Determining nitrate and sulfate pollution sources and transformations in a coastal aquifer impacted by seawater intrusion-A multi-isotopic approach combined with self-organizing maps and a Bayesian mixing model

Coupled processes involving ammonium inputs, microbial nitrification, and calcite dissolution control riverine nitrate pollution in the piedmont zone (Qingshui River, China)

Rivers in agricultural countries widely suffer from diffuse nitrate (NO3-) pollution. Although pollution sources and fates of riverine NO3- have been reported worldwide, the driving mechanisms of riverine NO3- pollution associated with mineral dissolution in piedmont zones remain unclear. This study combined hydrogeochemical compositions, stable isotopes (δ18O-NO3-, δ15N-NO3-, δ18O-H2O, and δ2H-H2O), and molecular bioinformation to determine the pollution sources, biogeochemical evolution, and natural attenuation of riverine NO3- in a typical piedmont zone (Qingshui River). High NO3- concentration (37.5 ± 9.44 mg/L) was mainly observed in the agricultural reaches of the river, with ~15.38 % of the samples exceeding the acceptable limit for drinking purpose (44 mg/L as NO3-) set by the World Health Organization. Ammonium inputs, microbial nitrification, and HNO3-induced calcite dissolution were the dominant driving factors that control riverine NO3- contamination in the piedmont zone. Approximately 99.4 % of riverine NO3- contents were derived from NH4+-containing pollutants, consisted of manure & domestic sewage (74.0 % ± 13.0 %), NH4+-synthetic fertilizer (16.1 % ± 8.99 %), and soil organic nitrogen (9.35 % ± 4.49 %). These NH4+-containing pollutants were converted to HNO3 (37.2 ± 9.38 mg/L) by nitrifying bacteria, and then the produced HNO3 preferentially participated in the carbonate (mainly calcite) dissolution, which accounted for 40.0 % ± 12.1 % of the total riverine Ca2+ + Mg2+, also resulting in the rapid release of NO3- into the river water. Thus, microbial nitrification could be a new and non-negligible contributor of riverine NO3- pollution, whereas the involvement of HNO3 in calcite dissolution acted as an accelerator of riverine NO3- pollution. However, denitrification had lesser contribution to natural attenuation for high NO3- pollution. The obtained results indicated that the mitigation of riverine NO3- pollution should focus on the management of ammonium discharges, and the HNO3-induced carbonate dissolution needs to be considered in comprehensively understanding riverine NO3- pollution in piedmont zones.

Tracing the impacts of ecological water replenishment on the sources and transformation of groundwater nitrate through isotope and microbial analysis

Ecological water replenishment (EWR) changes the recharge conditions, flow fields, and physicochemical properties of regional groundwater. However, the resulting impacts on mechanisms regulating the sources and transformation of groundwater nitrate remain unclear. This study investigated how EWR influences the sources and transformation processes of groundwater nitrate using an integrated approach of Water chemistry analysis and stable isotopes (δ15N-NO3- and δ18O-NO3-) along with microbial techniques. The results showed that groundwater NO3-N decreased from 12.98 ± 7.39 mg/L to 7.04 ± 8.52 mg/L after EWR. Water chemistry and isotopic characterization suggested that groundwater nitrate mainly originated from sewage and manure. The Bayesian isotope mixing model (MixSIAR) indicated that EWR increased the average contribution of sewage and manure sources to groundwater nitrate from 46 % to 61 %, whereas that of sources of chemical fertilizer decreased from 43 % to 21 %. Microbial community analysis revealed that EWR resulted in a substantial decrease in the relative abundance of Pseudomonas spp denitrificans, from 13.7 % to 0.6 %. Both water chemistry and microbial analysis indicated that EWR weakened denitrification and enhanced nitrification in groundwater. EWR increases the contribution of nitrate to groundwater by promoting the release of sewage and feces in the unsaturated zone. However, the dilution effect caused by EWR was stronger than the contribution of sewage and fecal sources to groundwater nitrate. As a result, EWR helped to reduce groundwater nitrate concentrations. This study showed the effectiveness of integrated isotope and microbial techniques for delineating the sources and transformations of groundwater nitrate influenced by EWR.

Spatial distribution, geochemical processes of high-content fluoride and nitrate groundwater, and an associated probabilistic human health risk appraisal in the Republic of Djibouti

In the northern East African Rift System, the Republic of Djibouti relies exclusively on groundwater, with levels of fluoride (up to 14 mg/L) and nitrate (up to 256 mg/L) posing potential health risks. To address this, 362 samples were considered, including 133 shallow groundwater samples, along with new and previously published data dating back to 2012 on deep (88) and thermal (141) groundwater samples. To understand the enrichment mechanisms, dissolved anion and cation constituents, geochemical and thermodynamic tools, and stable isotope ratios, such as δ2H(H2O), δ18O(H2O), δ15N(NO3-), and δ18O(NO3-), were used. In particular, two activity diagrams (Mg2+ vs. Ca2+ and Na+ vs. Ca2+), focused on aqueous and solid fluoride species in an updated thermodynamic dataset of 15 fluoride-bearing minerals, are shown for the first time. The dataset offers new and valuable insights into fluoride geochemistry (classic thermodynamic datasets combined with geochemical codes rely solely on fluorapatite and fluorite F-bearing minerals). Activity diagrams and geochemical modeling indicate that mineral dissolution primarily drives groundwater fluoride enrichment in all water types, whereas the elevated nitrate levels may stem from organic fertilizers like animal manure, as indicated by nitrate isotopes and NO3-/Cl- vs Cl- diagrams. Despite the arid climate and 2H18O enrichment in shallow waters, evaporation seems to play a minor role. Monte Carlo simulations and sensitivity analysis were used to assess the health risks associated with elevated F- and NO3- concentrations. Mapping-related spatial distribution analysis identified regional contamination hotspots using a global Moran's I and GIS tools. One fluoride and three nitrate contamination hotspots were identified at a p-value of 0.05. Groundwater chemistry revealed that 88 % of groundwater being consumed exceeded the permissible levels for fluoride and nitrate, posing potential health risks, particularly for teenagers and children. This study pinpoints specific areas with excessive nitrate and fluoride contamination, highlighting a high non-carcinogenic risk.

Community coalescence under variable hydrochemical conditions of the Chesapeake Bay shaped bacterial diversity and functional traits

Community coalescence related to bacterial mixing events regulates community characteristics and affects the health of estuary ecosystems. At present, bacterial coalescence and its driving factors are still unclear. The present study used a dataset from the Chesapeake Bay (2017) to address how bacterial community coalescence in response to variable hydrochemistry in estuarine ecosystems. We determined that variable hydrochemistry promoted the deterioration of water quality. Temperature, orthophosphate, dissolved oxygen, chlorophyll a, Secchi disk depth, and dissolved organic phosphorus were the key environmental factors driving community coalescence. Bacteria with high tolerance to environmental change were the primary taxa accumulated in community coalescence, and the significance of deterministic processes to communities was revealed. Community coalescence was significantly correlated with the pathways of metabolism and organismal systems, and promoted the co-occurrence of antibiotic resistance and virulence factor genes. Briefly, community coalescence under variable hydrochemical conditions shaped bacterial diversity and functional traits, to optimise strategies for energy acquisition and lay the foundation for alleviating environmental pressures. However, potential pathogenic bacteria in community coalescence may be harmful to human health and environmental safety. The present study provides a scientific reference for ecological management of estuaries.

Sources and transformations of riverine nitrogen across a coastal-plain river network of eastern China: New insights from multiple stable isotopes

Riverine nitrogen pollution is ubiquitous and attracts considerable global attention. Nitrate is commonly the dominant total nitrogen (TN) constituent in surface and ground waters; thus, stable isotopes of nitrate (δ15N/δ18O-NO3-) are widely used to differentiate nitrate sources. However, δ15N/δ18O-NO3- approach fails to present a holistic perspective of nitrogen pollution for many coastal-plain river networks because diverse nitrogen species contribute to high TN loads. In this study, multiple isotopes, namely, δ15N/δ18O-NO3-, δ18O-H2O, δ15N-NH4+, δ15N-PN, and δ15Nbulk/δ18O/SP-N2O in the Wen-Rui Tang River, a typical coastal-plain river network of Eastern China, were investigated to identify transformation processes and sources of nitrogen. Then, a stable isotope analysis in R (SIAR) model-TN source apportionment method was developed to quantify the contributions of different nitrogen sources to riverine TN loads. Results showed that nitrogen pollution in the river network was serious with TN concentrations ranging from 1.71 to 8.09 mg/L (mean ± SD: 3.77 ± 1.39 mg/L). Ammonium, nitrate, and suspended particulate nitrogen were the most prominent nitrogen components during the study period, constituting 45.4 %, 28.9 %, and 19.9 % of TN, respectively. Multiple hydrochemical and isotopic analysis identified nitrification as the dominant N cycling process. Biological assimilation and denitrification were minor N cycling processes, whereas ammonia volatilization was deemed negligible. Isotopic evidence and SIAR modeling revealed municipal sewage was the dominant contributor to nitrogen pollution. Based on quantitative estimates from the SIAR model, nitrogen source contributions to the Wen-Rui Tang River watershed followed: municipal sewage (40.6 %) ≈ soil nitrogen (39.5 %) > nitrogen fertilizer (9.7 %) > atmospheric deposition (2.8 %) during wet season; and municipal sewage (59.1 %) > soil nitrogen (30.4 %) > nitrogen fertilizer (4.1 %) > atmospheric deposition (1.0 %) during dry season. This study provides a deeper understanding of nitrogen dynamics in eutrophic coastal-plain river networks, which informs strategies for efficient control and remediation of riverine nitrogen pollution.

