Pollution Of Shallow Groundwater Research Articles

Spatial distribution characteristics and source analysis of shallow groundwater pollution in typical areas of Yangtze River Delta

With the accelerated industrialisation and urbanisation in the Yangtze River Delta region, shallow groundwater has also suffered some pollution. In order to clarify the current state of pollution and its causes, principal component analysis (PCA) was used to classify the main factors. An absolute principal component-multiple linear regression model (APCS-MLR) was also used to determine the contribution of the main pollution sources to the shallow groundwater quality. The analysis results showed that the exceedance of water quality indicators such as iron, manganese, aluminium and COD in shallow groundwater in the study area was more serious. With the exception of Mg2+, the other indicators are highly variable and are more likely to be influenced by human factors. The main pollution factor affecting the quality of shallow groundwater is the dissolution filtration - migration enrichment factor, followed by agricultural and urban sewage factors, industrial pollution factors, and geological environmental background factors. And the main sources of pollution in shallow groundwater are mainly located in the western, northwestern and northern parts of the study area. The use of fertilizers and pesticides in urban life and urban runoff, industrial production and agricultural production are the main causes of pollution. The effects of leaching and transport enrichment, agricultural and urban runoff, and industrial pollution on groundwater quality are significant. The predicted concentrations calculated by the model are generally consistent with the measured concentrations, indicating the accuracy of the calculation of the contribution of each pollution source. This study is applicable to the analysis of shallow groundwater pollution sources in the study area, and also provides a scientific basis for the evaluation of regional groundwater resources and pollution prevention.

Modeling potential arsenic enrichment and distribution using stacking ensemble learning in the lower Yellow River Plain, China

In the high arsenic area of the northern Henan Plain in the lower Yellow River, the interaction between surface water and groundwater is frequent due to the control of groundwater over exploitation and the ecological replenishment of the rivers. It is not clear that what leads to the cause and dynamic change in the mechanism of arsenic pollution in shallow groundwater. Using machine learning algorithms to model the risk of high arsenic occurrence in the groundwater can help analyze mechanism of arsenic in groundwater. In this study, a stacking ensemble learning model was constructed to predict the risk distribution of shallow high arsenic groundwater in the lower reaches of the Yellow River in northern Henan Province using multi-variate parameters. Furthermore, we analyzed the potential areas at risk of high arsenic enrichment under different groundwater levels by control. The results show that the groundwater arsenic exceedance rate was 16.76%, and the high arsenic groundwater distributed from northeast to southwest, while that in the middle and south mainly distributed in the alluvial pre-fan depressions and the Yellow River crevasse splay. Compared with the single model, the stacking ensemble learning model has the Area Under the Curve (0.87), accuracy (0.82), and specificity (0.88) and sensitivity (0.77). With the best overall performance, the predicted risk distribution of groundwater arsenic is highly consistent with the observed results, and the potential groundwater area with high arsenic risk accounts for 19.67% of the total area. The impact of the Yellow River burst, average annual temperature, annual precipitation, ground elevation, and hydraulic gradient as the most significant indicator factors are affecting groundwater arsenic enrichment in the study area. Among these factors, the sedimentary environment accounts for 27.10% in the process of arsenic enrichment. Groundwater also plays an important role, with a relative share of 13.69%. In the simulation of groundwater rebound process, it was found that when the groundwater level raised in the range of 1 m −3 m, the high arsenic area could be reduced by up to 19.52%. The methods and findings in this work can support the management and control of arsenic enrichment and distribution in shallow groundwater systems around the world.

Using stable isotopes (δ2H and δ18O) and hydrochemistry to understand the genesis and hydrochemical processes of groundwater in Chongming Island, Yangtze Estuary.

Groundwater is an indispensable freshwater resource and its quality is significant in supporting sustainable social and economic development, particularly in estuarine islands where aquifers are complicated. In this study, a total of 19 groundwater and 4 surface water samples were collected in September 2022 to identify the origin and hydrogeochemical evolution processes of groundwater using stable isotopes and hydrochemistry in Chongming Island, which is the largest estuarine alluvial island in the world. The stable isotopic composition indicated that shallow groundwater and surface water are all derived from precipitation recharge under a humid climate, and the evaporative effect incurs the enrichment of isotopic compositions. The shallow groundwater and surface water were primarily of Ca-HCO3 type. Gibbs diagram, ionic correlation analysis, ionic ratios analysis, and mineral saturation indices suggested that water-rock interactions like carbonate and silicate weathering play a vital role in groundwater chemistry, but cation exchange reactions are weak. Revelle index (RI) result indicated that 10.5% of shallow groundwater samples were found to suffer seawater intrusion. The NO3- concentrations were between l2.0 and 180.8mg/L with 31.6% of groundwater samples exceeding the World health organization (WHO) standards (50mg/L). Agricultural activities and industrial activities were found to be mainly responsible for groundwater pollution in shallow groundwater. The findings of this study provide a scientific basis for better managing groundwater resources on coastal estuarine islands.

