Groundwater pollution source identification and health risk assessment in the North Anhui Plain, eastern China: Insights from positive matrix factorization and Monte Carlo simulation

Two-dimensional Monte Carlo simulation coupled with multilinear regression modeling of source-specific health risks from groundwater

Effective protection of groundwater requires an accurate health risk assessment of contaminants; however, the diversity of pollution sources, variability, and uncertainties in exposure parameters present significant challenges in this assessment. In this study, groundwater risk estimates associated with NO3-, and F-, along with fourteen heavy metal(loid)s (V, Cr, Mn, Fe, Ni, Cu, As, Co, Cd, Se, Pb, Hg, Zn, and Al) in an agricultural area were optimized by implementing positive matrix factorization (PMF), multilinear regression, and two-dimensional Monte Carlo simulations to characterize source-specific health risks. Groundwater pollution was analyzed considering regional variations, including differences in elevation, land use and land cover, and soil types. Three pollution sources were identified: agricultural practices, traffic, and natural processes. Moreover, the results revealed NO3- from an agricultural source as the primary control contaminant. Additionally, both adults and children in the study area face significant non-carcinogenic health risks. To mitigate these risks, this study recommends maximum consumption levels of 1.44 L/day for adults and 0.35 L/day for children. Furthermore, adults weighing > 68.1 kg and children weighing > 15.9 kg are likely to be at reduced risk of experiencing adverse health effects. Compared to deterministic health risk assessment and one-dimensional Monte Carlo simulation of health risks, two-dimensional Monte Carlo simulation showed improved performance, providing better accuracy and higher precision in health risk assessment results. Thus, this research is expected to enhance the understanding of health risk assessment related to groundwater and to provide valuable guidance for managing groundwater pollution.

Joint identification of groundwater contaminant sources: an improved optimization algorithm

Rapid identification of contaminant source information is critical for solving sudden groundwater contamination events. This paper constructs a combined EnKF-SPSO algorithm based on the ensemble Kalman filter (EnKF) and survival particle swarm optimization (SPSO) algorithms to groundwater contamination source identification, which includes determining the location of the source, initial concentration, and emission time. The proposed hybrid architecture improves upon conventional single-algorithm approaches by decoupling the identification process into two stages. First, the EnKF searches for the contaminant source's location, thereby reducing the search space. Next, the SPSO estimates the initial concentration and emission time within the reduced domain. This two-stage process effectively mitigates the curse of dimensionality often encountered in standalone optimization methods. We set up two solute transport scenarios with different numbers of contaminant sources to examine the effectiveness of the algorithm and compare it with the EnKF, particle swarm optimization (PSO), and SPSO algorithms. The results show that the EnKF-SPSO algorithm can identify the contaminant characteristics more accurately without falling into a local optimum, and the average relative error is less than 1%. In addition, the EnKF-SPSO algorithm, for cases with measurement errors, is highly reliable. The combined algorithm can provide technical support for groundwater contamination remediations, risk assessments, and liability determinations.

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

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

Heavy metal enrichment characteristics and synergistic evaluation in soil-crop-human systems of agricultural land with different soil parent materials

Heavy metal (HM) pollution in agricultural areas seriously threatens food security and ecological health. In this study, based on different soil parent materials, the HMs enrichment in the soil-crop systems of two typical eastern Chinese agricultural lands was compared and analyzed. Multivariate linear stepwise regression analysis, influence index of comprehensive quality and HHRA model were used to understand the bioaccumulation and to evaluate the soil-crop-human system. The study showed that HMs exhibited different enrichment characteristics in the two soil parent material areas. Cd faced a higher risk control rate and was a priority pollutant in the soil environment. The acidification soils in the granitic parent material area led to more widespread Ni pollution in wheat grains. The HM absorption model clarifies that driving factors such as the HM content, physicochemical properties and the distance to the river can well explain the enrichment ability of HMs in wheat grains. The synergistic evaluation revealed that only 13.04% of soil and crops were at a clean level. Soil contamination is more prevalent in the metamorphic rocks area, while crop contamination is more severe in the granitic parent material area. Probabilistic health risk assessment indicated that HMs primarily impact health through the ingestion of contaminated wheat, so residents of the granitic parent material area face a slightly higher HI. This information will be crucial for understanding the translocation and accumulation of HMs within soil-crop-human health systems of agricultural land in different soil parent material areas and for developing effective pollution prevention and control programs.