Implication of self-organizing map, stable isotopes combined with MixSIAR model for accurate nitrogen control in a well-protected reservoir

Nitrogen pollution and eutrophication in reservoirs is a global environmental geochemical concern. Occasional algal blooms still exist in reservoirs that have undergone pollution treatment. The lack of quantitative evidence of nitrogen sources and fate limits long-term stable ecological safety management. This work applied an approach integrated zonal mapping, stable isotopes (δ18OH2O, δ15Nnitrate, δ18Onitrate, and δ13C-DIC) and a Bayesian isotope model to analyze regional and seasonal differences in the contribution and sources of nitrogen to a well-protected reservoir. The values of δ18Onitrate and the positive relationship between NO3- and δ13C-DIC suggested that nitrification was the primary NO3- production in the rivers. While Denitrification was present at only a few sites. Results of the MixSIAR model coupled the NO3-/Cl- indicator revealed that the domestic sewage contributed high riverine NO3- loading (68.6 ± 10.6 %) in the dry season. In the wet season, the main nitrate sources of upper watershed were ammonia and carbamide fertilizers (47.5 % and 40.3 %). While the domestic sewage was still the major contributor of downstream region (a dense residential area), indicating possible problems with rainwater and sewage drainage networks. The results implied that the colleting and treatment of sewages were the priority in downstream region, and non-point source pollution control and wastewater treatment plant upgrading were essential to control nitrate pollution in the two upstream regions. These findings provide new insights into precise nitrogen pollution traceability and identification of treatment priorities in the sub-region, and promote the management other well-protected watershed in similar need of further nitrogen contamination control.

Groundwater hydrochemical signatures, nitrate sources, and potential health risks in a typical karst catchment of North China using hydrochemistry and multiple stable isotopes

Nitrate pollution in aquatic ecosystems has received growing concern, particularly in fragile karst basins. In this study, hydrochemical compositions, multiple stable isotopes (δ2H-H2O, δ18Ο-Η2Ο, δ15Ν-ΝΟ3-, and δ18Ο-ΝΟ3-), and Bayesian stable isotope mixing model (MixSIAR) were applied to elucidate nitrate pollution sources in groundwater of the Yangzhuang Basin. The Durov diagram identified the dominant groundwater chemical face as Ca-HCO3 type. The NO3- concentration ranged from 10.89 to 90.45 mg/L (average 47.34 mg/L), showing an increasing trend from the upstream forest and grassland to the downstream agricultural dominant area. It is worth noting that 47.2% of groundwater samples exceeded the NO3- threshold value of 50 mg/L for drinking water recommended by the World Health Organization. The relationship between NO3-/Cl- and Cl- ratios suggested that most groundwater samples were located in nitrate mixed endmember from agricultural input, soil organic nitrogen, and manure & sewage. The Self-Organizing Map (SOM) and Pearson correlations analysis further indicated that the application of calcium fertilizer, sodium fertilizer, and livestock and poultry excrement in farmland elevated NO3- level in groundwater. The output results of the MixSIAR model showed that the primary sources of NO3- in groundwater were soil organic nitrogen (55.3%), followed by chemical fertilizers (28.5%), sewage & manure (12.7%), and atmospheric deposition (3.4%). Microbial nitrification was a dominant nitrogen conversion pathway elevating NO3- levels in groundwater, while the denitrification can be neglectable across the study area. The human health risk assessment (HHRA) model identified that about 88.9%, 77.8%, 72.2%, and 50.0% of groundwater samples posing nitrate's non-carcinogenic health hazards (HQ > 1) through oral intake for infants, children, females, and males, respectively. The findings of this study can offer useful biogeochemical information on nitrogen pollution in karst groundwater to support sustainable groundwater management in similar human-affected karst regions.

Riverine nitrate source identification combining δ15N/δ18O-NO3- with Δ17O-NO3- and a nitrification 15N-enrichment factor in a drinking water source region

Dual nitrate isotopes (δ15N/δ18O-NO3-) are an effective tool for tracing nitrate sources in freshwater systems worldwide. However, the initial δ15N/δ18O values of different nitrate sources might be altered by isotopic fractionation during nitrification, thereby limiting the efficiency of source apportionment results. This study integrated hydrochemical parameters, site-specific isotopic compositions of potential nitrate sources, multiple stable isotopes (δD/δ18O-H2O, δ15N/δ18O-NO3- and Δ17O-NO3-), soil incubation experiments assessing the nitrification 15N-enrichment factor (εN), and a Bayesian mixing model (MixSIAR) to reduce/eliminate the influence of 15N/18O-fractionations on nitrate source apportionment. Surface water samples from a typical drinking water source region were collected quarterly (June 2021 to March 2022). Nitrate concentrations ranged from 0.35 to 3.06 mg/L (mean = 0.78 ± 0.46 mg/L), constituting ∼70 % of total nitrogen. A MixSIAR model was developed based on δ15N/δ18O-NO3- values of surface waters and the incorporation of a nitrification εN (-6.9 ± 1.8 ‰). Model source apportionment followed: manure/sewage (46.2 ± 10.7 %) > soil organic nitrogen (32.3 ± 18.5 %) > nitrogen fertilizer (19.7 ± 13.1 %) > atmospheric deposition (1.8 ± 1.6 %). An additional MixSIAR model coupling δ15N/δ18O-NO3- with Δ17O-NO3- and εN was constructed to estimate the potential nitrate source contributions for the June 2021 water samples. Results revealed similar nitrate source contributions (manure/sewage = 43.4 ± 14.1 %, soil organic nitrogen = 29.3 ± 19.4 %, nitrogen fertilizer = 19.8 ± 13.8 %, atmospheric deposition = 7.5 ± 1.6 %) to the original MixSIAR model based on εN and δ15N/δ18O-NO3-. Finally, an uncertainty analysis indicated the MixSIAR model coupling δ15N/δ18O-NO3- with Δ17O-NO3- and εN performed better as it generated lower uncertainties with uncertainty index (UI90) of 0.435 compared with the MixSIAR model based on δ15N/δ18O-NO3- (UI90 = 0.522) and the MixSIAR model based on δ15N/δ18O-NO3- and εN (UI90 = 0.442).

Insights into biogeochemistry and hot spots distribution characteristics of redox-sensitive elements in the hyporheic zone: Transformation mechanisms and contributing factors

Biogeochemical hot spots play a crucial role in the cycling and transport of redox-sensitive elements (RSEs) in the hyporheic zone (HZ). However, the transformation mechanisms of RSEs and patterns of RSEs hot spots in the HZ remain poorly understood. In this study, hydrochemistry and multi-isotope (N/C/S/O) datasets were collected to investigate the transformation mechanisms of RSEs, and explore the distribution characteristics of RSEs transformation hot spots. The results showed that spatial variability in key drivers was evident, while temporal change in RSEs concentration was not significant, except for dissolved organic carbon. Bacterial sulfate reduction (BSR) was the primary biogeochemical process for sulfate and occurred throughout the area. Ammonium enrichment was mainly caused by the mineralization of nitrogenous organic matter and anthropogenic inputs, with adsorption serving as the primary attenuation mechanism. Carbon dynamics were influenced by various biogeochemical processes, with dissolved organic carbon mainly derived from C3 plants and dissolved inorganic carbon from weathering of carbonate rocks and decomposition of organic matter. The peak contribution of dissolved organic carbon decomposition to the DIC pool was 46.44 %. The concentration thresholds for the ammonium enrichment and BSR hot spots were identified as 1.5 mg/L and 8.84 mg/L, respectively. The distribution pattern of RSEs hot spots was closely related to the hydrogeological conditions. Our findings reveal the complex evolution mechanisms and hot spots distribution characteristics of RSEs in the HZ, providing a basis for the safe utilization and protection of groundwater resources.

Identification of groundwater nitrate sources in an urban aquifer (Alborz Province, Iran) using a multi-parameter approach

High concentrations of NO3̄ in water resources are detrimental to both human health and aquatic ecosystems. Identification of NO3̄ sources and biogeochemical processes is a crucial step in managing and controlling NO3̄ pollution. In this study, land use, hydrochemical data, dual stable isotopic ratios and Bayesian Stable Isotope Mixing Models (BSIMM) were integrated to identify NO3̄ sources and estimate their proportional contributions to the contamination of the Karaj Urban Aquifer (Iran). Elevated NO3̄ concentrations indicated a severe NO3̄ pollution, with 39 and 52% of groundwater (GW) samples displaying the concentrations of NO3̄ in exceedance of the World Health Organization (WHO) standard of 50 mg NO3̄ L-1 in the rainy and dry seasons, respectively. Dual stable isotopes inferred that urban sewage is the main NO3̄ source in the Karaj Plain. The diagram of NO3̄/Cl‾ versus Cl‾ confirmed that municipal sewage is the major source of NO3̄. Results also showed that biogeochemical nitrogen dynamics are mainly influenced by nitrification, while denitrification is minimal. The BSIMM model suggested that NO3̄ originated predominantly from urban sewage (78.2%), followed by soil organic nitrogen (12.2%), and chemical fertilizer (9.5%) in the dry season. In the wet season, the relative contributions of urban sewage, soil nitrogen and chemical fertilizer were 87.5, 6.7, and 5.5%, respectively. The sensitivity analysis for the BSIMM modeling indicates that the isotopic signatures of sewage had the major impact on the overall GW NO3̄ source apportionment. The findings provide important insights for local authorities to support effective and sustainable GW resources management in the Karaj Urban Aquifer. It also demonstrates that employing Bayesian models combined with multi-parameters can improve the accuracy of NO3̄ source identification.

