74%) than for adults (52.65-28.26%). Therefore, most residents in the oasis are exposed to the nononcogenic health risks of fluoride in groundwater via the water drinking pathway, with children being highly sensitive. The fluoride content of groundwater in the study area significantly influences the nononcogenic health risk assessment for residents, with a variance contribution rate of 87.8-94.3%. Therefore, reducing the fluoride content in groundwater should be prioritized in decision-making regarding the safety of drinking water in the oasis.

Bionanotechnology: A Paradigm for Advancing Environmental Sustainability

The urgent need for innovative solutions to global environmental challenges has driven the convergence of biology and nanotechnology, resulting in the emergence of bionanotechnology as a transformative force. This comprehensive review paper explores the fundamental principles, applications, benefits, and potential risks associated with harnessing bionanotechnology to advance environmental sustainability. Beginning with an elucidation of the fundamental concepts underlying bionanotechnology, this paper establishes the synergy between biological systems and nanomaterials. The unique properties of nanomaterials, coupled with the adaptability of biological processes, form the foundation for a diverse array of real-world applications. Focusing on applications, the paper highlights how bionanotechnology addresses critical environmental issues. It showcases case studies that exemplify its impact on water purification, air quality improvement, waste management, renewable energy production, and more. These case studies underscore the tangible benefits and efficacy of bionanotechnology in tackling complex challenges. However, as the potential of bionanotechnology is harnessed, it is crucial to navigate potential ecological risks. The paper emphasizes the importance of ecotoxicological considerations, discussing how nanomaterials interact with ecosystems and organisms. Ethical and responsible development of bionanotechnology, informed by these considerations, ensures that its benefits are maximized while minimizing potential harm. In conclusion, this review paper underscores bionanotechnology's potential to revolutionize environmental sustainability. By fusing the power of nanomaterials and biology, bionanotechnology offers a holistic approach to address pressing global challenges. While celebrating its transformative promise, the paper emphasizes the need for a balanced approach that safeguards environmental health. As society looks towards a more sustainable future, bionanotechnology stands as a pivotal paradigm for shaping an environmentally conscious world.

A comparative hydrochemical assessment of groundwater quality for drinking and irrigation purposes using different statistical and ML models in lower gangetic alluvial plain, eastern India

Groundwater toxicity and water level depletion are serious concerns today. Assessing groundwater quality (GWQ) is crucial for effective planning and management due to increasing demands for drinking and irrigation water. Therefore, this study aims to analyze groundwater hydrochemistry, variability, and factors influencing quality for drinking and irrigation purposes using indices and models. For this purpose, 107 sampling sites were investigated considering 14 parameters. To assess the suitability of irrigation water, nine irrigation indices (magnesium hazard, sodium-adsorption-ratio, residual sodium-carbonate, residual sodium-bicarbonate, sodium percentage, potential salinity, Kelly's index, total hardness and permeability index) were applied. Shannon-entropy-based water quality index (SEWQI) and statistical techniques such as Pearson correlation, principal component analysis, and hierarchical cluster analysis were used assess to the selected parameters. Six machine learning models, both conventional and ensemble, (AdaBoost, DT, MLP, SVM, RF, and XGBoost) were employed for predictive analysis. The SEWQI reveals 38% samples are excellent to good, while 62% are poor to unsuitable, covering 5905.64 km2 area. Assessed irrigation indices confirm most samples are unsuitable. As per Gibbs and USSL diagrams, groundwater samples are primarily affected by rock dominance and suitable for irrigation despite high salinity and low sodium (C3S1 = 43.99%). Overall, the rock dominance zone is shaped by silicate and carbonate mineral dissolution and human activities, impacting GWQ. Hyperparameter optimization using the grid search method improves the performance accuracy of the XGBoost model with R2 of 0.999 and RMSE of 0.269. The results of this study can help implement appropriate management and monitoring strategies and provide insights into safe drinking water in the future.

