Identifying nitrate sources and transformations in an agricultural watershed in Northeast China: Insights from multiple isotopes

Integrated quantitative tracing for Karst groundwater contamination: A case study of landfill in Zunyi, Guizhou Province, China

Sudden groundwater pollution in karst areas poses a serious threat to drinking water safety. Tracing contamination sources is crucial for managing and remediating groundwater pollution. Traditional tracing methods often lack accuracy, so this study combined multiple techniques to trace and quantify pollution sources near the municipal solid waste (MSW) landfill in Zunyi City, Guizhou Province, China. Analysis revealed that 83.2% of samples exceeded Chinese standards for ammonium, 81.5% for CODMn, and 47.9% for chloride, indicating severe pollution. To address these alarming findings, we implemented a comprehensive approach to identify and quantify the sources of contamination more accurately. First, major element geochemical tracing identified primary contamination sources. Second, trace element analysis provided more precise identification and highlighted additional sources. Third, isotopic tracing (δ15N-NO3-, δ18O-NO3-) determined types and quantities of pollution sources. Finally, long-term water quality monitoring and the PMF model enabled quantitative source apportionment of pollutants. This integrated approach found that the primary pollutants were landfill leachate (64.6%), domestic sewage (19.0%), and solute filtration from water-soil-rock interactions (16.4%). Our findings demonstrate that combining these methods enhances source resolution accuracy in aquatic environments and has the potential to be utilized in other karst regions worldwide.

Sources and fate of nitrate in the unsaturated zone in an alluvial-lacustrine plain

Nitrate pollution in terrestrial and aquatic ecosystems in global agricultural areas poses an environmental concern. However, there is limited understanding of hydrogeological controls on the behavior of nitrogen compounds in unsaturated zones. Here, Self-Organizing Map and multiple isotopes approaches (δ15N-NO3-, δ18O-NO3-, and δ15N-NH4+) were used to investigate the sources, transport and transformation of N-species in the unsaturated zone in an alluvial-lacustrine plain, southeast China. The results revealed significant spatial heterogeneity in soil texture and physicochemical properties with vertically four soil geochemical and N-species zones (high NO₃⁻, high Fe(Ⅲ) and Mn, low ionic, and high NH₄⁺ contents), dominated by agricultural input, soil minerals and redox conditions. Nitrate in the unsaturated zone primarily originated from fertilizers and soil nitrogen. Excess nitrogen fertilizers infiltrated into the soil, where mineralization, nitrification, and dissimilatory nitrate reduction to ammonium (DNRA) acted as key mechanisms for nitrogen transformation. The change in the depositional environment from the plain to the lakeshore area led to nitrification gradual decrease and DNRA significant increase. Consequently, a conceptual model of reactive transport of N-species, influenced by hydrogeologic conditions and biogeochemical processes, was proposed. This study provides a new insight into the nitrate behaviors in unsaturated zone and contributes to groundwater nitrogen management strategies.

Integrating isotope mixing and hydrologic models towards a more accurate riverine nitrate source apportionment

Nitrate (NO3-) is the major form of bioavailable nitrogen in most rivers, and its dramatic increase may lead to a number of serious environmental issues, such as eutrophication and biodiversity decline. Quantification of NO3- sources and fluxes in rivers is essential for effective management of NO3- pollution. Isotope mixing and hydrological models are proven practical tools for quantifying the sources of NO3- in rivers, yet both methods have severe limitations. To improve the accuracy and reliability of riverine NO3- source apportionment, this study proposed a protocol that integrates the strengths of both tools, capable of solving issues such as the calculation bias caused by isotope endmember overprinting in isotope mixing model and the lack of validation data for hydrological models. We applied the framework to a typical agricultural river, the Qihe River, and illustrated the effectiveness of the method in quantifying riverine NO3- sources. The proportional contribution of sewage simulated by the SWAT model approximated that estimated by the isotopic mixing model, yet the SWAT-based contributions of soil organic nitrogen and chemical fertilizer were 16.3 % lower and 14.0 % higher, respectively than the MCMC-based results. After integrating both models, we adopted the proportions of NO3- sources in the river from chemical fertilizer, sewage, and soil organic nitrogen as 45.1 %, 30.9 %, and 23.9 %, respectively. This study showed that coupling isotopic and hydrological models provided a new dimension for the accurate quantification of N sources in rivers.