Nitrate prediction in groundwater of data scarce regions: The futuristic fresh-water management outlook

Nitrate contamination in groundwater poses a significant threat to water quality and public health, especially in regions with limited data availability. This study addresses this challenge by employing machine learning (ML) techniques to predict nitrate (NO3--N) concentrations in Mexico's groundwater. Four ML algorithms-Extreme Gradient Boosting (XGB), Boosted Regression Trees (BRT), Random Forest (RF), and Support Vector Machines (SVM)-were executed to model NO3--N concentrations across the country. Despite data limitations, the ML models achieved robust predictive performances. XGB and BRT algorithms demonstrated superior accuracy (0.80 and 0.78, respectively). Notably, this was achieved using ∼10 times less information than previous large-scale assessments. The novelty lies in the first-ever implementation of the 'Support Points-based Split Approach' during data pre-processing. The models considered initially 68 covariates and identified 13-19 significant predictors of NO3--N concentration spanning from climate, geomorphology, soil, hydrogeology, and human factors. Rainfall, elevation, and slope emerged as key predictors. A validation incorporated nationwide waste disposal sites, yielding an encouraging correlation. Spatial risk mapping unveiled significant pollution hotspots across Mexico. Regions with elevated NO3--N concentrations (>10 mg/L) were identified, particularly in the north-central and northeast parts of the country, associated with agricultural and industrial activities. Approximately 21 million people, accounting for 10 % of Mexico's population, are potentially exposed to elevated NO3--N levels in groundwater. Moreover, the NO3--N hotspots align with reported NO3--N health implications such as gastric and colorectal cancer. This study not only demonstrates the potential of ML in data-scarce regions but also offers actionable insights for policy and management strategies. Our research underscores the urgency of implementing sustainable agricultural practices and comprehensive domestic waste management measures to mitigate NO3--N contamination. Moreover, it advocates for the establishment of effective policies based on real-time monitoring and collaboration among stakeholders.

Identification and apportionment of groundwater nitrate sources in Chakari Plain (Afghanistan)

The Chakari alluvial aquifer is the primary source of water for human, animal, and irrigation applications. In this study, the geochemistry of major ions and stable isotope ratios (δ2H-H2O, δ18O-H2O, δ15N-NO3̄, and δ18O-NO3̄) of groundwater and river water samples from the Chakari Plain were analyzed to better understand characteristics of nitrate. Herein, we employed nitrate isotopic ratios and BSIMM modeling to quantify the proportional contributions of major sources of nitrate pollution in the Chakari Plain. The cross-plot diagram of δ15N-NO3̄ against δ18O-NO3̄ suggests that manure and sewage are the main source of nitrate in the plain. Nitrification is the primary biogeochemical process, whereas denitrification did not have a significant influence on biogeochemical nitrogen dynamics in the plain. The results of this study revealed that the natural attenuation of nitrate in groundwater of Chakari aquifer is negligible. The BSIMM results indicate that nitrate originated mainly from sewage and manure (S&M, 75‰), followed by soil nitrogen (SN, 13‰), and chemical fertilizers (CF, 9.5‰). Large uncertainties were shown in the UI90 values for S&M (0.6) and SN (0.47), whereas moderate uncertainty was exhibited in the UI90 value for CF (0.29). The findings provide useful insights for decision makers to verify groundwater pollution and develop a sustainable groundwater management strategy.

Toxic effects of combined exposure to cadmium and nitrate on intestinal morphology, immune response, and microbiota in juvenile Japanese flounder (Paralichthys olivaceus)

Cadmium (Cd2+) and nitrate (NO3-) are important environmental pollutants in the offshore marine ecological environment. However, limited research has explored their combined effects, particularly regarding their impact on the microbiota and intestinal health of marine fish. In this study, juvenile Japanese flounders (P. olivaceus) were immersed in seawater samples with different combinations of Cd2+ (0, 0.2, and 2 mg/L) and NO3- (0 and 80 mg/L NO3N) for 30 days to explore their toxic impacts on intestinal morphology, tight junction (TJ) barrier, immune response, and microbiota. Our results showed that Cd2+ or NO3- exposure alone led to histopathological damage of the gut, while their co-exposure aggravated intestinal damage. Moreover, co-exposure substantially decreased TJ-related gene expression, including occludin, claudin-10, and ZO-2, suggesting increased TJ permeability in the gut. Regarding the immune response, we observed upregulated expression of immune-related markers such as HSP40, IL-1β, TNF-α, and MT, suggesting the onset of intestinal inflammation. Furthermore, Cd2+ and NO3- exposure led to changes in intestinal microflora, characterized by decreased the abundance of Sediminibacterium and NS3a_marine_group while increasing the prevalence of pathogens or opportunistic pathogens such as Ralstonia, Proteus, and Staphylococcus. This alteration in microbiota composition increased network complexity and α-diversity, ultimately causing dysbiosis in the fish gut. Additionally, combined exposure resulted in metabolic disorders that affected the predicted functions of the intestinal microbiota. Overall, our study demonstrates that Cd2+-NO3- co-exposure amplifies the deleterious effects compared to single exposure. These findings enhance our understanding of the ecological risks posed by Cd2+-NO3- co-exposure in marine ecosystems.

Integrated clustering analysis for delineating seawater intrusion and heavy metals in Arabian Gulf Coastal groundwater of Saudi Arabia

The intrusion of seawater (SWI) into coastal aquifers is a major concern worldwide, affecting the quantity and quality of groundwater resources. The region of Saudi Arabia that lies along the eastern coast has been affected by SWI, making it crucial to accurately identify and monitor the affected areas. This investigation aimed to map the degree of seawater intrusion in a complex aquifer system in the study area using an integrated clustering analysis approach. The study collected 41 groundwater samples from wells penetrating multi-layered aquifers, and the samples were analyzed for physicochemical properties and major ions. Clustering analysis methods, including Hierarchical Clustering Analysis (double-clustering) (HCA-DC), K-mean (KMC), and fuzzy k-mean clustering (FKM), were employed to evaluate the spatial distribution and association of the groundwater properties. The results revealed that the analyzed GW samples were divided into four clusters with varying degrees of SWI. Clusters A, B, C, and D contained GW samples with very low (fsea of 1.9%), high (fsea of 14.9%), intermediate (fsea of 7.9%), and low (fsea of 5.2%) degrees of SWI, respectively. FKM clustering exhibited superior performance with a silhouette score of 0.83. Additionally, the study found a direct correlation between the degree of SWI and increased concentrations of boron, strontium, and iron, demonstrating SWI's impact on heavy metal levels. Notably, the boron concentration in cluster B, which endured high SWI, exceeded WHO guidelines. The study demonstrates the value of clustering analysis for accurately monitoring SWI and associated heavy metals. The findings can guide policies to mitigate SWI impacts and benefit groundwater-dependent communities. Further research can help develop effective strategies to mitigate SWI effects on groundwater quality and availability.

An appraisal to hydrochemical characterization, source identification, and potential health risks of sulfate and nitrate in groundwater of Bemetara district, Central India

Gypsum-enriched aquifers (GEA) and intensive agriculture regions (IAR) in semi-arid regions are responsible for very high amounts of sulfate and nitrate in many groundwater systems of the world, respectively. However, in such regions, the problem of nitrate pollution and its associated health risk has been increasing and emerging as a global issue. However, along with nitrate, sulfate contamination and its potential health risks are often neglected worldwide in these regions. Therefore, considering sulfate along with nitrate as a significant threat to water quality in such regions, this study aimed to characterize hydrochemistry, factors controlling groundwater quality, and assessment of risk to human health. To accomplish this objective, 116 groundwater samples were collected over pre-monsoon (PRM) and post-monsoon (POM) (2019) seasons in Bemetara district. As per Bureau of Indian standards (BIS) for drinking, SO42- (28 and 19%) and NO3- (7 and 35%) exceeded the permissible limits in PRM and POM seasons, respectively; thereby, groundwater was not suitable for drinking. SO42- and NO3- pollution sources were identified and mainly attributed to gypsum dissolution and agricultural activities as well as domestic sewage discharge, respectively. In addition, SO42-and NO3- risk assessment results show that total 20% to 46% of all samples surpassed the permissible limit (HQ = 1) of risk to children and adults, over both seasons. To ensure drinking water security in this region, sustainable management of agricultural activities and treatment should be done to reduce the potential health risks due to SO42- and NO3-.

