Appraising the factors favouring uranium mobilization and associated health risk assessment in groundwaters of north-western India

An attempt has been made in this study to evaluate the factors favoring the uranium mobilization into the groundwater of Northwest India using uranium isotope activity ratio (²³⁴U/²³⁸U), radon (²²²Rn) and environmental isotopes of water (²H, ¹⁸O and ³H). The values range from 23 - 597 µg/L for total uranium and 634-3210 Bq/m³ for radon and the corresponding annual effective dose is estimated to be 18.9-490 µSv/a and 6.2-31.5 μSv/a respectively. Uranium activity ratio (UAR) varies from 0.68 - 1.17 and maximum samples indicate secular equilibrium. Environmental isotopic data indicates that the source to groundwater is vertical percolation of rainwater in the case of shallow zone while regional flows from outcrop areas recharge the deep groundwater. A wide scatter is noticed in environmental ³H content (0.23-6.62 TU) indicating both fast and sluggish water flows. The UAR phase diagram suggests that leaching process controls the uranium mobilization into the groundwater. The correlations among UAR, uranium and U_excess further indicate oxidative nature of leaching process. Statistical treatment of the obtained data along with available geochemical and isotope evidences suggest that source of uranium is common but the driving processes are different for shallow and deep zone. Influences of root zone CO₂, oxic species from irrigation return flows and water level fluctuations are also evaluated. Low uranium, low UAR, low ³H and high ²²²Rn activity in deep zone suggest uranium being released from the roll front as well as transported from outcrop regions. This study highlights the application of uranium isotope ratio, radon and environmental isotopes in assessing vulnerability of alluvial aquifers towards uranium contamination.

Assessment and simulation of a solid waste dumpsite impact on the surrounding water resources: A case study in Abu Zaabal, Egypt

Indiscriminate dumping of solid wastes and the resulting groundwater contamination is a major issue, especially for developing countries. The main objective of this paper is to develop a groundwater mass transport model in order to study the effect of an open solid waste dumpsite on the water quality of water resources within the region around it. The harmful effects of indiscriminate solid wastes disposal by open dumping, which is still followed in many developing countries around the world, is highlighted. Abu Zaabal dumpsite; which is located in Qalyubiyah Governorate, Egypt; receives huge amounts of wastes daily causing leachate generation that percolates deep into the soil and polluting the shallow aquifer. The Groundwater Modeling System (GMS) software was used to model the groundwater flow and mass transport, using data collected from the site investigation and literature historical data available. Of the several contaminants measured in the site, six critical contaminants; namely Total Dissolved Solids (TDS), Lead, Boron, Nitrate, Manganese and Chemical Oxygen Demand (COD); were chosen to be modeled. The developed model was used to simulate the six contaminants using a transient-state model and concentration values for two different scenarios. Scenario-1 assumes that the dumpsite will be active until 2080, whereas Scenario-2 represents imminent closure of the dumpsite. The model results of each contaminant were calculated over 100-year interval, from 1980 until 2080, and the results of 2080 were presented. The results showed that the dumpsite had a major impact on the nearby water bodies, Abu Zaabal ponds and Belbais Drain. Moreover, the closure of the dumpsite showed that the maximum concentration of the majority of the considered contaminants was decreased by approximately 60–65%.

Effectiveness and comparison of physical barriers on seawater intrusion and nitrate accumulation in upstream aquifers

Physical barrier is a coastal engineering widely used to prevent seawater intrusion. However, previous studies have not evaluated the combined influence of type and structure of the physical barrier on nitrate accumulation in upstream aquifers. Furthermore, the mechanisms of nitrate accumulation caused by the physical barriers are still unclear. In this study, numerical simulations were conducted to investigate the mechanisms and influence of the physical barrier on seawater intrusion and NO₃^- accumulation. The results show that constructing physical barrier can result in the reduction of nitrate discharge to the sea and accumulation of nitrate in upstream aquifers. The accumulation degree is significant if the barrier height is large; the barrier location is near the sea; the nitrate infiltration rate is large; the infiltration nitrate concentration is large; the inflow is weak, and the inflow DOC concentration is low. A cut-off wall is more likely to cause nitrate accumulation than a subsurface dam. It can result in mean nitrate concentration in groundwater upstream increasing by more than 30 %. Because a nitrate accumulation zone is formed behind the cut-off wall where the flow is slow and dissolved oxygen carbon is difficult to be replenished so that the denitrification is weak. Despite the subsurface dam may not result in a significant increase in nitrate concentration, it cannot be applied to the areas where SI has occurred due to the residual seawater problem. The nitrate accumulation in the upstream aquifer is a long-term process that lasts for more than three years to reach a pseudo-steady state. Seasonal variations of inflow and infiltration lead to fluctuation of mean nitrate concentration, thereby the nitrate accumulation rate increased after April and weakened between July and December.

