Groundwater Pollution Control Research Articles

Leaching behavior of arsenic in coal under the action of mine water

Arsenic, a potentially harmful element in coal, has a detrimental effect on the quality of groundwater and the water cycle. There is a significant safety risk to the drinking water and overall health of residents living near mining areas. It is of great significance to explore the leaching pattern of arsenic in coal under the influence of mining and identify the main controlling factors for the prevention and control of groundwater pollution in mining areas. In this paper, we selected long flame coal and non-caking coal from Wulanmulun Mine, along with four types of water samples from the mine area, as the research subjects. Our aim was to investigate the leaching mechanism of arsenic in groundwater under the influence of coal-water interaction in the mine area. To achieve this, we conducted indoor batch coal-water leaching simulation experiments. The results show that: 1) The four leaching solutions, which correspond to four groundwater types at the coal mine production site, exhibit similar trends in the presence of arsenic ions after water-coal interaction. The leaching process can be divided into three distinct zones: a rapid descent zone, a dissolution shock zone, and a dissolution linear stable zone. The initial decline rate of arsenic content in different water samples is proportional to the initial concentration of arsenic in the water samples. 2) The dissolution of arsenic has a strong negative correlation with DO, and the lower the oxygen content in the solution, the higher the arsenic ion content. There is a relatively strong negative correlation with pH value. It has a strong positive correlation with the leaching of Mg, K, V, Cr, and Fe, and a relatively small positive correlation with the leaching of Mn and Cu. The leaching degree of Mg, K, V, Cr and Fe can be used as a sign to explore the leaching or content change of arsenic in actual mining environment. 3) Most arsenic in coal occurs in pyrite in the form of isomorphism or solid solution, and the dissolution of arsenic is related to pyrite content and its oxidative dissolution behavior. The higher the pyrite content, the greater its oxidation degree, and the higher the arsenic content in the solution. 4) Clay minerals, predominantly kaolinite, found in different coal samples demonstrate varying capacities for arsenic adsorption in the leaching solution. The results of this experiment indicate that the adsorption capacity of clay minerals in long flame coal is considerably higher than that observed in non-caking coal, leading to a substantial decrease in the concentration of arsenic ions in the solution. This reduction is associated with a notable decline in the arsenic concentration within the groundwater associated with the coal samples collected on-site. The results suggest that the leaching of arsenic from the coal samples will not lead to arsenic contamination in four distinct categories of groundwater. This finding holds considerable importance for the management and remediation of water pollution in mining contexts.

Hydrochemical characteristics, cross-layer pollution and environmental health risk of groundwater system in coal mine area: a case study of Jiangzhuang coal mine.

Long-term coal mining activities have significantly disturbed the groundwater system, resulting in aquifer water characterized by high levels of Na+, SO42-, and total dissolved solid (TDS), posing environmental health risks. To investigate the disturbance effects of coal mining activities on the groundwater system and ascertain the goaf water (OGW) environmental impacts, this study focuses on the surface water (SW), major aquifers, and OGW of Jiaozhuang Coal Mine. Through ion analysis and self-organizing map (SOM) clustering, the study analyzes the hydrochemical characteristics of the aquifer water, summarizes the accumulation patterns of OGW, and evaluates water quality of irrigation and drinking using sodium adsorption ratio (SAR), sodium percentage (SSP), and comprehensive pollution index (F). The results show that the hydrochemical characteristics of the groundwater system are influenced by a combination of cation exchange, dissolution, and mixing processes, with deep aquifers exhibiting high Na+ and SO42- levels. The OGW mainly originates from the coal roof sandstone aquifers water (RSW) and 3rd limestone aquifer water (3LW). Additionally, the groundwater shows high alkalinity and salinity hazards, with irrigation water quality assessments falling into general and unsuitable water quality area. Moreover, the groundwater quality is below Class III standards, with the worst being Class V, rendering it unsuitable as a drinking water source. Untreated discharge of OGW to the surface can easily threaten human drinking water health. The study results are helpful in identifying and controlling groundwater pollution caused by coal mining, ensuring the safety and sustainable utilization of water resources in mining areas and surrounding regions.