Treated wastewater and weak removal mechanisms enhance nitrate pollution in metropolitan rivers

The focus of urban water environment renovation has shifted to high nitrate (NO3-) load. Nitrate input and nitrogen conversion are responsible for the continuous increase in nitrate levels in urban rivers. This study utilized nitrate stable isotopes (δ15N-NO3- and δ18O-NO3-) to investigate NO3- sources and transformation processes in Suzhou Creek, located in Shanghai. The results demonstrated that NO3- was the most common form of dissolved inorganic nitrogen (DIN), accounting for 66 ± 14% of total DIN with a mean value of 1.86 ± 0.85 mg L-1. The δ15N-NO3- and δ18O-NO3- values ranged from 5.72 to 12.42‰ (mean value: 8.38 ± 1.54‰) and -5.01 to 10.39‰ (mean value: 0.58 ± 1.76‰), respectively. Based on isotopic evidence, the river received a significant amount of nitrate through direct exogenous input and sewage ammonium nitrification, while nitrate removal (denitrification) was insignificant, resulting in nitrate accumulation. Analysis using the MixSIAR model revealed that treated wastewater (68.3 ± 9.7%), soil nitrogen (15.7 ± 4.8%) and nitrogen fertilizer (15.5 ± 4.9%) were the main sources of NO3- in rivers. Despite the fact that Shanghai's urban domestic sewage recovery rate has reached 92%, reducing nitrate concentrations in treated wastewater is crucial for addressing nitrogen pollution in urban rivers. Additional efforts are needed to upgrade urban sewage treatment during low flow periods and/or in the main stream, and to control non-point sources of nitrate, such as soil nitrogen and nitrogen fertilizer, during high flow periods and/or tributaries. This research provides insights into NO3- sources and transformations, and serves as a scientific basis for controlling NO3- in urban rivers.

Nitrogen sources and conversion processes in shallow groundwater around a plain lake (Northwest China): Evidenced by multiple isotopes and water chemistry

The groundwater quality is severely impacted by Nitrate (NO₃^--N) pollution worldwide. Effective lake quality management depends on understanding the origin and fate of nitrogen (N) in the groundwater around lakes. This study combined data for multiple stable isotopes (δ²H-H₂O and δ¹⁸O-H₂O, δ¹⁵N-NO₃ and δ¹⁸O-NO₃) and hydrochemistry with the hydrodynamic monitoring profile and a Bayesian isotope mixing (MixSIAR) model to clarify the sources and transformation of N within shallow groundwater around Shahu Lake in the arid area plain of Northwest China. In May 2022, multiple water samples were collected from aquifers (n = 33), drainage water (n = 1), channel water (n = 1), and lake water (n = 7). The results showed that 57% of groundwater samples had high NO₃^--N concentrations exceeding the World Health Organisation threshold for drinking water (10 mg/L). The high variation in δ¹⁵N-NO₃ (from -9.21‰ to +27.57‰) and δ¹⁸O-NO₃ (from -8.32‰ to +19.04‰) revealed multiple N sources and conversion processes. According to nitrate isotopes and the MixSIAR model, N fertilizer, soil organic N and manure, and sewage are the main sources of nitrogen in groundwater and lake water, which account for 40.61%, 35.86%, and 21.55% of groundwater NO₃^--N, respectively, and 35.07%, 34.43%, and 27.49% of lake water NO₃^--N. Hydrodynamic monitoring combined with water isotopes showed that upper groundwater (5-10 m) within 1.22 km of the adjacent lake shore strongly interacted with the lake. In groundwater, nitrification predominated, while local denitrification remained a possibility. In conclusion, this research offers a comprehensive approach to determining the sources and conversion of N in contaminated groundwater.

Self-organizing map algorithm for assessing spatial and temporal patterns of pollutants in environmental compartments: A review

The evaluation of the spatial and temporal distribution of pollutants is a crucial issue to assess the anthropogenic burden on the environment. Numerous chemometric approaches are available for data exploration and they have been applied for environmental health assessment purposes. Among the unsupervised methods, Self-Organizing Map (SOM) is an artificial neural network able to handle non-linear problems that can be used for exploratory data analysis, pattern recognition, and variable relationship assessment. Much more interpretation ability is gained when the SOM-based model is merged with clustering algorithms. This review comprises: (i) a description of the algorithm operation principle with a focus on the key parameters used for the SOM initialization; (ii) a description of the SOM output features and how they can be used for data mining; (iii) a list of available software tools for performing calculations; (iv) an overview of the SOM application for obtaining spatial and temporal pollution patterns in the environmental compartments with focus on model training and result visualization; (v) advice on reporting SOM model details in a paper to attain comparability and reproducibility among published papers as well as advice for extracting valuable information from the model results is presented.

Nitrate with enriched heavy oxygen isotope linked to changes in nitrogen source and transformation as groundwater table rises

Nitrate is a significant constituent of the total nitrogen pool in shallow aquifers and poses an escalating threat to groundwater resources, making it crucial to comprehend the source, conversion, and elimination of nitrogen using appropriate techniques. Although dual-isotope dynamics in nitrate have been widely used, uncertainties remain regarding the asynchronously temporal changes in δ¹⁸O-NO₃^- and δ¹⁵N-NO₃^- observed in hypoxic aquifers. This study aimed to investigate changes in nitrogen sources and transformations using temporal changes in field-based NO₃^- isotopic composition, hydro-chemical variables, and environmental DNA profiling, as the groundwater table varied. The results showed that the larger enrichment in δ¹⁸O-NO₃^- (+13‰) compared with δ¹⁵N-NO₃^- (-2‰) on average during groundwater table rise was due to a combination of factors, including high ¹⁸O-based atmospheric N deposition, canopies nitrification, and soil nitrification transported vertically by rainfalls, and ¹⁸O-enriched O₂ produced through microbial and root respiration within denitrification. The strong association between functional gene abundance and nitrogen-related indicators suggests that anammox was actively processed with nitrification but in small bacterial population during groundwater table rise. Furthermore, bacterial species associated with nitrogen-associated gradients provided insight into subsurface nitrogen transformation, with Burkholderiaceae species and Pseudorhodobacter potentially serving as bioindicators of denitrification, while Candidatus Nitrotogn represents soil nitrification. Fluctuating groundwater tables can cause shifts in hydro-chemical and isotopic composition, which in turn can indicate changes in nitrogen sources and transformations. These changes can be used to improve input sources for mixture models and aid in microbial remediation of nitrate.

Facile degradation of chitosan-sodium alginate-chromium (III) gel in relation to leather re-tanning and filling

Natural polysaccharide hydrogel, exemplified by chitosan‑sodium alginate (CS-SA), has been prevailing in adsorption of chromium (III) (Cr(III)) containing contaminant. However, the traditional desorption of CS-SA-Cr(III) to recycle the adsorbent faces the problems including chemical desorbents secondary pollution, resource waste of the terminal CS-SA adsorbents, and tedious work of reusing the desorbed Cr(III). Herein, the adsorption product, CS-SA-Cr(III) gel, was degraded to CS/SA/Cr(III) sol and applied in leather re-tanning and filling processes directly. To achieve this goal, three degradation methods were used to transform the gel to sol. Due to the excellent overall performance of the CS/SA/Cr(III)-HMD₄ sol (obtained by the hydrothermal-mechanical degradation method for 4 h (HMD₄)), including wide size and distribution range, moderate viscosity (54 ± 3.1 mPa·s), high electronegativity (-38.6 ± 5.8 mV), and good stability, the resultant leather after re-tanning and filling by the sol achieved fascinating properties such as good thermal stability (T_s, 116.8 ± 1.8 °C; T_d, 94.2 ± 1.7 °C), mechanical performance (tensile strength, 6.9 ± 0.52 MPa; elongation at break, 95 ± 3.0 %), and superduper thickening rate (31.8 %). Moreover, the mechanism of good re-tanning and filling effects was deciphered. Therefore, this work intends to overcome the limitation of traditional desorption technology and further realizes the high-valued application of the exhausted CS-SA-Cr(III) in leather re-tanning and filling processes.

Seawater intrusion alters nitrogen cycling patterns through hydrodynamic behavior and biochemical reactions: Based on Bayesian isotope mixing model and microbial functional network

Seawater intrusion is a global coastal environmental issue of great concern and significantly impacts the regional biogeochemical environment and material cycles, including nitrogen cycling. To reveal the mechanism of seawater intrusion altering nitrogen cycling patterns through hydrodynamic behavior and biochemical reactions, the Bayesian mixing model (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-) and 16S rDNA gene amplicon sequencing are used to establish nitrogen cycling pathways and microbial functional network. The results show that the nitrate in the coastal groundwater is from manure and septic waste (M&S, over 44 %), soil organic nitrogen (SON, over 20 %), and nitrogen fertilizer (FN, over 16 %). The hydrological interaction has promoted the coupling between material cycling and microbial community in the coastal groundwater systems. Among them, precipitation infiltration has caused the gradual decrease of specific microbes along the flow direction, such as Lactobacillus, Acinetobacter, Bifidobacterium, etc. And seawater intrusion has caused the mutations of specific microbes (Planktomarina, Clade_Ia, Wenyingzhuangia, Glaciecola, etc.) and convergence of microbial community at the salt-freshwater interface in the aquifer. In the coastal intruded aquifer systems, the nitrogen cycling pattern can be divided into oxidation and reduction processes. The oxidation process involves the enhancement of nitrification while the weakening of denitrification and anammox with the increase of aquifer depth. The reduction process consists of the enhancement of denitrification and anammox while the erosion of nitrification and ammonification with increased seawater intrusion. In addition, seawater intrusion can mitigate nitrate contamination by promoting denitrification and anammox in coastal areas.