A comprehensive review on arsenic contamination in groundwater: Sources, detection, mitigation strategies and cost analysis

While groundwater is commonly perceived as safe, the excessive presence of trace metals, particularly arsenic (As), can pose significant health hazards. This review examines the current scenario of pollutants and their mitigations focusing on As contamination in groundwater across multiple nations, with a specific emphasis on the Indian Peninsula. Arsenic pollution surpasses the WHO limit of 10 ppb in 107 countries, impacting around 230 million people worldwide, with a substantial portion in Asia, including 20 states and four union territories in India. Analysis of the correlation between the aquifer and arsenic poisoning highlights severe contamination in groundwater originating from loose sedimentary aquifer strata, particularly in recently formed mountain ranges with geological sources presumed to contribute over 90% of arsenic pollution, i.e. a big environmental challenge. A myriad of techniques, including chromatographic, electrochemical, biological, spectroscopic, and colorimetric methods among others, are available for the detection and removal of arsenic from groundwater. Removal strategies encompass a wide array of approaches such as bioremediation, adsorption, coagulation/flocculation, ion exchange, biological processes, membrane treatment, and oxidation techniques specifically tailored for affected areas. Constructed wetlands help to eliminate heavy metal impurities such as As, Zn, Cd, Cu, Ni, Fe, and Cr. Their efficiency is influenced by design and environmental factors. Nanotechnology and nanoparticles have recently been studied to remove arsenic and toxic metal ions from water. Cost-effective solutions including community-based mitigation initiatives, alongside policy and regulatory frameworks addressing arsenic contamination, are essential considerations.

Evaluation of groundwater quality and health risk assessment in Dawen River Basin, North China

Groundwater is the principal water source of drinking and irrigation in the Dawen River Basin of Shandong Province. Thus, its investigations and evaluations are of significant importances. Based on collected groundwater samples, this study employed a combination of the entropy-weighted water quality index(EWQI), Nitrate Pollution Index(NPI) and the human health risk assessment(HHRA) model to evaluate groundwater quality and associated health risks. The combination of EWQI and NPI provides a more refined classification of groundwater quality in the Dawen River Basin. Geostatistical and GIS spatial analysis methods are employed to analyze the spatial characteristics of groundwater quality and its relationship with geomorphology. Results indicate that the region generally enjoys good water quality, with Entropy Water Quality Index (EWQI) values ranging from 20.32 to 302.37, and an average of 70.88. Downstream quality is poorer than upstream, and flat terrains typically exhibit poorer water quality. The major indicators affecting groundwater quality include Na⁺, Cl⁻, SO₄2⁻, and NO₃⁻. The NPI results show that due to differences in anthropogenic sources, 38.1%, 27.38%, 26.19%, 4.76%, and 3.57% of the groundwater samples are classified into non-polluted, slightly polluted, moderately polluted, significantly polluted, and extremely significantly polluted types, respectively. The HHRA model reveals high potential non-carcinogenic risks for NO₃⁻ and low risks for F⁻ in the study area. The health risks associated with high levels of NO3- in the areas surrounding Dongping Lake and Ningyang County are greater than in those other regions and therefore should be a significant concern for public health. Furthermore, this study attempts to combine the EWQI and NPI to categorize groundwater protection and governance statuses into four types: protective, utilizable, preventive, and remedial. This approach addresses the shortcomings in comprehensively identifying water quality types by single evaluation methods and offers valuable insights for distinguishing water quality types under nitrogen pollution conditions.

Denitrification performance of the nitrate-dependent manganese redox strain Dechloromonas sp. YZ8 under copper ion (Cu(Ⅱ)) stress: Promotion mechanism and immobilization efficacy

A novel nitrate-dependent manganese (Mn) redox strain was isolated and identified as Dechloromonas sp.YZ8 in this study. The growth conditions of strain YZ8 were optimized by kinetic experiments. The nitrate (NO3--N) removal efficiency was 100.0 % at 16 h at C/N of 2.0, pH of 7.0, and Mn(II) or Mn(IV) addition of 10.0 or 500.0 mg L-1, along with an excellent Mn redox capacity. Transmission electron microscopy supported the Mn redox process inside and outside the cells of strain YZ8. When strain YZ8 was exposed to different concentrations of copper ion (Cu(II)), it turned out that moderate amounts of Cu(II) increased microbial activity and metabolic activities. Moreover, it was discovered that the appropriate amount of Cu(II) promoted the conversion of Mn(IV) and Mn(II) to Mn(III) and improved electron transfer capacity in the Mn redox system, especially the Mn redox process dominated by Mn(IV) reduction. Then, δ-MnO2 and bio-manganese oxides (BMO) produced during the reaction process have strong adsorption of Cu(II). The surface valence changes of δ-MnO2 before and after the reaction and the production of BMO, Mn(III)-rich intermediate black manganese ore (Mn3O4), and Mn secondary minerals together confirmed the Mn redox pathway. The study provided new insights into the promotion mechanism and immobilization effects of redox-coupled denitrification of Mn in groundwater under Cu(II) stress.