Private groundwater management and risk awareness: A cross-sectional analysis of two age-related subsets in the Republic of Ireland

Risk communication represents the optimal instrument for decreasing the incidence of private groundwater contamination and associated waterborne illnesses. However, despite attempts to promote voluntary well maintenance in high groundwater-reliant regions such as the Republic of Ireland, awareness levels of supply status (e.g. structural integrity) have remained low. As investigations of supply awareness are often thematically narrow and homogeneous with respect to sub-population, revised analyses of awareness among both current and future supply owners (i.e. adults of typical well owner and student age) are necessary. Accordingly, the current study utilised a national survey of well users and an age-based comparison of supply awareness. Awareness was measured among 560 Irish private well users using a multi-domain scoring framework and analysed in conjunction with experiential variables including experience of extreme weather events and previous household infections, and perceived self-efficacy in maintaining supply. Respondents displayed a median overall awareness score of 66.7%, with supply owners (n = 399) and students (n = 161) exhibiting median scores of 75% and 58.3%. Awareness among both combined respondent subsets and well owners was significantly related to gender, well use factors and self-perceived behavioural efficacy while awareness among students was not correlated with any independent variable. Cluster analysis identified three distinct respondent groups characterised by awareness score and gender in both current and future well owner subsets. Male well owners and students displayed higher perceived self-efficacy irrespective of awareness score while female well owners that demonstrated high awareness were significantly more likely to report postgraduate educational (p < 0.001). Findings suggest that recent experience of extreme weather events does not significantly influence supply awareness and mirror previously identified knowledge differences between well owners and young adults. Age, gender, supply use and perceived self-efficacy emerge as recurring focal points and accordingly merit consideration from groundwater and health communication practitioners for future risk interventions.

Identifying influencing groundwater parameter on human health associate with irrigation indices using the Automatic Linear Model (ALM) in a semi-arid region in India

Quality of water for the purposes of irrigation is a serious threat to the sustainable development of the agriculture sector. The main objective of this study is to evaluate the suitability of groundwater for irrigation purposes using various irrigation indices such as: Sodium Absorption Ratio (SAR), Residual Sodium Carbonate (RSC), Percentage Sodium (%Na), Magnesium Hazards (MH), Permeability Index (PI), Potential Salinity (PS), Residual Sodium Bicarbonate (RBSC), Kelly's Ratio (KR), Synthetic Harmful Coefficient (K), and Exchangeable Sodium Percentage (ESP). A total of 30 samples were collected from the bore well of agricultural farmland and analysed for cations and anions. MH reveal that 53.33 % of samples exceed the permissible level. PS shows that 43.33 % of samples are marginally affected and 33.33 % of samples are unsuitable for use in irrigation. About 76 % of the groundwater samples were suitable for irrigation and the remainder require treatment before use. Automatic Linear Modelling (ALM) is used to predict the major influence parameter for MH and PS are RBSC, RSC and K value of groundwater. ALM shows that excess magnesium concentration and salinity are the primary factors that affect the suitability of groundwater for irrigation use. This integrated technique showed that water from approximately 25 % of the sample locations would require treatment before use. This study will improve the pattern of irrigation, identify sources of contamination and highlight the importance of organic fertilizers to develop and enhance the sustainable practices in the study region.

The use of statistical methods to assess groundwater contamination in the Lower Tano river basin, Ghana, West Africa

In this study, descriptive statistics, correlation matrix, multiple regression model, and geostatistical models were used to assess the contamination of groundwater with respect to trace elements in the Lower Tano river basin, Ghana, West Africa. A total number of 48 boreholes drilled across the basin with depths ranging from 18 to 60 m were used as data sources in this study. The results of the descriptive statistics showed that the average lead, iron, and aluminium concentrations exceeded the WHO permissible limits of 0.3 mg/L, 0.01 mg/L, and 0.2 mg/L respectively. Furthermore, copper, chromium, aluminium, zinc, manganese, nickel, iron, arsenic, electrical conductivity, and total dissolved solids were found to be extreme and highly positively skewed. Even though significant correlations exist among some variables, the statistical results showed that the quality of the boreholes drilled across the basin was mainly originating from geogenic and anthropogenic sources. In addition, each pair of correlated physical parameters and trace elements in the drilled boreholes were predicted using multiple regression models. Likewise, geostatistical modelling was used to assess the spatial analysis of each pair of correlated physical parameters and trace elements in the drilled boreholes. The cross-validation results revealed kriging model, as the most precise model for the spatial distribution maps for the correlated physical parameters, and correlated trace elements concentration in the boreholes drilled across the study region. The semivariogram models showed that most of the correlated physical parameters and correlated trace elements were weak moderately and strongly spatially dependent, suggesting fewer agronomic influences. The results of the spatial analysis were consistent with the multiple regression model and the Pearson correlation matrix.