Estimation of nutrient sources and fate in groundwater near a large weir-regulated river using multiple isotopes and microbial signatures

The excessive input of nutrients into groundwater can accelerate eutrophication in associated surface water systems. This study combined hydrogeochemistry, multi isotope tracers, and microbiological data to estimate nutrient sources and the effects of groundwater-surface water interactions on the spatiotemporal variation of nutrients in groundwater connected to a large weir-regulated river in South Korea. δ11B and δ15N-NO3- values, in combination with a Bayesian mixing model, revealed that manure and sewage contributed 40 % and 25 % respectively to groundwater nitrate, and 42 % and 27 % to nitrate in surface water during the wet season. In the dry season, the source apportionment was similar for groundwater while the sewage contribution increased to 52 % of nitrate in river water. River water displayed a high correlation between NO3- concentration and cyanobacteria (Microcystis and Prochlorococcus) in the wet season. The mixing model using multiple isotopes indicated that manure-derived nutrients delivered with increased contributions of groundwater to the river during the wet season governed the occurrence of cyanobacterial blooms in the river. We postulate that the integrated approach using multi-isotopic and microbiological data is highly effective for evaluating nutrient sources and for delineating hydrological interactions between groundwater and surface water, as well as for investigating surface water quality including eutrophication in riverine and other surface water systems.

Seawater intrusion pattern recognition supported by unsupervised learning: A systematic review and application

Seawater intrusion is among the world's leading causes of groundwater contamination, as salty water can affect potable water access, food production, and ecosystem functions. To explore such contamination sources, multivariate analysis supported by unsupervised learning tools has been used for decades to aid in water resource pattern recognition, clustering, and water quality data variability characterization. This study proposes a systematic review of these techniques applied for supporting seawater intrusion identification based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and subsequent bibliometric analysis of 102 coastal hydrogeological studies. The most relevant identified methods, including principal components analysis (PCA), hierarchical clustering analysis, K-means clustering, and self-organizing maps, are explained and applied to a case study. Although 74 % of the studies that applied dimensional reduction methods, such as PCA, associated most of the database variance with the salinization process, 77 % of the studies that applied clustering methods associated at least one water sample cluster with the influence of seawater intrusion. Based on the review and a practical demonstration using the open-source R software platform, recommendations are made regarding data preprocessing, research opportunities, and publishing information necessary to replicate and validate the studies.

Spatial variability of source contributions to nitrate in regional groundwater based on the positive matrix factorization and Bayesian model

Groundwater nitrate (NO₃^-) pollution has attracted widespread attention; however, accurately evaluating the sources of NO₃^- and their contribution patterns in regional groundwater is difficult in areas with multiple sources and complex hydrogeological conditions. In this study, 161 groundwater samples were collected from the Poyang Lake Basin for hydrochemical and dual NO₃^- isotope analyses to explore the sources of NO₃^- and their spatial contribution using the Positive Matrix Factorization (PMF) and Bayesian stable isotope mixing (MixSIAR) models. The results revealed that the enrichment of NO₃^- in groundwater was primarily attributed to sewage/manure (SM), which accounted for more than 50 %. The contributions of nitrogen fertilizer and soil organic nitrogen should also be considered. Groundwater NO₃^- sources showed obvious spatial differences in contributions. Regions with large contributions of SM (>90 %) were located in the southeastern part of the study area and downstream of Nanchang, which are areas with relatively high population density. Nitrogen fertilizer and soil organic nitrogen showed concentrated contributions in paddy soil in the lower reaches of the Gan and Rao Rivers, and these accumulations were mainly driven by the soil type, land use type, and topography. This study provides insight into groundwater NO₃^- contamination on a regional scale.

Combining metal and sulfate isotopes measurements to identify different anthropogenic impacts on dissolved heavy metals levels in river water

Dissolved heavy metals (DHMs) contamination has raised global concern for ecological and human health development. Weathering of sulfide-bearing ore metals can produce acidic, sulfate-rich solutions in the presence of water and oxygen (O₂), and DHMs are released to deprave the river water quality. Sulfur and oxygen isotope signatures (δ³⁴S_SO4 and δ¹⁸O_SO4) could identify this pyrite-derived sulfate; however, it is yet not well known whether the δ³⁴S_SO4 and δ¹⁸O_SO4 values could limit the DHMs sources and illustrate anthropogenic impacts on DHMs along the river corridor. We tried to solve this problem through field works in the Luohe River and Yihe River, two tributaries of the Yellow River, China, where metal sulfide mine activities mostly occurred upstream, but agricultural and domestic behaviors concentrated in the lower plain reaches. In the Luohe River upper areas, δ³⁴S_SO4 values had negative correlations with concentrations of cadmium (Cd) (p < 0.01), nickel (Ni) (p < 0.05), molybdenum (Mo) (p < 0.01), uranium (U) (p < 0.01), and SO₄^2- (p < 0.01). However, as the δ³⁴S_SO4 values increased downstream in the Luohe River, concentrations of copper (Cu) (p < 0.05), mercury (Hg) (p < 0.05), Ni (p < 0.05), and SO₄^2- (p < 0.01) simultaneously elevated. The Bayesian Isotope Mixing Model (BIMM) results via δ³⁴S_SO4 values demonstrated 64.3%-65.3% of SO₄^2- from acid mine drainage (AMD) in the Luohe River's upper reaches and 63.5%-67.7% in the Yihe River's upper reaches, and about 33% from sewage and industrial effluents in the Luohe River's lower reaches and 27% in Yihe River's lower reaches. Our results confirmed the different anthropogenic impacts on the DHMs concentrations in Luohe River and Yihe River and provided a robust method for DHMs sources appointment and pollution management in river systems.

Quantitative identification of nitrate and sulfate sources of a multiple land-use area impacted by mine drainage

The rapid increase in urbanization and intensive coal mining activities have accelerated the deterioration of surface water quality. Environmental problems caused by the accumulation of nitrate and sulfate from natural, urban, and agricultural sources have attracted extensive attention. Information on nitrate and sulfate sources and their transformations is crucial for understanding the nitrogen and sulfur cycles in surface water. In this study, we monitored nitrate and sulfate in three representative rivers in mining cities in northern China. The main pollution sources and biogeochemical processes were identified by using stable isotopes (δD, δ¹⁸O_H2O, δ¹⁵N, δ¹⁸O_NO3, δ³⁴S and δ¹⁸O_SO4) and hydrochemistry. The contribution of natural and anthropogenic sources was quantitatively estimated based on a Bayesian mixed model. The results indicated a large variation in sulfate and nitrate sources between the different rivers. Nitrate in the Tuohe River mainly derived from manure/sewage (57.9%) and soil N (26.9%), while sulfate mainly derived from manure/sewage (41.7%) and evaporite dissolution (26.8%). For the Suihe River, nitrate was primarily sourced from chemical fertilizer (37.9%) and soil nitrogen (34.8%), while sulfate was mainly sourced from manure/sewage (33.1%) and chemical fertilizer (21.4%). For the Huihe River, nitrate mainly derived from mine drainage (56.6%) and manure/sewage (30.6%), while sulfate predominantly originated from mine drainage (58.3%) and evaporite dissolution (12.9%). Microbial nitrification was the major pathway for the migration and transformation of nitrate in the surface water. However, denitrification and bacterial sulfate reduction (BSR) did not play a significant role as aerobic conditions prevailed. In this study, we elucidated the sources and transformation mechanisms of nitrate and sulfate. Additionally, we provided a reference for formulating a comprehensive strategy for effective management and remediation of surface water contaminated with nitrate and sulfate in mining cities.

Determination of the Acute and Chronic Toxicity of Sulfate from the Sulfur Autotrophic Denitrification Process to Juvenile Zebrafish (Danio rerio)

Sulfur-based materials are widely used as electron donors for denitrification to enhance nitrogen removal from water. This leads to an increased sulfate concentration in the effluent or sulfate accumulation in recirculating aquaculture systems. This study explored acute and chronic toxicity of sulfate to juvenile zebrafish (Danio rerio) and investigated the histopathological changes in the gills of juvenile zebrafish exposed to sulfate. Results show that zebrafish had a high tolerance to sulfate, with no acute toxicity at sulfate concentrations from 250 to 3200 mg/L. For the chronic toxicity study, it was found that zebrafish mortality decreased with the increase in sulfate concentrations ranging from 250 to 1500 mg/L. In contrast, when the sulfate concentration was 1500-3000 mg/L, zebrafish mortality increased with the increasing sulfate concentration. In addition, in the ion balance test, KCl was added to balance the effects of Na⁺ from the Na₂SO₄ used to obtain the desired sulfate concentrations, showing that fish mortality correspondingly increased with increasing KCl addition. Furthermore, when living in an environment with elevated sulfate concentrations for a long period, changes were observed in the morphology, behavior, and gill tissue of the zebrafish, including slow and lateral swimming; bottom settling; and large opening and closing, lamellar fusion, and necrosis of gills. This research reveals the toxicity of sulfate to aquatic organisms, providing a scientific basis for the promotion and application of sulfur or sulfur-based materials in autotrophic reduction processes for wastewater treatment.