Evaluation of groundwater quality with multi-source pollution based on source identification and health risks

Groundwater is a crucial water supply source in Chengdu City, western China, a region experiencing significant water scarcity. The sources of inorganic pollutants in groundwater and their potential health risks are of great concern. In this study, based on 156 groundwater samples collected in 2021 in the study area were analyzed for hydrochemical characterization and controlling factors. The Positive Matrix Factorization (PMF) model was used for contaminant source analysis, and Monte Carlo Simulation (MCS) combined with the Health Risk Evaluation Model (HREM) was used to quantify the health risks. The results indicate that the groundwater in the study area is predominantly of the Ca·Na-SO4·HCO3, Ca·Na-HCO3·SO4 and Ca-HCO3·SO4 types, mainly influenced by the combination of evaporation-concentration-crystallization and rock leaching-weathering. K+, Na+, and Cl- mainly originate from the weathering and dissolution of potassium feldspar and rock salt, while Ca2+, Mg2+, HCO3-, and SO42- primarily come from the weathering and dissolution of sulfate minerals. The main sources of groundwater pollution and their contributions are as follows: domestic pollution (25.6 %), dissolution-filtration-evaporation-concentration action (22.8 %), hydrogeochemical evolution (15.8 %), water-rock interactions (12.8 %), primary geologic context (12.1 %), and agricultural non-point source pollution (11.0 %). Cl- and As are the primary contributors to non-carcinogenic and carcinogenic risks, respectively. Non-carcinogenic risks are below USEPA standards, while the average carcinogenic risk for arsenic exceeded the maximum acceptable risk level thresholds by 23 and 109 times for adults and children, respectively. Non-carcinogenic and carcinogenic health risks were mainly influenced by pollutant concentrations. The primary geological background and domestic pollution contributed the most to the non-carcinogenic risk for adults (50.3 %) and children (77.1 %), and 38.2 % and 10.3 %, respectively. This study highlights the necessity of establishing a comprehensive groundwater pollution monitoring system, enhancing industrial waste management practices, and raising public awareness to mitigate contamination and ensure the sustainable use of groundwater resources in Chengdu City.

Characteristics and Mechanism of Hematite Dissolution and Release on Arsenic Migration in Heterogeneous Materials

The migration of arsenic in groundwater is influenced by the heterogeneity of the medium, and the presence of iron minerals adds complexity and uncertainty to this effect. In this study, a stratified heterogeneous sand column with an embedded hematite lens at the coarse-to-medium sand interface was designed. We introduced an arsenic-laden solution and controlled groundwater flow to investigate the spatiotemporal characteristics of arsenic migration and the impact of hematite dissolution. The results showed that the medium structure significantly influenced the arsenic migration and distribution within the lens-containing sand column. The clay layers directed the lateral migration of arsenic, and the arsenic concentrations in deeper layers were up to seven times greater than those on the surface. The extraction experiments of solid-phase arsenic revealed that the main adsorption modes on quartz sand surfaces were the specific adsorption (F2) and adsorption on weakly crystalline iron-aluminum oxides (F3), correlating to the specific and colloidal adsorption modes, respectively. Monitoring the total iron ions (Fe(aq)) revealed rapid increases within the first 14 days, reaching a maximum on day 15, and then gradually declining; these results indicate that hematite did not continuously dissolve. This study can aid in the prevention and control of arsenic contamination in groundwater.