Simulation study of oxytetracycline contamination remediation in groundwater circulation wells enhanced by nano-calcium peroxide and ozone

The widespread use of antibiotics in recent years has led to increasing antibiotic contamination of shallow groundwater. As the most widely used tetracycline antibiotic, oxytetracycline has received a lot of attention from researchers due to its stable molecular structure and difficulty in degradation. Aiming at remediation of oxytetracycline pollution in shallow groundwater, nano-calcium peroxide (nCaO2) and ozone (O3) are used to enhance the degradation of oxytetracycline in groundwater circulation well (GCW). A three-dimensional sand box test device for circulation wells is designed to explore the repair efficiency of circulation wells strengthened by different oxidants. The results show that after nCaO2 and O3 enhancing circulation wells operate for 10 h, the average removal rate of OTC reaches 83%, and the highest removal rate is 88.13%, which is 79.23% and 13.96% respectively higher than that of nCaO2 and O3 enhanced circulation wells alone, and there is no rebound phenomenon after aeration stops. The in-situ treatment of enhanced GCW by nCaO2 and O3 has potential applications for the removal of OTC in groundwater environments.

Characteristics of Nitrate Pollution in Shallow Groundwater on the South Slope of Mount Merapi, Yogyakarta, Indonesia

Groundwater is the primary clean water source for most Indonesian society. The increasing use of groundwater is inevitable due to the rapid development in Indonesia, particularly in Yogyakarta. Shallow aquifers are vulnerable to contamination due to anthropogenic influences. Therefore, this research aims to determine shallow groundwater's physicochemical and chemical characteristics on the southern slope of Mount Merapi, specifically focusing on nitrate and chloride concentrations in groundwater. This research collected monthly data from eighteen dug wells or springs and rainfall data in the study area during the rainy and dry seasons from August 2022 to January 2023. The analyzing sample used argentometry to determine chloride concentration and ultraviolet spectrophotometric to determine nitrate concentration in Yogyakarta Environmental Health and Disease Control Technical Center (BBTKLPP) laboratory. The physicochemical parameters were tested directly in the field using Hanna instruments. The results indicate that a significant portion of shallow groundwater has high nitrate concentrations, corresponding to the growing settlements in the research area. Furthermore, according to the comparison graph between nitrate and chloride, the nitrate source was indicated as anthropogenic. Fecal matter from sanitation practices using septic tanks will likely influence the nitrate increase.

A parsimonious model for predicting the NO3−-N concentration in shallow groundwater in intensive agricultural areas using few easily accessible indicators and small datasets based on machine learning

Groundwater nitrate poses a health risk to humans, and monitoring groundwater quality is time-consuming and expensive. To improve the efficiency and reduce the costs of monitoring groundwater nitrate, a parsimonious model was developed using easily accessible predictors and small datasets based on random forest (RF), neural network (NN), and support vector machine (SVM) algorithms. Groundwater NO3−-N concentrations of 1196 groundwater samples from intensive agricultural areas along with data on 13 predictors were obtained for the construction of prediction models. R2 and RMSE metrics were used to evaluate the models, with an emphasis on a minimal number of predictors and a low data size. The results showed that even with few readily available predictors (conductivity, EC; chemical nitrogen fertilization rate, NF; and precipitation, PPT) and a small dataset (260–700 observations), the three models achieved good precision, with R2 and RMSE values of 0.70–0.80 and 6.87–8.13, respectively. In these prediction models, EC was the primary predictor acting as an intrinsic factor, NF acted as a loading factor to supplement the blind area of EC for NO3−-N prediction, and PPT was introduced because of its accessibility to improve predictive performance. The final predictors applied in this study link the two currently dominant prediction methods by combining the high predictive accuracy of the intrinsic predictor with the accessibility of the extrinsic predictor, and the results demonstrate the practicability and applicability advantages of this model in groundwater NO3−-N prediction. This model provides technical support for the rapid and low-cost realization of the online monitoring of NO3−-N pollution in shallow groundwater in intensive agricultural areas.