Sources and Transformation of Nitrate in Shallow Groundwater in the Three Gorges Reservoir Area: Hydrogeochemistry and Isotopes

Nitrate is among the most widely occurring contaminants in groundwater on a global scale, posing a serious threat to drinking water supplies. With the advancement of urbanization and mountainous agriculture, the nitrate in the groundwater of Wanzhou District in the Three Gorges Reservoir Area has formed a complex combination of pollution sources. To more accurately identify the sources of nitrate in groundwater, this study integrates hydrochemical methods and environmental isotope techniques to analyze the sources and transformation processes in shallow groundwater nitrate under different land-use types. Furthermore, the Bayesian isotope mixing model (MixSAIR) is employed to calculate the contribution rates in various nitrate sources. The results indicate that nitrate is the primary form of inorganic nitrogen in shallow groundwater within the study area, with nitrate concentrations in cultivated groundwater generally higher than those in construction land and forest land. The transformation process of nitrate is predominantly nitrification, with little to no denitrification observed. In cultivated shallow groundwater, nitrate mainly originates from chemical fertilizers (36.3%), sewage and manure (35.4%), and soil organic nitrogen (24.7%); in forested areas, nitrate primarily comes from atmospheric precipitation (35.3%), chemical fertilizers (31.3%), and soil organic nitrogen (22.1%); while in constructed areas, nitrate mainly derives from chemical fertilizers (46.0%) and sewage and manure (32.2%). These results establish a scientific foundation for formulating groundwater pollution control and management strategies in the region and serve as a reference for identifying nitrate sources in groundwater in regions with comparable hydrogeological features and pollution profiles.

Developing PDE-constrained optimal control of multicomponent contamination flows in porous media

This paper develops a robust and efficient PDE-constrained optimal control model for multicomponent pollutions in porous media, which takes into account nonlinear multi-component contamination flows of groundwater. The objective of the pollution optimal control is to identify the optimal injection rates from the top part boundary of domain, which can minimize the least squares error between the concentrations that are simulated and the allowable observed concentrations at observation sites, combining with the affection of costs associated with reducing emissions at injection locations. To discrete the constrained governing system of nonlinear multi-component flows, the splitting improved upwind finite difference scheme is developed for multicomponent PDEs system involving nonlinear chemical reactions of multicomponent pollutants and the pollutant injected rates on the upper part boundary. We employ the differential evolution (DE) optimization algorithm to solve the optimization. We numerically demonstrate the effectiveness of our model by analyzing the flow simulation on a simple geometric aquifer and identifying the optimal injection rates by minimizing the concentration derivation and the abatement costs. We also investigate the simulation of the contamination flow in a more realistic-shaped aquifer, which further validates our model's robustness and efficacy. The developed PDE-constrained control model and algorithm can be applied to applications of groundwater pollution control.

Direct Meshless Method for Stable Seepage Flow Calculation

Abstract Predicting stable groundwater seepage using known data is an important task in groundwater dynamics. This is crucial for ensuring the rational utilization of groundwater resources and effectively controlling groundwater pollution. However, traditional finite difference methods and analytical solutions have significant limitations in dealing with complex groundwater flow problems, such as poor applicability and low computational efficiency under irregular boundary conditions. In recent years, although methods based on radial basis function (RBF) have improved in accuracy, they still face the problem of insufficient flexibility in high-dimensional space. This article proposes a new method for predicting stable groundwater seepage, using the multiple quadratic curve (MQ) numerical method to address this challenge. We first use RBF interpolation to decompose the groundwater flow field, and then solve the corresponding linear equation system to obtain a numerical solution for stable groundwater seepage. This method abandons the traditional construction of grids and elements, provides greater flexibility in high-dimensional space, and adopts a node based approximation method to ensure computational accuracy. The experimental results show that this method performs well in simulating groundwater flow and changes, with relative errors as low as a specific value. Compared with higher precision radial basis function methods, this new method improves the accuracy by two orders of magnitude, providing a new solution for accurate prediction of groundwater flow.