Occurrence, migration, and assessment of human health and ecological risks of PFASs and EDCs in groundwater of Northeast China

Northeast China as an important base of grain production in China, has been suffering from potential groundwater pollution due to the excessive and prolonged application of fertilizers and pesticides. However, exploration of emerging contaminants pollution in groundwater and assessment of human health and ecological risks caused by large-scale agricultural activities have been relatively scarce. This study collected groundwater samples from typical agricultural areas in Northeast China to investigate the extent of contamination by nitrate, per- and polyfluoroalkyl substances (PFASs) and endocrine-disrupting compounds (EDCs), and then compared the levels of these pollutants with those in other regions of China. Groundwater nitrate pollution caused by strong agricultural activity is widespread in Northeast China, with nitrate-nitrogen (NO3N) concentrations exceeding 10 mg/L in as many as 40.3 % of 429 samples. 8 types of PFASs (3.7-7.1 ng/L) and 11 types of EDCs (18,114.0-62,029.8 ng/L) were detected in the collected groundwater samples. Using the Risk Quotient (RQ) method, this study assessed ecological risk and found that the risk level of perfluorooctane sulfonate (PFOS) was higher than that of other PFASs. The groundwater EDCs risks in Northeast China was higher compared to other regions in China, with dibutyl phthalate (DBP), Di-(2-ethylhexyl) phthalate (DEHP), Bisphenol A (BPA) having high ecological risk levels. Nitrate, PFASs and EDCs have been detected in deep groundwater (70-100 m depth), indicating that the deeper aquifers could be significantly threatened by pollutants due to human activities. Fertilizers, pesticides, domestic wastewater, and industrial discharges are major sources of groundwater pollutants in the agricultural regions. Industrial-sourced EDCs were widely detected in groundwater of agricultural area, suggesting that the transport of these pollutants is very active in groundwater system. Groundwater monitoring and pollution prevention are extremely urgent, especially for emerging contaminants. This study can provide important warnings and water resource management references for other agricultural areas affected by intensively agricultural activities in the world.

Revealing nitrate sources seasonal difference between groundwater and surface water in China's largest fresh water lake (Poyang Lake): Insights from sources proportion, dynamic evolution and driving forces

Tracing the source of nitrate is the key path to solve the problem of nitrogen pollution. However, the seasonal difference of nitrate sources in groundwater and surface water and its dynamic evolution process and mechanism in large fresh water lake area are still not clear. In this study, 126 water samples were collected from groundwater and surface water in China's largest fresh water lake (Poyang Lake) region from 2022 to 2023. Bayesian stable isotope mixing model, absolute principal component score-multiple linear regression, ion ratio coefficients and uncertainty index (UI90) were used to investigate the nitrate sources variation in groundwater and surface water as well as its uncertainty in Poyang Lake area. Results showed that anthropogenic influence had significant influence on nitrate sources, which was mainly affected by chemical fertilizer (CF), soil nitrogen (SN) and manure and sewage input (M&S). Specifically, from 2022 to 2023, CF contributed 16.6 % to 32.4 %, SN contributed 26.0 % to 38.1 %, M&S contributed 26.5 % to 48.2 % to groundwater. CF contributed 38.8 % to 43.9 %, SN contributed 37.6 % to 40.6 %, M&S contributed 12.3 % to 18.6 % to surface water. The sources and proportion of nitrate in groundwater and surface water exhibited obvious difference. Temporal heterogeneity, land use type, population density and vegetation cover type had influence on nitrate sources. UI90 results showed that there was uncertainty in nitrate sources tracing process, with SN (mean 0.78), CF (mean 0.64), M&S (mean 0.35) and AD (mean 0.09), respectively. These results will provide vital references for understanding nitrate sources variation, controlling and removing nitrate surplus in groundwater-surface water system in the similar large fresh water lake areas.

Multi-evidences investigation into spatiotemporal variety, sources tracing, and health risk assessment of surface water nitrogen contamination in China

A comprehensive understanding of nitrogen pollution status, especially the identification of sources and fate of nitrate is essential for effective water quality management at the local scale. However, the nitrogen contamination of surface water across China was poorly understood at the national scale. A dataset related to nitrogen was established based on 111 pieces of literature from 2000 to 2020 in this study. The spatiotemporal variability, source tracing, health risk assessment, and drivers of China's surface water nitrogen pollution were analyzed by integrating multiple methods. These results revealed a significant spatiotemporal heterogeneity in the nitrogen concentration of surface water across China. Spatially, the Haihe River Basin and Yellow River Basin were the basins where surface water was seriously contaminated by nitrogen in China, while the surface water of Southwest Basin was less affected. Temporally, significant differences were observed in the nitrogen content of surface water in the Songhua and Liaohe River Basin, Pearl River Basin, Southeast Basin, and Yellow River Basin. There were 1%, 1%, 12%, and 46% probability exceeding the unacceptable risk level (HI＞1) for children in the Songhua and Liaohe River Basin, Pearl River Basin, Haihe River Basin, and Yellow River Basin, respectively. The primary sources of surface water nitrate in China were found to be domestic sewage and manure (37.7%), soil nitrogen (31.7%), and chemical fertilizer (26.9%), with a limited contribution from atmospheric precipitation (3.7%). Human activities determined the current spatiotemporal distribution of nitrogen contamination in China as well as the future development trend. This research could provide scientifically reasonable recommendations for the containment of surface water nitrogen contamination in China and even globally.