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-SO₄^2- 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 SO₄^2- 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-SO₄^2- varied from 10.6‰ to 26.9‰ and 6.9‰ to 14.1‰, respectively, in the groundwater. Analyses of SO₄^2- and Sr isotopes and water chemistry indicated that SO₄^2- 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 SO₄^2- 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 SO₄^2- were lower. The research results revealed the source of SO₄^2- pollution in shallow groundwater in the coal mine area and provided an important scientific basis for the effective management and protection of groundwater resources.

Isotope evidence for temporal and spatial variations of anthropogenic sulfate input in the Yihe River during the last decade

Pyrite oxidation and sedimentary sulfate dissolution are the primary components of riverine sulfate (SO₄^2-) and are predominant in global SO₄^2- flux into the ocean. However, the proportions of anthropogenic SO₄^2- inputs have been unclear, and their tempo-spatial variations due to human activities have been unknown. Thus, field work was conducted in a spatially heterogeneous human-affected area of the Yihe River Basin (YRB) during a wet year (2010) and drought years (2017/2018). Dual sulfate isotopes (δ³⁴S-SO₄^2- and δ¹⁸O-SO₄^2-) and Bayesian isotope mixing models were used to calculate the variable anthropogenic SO₄^2- inputs and elucidate their temporal impacts on riverine SO₄^2- flux. The results of the mixing models indicated acid mine drainage (AMD) contributions increased from 56.1% to 83.1% of upstream sulfate and slightly decreased from 46.3% to 44.0% of midstream sulfate in 2010 and 2017/2018, respectively, in the Yihe River Basin. The higher upstream contribution was due to extensive metal-sulfide-bearing mine drainage. Sewage-derived SO₄^2- and fertilizer-derived SO₄^2- inputs in the lower reaches had dramatically altered SO₄^2- concentrations and δ³⁴S-SO₄^2- and δ¹⁸O-SO₄^2- values. Due to climate change, the water flow discharge decreased by about 70% between 2010 and 2017/2018, but the riverine sulfate flux was reduced by only about 58%. The non-proportional increases in anthropogenic sulfate inputs led to decreases in the flow-weighted average values of δ³⁴S-SO₄^2- and δ¹⁸O-SO₄^2- from 10.3‰ to 9.9‰ and from 6.1‰ to 4.4‰, respectively. These outcomes confirm that anthropogenic SO₄^2- inputs from acid mine drainage (AMD) have increased, but sewage effluents SO₄^2- inputs have decreased.

Self-organizing map improves understanding on the hydrochemical processes in aquifer systems

The holistic understanding of hydrochemical features is a crucial task for management and protection of water resources. However, it is challenging for a complex region, where multiple factors can cause hydrochemical changes in studied catchment. We collected 208 groundwater samples from such region in Kumamoto, southern Japan to explicitly characterize these processes by applying machine learning technique. The analyzed groundwater chemistry data like major cations and anions were fed to the self-organizing map (SOM) and the results were compared with classical classification approaches like Stiff diagram, standalone cluster analysis and score plots of principal component analysis (PCA). The SOM with integrated application of clustering divided the data into 11 clusters in this complex region. We confirmed that the results provide much greater details for the associated hydrochemical and contamination processes than the traditional approaches, which show quite good correspondence with the recent high resolution hydrological simulation model and aspects from geochemical modeling. However, the careful application of the SOM is necessary for obtaining accurate results. This study tested different normalization approaches for selecting the best SOM map and found that the topographic error (TE) was more important over the quantization error (QE). For instance, the lower QE obtained from min-max and log normalizations showed problems after clustering the SOM map, since the QE did not confirm the topological preservation. In contrast, the lowest TE obtained from Z-transformation data showed better spatial matching of the clusters with relevant hydrochemical characteristics. The results from this study clearly demonstrated that the SOM is a helpful approach for explicit understanding of the hydrochemical processes on reginal scale that may capably facilitate better groundwater resource management.

Multi-isotope tracing nitrate dynamics and sources during thermal stratification in a deep reservoir

Excessive nitrate (NO₃^-) input to reservoirs is a global concern. However, the dynamics and sources of NO₃^- under thermal stratification in deep reservoirs were rarely explored. In this study, multi-stable isotopes (δ¹⁵N/δ¹⁸O-NO₃^-, δ¹⁵N-particulate nitrogen (PN), δ¹⁵N-dissolved total nitrogen (DTN), and δ²H/δ¹⁸O-H₂O) and a Bayesian mixing model were applied to reveal the biogeochemical processes and sources of NO₃^- in a deep reservoir with obvious nitrogen pollution. The results showed that the reservoir was thermally stratified in July while vertically mixed in October. The distribution of δ²H-H₂O suggested that riverine nitrogen migrated to the epilimnion and metalimnion during stratification in the reservoir. In the epilimnion and metalimnion, the significant reduction in NO₃^- concentration was related to the enhancement of assimilation by thermal stratification. Meanwhile, the positive linear correlations between δ¹⁸O-NO₃^- and δ¹⁸O-H₂O suggested that in-reservoir nitrification occurred, with its depth confined above the hypolimnion. In the hypolimnion, denitrification processes were absent due to the aerobic environment. Overall, NO₃^- dynamics were mainly controlled by nitrogen inflow, in-reservoir nitrification, and assimilation during thermal stratification. The results of the Bayesian mixing model showed that manure and sewage, and soil nitrogen were the dominant NO₃^- sources of the reservoir. This study provides new insights and data to help manage and restore deep waters worldwide in tackling a similar situation of nitrogen contamination.

Identifying the characteristics and potential risk of seawater intrusion for southern China by the SBM-DEA model

Seawater intrusion (SWI) seriously affects the economic development of coastal areas in southern China, and understanding its mechanisms is the basis for effective control of SWI. Hydrogeochemical methods and slack-based measurement data envelopment analysis (SBM-DEA) are used to study the characteristics and potential risk of SWI in coastal cities of southern China. Types and distribution of SWI, coastal groundwater evolution, geological-geographic and economic threatens of SWI, potential SWI risk, and environmental management recommendations are explored. The results show that the intrusion areas of Zhejiang and Guangdong account for 94.1 % of the total intrusion area of southern China, and the intrusion degree in Zhejiang is the highest, followed by Guangdong and Fujian. SWI is prone to occur on the sandy and silty coasts of the plain area of southern China; it accelerates the groundwater evolution speed and shortens the evolution path. SBM-DEA can be well applied to evaluate the potential risk of SWI events, and the results indicate a noticeable difference in the environmental performance level of coastal cities in southern China. The low environmental performance level (<0.3) and severe SWI of Taizhou and Zhanjiang indicate that SWI gradually worsens with economic development. In contrast, the high environmental performance level (>0.7) and low SWI of Wenzhou, Fuzhou, Quanzhou, Shantou, and Beihai indicate that the potential risk of SWI is gradually decreasing. Moreover, this study confirms that the environmental Kuznets curve (EKC) phenomenon exists in SWI events for southern China, and SWI-EKC indicates that the urban development of south China is approaching maturity. The specific case of SWI and EPL in coastal cities of south China jointly indicates that optimizing industrial structure, implementing a resources management policy, and improving citizens' environmental awareness are fundamental measures to resolve the contradiction between economic development and environmental problems.

Nitrate pollution source apportionment, uncertainty and sensitivity analysis across a rural-urban river network based on δ15N/δ18O-NO3- isotopes and SIAR modeling

Nitrate pollution is of considerable global concern as a threat to human health and aquatic ecosystems. Nowadays, δ¹⁵N/δ¹⁸O-NO₃^- combined with a Bayesian-based SIAR model are widely used to identify riverine nitrate sources. However, little is known regarding the effect of variations in pollution source isotopic composition on nitrate source contributions. Herein, we used δ¹⁵N/δ¹⁸O-NO₃^-, SIAR modeling, probability statistical analysis and a perturbing method to quantify the contributions and uncertainties of riverine nitrate sources in the Wen-Rui Tang River of China and to further investigate the model sensitivity of each nitrate source. The SIAR model confirmed municipal sewage (MS) as the major nitrate source (58.5-75.7%). Nitrogen fertilizer (NF, 8.6-20.9%) and soil nitrogen (SN, 7.8-20.1%) were also identified as secondary nitrate sources, while atmospheric deposition (AD, <0.1-7.9%) was a minor source. Uncertainties associated with NF (UI₉₀ = 0.32) and SN (UI₉₀ = 0.30) were high, whereas those associated with MS (UI₉₀ = 0.14) were moderate and AD low (UI₉₀ = 0.0087). A sensitivity analysis was performed for the SIAR modeling and indicated that the isotopic composition of the predominant source (i.e., MS in this study) had the strongest effect on the overall riverine nitrate source apportionment results.