Analysis of Leachate Water Distribution in Bakung Final Waste Disposal Location (TPA) Using Resistance Geoelectric Methods in Keteguhan Permai Housing Bandar Lampung

Poor waste management is one of the most frequent environmental problems in Indonesia. We know that the waste generated as a result of daily human activities will be transported, then disposed of at the Final Disposal Site (TPA). The lack of attention to WWTP maintenance at the Daffodil TPA can be seen from the thickness of the sediment at the WWTP dam. The thickness of the sediment in the WWTP causes leachate from the TPA not to fully enter the WWTP but flows directly into the river and seeps into the ground. Thus, this research was conducted as an aim to explain the spread of leachate pollution in shallow groundwater in the Keteguhan Permai housing complex. The method is quantitative. The results of this study indicate that groundwater is shallow in the study area, namely, Keteguhan Permai housing has been polluted by leachate. The average leachate intrusion depth in this study area is less than 13 meters with a resistivity value of less than 10?m.

Simulation Study on Nitrogen Pollution in Shallow Groundwater in Small Agricultural Watersheds in the Huixian Wetland

In this study, we investigated the influence of different simulations on the transport of shallow groundwater nitrogen in the Mudong River watershed of the Huixian Wetland, a karst wetland. Based on GMS (Groundwater Modeling System) software, the equivalent porous media model was used to simulate the transport of total nitrogen under different conditions in the study area. Two years of field monitoring data in the study area provided the input for the modeling. The SWAT (soil and water assessment tool) model was used to divide the study area into sub-basins. The initial concentration flux index W is first introduced in the equivalent porous medium model to calculate the initial concentration. The simulation results showed the difference between the simulated and monitored values of total nitrogen concentration was between 20% and 40% in 22.2% of the cases, and less than 20% in 66.7% of the cases, indicating that the solute transport model has good applicability in the Huixian Wetland. Parameter sensitivity analysis showed that fertilizer application was the main factor influencing total nitrogen. A 25% reduction in fertilizer application reduced total nitrogen emissions by 31.5% in sub-basin S3 and 22.5% in sub-basin S4. These reductions were greater than the abatement effect of changing land cover and managing river pollution. The pollution plume of total nitrogen was reduced by 38.5% in the southern part of sub-basin S3 (Mudong Lake) and by 40.2% in the western part of sub-basin S4 (Blacksmithing Village). The average concentration was reduced by 2.04 mg/L and 1.22 mg/L, respectively. This study shows that reasonable control of double-season rice nitrogen fertilizer application and appropriate land cover modification can help reduce total nitrogen emissions from wetlands in the Li River watershed and ensure the sustainable development of the local economy and groundwater.

A hydrochemical and multi-isotopic study of groundwater sulfate origin and contribution in the coal mining area

Coal mining cities are universally confronted with the degradation of groundwater quality, and the sulfate pollution of groundwater has become a widely studied environmental problem. In this study, we combined multi-isotope (δ34S, δ18O-SO42- and 87Sr/86Sr) approach with hydrochemical technique and a Bayesian mixed model to clarify sources and transformations and to quantitatively assess the contribution of sulfate from potential sources. The concentrations of SO42- in groundwater ranged from 7.7 mg/L to 172.9 mg/L, and the high-value areas were located in coal mining area and residential area. The total values of δ34S and δ18O-SO42- varied from 10.6‰ to 26.9‰ and 6.9‰ to 14.1‰, respectively, in the groundwater. Analyses of SO42- and Sr isotopes and water chemistry indicated that SO42- in groundwater originated from various sources, such as atmospheric precipitation, sulfide mineral oxidation, evaporite dissolution, sewage and mine drainage. The oxidation of pyrite and bacterial sulfate reduction (BSR) had no significant impact on the stable isotopes of groundwater. At the same time, the calculation results of the Bayesian mixed model showed that the sources of SO42- in groundwater mainly include evaporite dissolution in aquifer and mine drainage in the mixture of shallow and deep groundwater, with high contribution proportions of 39.8 ± 10.9% and 31.9 ± 5.7%, respectively, while the contributions of sewage (13.9 ± 8.5%), atmospheric precipitation (9.6 ± 8.6%) and the oxidation of sulfide (4.7 ± 3.3%) to SO42- were lower. The research results revealed the source of SO42- pollution in shallow groundwater in the coal mine area and provided an important scientific basis for the effective management and protection of groundwater resources.