Assessment of groundwater quality variation characteristics and influencing factors in an intensified agricultural area: An integrated hydrochemical and machine learning approach

The decline in groundwater quality in intensive agricultural areas in recent years, driven by environmental change and intensified human activity, poses a significant threat to agricultural production and public health, requiring attention and effective management. However, distinguishing the specific impacts of various factors on groundwater quality remains challenging, which hinders the effective management and prevention of groundwater pollution. This research integrates a hydrochemical analysis with the Entropy-weighted Water Quality Index, Self-Organizing Map (SOM) approach, and Boruta algorithm to investigate groundwater chemical variations and their influencing factors in the Sanjiang Plain, an important grain-producing region in China. The findings reveal that, compared to 2012, the deep groundwater quality has improved, while the shallow groundwater quality has markedly deteriorated. This decline in shallow groundwater quality is primarily attributable to human activities and is characterized by elevated levels of chloride, sulfate, and nitrate and a shift in the groundwater hydrochemical facies from an HCO3-Ca·Mg type to a mixed HCO3-Ca·Mg and SO4·Cl-Ca·Mg type. The SOM results suggested that land use type significantly affects shallow groundwater quality. Further analysis with the Boruta algorithm identified increased sewage and manure emissions from expanding livestock operations as well as enhanced pollutant leakage from the expansion of paddy fields as the primary contributors to the decline in shallow groundwater quality. These findings offer new insights into the mechanisms of groundwater quality changes in agriculturally intensive regions and provide a foundation for improved groundwater pollution management in the Sanjiang Plain and similar areas.

Identification of groundwater nitrate sources and its human health risks in a typical agriculture-dominated watershed, North China

Identifying nitrate sources and migratory pathways is crucial for controlling groundwater nitrate pollution in agricultural watersheds. This study collected 35 shallow groundwater samples in the Nansi Lake Basin (NLB) to identify groundwater nitrate sources and potential health risks. Results showed that NO3- concentration in 62.9% of groundwater samples exceeded the drinking water standard (50 mg/L). Hierarchical cluster analysis (HCA) was used to classify the sampling points into three groups based on hydrochemical and isotopic data. Groups A and C were situated in the eastern recharge and discharge regions of Nansi Lake, while Group B was located in the Yellow River floodplain west of the lake. Hydrochemical data and nitrate stable isotopes (δ15N-NO3- and δ18O-NO3-) indicated that elevated NO3- primarily originated from soil organic nitrogen (SON) in Group A, while manure and sewage (M&S) were the primary sources in Groups B and C samples. Microbial nitrification was identified as the primary nitrogen transformation process across all groups. The source apportionment results indicated that SON contributed approximately 40.1% in Group A, while M&S contributed about 53.9% and 81.2% in Groups B and C, respectively. The Human Health Risk Assessment (HHRA) model indicated significant non-carcinogenic risks for residents east of Nansi Lake, primarily through the oral pathway, with NO3- concentration identified as the most influential factor by sensitivity analysis. These findings provide new perspectives on identifying and handling groundwater nitrogen pollution in agriculture-dominated NLB and similar basins that require enhanced nitrogen contamination management.

Deciphering and quantifying nitrate sources and processes in the central Yellow Sea using dual isotopes of nitrate

Anthropogenic activities pose significant challenges to the accumulation of coastal nitrogen (N). Accurate identification of nitrate (NO3-) sources is thus essential for mitigating excessive N in many marginal seas. We investigated the dual isotopes of NO3- in the central Yellow Sea to elucidate the sources and cycling processes of NO3-. The results revealed significant spatial variability in NO3- concentrations among the Yellow Sea Surface Water (YSSW), Changjiang Diluted Water (CDW), Yellow Sea Cold Water Mass (YSCWM), and Taiwan Warm Current Water (TWCW). Stratification played a crucial role in restricting vertical nutrient transport, leading to distinct nutrient sources and concentrations in different water masses. The dual NO3- isotopic signature indicated that atmospheric deposition was the primary source of surface NO3-, contributing approximately 30 % to the NO3- in the YSSW. In the NO3--rich CDW, the heavier δ15N-NO3- and δ18O-NO3- suggested incomplete NO3- assimilation. Organic matter mineralization and water stratification played crucial roles in the accumulation of nutrients within the YSCWM and TWCW. Notably, regenerated NO3- accounted for approximately half of the NO3- stored in the YSCWM. A synthesis of NO3- dual isotope data across the coastal China seas revealed significant spatial and seasonal variations in the N source. The study emphasized the dynamics of coastal NO3- supply, which are shaped by the complex interconnections among marine, terrestrial, and atmospheric processes. Our approach is a feasible method for exploring the origins of N amidst the escalating pressures of anthropogenic nutrient pollution in coastal waters.