Investigation into factors controlling groundwater evolution in mining areas with an integrated approach

The study of groundwater evolution is of great significance for water resource protection and management, groundwater pollution control, and ecological environment protection. Experts and scholars have found that the hydrochemical processes and evolutionary patterns of groundwater are determined by both natural processes and human activities. However, there is relatively little research on the evolution of groundwater in mining areas where human activities have a significant impact. Therefore, to study the main controlling factors affecting the hydrogeochemical evolution of groundwater in mining areas, this paper proposes a method combining mixed ratio calculation and multivariate statistical analysis. Firstly, a total of 40 groundwater samples are classified into six clusters via hierarchical cluster analysis. By comprehensively analyzing the spatial location of the samples, it was found that there was no obvious distribution pattern of groundwater in space. Furthermore, the rationality of the cluster analysis is evaluated via principal component analysis. Next, hydrochemical and isotopic analyses were conducted to determine the source of groundwater in the mining area, and a three terminal element mixing model was established to identify the source of pollutants and calculate the terminal element mixing ratio. The research results indicate that groundwater in mining areas is formed by a mixture of shallow bedrock fissure water, deep bedrock fissure water, and rainwater, and the mixing effect is the main factor affecting the evolution of groundwater in mining areas, with a more significant impact than the depth of groundwater circulation. In addition, different types and degrees of water–rock interaction in different regions have altered the hydrochemical characteristics of groundwater in mining areas, such as the dissolution of multiple minerals, cation exchange, and common ion effects. Based on the above analysis results, a water circulation model for the mining area has been established. The findings of this study not only contribute to the protection of shallow fissure groundwater in the study area, but also provide a basis for investigating the groundwater evolution patterns in other metal mines.

Mechanisms of evolution and pollution source identification in groundwater quality of the Fen River Basin driven by precipitation

Groundwater pollution has attracted widespread attention as a threat to human health and aquatic ecosystems. However, the mechanisms of pollutant enrichment and migration are unclear, and the spatiotemporal distributions of human health risks are poorly understood, indicating insufficient groundwater management and monitoring. This study assessed groundwater quality, human health risks, and pollutant sources in the Fen River Basin(FRB). Groundwater quality in the FRB is good, with approximately 87 % of groundwater samples rated as “excellent” or “good” in both the dry and rainy seasons. Significant precipitation elevates groundwater levels, making it more susceptible to human activities during the rainy season, slightly deteriorating water quality. Some sampling points in the southern of Taiyuan Basin are severely contaminated by mine drainage, with water quality index values up to 533.80, over twice the limit. Human health risks are mainly from As, F, NO3−, and Cr. Drinking water is the primary pathway of risk. From 2019 to 2020, the average non-carcinogenic risk of As, F, and NO3− increased by approximately 28 %, 170 % and 8.5 %, respectively. The average carcinogenic risk of As and Cr increased by 28 % and 786 %, the overall trend of human health risks is increasing. Source tracing indicates As and F mainly originate from geological factors, while NO3− and Cr are significantly influenced by human activities. Various natural factors, such as hydrogeochemical conditions and aquifer environments, and processes like evaporation, cation exchange, and nitrification/denitrification, affect pollutant concentrations. A multi-tracer approach, integrating hydrochemical and isotopic tracers, was employed to identify the groundwater pollution in the FRB, and the response of groundwater environment to pollutant enrichment. This study provides a scientific basis for the effective control of groundwater pollution at the watershed scale, which is very important in the Loess Plateau.

The new region demarcation framework for implementing the joint prevention and control of groundwater pollution: A case study in western of Bohai Bay, China

The joint groundwater pollution prevention and control (GPPC) strategy has been extensively implemented to address the coastal region groundwater pollution challenges in China. However, regional groundwater pollution control and treatment efficiency cannot achieve the expected results due to the lack of regional priority control orders and accurate restoration levels. Thus, this study developed a new region demarcation framework method for delineating GPPC zones, in tandem with a comprehensive pollution index method, the DRASTIC model, source apportionment. To validate the new methodological framework, a case study of groundwater pollution in Qinhuangdao, the western of Bohai Bay, China, was implemented to calculate pollution prevention and control zoning. In total, 340 groundwater samples from shallow aquifers with 9 target pollutants (NO3-, NO2-, NH4+, As, Cd, Cr, Cu, Pb, and Ni) were selected as the dataset for GPPC regionalization. The results showed that GPPC zoning further clarified the direction of groundwater pollution protection and management in Qinhuangdao. Compared to the traditional method, the new GPPC zoning better reflects groundwater mobility characteristics and pollution transport and enrichment patterns in terms of groundwater functional integrity and delineation. This new regional demarcation framework method contributes to providing support for the fine division of groundwater pollution zoning and precise pollution control for groundwater resource management in China.

Unraveling the hydrogeochemical characteristics and pollution sources of groundwater in an intensive industrial area, East China.