Health Risk Assessment of Heavy Metals in Shallow Groundwater of Coal-Poultry Farming Districts.

This study aimed to assess the heavy metal (Mn, Ni, Cu, Zn, Sr, Cd, Pb, and Cr) pollution characteristics, sources, and human health risks in shallow groundwater in the impact zones of urban and rural semi-intensive poultry farms in Suzhou City. Ordinary kriging interpolation showed that poultry farming contributed substantially to the pollution of shallow groundwater by Mn, Zn, and Cu. Positive matrix factorization was applied to identify the sources of heavy metals, and the health risks were assessed based on the hazard index and carcinogenic risks of the various sources. Heavy metal enrichment was closely related to anthropogenic activities. In addition, four sources were identified: poultry manure (29.33%), natural source (27.94%), industrial activities (22.29%), and poultry wastewater (20.48%). The main exposure route of carcinogenic and non-carcinogenic risks to adults and children was oral ingestion. The non-carcinogenic risk of oral ingestion in children was higher than that in adults; the carcinogenic risk was higher in adults than in children. Poultry manure (42.0%) was considered the largest contributor to non-carcinogenic risk, followed by poultry wastewater (21%), industrial activities (20%), and natural sources (17%). Industrial activity (44%) was the primary contributor to carcinogenic risk, followed by poultry wastewater (25%), poultry manure (19%), and natural sources (12%).

Morphological Distribution and Formation Mechanisms of Antimony in the Shallow Groundwater of the Xikuangshan Antimony Mine in Hunan, China

The century-old mining development and utilization of antimony (Sb) ore in Xikuangshan (XKS) mine, groundwater antimony pollution has attracted great attention. At present, the sources and geochemical behaviors of high Sb groundwater in this area have been widely recognized, but morphological distribution and formation mechanisms of Sb(V) and Sb(III) in shallow groundwater were still little known. Forty-three groundwater samples of Magunao aquifer (D3x4) were collected between June and September 2020 to determine morphological distribution and formation mechanisms of Sb valence state in the recharge area, runoff area and discharge area. The range of Sb content in the recharge area, runoff area, and discharge area of the D3x4 water was 3.300 × 10−3–7.982 mg/L, 1.760 × 10−2–17.326 mg/L and 1.230 × 10−2–16.773 mg/L, respectively. The D3x4 water is dominated by Sb(V), which form was Sb(OH)6−. The Sb(V) mainly comes from the oxidative dissolution of Sb2S3, the mining activities, and the leaching of arsenic alkali residues. The silicate mineral weathering, carbonate mineral dissolution, and ion exchange promote the dissolution of Sb2S3. At the same time, redox and competitive adsorption in the runoff area increase the Sb(V) content in the water environment. The results of this research provide an understanding of the mechanism of Sb pollution in shallow groundwater and will help in controlling water-environment pollution and securing water-resource in mining areas.

Shallow Groundwater Around Plateau Lakes: Spatiotemporal Distribution of Phosphorus and Its Driving Factors

The extensive application of phosphorus fertilizers to croplands and the aggregation of towns and villages around plateau lakes has resulted in the continuous accumulation of phosphorus in the soil profile and the discharge of phosphorus pollutants, which causes phosphorus pollution in shallow groundwater around the lakes. The phosphorus entering the lake with shallow underground runoff in the region around the lake also affects the water quality safety of plateau lakes. The spatiotemporal differences in phosphorus concentrations in 452 shallow groundwater samples and the driving factors were analyzed by monitoring wells in croplands and residential areas around the eight lakes in Yunnan province during the rainy and dry seasons from 2019 to 2021. The results showed that seasonal changes and land use influenced phosphorus concentrations and their composition in shallow groundwater. The concentration of phosphorus in shallow groundwater in the rainy season was higher than that in the dry season, and it was also greater in cropland than that in residential areas. DTP was the dominant form of TP, accounting for 75%-81%, and DIP was the dominant form of DTP, accounting for 74%-80%. Nearly 30% of the samples around the eight lakes had TP concentrations exceeding the surface water Class Ⅲ standard (GB 3838); the exceeded rates of phosphorus in groundwater around the Erhai Lake (52%), Qiluhu Lake (45%), Xingyun Lake (42%), and Dianchi Lake (29%) were far higher than those of Yangzonghai Lake (16%), Fuxianhu Lake (13%), Chenghai Lake (6%), and Yilonghu Lake (5%). The key driving factors of phosphorus concentrations in shallow groundwater were water-soluble phosphorus (WEP), water content (MWC), soil organic matter (SOM), total nitrogen (TN), pH in the soil profile, and pH and groundwater level in the shallow groundwater (P<0.05). The increases in WEP, SOM, TN, and MWC in the soil and pH in groundwater significantly increased the concentrations of DIP and DTP in shallow groundwater, whereas the decrease in groundwater level significantly reduced the concentrations of DTP and DIP in the groundwater.