Groundwater pollution risk, health effects and sustainable management of halocarbons in typical industrial parks

As important chemical raw materials and organic solvents, halogenated hydrocarbons not only play an important role in economic development, but are also the main source of environmental pollution. This study proposed an improved groundwater risk assessment model system, aimed at identifying and treating contaminants at leak sites. Groundwater ubiquity score (GUS) was used to evaluate the leachability of organic pollutants. The entropy-weighted water quality index (EWQI) method was used to assess the comprehensive quality of groundwater at the site. An improved groundwater health risk assessment model was constructed to analyze the health risks of groundwater. The sources of organic pollutants were identified based on the positive matrix factorization (PMF) model. Self-organizing mapping (SOM) and the K-means algorithm were integrated to classify and manage pollution source areas. The results showed that groundwater in the study area was strongly affected by human activities. The pollution source was located in a factory near S05. Different organic pollutants were highly leachable and had high potential to contaminate surrounding groundwater. 1,2-dichloropropane and 1,2,3-trichloropropane caused the largest range of contamination. The groundwater pollution index in the study area was high, and 72% of the monitoring points were non-drinkable. Both the carcinogenic and non-carcinogenic indexes of groundwater far exceeded the international standard limits and had a great impact on human health. 1,2,3-trichloropropane and 1,2-dichloropropane were major non-carcinogenic risk factors. The leakage of pollutants and pesticide solvents were the main causes of groundwater pollution. Cluster areas III and II were areas with significant pollution impacts and needed to be monitored intensively. Most areas were cluster I, with relatively low risk. This study can provide technical support for groundwater pollution risk assessment and management in similar industrial parks.

Hydro-chemical based assessment of groundwater vulnerability in the Holocene multi-aquifers of Ganges delta

Determining the degree of high groundwater arsenic (As) and fluoride (F-) risk is crucial for successful groundwater management and protection of public health, as elevated contamination in groundwater poses a risk to the environment and human health. It is a fact that several non-point sources of pollutants contaminate the groundwater of the multi-aquifers of the Ganges delta. This study used logistic regression (LR), random forest (RF) and artificial neural network (ANN) machine learning algorithm to evaluate groundwater vulnerability in the Holocene multi-layered aquifers of Ganges delta, which is part of the Indo-Bangladesh region. Fifteen hydro-chemical data were used for modelling purposes and sophisticated statistical tests were carried out to check the dataset regarding their dependent relationships. ANN performed best with an AUC of 0.902 in the validation dataset and prepared a groundwater vulnerability map accordingly. The spatial distribution of the vulnerability map indicates that eastern and some isolated south-eastern and central middle portions are very vulnerable in terms of As and F- concentration. The overall prediction demonstrates that 29% of the areal coverage of the Ganges delta is very vulnerable to As and F- contents. Finally, this study discusses major contamination categories, rising security issues, and problems related to groundwater quality globally. Henceforth, groundwater quality monitoring must be significantly improved to successfully detect and reduce hazards to groundwater from past, present, and future contamination.

Arsenic removal adsorbent using limonite-polyethersulfone composite fiber via continuous flow column process

This research introduces an enhanced limonite-based composite fiber adsorbent for arsenic (As) removal. The modification involves creating polyethersulfone (PES)-limonite composite fibers loaded with 60 wt% limonite powders, designed to be applicable in water flow environments. The fibers were prepared using a wet-spinning process based on phase inversion, with varying concentrations (10, 20, and 30 wt%) of PES in NMP solution. The composite fiber with 10 wt% NMP exhibited a porous structure and demonstrated efficient absorption of both As(III) and As(V). Adsorption followed the Langmuir model, with qm values of 1.5 mg/g for As(III) and 3.2 mg/g for As(V) at pH 6. In column experiments, As removal rates increased with contact time, attributed to decreased flow rates (1 mL/min). Moreover, increasing fiber column height led to enhanced removal rates, as indicated by the Adams-Bohart model. The mechanism for As(V) removal involved the formation of an inner-sphere complex through ion exchange between α-FeOOH and HAsO4 - and H2 AsO4 2- in an aqueous solution at pH 6.8. PRACTITIONER POINTS: Changing the polyethersulfone ratio in the composite leads to variations in the appearance of limonite within each composite fiber. Limonite composite fibers effectively remove As(III) and As(V) at neutral pH. The adsorption behavior follows Langmuir kinetic model, the qm of 1.5 mg/g for As(III) and 3.2 mg/g for As(V). Longer columns and contact times enhance arsenic (As) removal in practical water treatment systems. Adam-Bohart model aids in predicting breakthrough and saturation time in As adsorption column design.