It is challenging to interpret hydrogeochemical datasets with complex natural and anthropogenic genesis in intensive industrial areas. This paper elucidates the hydrogeochemical characteristics and pollution sources of groundwater in an industrial park, East China, combining the self-organizing map (SOM), hydrochemical graphs, and correlation analysis. The results show that the total dissolved solids of groundwater range from 73.45 to 997.92mg/L and can be regarded as freshwater. The pH varies greatly from 6.44 to 9.90, most of samples belonging to weakly acidic-weakly alkaline. The groundwater can be classified into five clusters by SOM, representing the non- or least-polluted groundwater (cluster D), high salt groundwater (cluster A), high NH4+-N and HCO3- groundwater (cluster B), high Fe and Mn groundwater (cluster C), and high pH groundwater (cluster E), which were contaminated by industrial salts, historical agriculture activity, industrial reducing substances, and industrial alkali, respectively. The natural evolution of groundwater (cluster D) in the study area is mainly controlled by mineral weathering/dissolution. The contributions of calcite, dolomite, gypsum, halite, and silicate mineral to groundwater solute are 55.8-66.3%, 15.1-18.0%, 9.0-10.7%, 2.5-10.1%, and 2.3-9.4%, respectively, based on the mass conservation. The contaminated groundwaters (all other clusters except for cluster D) have different hydrochemical characteristics associated with the pollution sources. In addition, the relatively reductive environment in quaternary flu-lacustrine sediments favored the formation of high level of Fe, Mn, and NH4+-N in groundwater. This study provides a new insight into the characteristic contaminants and their distributions in groundwater and the associated pollution sources based on the large datasets in an intensive industrial area. The data evaluation methods and results of this study could be useful to the groundwater usage management and pollution control in this area and other industrial areas.

Experimental study on migration characteristics of LNAPL in the aquitard under pumping conditions.

Research on the migration behaviors of contaminants in the aquitard has been deficient for an extended period. Clay is commonly employed as an impermeable layer or barrier to stop the migration of contaminants. However, under certain conditions, the clay layer may exhibit permeability to water, thereby allowing contaminants to infiltrate and potentially contaminate adjacent aquifers. Consequently, it holds immense importance to scrutinize and investigate the migration characteristics of light non-aqueous phase liquid (LNAPL) within the aquitard for the purposes of groundwater pollution control and remediation. To evaluate the environmental risk posed by organic contaminants in the aquitard, an experimental model was formulated and devised to monitor the LNAPL concentration in the aquitard under pumping conditions. The correlation between pumping rate and LNAPL concentration was investigated. A self-developed plexiglass sandbox model was used to simulate the migration characteristics of LNAPL in the aquitard under pumping conditions. Four experimental scenarios were designed, varying pumping rates, aquitard thicknesses, and groundwater level changes. The LNAPL concentration curve was derived by systematically tracking and analyzing LNAPL levels at various locations within the aquitard. The results indicated that higher pumping rates corresponded to increased migration of LNAPL, resulting in greater LNAPL ingress into the pumping well during extraction. A thicker aquitard demonstrated a more pronounced inhibitory effect on LNAPL, leading to an extended penetration time of LNAPL within the aquitard. The drawdown within the aquitard exerted a discernible influence on LNAPL migration, with the LNAPL concentration continuing to decrease in tandem with declining water levels during pumping. These research findings can establish a scientific foundation for the control and remediation of contaminants within aquitards.

Quantitative Assessment and Validation of Groundwater Pollution Risk in Southwest Karst Area

AbstractGroundwater pollution risk assessment is a useful tool for groundwater pollution prevention and control. However, it is difficult to accurately quantify groundwater flow and contaminant fluxes in karst areas and different types of karst areas have different hydrogeological characteristics. Therefore, the assessment of groundwater pollution risk in karst areas must use different assessment indicator systems. This study developed a new methodology that modified the vulnerability assessment model PLEIK, determined pollutant fluxes considering hydrogeological conditions, and revised parameter weights using the random forest method. The resulting PLEIKD-RF model was used to assess the risk of groundwater contamination in the southwestern karst region and its validity was verified. The results showed that the groundwater pollution risk in the region was low, with 65.64% of the low and relatively low risk areas located in the middle and high mountainous regions. 11.81% of the high and relatively high risk areas were sporadically located in the western and central regions, which were mainly controlled by the distribution of the pollution sources and the karst development. The accuracy of the results of groundwater pollution risk assessment in the study area was 71.87% as verified by the horizontal difference method. The results of the sensitivity analysis indicated that accurate, detailed, and representative data on the protective layer, surface water-groundwater interactions, and pollution source loads would improve the accuracy of groundwater pollution risk zoning. This assessment method provided a reference for similar assessments and the results provide a basis for the protection and management of groundwater resources in the region.