Identification of hydrogeochemical processes in shallow groundwater using multivariate statistical analysis and inverse geochemical modeling

Identifying key factors that control the chemical evolution of groundwater along groundwater flow direction is essential in ensuring the safety of groundwater resources in upper watersheds and lower plains. In this study, the ion ratio, multivariate statistics, and inverse geochemical modeling were used to investigate and explore the chemical characteristics of groundwater and factors driving the formation of groundwater components in the plain area of Deyang City, China. The chemical type of groundwater in the area was dominated by the HCO3-Ca type, and the variation in groundwater chemical composition was mainly affected by water-rock interaction and human interference. The water-rock interaction process includes carbonate dissolution, oxidation-reduction reactions, and cation exchange. Furthermore, inverse geochemical modeling revealed that the dissolution of evaporite minerals, dissolution/precipitation of carbonate minerals, and weathering of silicate minerals play a key role in the hydrogeochemical evolution of groundwater. Owing to dissimilar geological and hydrological conditions, hydrogeochemical evolution processes differ along different and similar paths. Overall, this study not only provides a conceptual framework for hydrochemical evolution in plains but also has important implications for the sustainable management of groundwater resources in other basins within plains.

Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence

Groundwater is vital for agricultural cities, but intensive farming and fertilizer use have increased contamination risks, particularly for non-carcinogenic health hazards. This study reveals the sources of contaminants in groundwater, their health impacts, and targeted strategies in such cities. The study analyzed 115 groundwater samples, with the main groundwater chemical type being HCO₃-Na·Ca. Significant exceedances were found in Mg²⁺, HCO₃-, F-, total hardness (TH), and Mn, with HCO₃- and Mg²⁺ surpassing standards in nearly all samples. The average Comprehensive Environmental Water Quality Index (CEWQI) was 100.68, indicating that overall groundwater quality in the study area is good. High-quality water is mainly found near reservoirs and rivers, while urban and eastern regions have relatively poorer water quality. The proportion of groundwater unsuitable for drinking is low. Monte Carlo risk assessments revealed that F- and NO₃- pose non-carcinogenic risks to both adults and children, with NO₃- presenting a higher potential health risk. The Positive Matrix Factorization (PMF) model identified that groundwater pollution primarily results from natural geological processes and human activities, with agriculture being the major anthropogenic factor. AI-based zoning strategies highlighted industrial areas and high-fluoride zones as critical areas requiring enhanced prevention and control measures.

Spatiotemporal variability of groundwater chemistry, source identification and health risks in the southern Chinese Loess Plateau

Groundwater pollution of the loess plateau regions has become a global concern due to its vulnerability to natural and anthropogenic influences. In this study, 146 water samples were investigated to identify the spatiotemporal variability in groundwater chemistry, pollution sources and nitrate health risks in two interconnected river basins of a typical loess region. The results showed that except for bicarbonate, spatiotemporal variability of hydrochemical components in Malian River Basin (ML) was generally greater than that in Upper Jinghe River basin (JH-U) due to the hydrogeological conditions, and the hydrochemical facies in two river basins transformed from SO4·Cl and Cl·SO4 types to HCO3 and HCO3·SO4 types. The results of integrated-weight quality index (IWQI) showed that 77.8 % (1970s), 33.3 % (2004), 34.3 % (2015) of samples in ML exceeded the standard limits of Class IV groundwater quality, displaying a high pollution level with an improvement trend, while groundwater quality in JH-U indicated a very low pollution level with a deterioration trend. The geogenic source was identified as a main factor affecting groundwater quality, with contributions of 59.2 % and 48.7 % in JH-U and ML (2015), respectively. The anthropogenic sources including agricultural activities (20.7 % and 21.8 % in JH-U and ML) and coal mining activities (20.1 % and 29.5 % in JH-U and ML) also played a role in affecting groundwater quality. The nitrate health risk assessment demonstrated that 39.1 % and 20.3 % of groundwater samples (2015) significantly exceeded the standard threshold (Hazard Index = 1), implying a higher health risk to children than adults, and the nitrate health risk in ML was obviously greater than that in JH-U. This study provides novel insight into the spatiotemporal variability in groundwater chemistry, quality and health risk in loess regions under the influence of geogenic and anthropogenic factors.