Potentially toxic elements in groundwater: a hotspot research topic in environmental science and pollution research

A scientometric analysis based on the Scopus database was conducted to provide insight into research activities on the occurrence of potentially toxic elements (PTEs) (As, Cd, Co, Cr, Cu, Hg, Ni, Pb, Sb, and Zn) in groundwater during 1970-2019. The selection of these PTEs was based on their significance concerning their reference frequency in environmental science and pollution research (ESPR) studies and their toxicity to living organisms. The analysis utilizes data about the quantity, type, journal, geographical, institutional, and funding patterns of publications. The results indicate that the publications' annual output has increased over the years, and especially after 2000, it presents a remarkable growth rate. The most studied PTEs were As and Pb; nevertheless, the research on the rest of PTEs cannot be neglected as it shows continuously increasing trends over time. The evolution of instrumentation and the dissemination of contamination case studies that affect a large part of the world population contributed significantly to the scientific community and relative stakeholders' interest. According to the analysis, the USA and China are the two principal countries with the most considerable contribution, producing the most research regarding the number of publications, research institutions, and funding sponsors. China owns the most influential research institution (i.e., Chinese Academy of Sciences) and largest funding sponsor (i.e., National Natural Science Foundation of China; ≈5% of global funding) on a worldwide scale due to its investment in research and development (R&D) and is expected to become the greatest force in the future.

Private groundwater contamination and extreme weather events: The role of demographics, experience and cognitive factors on risk perceptions of Irish private well users

Extreme weather events (EWEs) may significantly increase pathogenic contamination of private (unregulated) groundwater supplies. However, due to the paucity of protective guidance, private well users may be ill-equipped to undertake adaptive actions. With rising instances of waterborne illness documented in groundwater-dependent, developed regions such as the Republic of Ireland, a better understanding of well user risk perceptions pertaining to EWEs is required to establish appropriate educational interventions. To this end, the current study employed an online and physical questionnaire to identify current risk perceptions and correspondent predictors among Irish private well users concerning extreme weather. Respondents were elicited via purposive sampling, with 515 private well users elucidating perceived supply contamination risk in the wake of five EWEs between the years 2013-2018 including drought and pluvial flooding. A novel scoring protocol was devised to quantify overall risk perception (i.e. perceived likelihood, severity and consequences) of extreme weather impacts. Overall risk perception of EWEs was found to demonstrate a significant relationship with gender (p = 0.017) and event experience (p < 0.001), with female respondents and those reporting prior event experience exhibiting higher median risk perception scores. Risk perception was additionally mediated by perceived self-efficacy in undertaking supply maintenance (p = 0.001), as well users citing confidence in ability scored significantly lower than those citing no confidence. Two-step cluster analysis identified three distinct respondent subsets based on risk perception of EWEs (high, moderate and low perception), with female respondents and those with a third-level education significantly more likely to fall within the high perception cluster. Study findings affirm that certain demographic, experiential and cognitive factors exert a significant influence on private well user risk perceptions of EWE impacts and highlight potential focal points for future educational interventions seeking to reduce the risk of human infection associated with groundwater and extreme weather.

Assessment of arsenic exposure in the population of Sabalpur village of Saran District of Bihar with mitigation approach

Arsenic poisoning through groundwater is the world's greatest normal groundwater catastrophe which got an immense effect on worldwide general wellbeing. India is confronting the outcomes of arsenic poisoning in the zone of Ganga Brahmaputra alluvial plains. In Bihar, out of 38 districts, 18 districts are exceptionally influenced with groundwater arsenic defilement. In the present study, we have assessed the current situation of arsenic exposure in Sabalpur village of Saran district of Bihar after reporting of breast, renal, skin and thyroid cancer cases from this village along with typical symptoms of arsenicosis. Such cancer patients were identified at our institute and were taken for the study. The present investigation deals with the quantification of arsenic in groundwater, hair and nail samples of subjects as well as the survey of entire village to know the overall health status of the village people. A total of n=128 household handpump water samples as well as n=128 human hair and nail samples were collected from over n=520 households. Using the graphite furnace atomic absorption spectrophotometer (GF-AAS), all the samples were analysed. The investigation resulted that the 61% of the analysed samples particularly the groundwater had the arsenic levels more than the permissible limit of WHO (> 10 μg/L) with 244.20 μg/L as the highest arsenic contamination in one of the handpump water sample. The exposure effect of hair sample was worst as 88% of all the collected samples were having high arsenic levels more than the permissible limit (> 0.2 mg/Kg). In case of nail samples, 92% of the samples were having high arsenic concentration more than the permissible limit (> 0.5 mg/Kg). The health survey study revealed high magnitude of disease burden in the exposed population with symptoms such as asthma, anaemia, hepatomegaly, diabetes, cardiac problem, skin fungal infections, breathlessness and mental disability. Few cancer cases of renal, skin, breast and cervix were also found among the exposed population of this village. The percentage of cancer cases in this village was 0.94% that was low, but it would be an aggravated situation in the near future if people will continue drinking arsenic-contaminated water. Therefore, a mitigation intervention was carried out in March 2020 by installing an arsenic filter plant. The health situation in the village in the present scenario is hope to improve in the coming years. However, motivation and awareness among the village population are still required.