Sensitivity analysis of factors influencing pollutant removal from shallow groundwater by the PRB method based on numerical simulation.

Permeable reactive barrier (PRB) is one of the most promising in situ treatment methods for shallow groundwater pollution. However, optimal design of PRB is very difficult due to a lack of comprehensive understanding of various complex influencing factors of PRB remediation. In this study, eight of the main factors of PRB, including hydraulic gradient I, permeability coefficient KPRB of PRB material, PRB length L, PRB width W, PRB distance from pollution source Dist., the ratio of the maximum adsorption capacity to Langmuir constant of PRB material Qmax/KL, the discharge rate of pollution source DR, and recharge concentration RC were investigated, to carry out the sensitivity analysis of PRB removal efficiency. The simulation experiments for Morris analysis were designed, and pollutant removal efficiency was numerically simulated by coupling MODFLOW and MT3DMS under two scenarios of high and low permeability and dispersivity. For a typical low permeability with low dispersity medium, the sensitivity ranking of factors from high to low is DR, RC, I, W, L, Dist., Qmax/KL, and KPRB, and for a typical high permeability with a high dispersity medium, the sensitivity ranking of factors from high to low is I, W, DR, Qmax/KL, L, RC, Dist., and KPRB. When considering multiple factors in PRB design, the greater the KPRB, L, W, Qmax/KL is, the higher the removal efficiency is; the greater the RC, I is, the lower the removal efficiency is. The rest factors remain ambiguous enhancement to removal efficiency.

Characteristics of Hydro-Geochemistry and Groundwater Pollution in Songnen Plain in Northeastern China

Agricultural production may cause groundwater pollution. This study investigated the characteristics of shallow groundwater pollution in a typical black land agricultural production area in Northeastern China and the geochemical behavior of major pollutants. A total of 27 and 23 shallow groundwater samples were collected for measuring on-site parameters and major components in 2000 and 2014, respectively. The improved integrated approach was used to assess groundwater contamination. The results showed that the groundwater was slightly polluted by agricultural activities. The average concentrations of major ions of shallow groundwater were found to be in the following order: Ca2+ &gt; Na+ &gt; Mg2+ &gt; K+ for cations and HCO3− &gt; SO42− &gt; Cl− &gt; NO3− for anions. Percentages of 7.4% and 34.8% of the total groundwater sample in 2000 and 2014, respectively, indicated that the shallow groundwater quality has gradually worsened in the past few decades. The concentration of NO3− was a major factor that influenced the observed groundwater quality changes. Scientific and effective fertilization of rice cultivation is an effective way to avoid groundwater pollution, and the improved groundwater quality evaluation methods can further improve the standard of groundwater resource management effectively.

Risk assessment of groundwater pollution during GLDA-assisted phytoremediation of Cd- and Pb-contaminated soil