Enrichment mechanism and probabilistic health risk assessment of high-fluoride groundwater in Gaomi City, China

Fluoride (F) is the most important inorganic pollutant in groundwater that affects human health, and analyzing the causes of high-fluoride groundwater is a prerequisite for protecting the health of residents. To comprehensively understand the enrichment characteristics of groundwater in the high-fluoride areas, this study systematically investigated the concentrations of fluoride in Gaomi City, a typical study area in the Jiaolai Plain and explored the spatiotemporal distribution patterns, enrichment mechanisms, and the probabilistic health risk associated with F-. The results indicate that there is serious fluorine pollution in groundwater, which is mainly concentrated in the alluvial plain in the north and affected by topographical and aquifer characteristics. Favorable runoff conditions effectively improve the fluoride status of shallow groundwater on both sides of rivers and in hilly areas. Hydrogeochemical methods reveal the mechanism of fluoride enrichment. The relative contributions rates of different hydrogeochemical processes to the fluoride enrichment are as follows: dissolution and precipitation (39.02%) > cation exchange (25.25%) > competitive adsorption (19.48%) > seawater intrusion (3.14%) > evaporative and concentration (1.99%). Health risk assessment based on Monte Carlo simulation shows that health risk susceptibilities of different populations are infants (76.07%), children (66.59%), teenagers (44.54%), and adults (5.68%), respectively. In addition, targeted management suggestions are put forward regarding the enrichment mechanisms of fluoride in groundwater and its impact on health. These findings have significant implications for controlling regional diffuse F- contamination in groundwater, protecting public health, and promoting social development in regions with a high risk of groundwater fluoride contamination.

Hydrochemical characteristics, control factors and health risk assessment of groundwater in typical arid region Hotan Area, Chinese Xinjiang

The Hotan region of Xinjiang is an arid region in northwest China, where water resources are scarce, and groundwater is the main water supply. In this study, a self-organizing map (SOM), positive matrix factorization (PMF), hydrochemical diagrams, and health risk assessment model were used to analyze the sources and controlling factors of groundwater chemistry, and evaluate health risks of nitrate and fluoride. The results showed that the evaporation process and water-rock interaction were the main factors influencing groundwater chemistry in the region. Based on the SOM, 239 groundwater samples were divided into six clusters. The main hydrochemical types were Cl-Na, HCO3-Na, and SO4-Ca. Natural factors such as evaporation, water-rock interaction and cation exchange play important roles in Cluster 1-2 and 4-6, while Cluster 3 is mainly polluted by nitrate. Fluoride pollution, primarily caused by geological processes, and nitrate pollution, caused by human activities, cannot be ignored. Attention should be paid to the high non-carcinogenic risk of fluoride and nitrate exposure through drinking water, especially for children. These results provide a theoretical basis for the rational development and utilization of local water resources and ecological environmental protection. The study suggested that the combined method of the SOM and PMF provides a reliable approach for interpreting nonlinear and high-dimensional hydrochemical data.

