Identifying the source and transformation of riverine nitrates in a karst watershed, North China: Comprehensive use of major ions, multiple isotopes and a Bayesian model

Hydrochemical processes and inorganic nitrogen sources of shallow groundwater in the Sanjiang Plain, northeast China

This study investigates the chemical characteristics, formation, and sources of inorganic nitrogen (IN) of shallow groundwater across the Sanjiang Plain, aiming to enhance drinking water safety management and pollution control. A total of 167 groundwater and 27 surface water samples were collected for constituents and isotopes (H2 and O18). The hydrogeochemical characteristics showed that the major type is HCO3- Ca·Mg, with low total dissolved solids and a neutral to weak alkaline nature. Rock weathering processes govern the hydrochemical composition of groundwater. Hydrogen and oxygen stable isotopes analyses revealed that precipitation serves as the main water source. In alluvial areas, oxidative conditions lead to the enrichment of NO3-N concentrations, with sewage, manure, and fertilizers being the primary IN sources. In lacustrine areas, intensive rice cultivation results in reductive conditions and strong denitrification processes, causing the loss of NO3-N and leaving NH4-N as the dominant IN form. Organic matter mineralization is likely a more significant contributor to NH4-N concentrations than ammonium fertilizers. These findings provide valuable information for further research on natural sources and groundwater pollution in areas with similar hydrogeological conditions. PRACTITIONER POINTS: Rock weathering processes govern the hydrochemical composition of groundwater, and precipitation serves as the main water source. In alluvial areas, oxidative conditions lead to the enrichment of NO3-N. In lacustrine areas, intensive rice cultivation results in reductive conditions and strong denitrification processes. Organic matter mineralization is likely a more significant contributor to NH4-N concentrations than ammonium fertilizers. These findings provide references for water management and information for further research on natural sources and groundwater pollution in areas with similar hydrogeological conditions.

Tracing groundwater nitrate sources in an intensive agricultural region integrated of a self-organizing map and end-member mixing model tool

The traceability of groundwater nitrate pollution is crucial for controlling and managing polluted groundwater. This study integrates hydrochemistry, nitrate isotope (δ15N-NO3- and δ18O-NO3-), and self-organizing map (SOM) and end-member mixing (EMMTE) models to identify the sources and quantify the contributions of nitrate pollution to groundwater in an intensive agricultural region in the Sha River Basin in southwestern Henan Province. The results indicate that the NO3--N concentration in 74% (n = 39) of the groundwater samples exceeded the WHO standard of 10 mg/L. According to the results of EMMTE modeling, soil nitrogen (68.4%) was the main source of nitrate in Cluster-1, followed by manure and sewage (16.5%), chemical fertilizer (11.9%) and atmospheric deposition (3.3%). In Cluster-2, soil nitrogen (60.1%) was the main source of nitrate, with a significant increase in the contribution of manure and sewage (35.5%). The considerable contributions of soil nitrogen may be attributed to the high nitrogen fertilizer usage that accumulated in the soil in this traditional agricultural area. Moreover, it is apparent that most Cluster-2 sampling sites with high contributions of manure and sewage are located around residential land. Therefore, the arbitrary discharge and leaching of domestic sewage may be responsible for these results. Therefore, this study provides useful assistance for the continuous management and pollution control of groundwater in the Sha River Basin.

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).

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.

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.

Unignorable enzyme-specific isotope fractionation for nitrate source identification in aquatic ecosystem

Nitrate contamination in aquatic systems is a widespread problem across the world. The isotopic composition (δ15N, δ18O) of nitrate and their isotope effect (15ε, 18ε) can facilitate the identification of the source and transformation of nitrate. Although previous researches claimed the isotope fractionations may change the original δ15N/δ18O values and further bias identification of nitrate sources, isotope effect was often ignored due to its complexity. To fill the gap between the understanding and application, it is crucial to develop a deep understanding of isotopic fractionation based on available evidence. In this regard, this study summarized the available methods to determine isotope effects, thereby systematically comparing the magnitude of isotope effects (15ε and 18ε) in nitrification, denitrification and anammox. We found that the enzymatic reaction plays the key role in isotope fractionations, which is significantly affected by the difference in the affinity, substrate channel properties and redox potential of active site. Due to the overlapping of microbial processes and accumulation of uncertainties, the significant isotope effects at small scales inevitably decrease in large-scale ecosystems. However, the proportionality of N and O isotope fractionation (δ18O/δ15N; 18ε/15ε) associated with nitrate reduction generally follows enzyme-specific proportionalities (i.e., Nar, 0.95; Nap, 0.57; eukNR, 0.98) in aquatic ecosystems, providing enzyme-specific constant factors for the identification of nitrate transformation. With these results, this study finally discussed feasible source portioning methods when considering the isotope effect and aimed to improve the accuracy in nitrate source identification.