Using biodegradable chelate agents during phytoremediation of heavy metal contaminated soil is a growing consensus. However, the potential risk of groundwater pollution and the corresponding quantification during biodegradable chelate-assisted phytoremediation is currently ignored. This study provides a risk-assessment framework containing the practical boundaries and the transport model of chelate-metal complexes and metals at the subsoil, to quantify and predict the leaching risk of biodegradable N,N-bis(carboxymethyl)glutamic acid (GLDA)-induced phytoremediation during heavy rainfall. The case of ethylenediaminetetraacetic acid (EDTA)-assisted phytoremediation was also considered. Here, adsorption experiments and percolation experiments were conducted based on the subsoil to obtain adsorption parameters and hydrodynamic parameters. Optimal parameters derived from inverse fitting and the boundary condition originated from pot leaching experiments were used for the framework establishment and Hydrus-1D simulation. Results showed that fewer GLDA-metal complexes were adsorbed on the soil particles compared with metals, inferring their great mobility in the subsoil. However, the chemical and physical non-equilibrium process indicated by the asymmetric breakthrough curves of the percolation experiments would also affect the transport behavior of contaminants in the sub-vadose zone. In addition, adsorption parameters and optimal hydrodynamic parameters aptly described breakthrough curves of the chelate-metal complexes, and could better predict their transport behavior at the subsoil. Opposite to the previous findings, prediction results showed that heavy rainfall during GLDA-assisted phytoextraction resulted in Cd and Pb pollution in shallow groundwater, where the pollution degree was related to properties of the soil horizon, depth of the water table, and types of contaminants. The degradation feature of GLDA-metal complexes would fail to keep groundwater from heavy metal contamination at the sub-vadose zone with high permeability. Thus, we recommend our risk-assessment framework to optimize the operating condition before utilizing the biodegradable chelate-assisted phytoremediation.

Geochemical identification of particulate lead pollution in shallow groundwater in inhabited areas in Kabwe, Zambia

The town of Kabwe has been exposed to the most severe lead pollution due to mining activities in the 20th century. A large tailing (slag) hill containing over 1% of Pb is still standing within the mine's licensed area. We analysed the chemical composition and lead isotope ratios in seventeen shallow wells, five deep wells in the inhabitants' area, three ponds and three borehole wells in the area of the mine, and in the surrounding areas, we examined two samples from the soil's surface and nineteen 1-m deep core samples at each of the 15 sites. We found low dissolved Pb (<0.04 μg/L) but high particulate Pb concentrations (2–100 μg/L) in seventeen shallow groundwater samples (aquifer depth of ca. 10 meters). Five shallow wells exceeded the World Health Organization (WHO) guideline (10 μg/L) for total-Pb concentration. However, three of the five shallow wells had low dissolved Zn and sulphate ion concentrations (<1 μg/L; <50 mg/L), suggesting a low amount of Pb transfers through the aquifer. The isotopic water and soil samples data clarified that the Pb pollution in the shallow groundwaters is derived from the tailings deposit.Most of the shallow groundwater samples had negative cerium (Ce) anomaly in the rare earth element (REE) pattern, indicating contributions of colloidal transport from the dolomite aquifer in this area. However, PHREEQC modelling shows that migration by hydroxide colloids from the mining area does not explain the high particulate lead concentrations in the well water. The positive correlation between Pb/Ce and Pb/Al ratios in the particulates exhibited that the lead pollutants were derived from the aluminosilicates on the land. The estimated Pb contents in particulates in most shallow-well water were 700–2800 mg/L, and they distributed geographically similar to the Pb bulk concentration contour map of the surface soil. The analysis of the grain-size fractions in a 2-km transect soil demonstrated that Pb was eight times enriched in the silt fraction (<53 μm) than a very coarse sand fraction (1–2 mm). Therefore, we hypothesized that the particulates in the well water were mainly derived from the aeolian dust (>0.45 μm) at the well site. Further studies are required to examine the hypothesis.

Changes of groundwater arsenic risk in different seasons in Hetao Basin based on machine learning model

Arsenic pollution of shallow groundwater is serious in Hetao Basin. At present, there are few studies on the seasonal variation and mechanism of high As groundwater. In order to master the risk difference and influence mechanism of high As groundwater in different seasons, we collected 506 shallow groundwater samples in the Hetao Basin, and used climatic factors, topographic factors, and others (influence of irrigation channels, vegetation index) that are closely distributed with As in groundwater to establish a high-precision random forest model of high As groundwater in the Hetao Basin in summer. We used climate factors as dynamic predictors to predict the distribution of high As risks in winter and established human health risk zones in the Hetao Basin. The results show that from winter to summer, the probability of high As in high risk areas further increases with the influence of factors such as temperature increase, rainfall increase, and enhanced evapotranspiration, while the probability of high As in low risk areas is the opposite and shows a downward trend. The areas with increased probability of high human health risks and stable areas are mainly distributed along the drainage canals and concentrated in the middle of the basin. From winter to summer, as the local residents' demand for groundwater increases, the probability of high As has increased and stabilized in high risk areas. The number of threatened populations reached 246,000 and 108,000, respectively. Therefore, we need to focus on them. The results of this research explored the changing trend and mechanism of high As groundwater risks under the influence of climate, further enriching the regional high As groundwater research system, and can also be provided as a reference for similar research in other regions.