Optimized groundwater quality evaluation using unsupervised machine learning, game theory and Monte-Carlo simulation

Assessing groundwater quality is essential for achieving sustainable development goals worldwide. However, it is challenging to conduct hydrochemical analysis and water quality evaluation by traditional methods. To fill this gap, this study analyzed the hydrochemical processes, drinking and irrigation water quality, and associated health risks of 93 groundwater samples from the Sichuan Basin in SW China using advanced unsupervised machine learning, the Combined-Weights Water Quality index, and Monte-Carlo simulations. Groundwater samples were categorized into three types using the self-organizing map with the K-means method: Cluster-1 was Ca-HCO3 type, Cluster-2 was dominated by Ca-HCO3, Na-HCO3, and mixed Na-Ca-HCO3 types, Cluster-3 was Ca-Cl and Ca-Mg-Cl types. Ion ratio diagrams revealed that carbonate dissolution and silicate weathering primarily influenced the hydrochemical characteristics. Cluster-1 samples exhibited high NO3- contents from intensive agricultural activities. Cluster-2 samples with high Na+ contents were characterized by positive cation exchange, while Cluster-3 samples with elevated Ca2+ and Mg2+ contents were influenced by reverse cation exchange. Combined-Weights Water Quality Index indicated that 62.37% of total samples were suitable for drinking, predominantly located in the central part of the study area. Irrigation Water Quality Index revealed that 33.34% of total samples were suitable for irrigation, mainly in the northeastern region. NO3- concentration and electrical conductivity (EC) value were the main indicators with the highest sensitivity for drinking and irrigation suitability, respectively. Probabilistic health risk assessments suggested that a significant portion of the groundwater samples posed a health risk greater than 1 to children (63%) and adults (52%) by Monte-Carlo simulation. The high-risk areas (hazard index >4), primarily in the eastern region, are closely associated with nitrate distribution. Sensitivity analysis demonstrated that NO3- concentration is the primary indicator accounting for health risks. Reducing the application of nitrogen-based fertilizers on cultivated land is the most effective approach to improve drinking quality and mitigate the associated health risks to the population. This study's findings aim to produce a novel groundwater quality evaluation for promoting the sustainable management and utilization of groundwater resources.

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.

Source-oriented health risk assessment of groundwater based on hydrochemistry and two-dimensional Monte Carlo simulation

Accurately assessing the health risks posed by major contaminants is essential for protecting groundwater. However, the complexity of pollution sources and the uncertainty of parameters pose challenges for quantitative health risk assessment. In this study, a source-oriented groundwater risk evaluation process was improved by screening key pollutants, employing a combined hydrochemical and positive matrix factorization (PMF) approach for source apportionment, and incorporating two-dimensional Monte Carlo simulation for risk characterization. The application of this process to groundwater assessment in Central Jiangxi Province identified NO3-, F-, Se and Mn as the key pollutants. The pollution sources were anthropogenic activities, rock dissolution, regional geological processes, and ion exchange. Anthropogenic sources contributed 36.8 % and 28.8 % of the pollution during the wet season and dry season, respectively, and accounted for more than half of the health risks. NO3- from anthropogenic sources was the primary controlling pollutant. Additionally, the risk assessment indicated that children were at the highest health risk during the dry season, with ingestion rate suggested to be controlled below 1.062 L·day-1 to make the health risk within an acceptable range. The improved assessment methodology could provide more accurate results and recommended intakes.

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.

Source-specific probabilistic health risk assessment of dust PAHs in urban parks based on positive matrix factorization and Monte Carlo simulation

Understanding the health risks of polycyclic aromatic hydrocarbons (PAHs) in dust from city parks and prioritizing sources for control are essential for public health and pollution management. The combination of Source-specific and Monte Carlo not only reduces management costs, but also improves the accuracy of assessments. To evaluate the sources of PAHs in urban park dust and the possible health risks caused by different sources, dust samples from 13 popular parks in Kaifeng City were analyzed for PAHs using gas chromatograph-mass spectrometer (GC-MS). The results showed that the surface dust PAH content in the study area ranged from 332.34 µg·kg-1 to 7823.03 µg·kg-1, with a mean value of 1756.59 µg·kg-1. Nemerow Composite Pollution Index in the study area ranged from 0.32 to 14.41, with a mean of 2.24, indicating that the overall pollution warrants attention. Four pollution sources were identified using the positive matrix factorization (PMF) model: transportation source, transportation-coal and biomass combustion source, coke oven emission source, and petroleum source, with contributions of 33.74%, 25.59%, 22.14%, and 18.54%, respectively. The Monte Carlo cancer risk simulation results indicated that park dust PAHs pose a potential cancer risk to all three populations (children, adult male and adult female). Additionally, the cancer risk for children was generally higher than that for adult males and females, with transportation sources being the main contributor to the carcinogenic risk. Lastly, sensitivity analyses results showed that the toxic equivalent concentration (CS) is the parameter contributing the most to carcinogenic risk, followed by Exposure duration (ED).