Enhanced groundwater vulnerability assessment to nitrate contamination in Chongqing, Southwest China: Integrating novel explainable machine learning algorithms with DRASTIC-LU

ABSTRACT Groundwater vulnerability to nitrate assessment serves as a measure of potential groundwater nitrate pollution in a target area. This study applies the DRASTIC-LU framework, nitrate distribution data, and three machine learning models (RF, XGB, SVM) to classify nitrate levels (exceeding 10 mg/L as nitrogen) in Chongqing, China. Model evaluation uses accuracy and F1 score metrics, with RF achieving the highest accuracy (92.9%), kappa (0.857), and AUC (0.948) on test dataset. Furthermore, the SHAP interpreter revealed that aquifer conductivity, lithology, agricultural activities, areas with high-intensity development, and groundwater recharge are the most influential indicators of groundwater vulnerability. The final groundwater vulnerability level distribution map, with a resolution of 1 km × 1 km, reveals that high and extremely high vulnerability levels are concentrated in areas with high-intensity urban development and karst trough valleys in the southeastern, northeastern, and central urban areas. This work represents the first attempt of using machine learning models for groundwater vulnerability assessment in the Chongqing region. It provides theoretical support for the construction layout of groundwater monitoring stations and the prevention and control of groundwater pollution in the future.

Numerical Simulation of the Solute Migration Regulated by Vertical Cutoff Wall based on FEFLOW

Cutoff wall has been widely used in desalination of coastal aquifers in many coastal regions and remediation of industrial waste water pollution. In recent years, the excessive exploitation of resources in the coastal brine distribution area leads to the salinization of deep soil. At the same time, the mine water pollution caused by improper discharge of industrial waste water into the abandoned mining area is a new form of pollution in Shandong, China. However, due to the complex geological conditions of abandoned mining areas, loose collapse of overlying strata in roadway and gob layer, it is difficult to prevent and control groundwater pollution in deep gob layer. It is a major difficulty in practical engineering to evaluate the cutoff interception performance of vertical cutoff wall on the pollution of gob layer in such mining areas and optimize cutoff interception measures. In this paper, a typical polluted abandoned mining area in Shandong, China is taken as an example, and COD is used as the main simulation factor for numerical simulation. The numerical simulation results show that in the process of groundwater pollution control, the cutoff wall with appropriate thickness and hydraulic conductivity can effectively block the diffusion of solute. The horizontal transport of solute can be significantly weakened when the thickness of the cutoff wall is 90 cm and the hydraulic conductivity is 1.0×10-4 m/d. Compared with increasing the thickness, reducing the hydraulic conductivity of the cutoff wall is more effective in controlling the migration of solute in the site. When the hydraulic conductivity is reduced by an order of magnitude, the diffusion range of solute is reduced by 19.74% compared to before. Therefore, priority should be given to reducing the hydraulic conductivity of the cutoff wall in order to optimize its influence on pollutant migration.

Construction and application of urban water resources spatial equilibrium model: A case study of Ulanqab City

ABSTRACT Evaluating the water resources spatial equilibrium (WRSE) is the foundation for scientifically planning the construction of an optimized water resource allocation system and achieving the high-standard development of the China Water Network Project. To elucidate the characteristics of WRSE variation in Ulanqab City, this study explored a novel WRSE assessment model based on connection number and the subtraction set pair potential method. The results indicate that: (1) there exists a mismatch between the distribution of water resources in Ulanqab City and its socio-economic development. In 2020, the Gini coefficients of water resources total quantity concerning resident population, gross domestic product (GDP), industrial output value, and irrigated land area were 0.48, 0.48, 0.51, and 0.28, respectively. (2) From 2011 to 2020, the overall WRSE level in Ulanqab City showed an increasing trend year by year. Among them, the WRSE levels in six counties improved, while Jining District consistently remained at a low equilibrium state due to the prominent contradiction between water supply and demand. (3) In the future, Ulanqab City can further enhance the WRSE level by promoting the reuse of recycled water, intensifying groundwater pollution control, and implementing a quota management system for agricultural water use.