Electrical conductivity and dissolved oxygen as predictors of nitrate concentrations in shallow groundwater in Erhai Lake region

Elevated nitrogen (N) concentration in shallow groundwater is becoming increasingly problematic, putting water resources under pressure. For more effective management of such a resource, more precise predictors of N level in groundwater using smart monitoring networks are needed. However, external factors such as land use type, rainfall, and N loads from multiple sources (residential and agricultural) make it difficult to accurately predict the spatial and temporal variations of N concentration. In order to identify the key factors affecting spatial and temporal N concentration in shallow groundwater and develop a predictive model, 635 groundwater samples from drinking wells in residential areas and agricultural wells in croplands of a typical agricultural watershed in the Erhai Lake Basin, southwest China, in the period from 2018 to 2020, were collected and analyzed. The results showed that the type of land use and seasonal variations significantly affected the N forms and their concentrations in the shallow groundwater, as the ratios of ON and NO3−-N to TN were 30%–39% and 52%–59% for the two land uses and 25%–44% and 46%–66% for seasonal changes. Their variations were reflected by electrical conductivity (EC) and redox environment. EC and dissolved oxygen (DO) had a positive non-linear relationship with the concentrations of total nitrogen (TN) and nitrate (NO3−-N). The fitted non-linear quantitative models were established separately to predict TN and NO3−-N concentrations in groundwater using easily available indictors (EC and DO). The high accuracy and performance of the models were investigated and approved by rRMSE, MAE, and 1:1 line. These findings can provide technical support for the rapid prediction and evaluation of N pollution in shallow groundwater through easily available indicators.

Distribution, source and health risk assessment based on the Monte Carlo method of heavy metals in shallow groundwater in an area affected by mining activities, China

Mining activities exert a far-reaching impact on the quality of groundwater, and health problems caused by heavy metal pollution have attracted global attention. In this study, inductively coupled plasma-mass spectrometry (ICP-MS) was employed to determine the contents of 8 heavy metals (Cd, Cr, As, Fe, Mn, Cu, Zn, and Pb) in shallow groundwater samples retrieved from a mining area in northern Anhui. Multivariate statistical methods were adopted to analyze the distribution and source of pollution and to evaluate 5% and 95% health risks based on Monte Carlo simulation. Fe, As and Cr significantly exceeded the safe drinking water standards of the World Health Organization (WHO). The average concentrations of As and Cr were as high as 46.45 μg/L and 133.96 μg/L, respectively. The correlation analysis and principal component analysis (PCA) results revealed that heavy metals are affected by complex factors, the main factor being human activities. The total carcinogenic health risks of Cr and As in adults were 2.49 × 10−3 and 3.43 × 10−4, respectively, which exceeded the maximum acceptable risk value (1 ×10−4) recommended by the United States Environmental Protection Agency (USEPA), affecting human health. According to the USEPA classification of hazardous ingestion (HI), at HI < 1, the impact of non-carcinogenic heavy metals on human health is negligible. These results indicate that local residents should strengthen the monitoring of Cr and As pollution in shallow groundwater.

Hydrochemical properties and influencing factors of nitrogen pollution for shallow groundwater in the Urban planning area of Suzhou City

Detailed study of the chemical analysis results of 14 shallow groundwater samples, representing different land use types, were carried out in an attempt to identify the hydrochemical properties and influencing factors of nitrogen pollution for the Urban planning area in Suzhou city, China. Hydrochemical properties were analyzed by water quality and its’ main influential factors of nitrogen pollution were analyzed by using ArcGIS geostatistics module and factor analysis method. The results show that the water chemistry type of shallow groundwater in the study area was mainly HCO3-Ca·Na type, the shallow groundwater was in a strong reducing geological environment rich in organic matter. Shallow groundwater shows a significant nitrogen occurrence with high ammonia and low nitrate owing to the strong reducing geological environment with abundant organic matter and low oxygen in the study area.The occurrence forms of nitrogen in shallow groundwater were controlled by the oxidation-reduction environment. Factor analysis shows that the nitrogen content and pollution of shallow groundwater are mainly controlled by human activities and geological conditions, followed by formation lithology, redox conditions and topography.