Natural background levels, source apportionment and health risks of potentially toxic elements in groundwater of highly urbanized area

Identifying the natural background levels (NBLs), threshold values (TVs), sources and health risks of potentially toxic elements in groundwater is crucial for ensuring the water security of residents in highly urbanized areas. In this study, 96 groundwater samples were collected in urban area of Sichuan Basin, SW China. The concentrations of potentially toxic elements (Li, Fe, Cu, Zn, Al, Pb, B, Ba and Ni) were analyzed for investigating the NBLs, TVs, sources and health risks. The potentially toxic elements followed the concentration order of Fe > Ba > B > Al > Zn > Li > Cu > Ni > Pb. The NBLs and TVs indicated the contamination of potentially toxic elements mainly occurred in the northern and central parts of the study area. The Positive Matrix Factorization (PMF) model identified elevated concentrations of Fe, Al, Li, and B were found to determine groundwater quality. The primary sources of Fe, Al, Pb, and Ni were attributed to the dissolution of oxidation products, with Fe additionally affected by anthropogenic reduction environments. Li and B were determined to be originated from the weathering of tourmaline. High levels of Ni and Cu concentrations were derived from electronic waste leakage, while excessive Ba and Zn were linked to factory emissions and tire wear. The reasonable maximum exposure (RME) of hazard index (HI) was higher than safety standard and reveal the potential health risks in the southwestern study area. Sensitivity analysis demonstrated the Li concentrations possessed the highest weight contributing to health risk. This study provides a valuable information for source-specific risk assessments of potentially toxic elements in groundwater associated with urban areas.

Groundwater suitability assessment for irrigation and drinking purposes by integrating spatial analysis, machine learning, water quality index, and health risk model

An in-depth understanding of nitrate-contaminated surface water and groundwater quality and associated risks is important for groundwater management. Hydrochemical characteristics and driving forces of groundwater quality and non-carcinogenic risks of nitrate were revealed by the integrated approaches of self-organizing map analysis, spatial visualization by geography information system, entropy and irrigation water quality indices, and human health risk model. Groundwater samples were categorized into two clusters by SOM analysis. Cluster I including three samples were Ca-SO4 type and cluster II of remaining 136 samples were Ca-HCO3 type. Hydrochemical compositions of two cluster samples were dominated by water-rock interaction: (1) calcite and gypsum dissolution for cluster I samples and (2) calcite dissolution, silicate weathering, and positive cation exchange for cluster II samples. Nitrate contamination occurred in both cluster I and II samples, primarily induced by agricultural nitrogen fertilizer. The EWQI results showed that 90.97% in total groundwater samples were suitable for drinking purpose, while the IWQI results demonstrated that 65.03% in total groundwater samples were appropriate for irrigation purpose. The HHR model and Monte Carlo simulation indicated that the non-carcinogenic nitrated risk was highest in children. Exposure frequency was the most sensitive factor (86.33% in total) influencing the total non-carcinogenic risk, indicated by sensitivity analysis. Compared with the two clusters of groundwater, surface water has a shorter circulation cycle and lower ion concentrations resulting in better water quality. This study can provide scientific basis for groundwater quality evaluation in other parts of the world.