Simultaneous identification of groundwater contamination source and aquifer parameters with a new weighted-average wavelet variable-threshold denoising method

This paper first proposed a parallel heuristic search strategy for simultaneous identification of groundwater contamination source and aquifer parameters. As identification results are influenced by many factors, such as noisy contamination concentration data, data denoising is necessary. The existing wavelet threshold denoising method has unavoidable shortcomings; therefore, this paper first proposed a new weighted-average wavelet variable-threshold denoising (WWVD) method to improve the denoising effect for concentration data, which further enhanced the subsequent identification accuracy. However, frequent calls to the simulation model could produce high computational cost during likelihood calculation. Hence, single surrogate model of the simulation model was developed to reduce cost; however, it presented limitation. Thus, this paper first developed a differential evolution-tabu search (DE-TS) hybrid algorithm to construct an optimal ensemble surrogate model, which assembled Gaussian process, kernel extreme learning machine, and support vector regression. The first proposed DE-TS algorithm also improved the approximation accuracy of surrogate model to simulation model. This paper first proposed and implemented a parallel heuristic search iterative process for simultaneous identification, and the identification results were obtained when the iteration process terminated. The accuracy and efficiency of these newly proposed approaches were tested through a hypothetical case. Results showed that the WWVD method not only improved the denoising effect for concentration data but also enhanced the subsequent identification accuracy. The OES model using DE-TS hybrid algorithm improved the approximation accuracy of surrogate model to simulation model, and the parallel heuristic search strategy is helpful for simultaneous identification of groundwater contamination source and aquifer parameters.

Developing a fuzzy logic-based risk assessment for groundwater contamination from well integrity failure during hydraulic fracturing

Recent natural gas development by means of hydraulic fracturing requires a detailed risk analysis to eliminate or mitigate damage to the natural environment. Such geo-energy related subsurface activities involve complex engineering processes and uncertain data, making comprehensive, quantitative risk assessments a challenge to develop. This research seeks to develop a risk framework utilising data for quantitative numerical analysis and expert knowledge for qualitative analysis in the form of fuzzy logic, focusing on hydraulically fractured wells during the well stimulation stage applied to scenarios in the UK and Canada. New fault trees are developed for assessing cement failure in the vertical and horizontal directions, resulting in probabilities of failure of 3.42% and 0.84%, respectively. An overall probability of migration to groundwater during the well injection stage was determined as 0.0006%, compared with a Canadian case study which considered 0.13% of wells failed during any stage of the wells life cycle. It incorporates various data types to represent the complexity of hydraulic fracturing, encouraging a more complete and accurate analysis of risk failures which engineers can directly apply to old and new hydraulic fracturing sites without the necessity for extensive historic and probabilistic data. This framework can be extended to assess risk across all stages of well development, which would lead to a gap in the modelled and actual probabilities narrowing. The framework developed has relevance to other geo-energy related subsurface activities such as CO₂ sequestration, geothermal, and waste fluid injection disposal.

Glyphosate effects on tree species natives from Cerrado and Caatinga Brazilian biome: Assessing sensitivity to two ways of contamination

Glyphosate is applied for dissection in no-till and post-emergence management in transgenic crops in agricultural fields near the Cerrado and Caatinga biomes. These biomes together represent 33.8% of the Brazilian territory, contributing to the maintenance of great world diversity in flora and fauna. Despite actions to protect them, the proximity with agricultural areas and intense use of glyphosate puts at risk the preservation of native vegetation due to the contamination via herbicide transport processes. Our objectives were: i) to determine the sensitivity of native species from the Cerrado and Caatinga to glyphosate contamination via drift and groundwater; ii) evaluate the level of sensitivity to glyphosate among the different organs of plants. The highest intoxications (upper 80%) were observed for Bauhinia cheilantha, Mimosa caesalpiniaefolia, Mimosa tenuiflora and Amburana cearensis due to drift simullation. The species with 90% of total dry matter reduction were Bauhinia cheilantha, Enterolobium contortisiliquum, Mimosa caesalpiniaefolia, Mimosa tenuiflora, Tabebuia aurea. B. cheilantha and M. tenuiflora are most affected by exposure to glyphosate drift, with 50% of total dry matter reduction when exposed to doses below 444,0 g ha-1. Leaf growth is more sensitive to glyphosate for drift exposure for most species. Hymenaea courbaril is an exception, with greater sensitivity to root growth (50% dry matter reduction at doses below 666,0 g ha-1). B. cheilantha is the species most sensitive to drift exposure; however, it showed complete tolerance to contamination in subsurface waters. Other species such as Anadenanthera macrocarpa and M. caesalpiniifolia are also sensitive to drift, but without reach 90% of total dry matter reduction. A. macrocarpa, M. caesalpiniifolia and T. aurea were tolerant to contamination by subsurface water. The differential tolerance of trees confirms glyphosate's potential as a species selection agent in the Cerrado and Caatinga biomes.