Iron-scrap and pyrite mediated autotrophic denitrification in constructed wetland for enhancing nitrate-polluted groundwater remediation: Performance and mechanism

Nitrate (NO3−-N) is ubiquitously present in groundwater, constituting a growing threat to human health. In this study, iron-scrap and pyrite-based constructed wetlands (CWs) were constructed to investigate the treatment performance and removal mechanisms in purifying nitrate-contaminated groundwater. Results showed that the NO3−-N removal efficiency of iron-scrap-based CWs (87.1%) was higher than that of pyrite-based CWs (59.5%), and the higher N2O emission (28.46 μg/(m2•h)) was also obtained in CW with iron-scrap. Nevertheless, total nitrogen removal did not exhibit a significant difference between two CWs due to the accumulation of ammonium nitrogen (NH4+-N) in iron-scrap-based CWs. Additionally, sulfate was produced in CW with pyrite, as a by-product, and caused oxidative stress damage to plants. Metagenomic analysis showed that the addition of iron-scrap could increase microbial diversity and enrich autotrophs denitrifies (e.g., Ferritrophicum), which explained the higher NO3−-N removal reasonably. Additionally, the abundance of dissimilatory nitrate reduction bacterium was enhanced in iron-scrap-based CW, explaining the NH₄⁺-N accumulation. Further metabolic analysis confirmed the occurrence of Fe cycle in CW with iron-scrap, and functional genes related to NO3−-N removal and TCA cycle were up-regulated, offering a rationale for the improved NO3−-N removal in CW with iron-scrap. This study offers comprehensive insights into the NO3−-N removal and its mechanism through iron mediated CWs in controlling groundwater pollution.

Self-powered system based on triboelectric nanogenerator in agricultural groundwater pollution monitoring and control

Self-powered system based on triboelectric nanogenerator in agricultural groundwater pollution monitoring and control

Recent advances in clay minerals for groundwater pollution control and remediation.

Clay minerals are abundant on Earth and have been crucial to the advancement of human civilization. The ability of clay minerals to absorb chemicals is frequently utilized to remove hazardous compounds from aquatic environments. Moreover, clay-based adsorbent products are both environmentally acceptable and affordable. This study provides an overview of advances in clay minerals in the field of groundwater remediation and related predictions. The existing literature was examined using data and information aggregation approaches. Keyword clustering analysis of the relevant literature revealed that clay minerals are associated with groundwater utilization and soil pollution remediation. Principal component analysis was used to assess the relationships among clay mineral modification methods, pollutant properties, and the Langmuir adsorption capacity (Qmax). The results demonstrated that pollutant properties affect the Qmax of pollutants adsorbed by clay minerals. Systematic cluster analysis was utilized to classify the collected data and investigate the relationships. The pollution adsorption mechanism of the unique structure of clay minerals was investigated based on the characterization results. Modified clay minerals exhibited changes in surface functional groups, internal structure, and pHpzc. This review provides a summary of recent clay-based materials and their applications in groundwater remediation, as well as discussions of their challenges and future prospects.

Activation of iron oxide minerals in an aquifer by humic acid to promote adsorption of organic molecules

In aquifers, the sequestration and transformation of organic carbon are closely associated with soil iron oxides and can facilitate the release of iron ions from iron oxide minerals. There is a strong interaction between dissolved organic matter (DOM) and iron oxide minerals in aquifers, but the extent to which iron is activated by DOM exposure to active iron minerals in natural aquifers, the microscopic distribution of minerals on the surface, and the mechanisms involved in DOM molecular transformation are currently unclear. This study investigated the nonbiological reduction transformation and coupled adsorption of iron oxide minerals in aquifers containing DOM from both macro- and micro perspectives. The results of macroscopic dynamics experiments indicate that DOM can mediate soluble iron release during the reduction of iron oxide minerals, that pH strongly affects DOM removal, and that DOM is more efficiently degraded at low rather than high pH values, suggesting that a low pH is conducive to DOM adsorption and oxidation. Spherical aberration-corrected scanning transmission electron microscopy (SACTS) indicates that the reacted mineral surfaces are covered with large amounts of carbon and that dynamic agglomeration of iron, carbon, and oxygen occurs. At the nanoscale, three forms of DOM are found in the mineral surface agglomerates (on the surfaces, inside the surface agglomerates, and in the polymer pores). The microscopic organic carbon and iron mineral reaction patterns can form through oxidation reactions and selective adsorption effects. Fourier transform ion cyclotron resonance mass spectra indicate that both synergistic and antagonistic reactions occur between DOM and the minerals, that the release of iron is accompanied by DOM decomposition and humification, that large oxygen- and carbon-containing molecules are broken down into smaller oxygen- and carbon-containing compounds and that more molecules are produced through oxidation under acidic rather than alkaline conditions. These molecules provide adsorption sites for sediment, meaning that more iron can be released. Microscopic evidence for the release of iron was acquired. These results improve the understanding of the geochemical processes affecting iron in groundwater, the nonbiological transformation mechanisms that occur at the interfaces between natural iron minerals and organic matter, groundwater pollution control, and the environmental behavior of pollutants.