Stable isotopes reveal organic nitrogen pollution and cycling from point and non-point sources in a heavily cultivated (agricultural) Mediterranean river basin

The Pinios River Basin (PRB) is the most intensively cultivated area in Greece, which hosts numerous industries and other anthropogenic activities. The analysis of water samples collected monthly for ∼1 ½ years in eight monitoring sites in the PRB revealed nitrate pollution of organic origin extending from upstream to downstream and occurring throughout the year, masking the signal from the application of synthetic fertilizers. Nitrate concentrations reached up to 3.6 mg/l as NO3--N, without exceeding the drinking water threshold of ∼11.0 mg/l (as NO3--N). However, the water quality status was "poor" or "bad" in ∼50 % of the samples based on a local index, which considers the potential impact of nitrate on aquatic biological communities. The δ15Ν-ΝΟ3- and δ18O-NO3- values ranged from +4.4 ‰ to +20.3 ‰ and from -0.5 ‰ to +14.4 ‰, respectively. The application of a Bayesian model showed that the proportional contribution of organic pollution from industries, animal breeding facilities and manure fertilizers exceeded 70 % in most river sites with an overall uncertainty of ∼0.3 (UI90 index). The δ18O-NO3- and its relationship with δ18O-H2O revealed N-cycling and mixing processes, which were difficult to identify apart from the uptake of nutrients by phytoplankton during the growing season and metabolic activities. The strong correlation of δ15Ν-ΝΟ3- values with a Land Use Index (LUI) and a Point Source Index (PSI) highlighted not only the role of non-point nitrate sources but also of point sources of nitrate pollution on water quality degradation, which are usually overlooked. The nitrification of organic wastes is the dominant nitrate source in most rivers in Europe. The systematic monitoring of rivers for nitrate isotopes will help improve the understanding of N-cycling and the impact of these pollutants on ecosystems and better inform policies for protection measures so to achieve good ecological status.

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.

Sources and migration similarly determine nitrate concentrations: Integrating isotopic, landscape, and biological approaches

Rapid land use change has significantly increased nitrate (NO₃^-) loading to rivers, leading to eutrophication, and posing water security problems. Determining the sources of NO₃^- to waters and the underlying influential factors is critical for effectively reducing pollution and better managing water resources. Here, we identified the sources and influencing mechanisms of NO₃^- in a mixed land-use watershed by integrating stable isotopes (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-), molecular biology, water chemistry, and landscape metrics measurements. Weak transformation processes of NO₃^- were identified in the river, as evinced by water chemistry, isotopes, species compositions, and predicted microbial genes related to nitrogen metabolism. NO₃^- concentrations were primarily influenced by exogenous inputs (i.e., from soil nitrogen (NS), nitrogen fertilizer (NF), and manure & sewage (MS)). The proportions of NO₃^- sources seasonally varied. In the wet season, the source contributions followed the order of NS (38.6 %) > NF (31.4 %) > atmospheric deposition (ND, 16.2 %) > MS (13.8 %). In the dry season, the contributions were in the order of MS (39.2 %) > NS (29.2 %) > NF (29 %) > ND (2.6 %). Farmland and construction land were the original factors influencing the spatial distribution of NO₃^- in the wet and dry seasons, respectively, while slope, basin relief (HD), hypsometric integral (HI), and COHESION, HD were the primary indicators associated with NO₃^- transport in the wet and dry seasons, respectively. Additionally, spatial scale differences were observed for the effects of landscape structure on NO₃^- concentrations, with the greatest effect at the 1000-m buffer zone scale in the wet season and at the sub-basin scale in the dry season. This study overcomes the limitation of isotopes in identifying nitrate sources by combining multiple approaches and provides new research perspectives for the determination of nitrate sources and migration in other watersheds.