Sources, fate and influencing factors of nitrate in farmland drainage ditches of the irrigation area

Global irrigation areas face the contradictory challenges of controlling nitrate inputs and ensuring food-safe production. To prevent and control nitrate pollution in irrigation areas, the study using the Yellow River basin (Ningxia section) of China as a case study, employed nitrogen and oxygen dual isotope tracing and extensive field investigations to analyze the sources, fate, and influencing factors of nitrate in agricultural drainage ditches. The results of source tracing of nitrate showed that annual proportions of nitrate sources entering the Yellow River in the ditches are as follows: for manure & sewage, fertilizer, and natural sources, the ratios are 33%, 35%, and 32% overall. The results of nitrate fate showed that nitrates derived from nitrate fertilizer exhibit a lower residual rate in drainage ditches (ecological ditches) compared to ammonium fertilizer, which can undergo self-ecological restoration within one year. The results of influencing factors showed that crops with high water and nutrient requirements, such as vegetables, the nitrate pollution and environmental harm resulting from "exploitative cultivation" are five times more than normal cultivation practices in dryland and paddy fields, especially winter irrigation without crop interception exacerbates the leaching of nitrate from the soil. Therefore, nitrate management in irrigation areas should focus on preventing and controlling "exploitative cultivation" and losses during winter irrigation, while appropriately adjusting the application ratio of ammonium nitrogen fertilizers. The results of the study can guide strategies to mitigate nitrate pollution in irrigated areas such as livestock farming, fertilizer application, irrigation management, ditch optimization, and crop cultivation.

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.

Hydrogeochemical characterization, quality assessment, and potential nitrate health risk of shallow groundwater in Dongwen River Basin, North China

Assessing groundwater geochemical formation processes and pollution circumstances is significant for sustainable watershed management. In the present study, 58 shallow groundwater samples were taken from the Dongwen River Basin (DRB) to comprehensively assess the hydrochemical sources, groundwater quality status, and potential risks of NO3- to human health. Based on the Box and Whisker plot, the cation's concentration followed the order of Ca2+  > Mg2+  > Na+  > K+, while anions' mean levels were HCO3-  > SO42-  > NO3-  > Cl-. The NO3- level in groundwater samples fluctuated between 4.2 and 301.3 mg/L, with 67.2% of samples beyond the World Health Organization (WHO) criteria (50 mg/L) for drinking. The Piper diagram indicated the hydrochemical type of groundwater and surface water were characterized as Ca·Mg-HCO3 type. Combining ionic ratio analysis with principal component analysis (PCA) results, agricultural activities contributed a significant effect on groundwater NO3-, with soil nitrogen input and manure/sewage inputs also potential sources. However, geogenic processes (e.g., carbonates and evaporite dissolution/precipitation) controlled other ion compositions in the study area. The groundwater samples with higher NO3- values were mainly found in river valley regions with intense anthropogenic activities. The entropy weight water quality index (EWQI) model identified that the groundwater quality rank ranged from excellent (70.7%) and good (25.9%) to medium (3.4%). However, the hazard quotient (HQ) used in the human health risk assessment (HHRA) model showed that above 91.38% of groundwater samples have a NO3- non-carcinogenic health risk for infants, 84.48% for children, 82.76% for females, and 72.41% for males. The findings of this study could provide a scientific basis for the rational development and usage of groundwater resources as well as for the preservation of the inhabitants' health in DRB.