Recent advances in the source identification and remediation techniques of nitrate contaminated groundwater: A review

Researchers have long been committed to identify nitrate sources in groundwater and to develop an advanced technique for its remediation because better apply remediation solution and management of water quality is highly dependent on the identification of the NO₃^- sources contamination in water. In this review, we systematically introduce nitrate source tracking tools used over the past ten years including dual isotope and multi isotope techniques, water chemistry profile, Bayesian mixing model, microbial tracers and land use/cover data. These techniques can be combined and exploited to track the source of NO₃^- as mineral or organic fertilizer, sewage, or atmospheric deposition. These available data have significant implications for making an appropriate measures and decisions by water managers. A continuous remediation strategy of groundwater was among the main management strategies that need to be applied in the contaminated area. Nitrate removal from groundwater can be accomplished using either separation or reduction based process. The application of these processes to nitrate removal is discussed in this review and some novel methods were presented for the first time. Moreover, the advantages and limitations of each approach are critically summarized and based on our own understanding of the subject some solutions to overcomes their drawbacks are recommended. Advanced techniques are capable to attain significantly higher nitrate and other co-contaminants removal from groundwater. However, the challenges of by-products generation and high energy consumption need to be addressed in implementing these technologies for groundwater remediation for potable use.

Multi-isotopes revealing the coastal river anthropogenic pollutants and natural material flux to ocean: Sr, C, N, S, and O isotope study

Coastal river exports massive terrestrial materials to the adjacent marine environment with information about chemical weathering, providing critical insights on riverine flux and the potential impact on marine ecosystem. In this study, the preliminary data of dissolved strontium (Sr) and ⁸⁷Sr/⁸⁶Sr in a typical coastal river in southeastern China were collected along with hydrochemistry and C, N, S, and O isotopes to discriminate the source of terrestrial weathering and the riverine flux. Sr concentrations exhibited a range of 0.084 ~ 1.307 μmol L^-1, and ⁸⁷Sr/⁸⁶Sr values ranged 0.7089 ~ 0.7164. The total cationic charge (TZ⁺) ranged 0.2 ~ 11.7 meq L^-1 with the predominant Ca²⁺ which accounted for > 50% of TZ⁺, while the anions were dominated by HCO₃^-. The extremely high Na⁺ and Cl^- near the estuary indicated seawater mixing in such a coastal river. δ¹³C-DIC, δ¹⁵N-NO₃^-, δ¹⁸O-NO₃^-, and δ³⁴S-SO₄^2- of river water ranged - 24.1‰ ~  - 9.2‰, 0.3‰ ~ 22.7‰, - 2.1‰ ~ 21.4‰, and - 9.3‰ ~ 18.0‰, respectively. δ¹³C enhanced correspondingly to decreased δ³⁴S, confirming the attendance of H₂SO₄ in carbonate weathering. Most δ¹⁸O values exhibited within ± 10‰, indicating the dominant nitrification process. δ¹⁵N presented slightly negative relationship with δ¹³C and no obvious correlation with δ³⁴S, indicating relatively limited impact of denitrification. The depleted δ¹³C and δ¹⁵N may be attributed to carbonate dissolution with nitric acids and the oxidation of organic matters into C and N pools. Quantitative analysis revealed that silicate weathering accounts for 79% of total dissolved Sr, indicating the dominant weathering process. The estimated monthly flux of dissolved Sr to the East China Sea was 138.1 tons, demonstrating an potential impact on seawater Sr isotope evolution. Overall, the investigations of multi-isotopes revealed the enhancement of weathering rates and the consequently depleted CO₂ consumption, which further proved the involvement of strong acids (H₂SO₄ and HNO₃). This study provides scientific insight in terrestrial weathering and anthropogenic impact of a typical coastal watershed and may orient the management of environmental issues related to coastal ecosystems.

Source identification and apportionment of the nitrogen in groundwater based on isotope methods in the Beilin region of Suihua basin, northeastern China

Multi-isotope method was used to analyze the migration and transformation characteristics of nitrogen in groundwater in the center of a typical confined water basin, and a simplified isotope mixing model was established to quantify the contribution of potential nitrate sources in the center of the basin. Based on the water quality monitoring results, the contour map of nitrate concentration in groundwater in the center of the basin was drawn. The results showed that the nitrate concentration in groundwater in the center of the basin increased gradually from upstream to downstream. The high value area of nitrate concentration in phreatic water is mainly affected by agricultural activities and infiltration of sewage discharge from upstream urban areas. The high value area of nitrate concentration in confined water is mainly due to the water level depression funnel caused by large exploitation of confined water. The quantitative results of N-O isotope mixing model for potential nitrate sources show that the main recharge sources of groundwater in the center of the basin are atmospheric precipitation, agricultural irrigation water, and the lateral inflow of upstream groundwater. Agricultural irrigation water has the highest contribution rate of 67.01%. The main recharge sources of confined aquifer in the center of the basin are phreatic water leakage and lateral inflow of upstream confined water. The contribution rate of upstream confined water is between 45.55% and 56.35%, which is basically maintained at about 50%. Compared with the calculation results of D-O isotope mixing model, the accuracy of the established N-O isotope mixing model meets the basic requirements. The results of this study can provide technical reference and theoretical support for the identification and quantitative research of potential nitrate sources in groundwater under the same type of hydrogeological conditions. PRACTITIONER POINTS: Multiple isotope fingerprint comparison to identify nitrate source contribution ratio. Migration and transformation of nitrogen in the center of a typical confined water basin Simplified the traditional isotope mixing model to quickly quantify the source of contamination.

Delineating the origins and processes of groundwater salinization and quality degradation in a coastal irrigated plain, Korba (Northeastern Tunisia)

From 2006 to 2020, groundwater investigations were conducted in the Korba coastal aquifer in northern Tunisia along two flow paths (transects S1 and S2), perpendicular to the shoreline. Groundwater sampling, hydrodynamic monitoring, and electrical tomography imaging were performed in situ. Geochemical analysis (Ionic ratios, ionic deltas, conventional diagrams, and stable isotopes) and modelling using PHREEQC, and multivariate statistical analysis were applied. The objective was to identify the potential origin of groundwater salinization (i.e., high TDS and NO₃) and to study associated processes. The groundwater flow inversion was corroborated by the piezometric survey in transect S1, where a piezometric depression of 5 m was detected at 4000 m from the seashore. Seawater intrusion and agricultural contamination, mainly through N-fertilizers, both contribute to groundwater mineralization and consequently salinization, according to PCA analysis. The impacted geochemical area of seawater intrusion was estimated to be 4000 and 1500 m, respectively, along transect S1 and transect S2. Inversely, agricultural contamination acts in internal areas beginning at 2000 m and 1500 m from the shoreline for S1 and S2, respectively. Results of different scenarios of inverse geochemical modelling along flow paths indicated that mixing, ion exchange, dissolution of gypsum, and precipitation of dolomite and calcite are the main processes controlling the groundwater composition in the coastal study area.

Unraveling the occurrence of contaminants of emerging concern in groundwater from urban setting: A combined multidisciplinary approach and self-organizing maps

In recent decades, changes in human behavior and new technologies have introduced thousands of new compounds into the environment called "contaminants of emerging concern" (CEC). These compounds have been detected in different environmental compartments such as soil, surface water, air, and groundwater. The presence of these contaminants in groundwater may pose risks to human health when used as potable water. In some urban areas in Brazil, groundwater is normally consumed without previous treatment. This study aimed to use statistical analysis by self-organizing maps (SOM) to evaluate the trends of CEC in urban groundwater systems. A total of 23 CEC compounds including pesticides, pharmaceuticals, and hormones were determined in groundwater samples using solid phase extraction and liquid chromatography-mass spectrometry. The CEC most frequently detected were atrazine and degradation products, fipronil, simazine, tebuconazole, hexazinone, and caffeine in concentrations up to 300 ng L^-1. All studied compounds were detected in groundwater at least in one sample. Patterns in the data through SOM have shown a strong positive correlation between atrazine, hexazinone, simazine, tebuthiuron, 2-hydroxyatrazine, and 17β-estradiol. The hormones estrone and testosterone also show a positive correlation due to their similar chemical properties. On the other hand, caffeine was detected in 90% of the samples, likely due to a population habit of taking daily a hot drink made of yerba mate associated with low rates of treated domestic sewage in the study area.

Nitrate source apportionment and risk assessment: A study in the largest ion-adsorption rare earth mine in China

Nitrate (NO₃^-) pollution in water bodies has received widespread attention, but studies on nitrogen transformation and pollution risk assessment are still limited, especially in rare earth mining areas. In this study, surface and groundwater samples were collected from the largest rare earth mining site in southern China, and analyzed for the hydrochemical and stable isotopic characteristics. The results showed that the NO₃^- concentrations ranged from 1.61 to 453.11 mg/L, with 35% of surface water and 53.3% of groundwater samples exceeding the WHO standard (i.e., 50 mg/L). Health risk assessment showed that 31.4% of the water samples had a moderate to high non-carcinogenic risk, and the high-risk areas were concentrated in rare earth mining regions. Additionally, adults were more vulnerable to the non-carcinogenic health risks than children. The high variability of δ¹⁵N-NO₃^- (from -6.43 to 17.09‰) and δ¹⁸O-NO₃^- (from -7.91 to 22.79‰) showed that NO₃^- was influenced by multiple nitrogen sources and transformation processes. Hydrochemistry and isotopic evidence further indicated that NO₃^- was primarily influenced by nitrification and hydraulic connection between surface and groundwater. The results of the Bayesian mixing model showed that about 70% of NO₃^- originated from mine drainage and soil N in the rare earth mining area, while more than 90% of NO₃^- originated from fertilizer, soil N, and manure and sewage in rural and urban areas in the middle and downstream. This study suggests reducing anthropogenic nitrogen discharge (e.g., leaching agents and fertilizer inputs) as the primary means of NO₃^- pollution control with biogeochemical processes (e.g., denitrification) to further reduce its pollution.