Transport and retention of porous silicon-coated zero-valent iron in saturated porous media

Porous silicon-coated zero-valent iron (Fe⁰@p-SiO₂) is a promising material for in-situ contaminated groundwater remediation. However, investigations of factors that affect the transport of Fe⁰@p-SiO₂ remain incomplete. In the present study, Fe⁰@p-SiO₂ composites were prepared by a SiO₂-coated technology, and a series of column experiments were conducted to examine the effects of media size, ionic strength, and injection velocity and concentration on retention and transport in saturated porous media. Results showed that the obtained Fe⁰@p-SiO₂ is a core-shell composite with zero-valent iron as the core and porous silicon as the shell. Media size, injection velocity, Fe⁰ concentration, and ionic strength had a significant impact on the transport of Fe⁰@p-SiO₂. Fe⁰@p-SiO₂ effluent concentrations decreased with a smaller media size. Increasing initial particle concentration and ionic strength led to a decrease in particle transport. High particle retention was observed near the middle of the column, especially with high injection concentration. That was also observable in the condition of lower injection velocity or finer media. The results indicated that two transport behaviors during particles transport, which were "agglomeration-straining" and "detachment-re-migration". Moreover, the dominated mechanisms for Fe⁰@p-SiO₂ transport and retention in saturated porous media are hydrodynamic dispersion and interception. Given the results, in practical engineering applications, proper injection velocity and concentration should be selected depending on the pollution status of groundwater and the geochemical environment to ensure an effective in-situ reaction zone.

Microfluidic pore model study of precipitates induced by the pore-scale mixing of an iron sulfate solution with simulated groundwater

Precipitates induced by the pore-scale mixing of iron sulfate solutions with simulated groundwater were investigated using a microfluidic pore model to assess the environmental impacts of the infiltration of acid mine drainage into a shallow aquifer. This model was employed to visualize the formation of precipitates in a porous network and to evaluate their physicochemical influences on pore flow. Four types of groundwater (Na-HCO₃, Na-SO₄, Na-Cl, and Ca-Cl) were evaluated, and precipitation rates were calculated by processing images of precipitates in the pores captured via microscopy. The results showed that all groundwater types formed a yellow-brownish precipitate at the interface of the iron solution and simulated groundwater flow. Microscopic X-ray analyses demonstrated that precipitate morphology varied with groundwater type. Faster precipitation was observed in the following order by groundwater type: Na-HCO₃ > Na-Cl > Na-SO₄ > Ca-Cl, which was attributed to the different stability constants of the major anions in each simulated groundwater with Fe ions. Chemical equilibrium models suggested that precipitates were Fe minerals, with FeOOH as the predominant form consistent with the results of X-ray photoelectron spectrometry. The presence of FeOOH implies that precipitates may serve as an effective sorption barrier against some nutrients and heavy metals for the underlying groundwater. However, dye-flow experiments suggested that the precipitates may clog aquifer pores, thereby altering hydrogeological properties in the aquifer.

Groundwater vulnerability assessment using GIS-based DRASTIC model in Nangasai River Basin, India with special emphasis on agricultural contamination

Nangasai basin is a semi-arid watershed where agriculture is the main source of economy. In present day, increasing population demands increase in food productivity which leads to increase use of fertilizers and chemical pesticides in agriculture. These fertilizers on the other hand mix up with the groundwater and increase the pollution, which affects human health adversely. So, for controlling the groundwater contamination risk proper water resource management and assessment of groundwater vulnerability is extremely important. Total 7 hydrogeological parameters have been considered for this study, and the final groundwater vulnerability map has been prepared by overlay weighted method with the help of DRASTIC index, which is classified into 5 vulnerable classes (very high, high, moderate, low, and very low). In the south and south-eastern regions of the basin namely Deghi, Bankada, Baram, Macha, Katin, Tilabani high groundwater contamination is been observed. For validating the model, the water quality parameters-nitrate and TDS have been used with the accuracy of 89% and 86% respectively. Using effective as well as scientifically approved methods, the anthropogenic and agricultural contamination can be controlled and managed which will lower the risk of contamination. This map can be further utilized as a base map for management of groundwater pollution and its planning.

Organic contaminants of emerging concern in leachate of historic municipal landfills

Many types of contaminants of emerging concern (CECs), including per- and poly-fluoroalkyl substances (PFAS), have been found in leachate of operating municipal landfills. However, there is only limited information on CECs presence in leachate of historic landfills (≥3 decades since closure, often lacking engineered liners or leachate collection systems) at concentrations that may pose a risk to nearby wells and surface water ecosystems. In this study, 48 samples of leachate-impacted groundwater were collected from 20 historic landfills in Ontario, Canada. The CECs measured included artificial sweeteners (ASs), PFAS, organophosphate esters (OPE), pharmaceuticals, bisphenols, sulfamic acid, perchlorate, and substituted phenols. The common presence of the AS saccharin, a known indicator of old landfill leachate, combined with mostly negligible levels of the AS acesulfame, an indicator of modern wastewater, revealed that most samples were strongly influenced by leachate and not cross-contaminated by wastewater (which can contain these same CECs). Several landfills, including ones closed in the 1960s, had total PFAS concentrations similar to those previously measured at modern landfills, with a maximum observed here of 12.7 μg/L. Notably elevated concentrations of several OPE, sulfamic acid, cotinine, and bisphenols A and S were found at many 30-60 year-old landfills. There was little indication of declining concentrations with landfill age, suggesting historic landfills can be long-term sources of CECs to groundwater and that certain CECs may be useful tracers for historic landfill leachate. These findings provide guidance on which CECs may require monitoring at historic landfill sites and wastewater treatment plants receiving their effluent.