Identification of nitrate accumulation mechanism of surface water in a mining-rural-urban agglomeration area based on multiple isotopic evidence

The accumulation of nitrate (NO3-) in surface waters resulting from mining activities and rapid urbanization has raised widespread concerns. Therefore, it is crucial to develop a nitrate transformation information system to elucidate the nitrogen cycle and ensure sustainable water quality management. In this study, we focused on the main river and subsidence area of the Huaibei mining region to monitor the temporal and spatial variations in the NO3- content. Multiple isotopes (δD, δ18O-H2O, δ15N-NO3-, δ18O-NO3-, and δ15N-NH4+) along with water chemistry indicators were employed to identify the key mechanisms responsible for nitrate accumulation (e.g., nitrification and denitrification). The NO3- concentrations in surface water ranged from 0.28 to 7.50 mg/L, with NO3- being the predominant form of nitrogen pollution. Moreover, the average NO3- levels were higher during the dry season than during the wet season. Nitrification was identified as the primary process driving NO3- accumulation in rivers and subsidence areas, which was further supported by the linear relationship between δ15N-NO3- and δ15N-NH4+. The redox conditions and the relationship between δ15N-NO3- and δ18O-NO3-, and lower isotope enrichment factor of denitrification indicated that denitrification was weakened. Phytoplankton preferentially utilized available NH4+ sources while inhibiting NO3- assimilation because of their abundance. These findings provide direct evidence regarding the mechanism underlying nitrate accumulation in mining areas, while aiding in formulating improved measures for effectively managing water environments to prevent further deterioration.

Nitrate transformation and source tracking of rivers draining into the Bohai Sea using a multi-tracer approach combined with an optimized Bayesian stable isotope mixing model

Excessive levels of NO3- can result in multiple eco-environmental issues due to potential toxicity, especially in coastal areas. Accurate source tracing is crucial for effective pollutant control and policy development. Bayesian models have been widely employed to trace NO3- sources, while limited studies have utilized optimized Bayesian models for NO3- tracing in the coastal rivers. The Bohai Rim is highly susceptible to ecological disturbances, particularly N pollution, and has emerged as a critical area. Therefore, identification the N fate and understanding their sources contribution is urgent for pollution mitigation efforts. In addition, understanding the influenced key driven factors to source dynamic in the past ten years is also implication to environmental management. In this study, water samples were collected from 36 major river estuaries that drain into the Bohai Sea of North China. The main transformation processes were analyzed and quantified the sources of NO3- using a Bayesian stable isotope mixing model (MixSIAR) with isotopic approach (δ15N-NO3- and δ18O-NO3-). The overall isotopic composition of δ15N-NO3- and δ18O-NO3- in estuary waters ranged from -0.8-19.3‰ (9.3 ± 4.6‰) and from -7.1-10.5‰ (5.0 ± 4.3‰), respectively. The main sources of nitrate in most river estuaries were manure & sewage, and chemical fertilizer, while weak denitrification and mixed processes were observed in Bohai Rim region. A temporal decrease in the nitrogen load entering the Bohai Sea indicates an improvement in water quality in recent years. By incorporating informative priors and utilizing the calculated coefficients, the accuracy of sourcing results was significantly improved. This study highlighted the optimized MixSIAR model enhanced its accuracy for sourcing analysis and providing valuable insights for policy formulation. Future efforts should focus on improving management strategies to reduce nitrogen into the bay.

Distribution, sources and main controlling factors of nitrate in a typical intensive agricultural region, northwestern China: Vertical profile perspectives

Nitrate (NO3-) pollution of groundwater is a global concern in agricultural areas. To gain a comprehensive understanding of the sources and destiny of nitrate in soil and groundwater within intensive agricultural areas, this study employed a combination of chemical indicators, dual isotopes of nitrate (δ15N-NO3- and δ18O-NO3-), random forest model, and Bayesian stable isotope mixing model (MixSIAR). These approaches were utilized to examine the spatial distribution of NO3- in soil profiles and groundwater, identify key variables influencing groundwater nitrate concentration, and quantify the sources contribution at various depths of the vadose zone and groundwater with different nitrate concentrations. The results showed that the nitrate accumulation in the cropland and kiwifruit orchard at depths of 0-400 cm increased, leading to subsequent leaching of nitrate into deeper vadose zones and ultimately groundwater. The mean concentration of nitrate in groundwater was 91.89 mg/L, and 52.94% of the samples exceeded the recommended grade III value (88.57 mg/L) according to national standards. The results of the random forest model suggested that the main variables affecting the nitrate concentration in groundwater were well depth (16.6%), dissolved oxygen (11.6%), and soil nitrate (10.4%). The MixSIAR results revealed that nitrate sources vary at different soil depths, which was caused by the biogeochemical process of nitrate. In addition, the highest contribution of nitrate in groundwater, both with high and low concentrations, was found to be soil nitrogen (SN), accounting for 56.0% and 63.0%, respectively, followed by chemical fertilizer (CF) and manure and sewage (M&S). Through the identification of NO3- pollution sources, this study can take targeted measures to ensure the safety of groundwater in intensive agricultural areas.