Mapping specific groundwater nitrate concentrations from spatial data using machine learning: A case study of chongqing, China

Groundwater resources is not only important essential water resources but also imperative connectors within the intricate framework of the ecological environment. High nitrate concentrations in groundwater can exerting adverse impacts on human health. It is imperative to accurately delineate the distribution characteristics of groundwater nitrate concentrations. Four different machine learning models (Gradient Boosting Regression (GB), Random Forest Regression (RF), Extreme Gradient Boosting Regression (XG) and Adaptive Boosting Regression (AD)) which combine spatial environmental data and different radius contributing area was developed to predict the distribution of nitrate concentration in groundwater. The models use 595 groundwater samples and included topography, remote sensing, hydrogeological and hydrological, climate, nitrate input, and socio-economic predictor. Gradient Boosting Regression model outperforms the other models (R2 = 0.627, MAE = 0.529, RMSE = 0.705, PICP = 0.924 for test dataset) under 500 m radius contributing area. A high-resolution (1 km) groundwater nitrate concentration distribution map reveal in the majority of the study area, groundwater nitrate concentrations are below 1 mg/L and high nitrate concentration (>10 mg/L) proportion in southeast, northeast and central main urban area karst valley regions is 1.89%, 0.91%, and 0.38% respectively. In study area, hydrogeological conditions, soil parameters, nitrogen input factors, and percentage of arable land are among the most influential explanatory factors. This work, serving as the inaugural application of utilizing effective spatial methods for predicting groundwater nitrate concentrations in Chongqing city, furnish decision-making support for the prevention and control of groundwater pollution, particularly in areas primarily dependent on groundwater for water supply and holds profound significance as a milestone achievement.

Groundwater quality and potential analysis using geospatial techniques: The case of Ashanti Region in Ghana

The ecosystem and economy's reliance on clean water is influenced by various factors such as geology, topography, soil types, activities, and the presence of plants and animals. The Ghana Water Company is encountering difficulties in delivering water to consumers in the Ashanti Region due to the shortage of surface water resources, leading to water rationing in the area. Furthermore, poor waste disposal practices, illegal mining, use of fertilizers, and industrial activities have resulted in surface and groundwater source damage. Therefore, there is a need to implement a reliable, simple, and timely method to assess groundwater quality. This study aims to employ GIS and RS techniques to evaluate groundwater quality and potential in the Ashanti Region, Ghana. The Water Quality Index (WQI) was estimated using pH, Total Dissolve Solid (TDS), Chloride, Total Hardness (TH), Nitrate, Temperature, Turbidity, Iron, and Electrical Conductivity (EC). The study then used the WQI distribution to conduct a groundwater potential analysis to identify suitable areas for borehole placement. Digital thematic layers and maps were developed to expose the spatial distribution of water quality parameters, enabling the identification of groundwater pollution control and remedial measures. The study estimated the region's groundwater potential using an integrated GIS and Analytical Hierarchical Process (AHP) technique, grouping under excellent, good, fair, and poor potential. The WQI in the Ashanti Region ranged from 5.208 to 134.232, with 32.252% of the study area having an excellent WQI and 60.168% of the study area having a good WQI. Poor water quality covered 7.550% of the study area. The results showed that the GIS-based AHP approach accurately mapped the spatial distribution of WQI and Groundwater Potential Zones (GWPZ). This information is helpful to planners in water resource management in groundwater exploration and future planning. Policymakers and stakeholders must ensure that groundwater sources are protected from pollution.