Identification of groundwater contamination sources and hydraulic parameters based on bayesian regularization deep neural network

Simultaneous identification of various features of groundwater contamination sources and hydraulic parameters, such as hydraulic conductivities, can result in high-nonlinear inverse problem, which significantly hinders identification. A surrogate model was proposed to relieve computational burden caused by massive callings to simulation model in identification. However, shallow learning surrogate model may show limited fitting ability to high nonlinear problem. Thus, in this study, a simulation-optimization method based on Bayesian regularization deep neural network (BRDNN) surrogate model was proposed to efficiently solve high-nonlinear inverse problem. This method identified eight variables including locations and release intensities of two pollution sources and hydraulic conductivities of two partitions. Three hidden layers were employed in the BRDNN surrogate model, which profoundly improved the fitting capacity of nonlinear mapping relationship to the simulation model. Furthermore, Bayesian regularization was applied in the training process of neural network to solve overfitting problem. The results indicated that BRDNN was capable of establishing input-output interplay of high nonlinear inverse problem, which substantially reduced computational cost while ensuring a desirable level of accuracy. The utility of simulation-optimization on the basis of BRDNN surrogate model provided stable and reliable inversion results for groundwater contamination sources and hydraulic parameters.

Factors influencing groundwater contamination near municipal solid waste landfill sites in the Qinghai-Tibetan plateau

Effective management of municipal solid waste (MSW) is essential for the conservation of ecosystems in the Qinghai-Tibetan Plateau (QTP). Considering the landfill is the major method of MSW management, the factors influencing groundwater contamination near MSW landfill sites in the QTP were studied, based on field investigations, environmental impact assessment, and meteorological and hydrogeological analyses. Results indicated that the groundwater was contaminated heavily by nitrate (PI = 7.5), particularly in the landfill without an anti-seepage system, followed by nitrite (PI = 3.5) and heavy metals including arsenic (PI = 4.1) and hexavalent chromium (PI = 2.8). Total hardness, total dissolved solids, nitrate, and lead in the groundwater near the investigated landfill sites were significantly different between the monsoon and the cold seasons. Both the rainfall infiltration and the leachate infiltration were considerably limited by environmental characteristics in the QTP, including high evaporation, low rainfall, and the presence of permafrost. Soil sample contamination near landfill sites was considered as moderate (28.6% of the soil samples) and moderate to heavy (71.4% of the soil samples), based on the geoaccumulation index of mercury. However, comparatively low generation and concentrations of leachate and good topsoil quality (PI = 0.84) reduced the quantity of pollutants infiltrating into the groundwater. The alkaline leachate (pH = 7.45-9.23) and soil (pH = 7.08-8.72) also considerably decreased the concentrations of contaminants dissolved in the infiltrated rainfall and leachate. Additionally, low groundwater level can delay preferential flow and enhance attenuation. Therefore, the groundwater contamination near the landfill sites was simply point pollution, which was influenced by leachate, soil, climate, and hydrogeology characteristics in the QTP. The anti-seepage system is a potential strategy for use in the prevention of groundwater contamination by MSW landfills in the QTP.

Occurrence, predictors and hazards of elevated groundwater arsenic across India through field observations and regional-scale AI-based modeling

Existence of wide spread elevated concentrations of groundwater arsenic (As) across South Asia, including India, has endangered a huge groundwater-based drinking water dependent population. Here, using high-spatial resolution As field-observations (~3 million groundwater sources) across India, we have delineated the regional-scale occurrence of elevated groundwater As (≥10 μg/L), along with the possible geologic-geomorphologic-hydrologic and human-sourced predictors that influence the spatial distribution of the contaminant. Using statistical and machine learning method, we also modeled the groundwater As concentrations probability at 1 Km resolution, along with probabilistic delineation of high As-hazard zones across India. The observed occurrence of groundwater As was found to be most strongly influenced by geology-tectonics, groundwater-fed irrigated area (%) and elevation. Pervasive As contamination is observed in major parts of the Himalayan mega-river Indus-Ganges-Brahmaputra basins, however it also occurs in several more-localized pockets, mostly related to ancient tectonic zones, igneous provinces, aquifers in modern delta and chalcophile mineralized regions. The model results suggest As-hazard potential in yet-undetected areas. Our model performed well in predicting groundwater arsenic, with accuracy: 82% and 84%; area under the curve (AUC): 0.89 and 0.88 for test data and validation datasets. An estimated ~90 million people across India are found to be exposed to high groundwater As from field-observed data, with the five states with highest hazard are West Bengal (28 million), Bihar (21 million), Uttar Pradesh (15 million), Assam (8.6 million) and Punjab (6 million). However it can be much more if the modeled hazard is considered (>250 million). Thus, our study provides a detailed, quantitative assessment of high groundwater As across India, with delineation of possible intrinsic influences and exogenous forcings. The predictive model is helpful in predicting As-hazard zones in the areas with limited measurements.