Formation of nitrated naphthalene in the sulfate radical oxidation process in the presence of nitrite

Polycyclic aromatic hydrocarbons (PAHs) have become a global environmental concern due to their potential hazardous implication for human health. In this study, we found that sulfate radical (SO4•-) could effectively degrade naphthalene (NAP), a representative PAH in groundwaters, generating 1-naphthol. This intermediate underwent further degradation, yielding ring-opening products including phthalic acid and salicylic acid. However, the presence of nitrite (NO2-), a prevalent ion in subsurface environments, was observed to compete with NAP for SO4•-, thus slowing down the NAP degradation. The reaction between NO2- and SO4•- generated a nitrogen dioxide radical (NO2•). Concurrently, in-situ formed 1-naphthol underwent further oxidization to the 1-naphthoxyl radical by SO4•-. The coupling of 1-naphthoxyl radicals with NO2• gave rise to a series of nitrated NAP, namely 2-nitro-1-naphthol, 4-nitro-1-naphthol, and 2,4-dinitro-1-naphthol. In addition, the in-situ formed phthalic acid and salicylic acid also underwent nitration, generating nitrophenolic products, although this pathway appeared less prominent than the nitration of 1-naphthol. When 10 μΜ NAP was subjected to heat activated peroxydisulfate oxidation in the presence of 10 μΜ NO2-, the total yield of nitrated products reached 0.730 μΜ in 120 min. Overall, the presence of NO2- dramatically altered the behavior of NAP degradation by SO4•- oxidation and contributed to the formation of toxic nitrated products. These findings raise awareness of the potential environmental risks associated with the application of SO4•--based oxidation processes for the remediation of PAHs-polluted sites in presence of NO2-.

Pollution levels and probability risk assessment of potential toxic elements in soil of Pb-Zn smelting areas

Soil pollution around Pb-Zn smelters has attracted widespread attention around the world. In this study, we compiled a database of eight potentially toxic elements (PTEs) Pb, Zn, Cd, As, Cr, Ni, Cu, and Mn in the soil of Pb-Zn smelting areas by screening the published research papers from 2000 to 2023. The pollution assessment and risk screening of eight PTEs were carried out by geo-accumulation index (Igeo), potential ecological risk index (PERI) and health risk assessment model, and Monte Carlo simulation employed to further evaluate the probabilistic health risks. The results suggested that the mean values of the eight PTEs all exceeded the corresponding values in the upper crust, and more than 60% of the study sites had serious Pb and Cd pollution (Igeo > 4), with Brazil, Belgium, China, France and Slovenia having higher levels of pollution than other regions. Besides, PTEs in smelting area caused serious ecological risk (PERI = 10912.12), in which Cd was the main contributor to PREI (86.02%). The average hazard index (HI) of the eight PTEs for adults and children was 7.19 and 9.73, respectively, and the average value of total carcinogenic risk (TCR) was 4.20 × 10-3 and 8.05 × 10-4, respectively. Pb and As are the main contributors to non-carcinogenic risk, while Cu and As are the main contributors to carcinogenic risk. The probability of non-carcinogenic risk in adults and children was 84.05% and 97.57%, while carcinogenic risk was 92.56% and 79.73%, respectively. In summary, there are high ecological and health risks of PTEs in the soil of Pb-Zn smelting areas, and Pb, Cd, As and Cu are the key elements that cause contamination and risk, which need to be paid attention to and controlled. This study is expected to provide guidance for soil remediation in Pb-Zn smelting areas.

Entropy-weighted water quality index, hydrogeochemistry, and Monte Carlo simulation of source-specific health risks of groundwater in the Morava River plain (Serbia)

Population growth, urbanization, industry, floods, and agriculture globally degrade groundwater in river plains, necessitating action for its quality assessment and management. Hence, a comprehensive methodology, including hydrogeochemical facies (Piper, Gibbs), irrigation indices (SAR, Wilcox), entropy-weighted water quality index (EWQI), positive matrix factorization (PMF), and Monte Carlo simulation of source-specific health risks was used in this study to analyze groundwater in the Morava river plain (Serbia). The results revealed a prevalent Ca-Mg-HCO3 groundwater type, influenced by water-rock interactions. Although groundwater was found suitable for irrigation, only 66.7 % of the samples were considered drinkable. Agricultural activities, natural processes, and municipal wastewater were identified as primary pollution sources. The incremental lifetime cancer risk (ILCR) and hazard index (HI) threshold exceedance for adults and children ranged from 8.5 % to 39 % of the samples, with arsenic identified as the most risk-contributing contaminant. These findings provide valuable insights for researchers studying groundwater vulnerability in river plains.