Multiple stable isotopes and geochemical approaches to elucidate groundwater salinity and contamination in the critical coastal zone: A case from the Bou-areg and Gareb aquifers (North-Eastern Morocco)

Mediterranean areas are characterized by complex hydrogeological systems, where water resources are faced with several issues such as salinity and pollution. Fifty-one water samples were gathered from the Bou-areg coastal and the Gareb aquifers to evaluate the source of water salinity and to reveal the processes of the different sources of pollution using a variety of chemical and isotopic indicators (δ²H-H2O, δ¹⁸O-H2O, δ³⁴S-SO4, and δ¹⁸O-SO4). The results of the hydrochemical analysis of water samples show that the order of dominated elements is Cl^- > HCO₃^- > SO4₂^- > NO₃^- and Na⁺ > Ca²⁺ > Mg²⁺ > K⁺ and evidenced extremely high salinity levels (EC up to 22000 μS/cm). All samples exceeded the WHO drinking water guidelines, making them unfit for human consumption. Ion ratio diagrams, isotopic results, and graphical comparing indicate that the mineralization of groundwater in the area, is controlled by carbonate dissolution, evaporite dissolution, ion exchange, and sewage invasion. The return of irrigation water plays a significant role as well in the groundwater recharge and its mineralization by fertilizers mainly. Evaporites (Gypsum), sewage, and fertilizers constitute the main sources of sulfates in the investigated water resources. These scientific results will be an added value for decision-makers to more improve the sustainable management of groundwater in water-stressed regions. The use of chemical and isotopic tracers once again shows their relevance in such zones where systematic monitoring is lacking.

Identification and apportionment of shallow groundwater nitrate pollution in Weining Plain, northwest China, using hydrochemical indices, nitrate stable isotopes, and the new Bayesian stable isotope mixing model (MixSIAR)

Groundwater nitrate (NO₃^-) pollution is a worldwide environmental problem. Therefore, identification and partitioning of its potential sources are of great importance for effective control of groundwater quality. The current study was carried out to identify the potential sources of groundwater NO₃^- pollution and determine their apportionment in different land use/land cover (LULC) types in a traditional agricultural area, Weining Plain, in Northwest China. Multiple hydrochemical indices, as well as dual NO₃^- isotopes (δ¹⁵N-NO₃ and δ¹⁸O-NO₃), were used to investigate the groundwater quality and its influencing factors. LULC patterns of the study area were first determined by interpreting remote sensing image data collected from the Sentinel-2 satellite, then the Bayesian stable isotope mixing model (MixSIAR) was used to estimate proportional contributions of the potential sources to groundwater NO₃^- concentrations. Groundwater quality in the study area was influenced by both natural and anthropogenic factors, with anthropological impact being more important. The results of LULC revealed that the irrigated land is the dominant LULC type in the plain, covering an area of 576.6 km² (57.18% of the total surface study area of the plain). On the other hand, the results of the NO₃^- isotopes suggested that manure and sewage (M&S), as well as soil nitrogen (SN), were the major contributors to groundwater NO₃^-. Moreover, the results obtained from the MixSIAR model showed that the mean proportional contributions of M&S to groundwater NO₃^- were 55.5, 43.4, 21.4, and 78.7% in the forest, irrigated, paddy, and urban lands, respectively. While SN showed mean proportional contributions of 29.9, 43.4, 61.5, and 12.7% in the forest, irrigated, paddy, and urban lands, respectively. The current study provides valuable information for local authorities to support sustainable groundwater management in the study region.

Multi-objective optimization-based reactive nitrogen transport modeling for the water-environment-agriculture nexus in a basin-scale coastal aquifer

The quantification of trade-offs between social-economic and environmental effects is of great importance, especially in the semi-arid coastal areas with highly developed agriculture. The study presents an integrated multi-objective simulation-optimization (S-O) framework to evaluate the basin-scale water-environment-agriculture (WEA) nexus. First, the variable-density groundwater model (SEAWAT) is coupled to the reactive transport model (RT3D) for the first attempt to simulate the environmental effects subject to seawater intrusion (SWI) and nitrate pollution (NP). Then, the surrogate assisted multi-objective optimization algorithm is utilized to investigate the trade-offs between the net agricultural benefits and extents of SWI and NP while considering the water supply, food security, and land availability simultaneously. The S-O modeling methodology is applied to the Dagu River Basin (DRB), a typical SWI region with intensive agricultural irrigation in China. It is shown that the three-objective space based on Pareto-optimal front can be achieved by optimizing planting area in the irrigation districts, indicating the optimal evolution of the WEA nexus system. The Pareto-optimal solutions generated by multi-objective S-O model are more realistic and pragmatic, avoiding the decision bias that may often lead to cognitive myopia caused by the low-dimensional objectives. Although the net agricultural benefits in Pareto-optimal solutions are declined to some extent, the environmental objectives (the extents of SWI and NP) are improved compared to those in the pre-optimized scheme. Therefore, the proposed multi-objective S-O framework can be applied to the WEA nexus in the river basin with intensive agriculture development, which is significant to implement the integrated management of water, food, and environment, especially for the semi-arid coastal aquifers.

Predicting adverse scenarios for a transboundary coastal aquifer system in the Atacama Desert (Peru/Chile)

The Caplina/Concordia transboundary coastal aquifer system, located in the Atacama Desert, is the primary source of water supply for domestic use and irrigation for La Yarada-Los Palos (Peru) and Concordia (Chile) agriculture districts, and to a lesser extent, for Tacna province public supply use (Peru). Despite the scarce amount of rainfall (<20 mm/year) in the area and the limited recharge coming from the Andean highlands, this transboundary aquifer system has been overexploited mainly for agriculture since before the 2000s on the Peruvian side. Consequently, this has caused groundwater depletion and seawater intrusion. In this study, comprehensive hydrogeological information was integrated to understand the aquifer system's behavior and the effects to which it has been subjected to groundwater overexploitation. To that end, a 3D hydrogeological framework was developed using the LEAPFROG software and a constant-density groundwater flow model with equivalent heads was generated in FEFLOW software, which was adjusted with Monte Carlo analysis and conventional automated calibration. Finally, eight scenarios, considering various water resource management options proposed by the authority and potential climatic trends (CMIP6), were simulated from 2020 to 2040. The results showed that between 2002 and 2020, the increase in the seawater wedge and the average groundwater level decline were 216 hm³/year and 7 m, respectively. It is expected that the depletion will continue with a groundwater level decline between 5 and 8 m and an increase in the seawater wedge between 1120 hm³/year and 1175 hm³/year for the forecast period. The study concludes that the aquifer system will remain unsustainable for the next 20 years, regardless of the selected scenarios, and suggests that any mitigation measure requires the participation of stakeholders from Peru, Chile, and Bolivia.

Origin of nitrate and sulfate sources in volcano-sedimentary aquifers of the East Africa Rift System: An example of the Ali-Sabieh groundwater (Republic of Djibouti)

Within the East African Rift System (EARS), the complex Ali-Sabieh aquifers system, located in the south of the Republic of Djibouti, was overexploited and subjected to anthropogenic and/or geogenic pollution with high concentrations of dissolved nitrate (up to 181 mg/l) and sulfates (up to 1540 mg/l). This study is the first undertaken on the hydrochemistry of this aquifer system, combining geochemical tools and multi-isotope - δ²H(H₂O), δ¹⁸O(H₂O), δ¹⁸O(SO₄), δ³⁴S(SO₄), δ¹⁵N(NO₃), δ¹⁸O(NO₃), δ¹³C(DIC), and ¹⁴C- was used to decipher the origin and fate of different nitrate and sulfate sources to groundwater. The groundwater samples of the region show a chemical evolution from fresh Ca(Na)-bicarbonate to brackish Na-Cl , mainly due to water-rock interaction. The combined chloride and water isotope data show that evaporation and transpiration are present, with the latter occurring primarily in the shallow alluvial aquifer waters. Inspection of δ¹⁵N(NO₃) vs. δ¹⁸O(NO₃) and NO₃/Cl vs. Cl diagrams show that dissolved nitrates are primarily of anthropogenic origin. In particular, higher nitrate concentrations may be related to animal manure used as organic fertilizers during agricultural activities. Sulfates are from a natural origin related to the interaction of water with gypsum of hydrothermal or sedimentary origin. SO₄/Cl ratio and isotopic composition show that dissolved sulfates in saline and ancient groundwater of the Cretaceous sandstone aquifer (between 7.4 ± 2.2 and 5.8 ± 1.4 k-years before the present) are generated by interaction with gypsum from oxidation of pre-existing (Jurassic?) sulfides. This work highlight that isotopic ratios of the two molecules -δ¹⁸O(SO₄), δ³⁴S(SO₄), δ¹⁵N(NO₃), δ¹⁸O(NO₃)- are not sufficient for tracing the origin of nitrate and sulfates in groundwater, but that a complete hydrogeochemical study is needed. In the absence of this, the relatively high concentration of chloride and sulfates could be wrongly linked to the anthropogenic source of nitrate (manure or sewage).