Probability mapping of groundwater contamination by hydrocarbon from the deep oil reservoirs using GIS-based machine-learning algorithms: a case study of the Dammam aquifer (middle of Iraq)

The Dammam Formation in the southern and western deserts of Iraq is an important aquifer because it contains a huge groundwater reserve suitable for various uses. In the Karbala-Najaf plateau and the neighboring areas of the middle of Iraq, the drilling of groundwater wells usually fails due to the contamination of this aquifer with hydrocarbon from the deep oil reservoirs. This work suggests a method for the spatial delineation of groundwater contamination in this aquifer. Three machine learning classifiers, backpropagation multi-layer perceptron artificial neural networks (ANN), support vector machine with radial basis function (SVM-radial), and random forest (RF) with GIS, were used to map the probability of contamination in this aquifer. An inventory map of 139 groundwater boreholes (contaminated and non-contaminated) was utilized for building the models with seven factors that are considered to control contamination: fault density, distance to faults in general and the Abu Jir fault in particular, groundwater depth, hydraulic conductivity, aquifer saturated thickness, and land-surface elevation. The Relief-F feature selection method indicated that all factors were relevant. Five statistical measures were used for comparing the model performance: accuracy, sensitivity, specificity, kappa, and the area under the receiver operating characteristics curve (AUC). Applying the models using the R statistical package indicated that all models had excellent goodness-of-fit (accuracy > 90%), but the ANN (accuracy = 97%, sensitivity = 1.00%, specificity = 96%, kappa = 0.93, and AUC = 0.97) and RF (accuracy = 95%, sensitivity = 1.00%, specificity = 93%, kappa = 0.88, and AUC = 0.98) outperformed SVM-radial (accuracy = 92%, sensitivity = 1.00%, specificity = 90%, kappa = 0.82, and AUC = 0.95). The contamination probability values produced by these three models were categorized into different contamination zones range from very low to very high. The finding of this analysis may be used as a guide for drilling uncontaminated wells of groundwater.

Effect of chelated iron activated peroxydisulfate oxidation on perchloroethene-degrading microbial consortium

In this work, the effect of In-Situ Chemical Oxidation (ISCO) using peroxydisulfate (PDS) on chloroethenes-degrading microbial consortium in the presence of perchloroethene (PCE; tetrachloroethene) was investigated. Degradation of PCE was examined using PDS without an activation, activated with iron Fe(II) chelated by citric acid (CA), and microbial consortium derived from chloroethenes-contaminated site in liquid and sand microcosms. Two different molar ratios of PCE/PDS/(Fe(II)+CA) (1/8/1.6 and 1/16/3.2) were tested. The PCE removal efficiency was the highest in the bacteria-free microcosms. An expected increase in the PCE removal efficiency by coupling PDS and microbial consortium was not confirmed. Surprisingly, the reduced capacity of PDS to remove PCE in the systems containing both PDS and microbial consortium was observed indicating that indigenous microbes may reduce the efficiency of PDS during a remediation. High-throughput 16S rRNA gene sequencing analysis revealed negative effect of PDS on organohalide-respiring bacteria (OHRB), which were not detected after 19 days of the experiment, unlike in biotic control. On the other hand, amplicon sequence variants (ASVs) affiliated with genera Brevundimonas and Pseudomonas that have been described for their capability of aerobic cometabolic/metabolic degradation of chloroethenes (CEs) were among the most frequently detected ASVs after the PDS treatment. Results further showed that the sole Fe(II)-CA affected the diversity of the microbial consortium. Overall, results of this study provide new insight into the coupling ISCO using PDS with in situ bioremediation of CEs.

Planning for the health impacts of climate change: Flooding, private groundwater contamination and waterborne infection - A cross-sectional study of risk perception, experience and behaviours in the Republic of Ireland

The frequency and severity of flooding events will increase over the coming decades due to global climate change. While close attention has typically been paid to infrastructural and environmental outcomes of flood events, the potential adverse human health consequences associated with post-event consumption from private groundwater sources have received minimal attention, leading to a poor understanding of private well users' preparedness and the drivers of positive behavioural adoption. The current study sought to quantify the capacity of private well users to cope with flood-triggered contamination risks and identify the social psychological determinants of proactive attitudes in the Republic of Ireland, using a cross-sectional questionnaire incorporating two distinct models of health behaviour, the Health Belief Model and Risk-Attitude-Norms-Ability-Self Regulation model. Adoption of healthy behaviours prior to flooding was evaluated with respect to respondents' risk exposure, risk experience and risk perception, in addition to systematic supply stewardship under normal conditions. Associations between adoption of protective behaviours and perception, experience and socio-demographic factors were evaluated through multinomial and multiple logistic regressions, while a multi-model inferential approach was employed with the predictors of health behaviour models. Findings suggest that floods are not considered likely to occur, nor were respondents worried about their occurrence, with 72.5% of respondents who reported previous flooding experience failing to adopt protective actions. Prior experience of well water contamination increased adoption of proactive attitudes when flooding occurred (+47%), with a failure to adopt healthy behaviours higher among rural non-agricultural residents (136%). Low levels of preparedness to deal with flood-related contamination risks are a side-effect of the general lack of appropriate well stewardship under normal conditions; just 10.1% of respondents adopted both water treatment and frequent testing, in concurrence with limited risk perception and poor awareness of the nexus between risk factors (e.g. floods, contamination sources) and groundwater quality. Perceived risk, personal norms and social norms were the best predictors of protective behaviour adoption and should be considered when developing future awareness campaigns.

Delineating the impacts of poultry burial leachate on shallow groundwater in a reclaimed agro-livestock farming area, using multivariate statistical analysis of hydrochemical data

Burial is applied to dispose of livestock carcasses due to its convenience and cost efficiency despite concerns about groundwater contamination by leachate from burial pits. In particular, the burial method has caused debates about groundwater contamination sources around on-farm livestock burial sites because of pre- and coexisting contamination from livestock production and agriculture. To assess the causes of groundwater contamination around poultry burial pits that were constructed after an outbreak of avian influenza in 2010-11 in Korea, hydrochemical data of groundwater samples from monitoring wells (MWs, n = 14) and household wells (HWs, n = 30) were monitored to differentiate contamination sources. Hydrochemical data indicated that groundwater from MWs is characterized by higher enrichments of inorganic constituents including electrical conductivity (EC), NH₄, Ca, Mg, K, SO₄, HCO₃, Fe_(Total), and Mn_(Total), but lower concentrations of DO than groundwater from HWs. The combined use of the principal component analysis (PCA) and K-means cluster analysis (KCA) indicated that groundwater in seven MWs was affected by leachate. The parameters such as NH₄, Ca, Mg, K, SO₄, HCO₃, Fe_(Total), and Mn_(Total) are expected to be useful to identify the impact of leachate on groundwater in agricultural areas. This study suggests that (1) regional hydrochemical characteristics should be assessed to distinguish the effect of livestock burial leachate from other contamination sources and (2) the combined use of PCA and KCA is effective to identify the weakened impact of leachate leakage among overlapping multiple sources and processes of groundwater contamination.

Plastic in agricultural soils - A global risk for groundwater systems and drinking water supplies? - A review

The global plastic contamination is one of the major challenges facing mankind as plastic is ubiquitously present in all environmental compartments. In contrast to freshwater and marine environments, plastic contamination of agricultural soils was only recently subject to investigations although it represents a significant amount (14%) of the global plastic pollution. Of concern is the vertical migration of plastic particles in agricultural soils and plastic-induced enhancement of pesticide transport towards underlying groundwater systems. To assess the risk of the large plastic inventory in agricultural soils for groundwater systems and drinking water supplies, this review critically synthesizes the current knowledge of the plastic mobility and plastic-pesticide interactions in agricultural soils, identifies future research directions and evaluates associated analytical challenges. The reviewed studies provide consistent evidence for vertical migration of plastic in agricultural soils towards aquifer systems, especially for sub-micrometer sized plastic particles, analogously to the well-known migration of natural particles in the sub-micrometer range (colloids). The reviewed investigations also showed that plastic changes the sorption behavior of pesticides in agricultural soils and enhances their transport towards underlying groundwater systems. Hence, the deposited plastic in agricultural soils likely poses a major risk for underlying aquifers and drinking water supplies that rely on groundwater resources below farmlands to be contaminated by plastic and pesticides. This demonstrates that improved regulatory measures are necessary regarding the general usage of plastic in the farming process to protect aquifers and drinking water supplies from plastic and pesticide contamination and to avoid a potential human health hazard.

Groundwater contamination by fluorinated aromatics: Benzotrifluoride and its derivatives

Benzotrifluoride (BTF) and its derivatives (BTFs) were found in the groundwater of the Veneto region (Italy) as a result of industrial contamination dating back to the 1970s. In the first survey, BTF and 6 BTFs were identified, out of which 4-chloro-3nitrobenzotrifluoride (3N4CBTF) was the only quantified analyte (concentration up to 1 mg L^-1) and was used to trace the contamination plume. A survey carried out in 2008-2009 after the development of more suitable analytical procedures based on GC-MS, allowed to determine 4 new derivatives in addition to BTF and BTFs previously identified, with the most abundant compounds found at concentrations up to 11.9 μg L^-1 and 7.2 μg L^-1 respectively. A systematic monitoring program for the evaluation of persistence and distribution of fluorinated compounds was carried out in 2013-2018, and new data about the BTF and BTFs occurrence and distribution were gathered. Additional BTFs were identified and high concentrations of individual BTFs were recorded near the contamination source (e.g. 20.3 μg L^-1 of 4-chloro-3-nitrobenzotrifluoride in 2017) as well as at large distance (e.g. 22.4 μg L^-1 of 3N4CBTF and 12.5 μg L^-1 of 4-chlorobenzotrifluoride in 2018). The results of BTFs monitoring campaigns carried out in 2008-2009 and 2017-2018 are compared and related to the historical data to assess the overall occurrence and distribution of BTFs contamination over a time range of ∼40 years. Remarkably, BTFs were still found (2018) at μg L^-1 range. Spatial and temporal occurrence of BTF and BTFs in groundwater has been assessed for the first time.