Identification of nitrate sources of groundwater and rivers in complex urban environments based on isotopic and hydro-chemical evidence

Contrasting nitrogen transport patterns in subtropical basins revealed by combined multiple isotopic analyzes and hydrological simulations

Although enhancing the knowledge of nitrogen (N) dynamics in aquatic systems is crucial for basin N management, there is still a lack of theories on the patterns of basin N sources and transport because of the intricate influence of human activities, climatic conditions, landscape patterns, and topography on the trajectory of basin N. To shed new light on the patterns of basin N sources and transport in the Chinese subtropical monsoon region, this study provides a comprehensive approach combining multiple isotopes and hydrological model based on monthly records of hydro-chemistry and isotopes (18O-NO3- /15N-NO-3 and 18O-H2O /2H-H2O) for river water, groundwater and rainfall in three basins over multiple years. Our observations of hydro-chemistry showed that fluvial N levels in highly urbanized basins (3.05 ± 1.42 mg·L-1) were the highest and were characterized by higher levels in the dry season. In the agricultural basin, fluvial N levels in February and March were approximately 1.9 times higher than those in the other months. The fluvial N load was higher in agricultural basins (0.624-0.728 T N km -2 y -1) than in urban basins (0.558 T N km -2 y -1), primarily because of variations in sewage treatment rates and fertilizer application. In highly urbanized basin, manure and sewage (46.9 %) were the dominant sources of fluvial N, which were discharged into rivers after treatment. In the plain agricultural basin, a substantial portion of diffused residential sewage leaches into aquifers and is stored. In the hilly agro-forest mixed basin, the high baseflow coefficient (75.8 %) and the key role of groundwater N, mainly from soil N (27.3 %), chemical fertilizers (20.2 %), manure and sewage (46.6 %), to fluvial N (26.5 %) indicated that a high proportion of the N sources leached into the aquifer and were then transported to rivers. For the first time, this study integrated multiple methods to substantiate the proposed typical patterns of N sources and transport within the basins. These findings have significant implications for tailored basin-specific N management strategies.

Mechanisms of evolution and pollution source identification in groundwater quality of the Fen River Basin driven by precipitation

Groundwater pollution has attracted widespread attention as a threat to human health and aquatic ecosystems. However, the mechanisms of pollutant enrichment and migration are unclear, and the spatiotemporal distributions of human health risks are poorly understood, indicating insufficient groundwater management and monitoring. This study assessed groundwater quality, human health risks, and pollutant sources in the Fen River Basin(FRB). Groundwater quality in the FRB is good, with approximately 87 % of groundwater samples rated as "excellent" or "good" in both the dry and rainy seasons. Significant precipitation elevates groundwater levels, making it more susceptible to human activities during the rainy season, slightly deteriorating water quality. Some sampling points in the southern of Taiyuan Basin are severely contaminated by mine drainage, with water quality index values up to 533.80, over twice the limit. Human health risks are mainly from As, F, NO3-, and Cr. Drinking water is the primary pathway of risk. From 2019 to 2020, the average non-carcinogenic risk of As, F, and NO3- increased by approximately 28 %, 170 % and 8.5 %, respectively. The average carcinogenic risk of As and Cr increased by 28 % and 786 %, the overall trend of human health risks is increasing. Source tracing indicates As and F mainly originate from geological factors, while NO3- and Cr are significantly influenced by human activities. Various natural factors, such as hydrogeochemical conditions and aquifer environments, and processes like evaporation, cation exchange, and nitrification/denitrification, affect pollutant concentrations. A multi-tracer approach, integrating hydrochemical and isotopic tracers, was employed to identify the groundwater pollution in the FRB, and the response of groundwater environment to pollutant enrichment. This study provides a scientific basis for the effective control of groundwater pollution at the watershed scale, which is very important in the Loess Plateau.

Modulation of soil nitrous oxide emissions and nitrogen leaching by hillslope hydrological processes

Soil nitrous oxide (N2O) emissions and nitrogen (N) leaching are key pathways for soil N loss in hillslope ecosystem, with potential implications for global warming and water body eutrophication. While soil N loss in hillslope ecosystem has been extensively studied, there is limited understanding of the spatiotemporal distribution patterns and factors driving soil N2O emissions and N leaching from a hillslope hydrology perspective. This study investigated N concentrations in leachate and soil N2O fluxes and their responses to soil hydrological factors on a tea plantation (TP) hillslope and a bamboo forest (BF) hillslope. Four distinct precipitation patterns-spring rainfall (SR), plum rain (PR), summer flood rain (SF), and drought period (DR)-were identified based on precipitation intensity, duration, and cumulative precipitation. Results showed that, soil N2O flux and leachate N concentrations were 8.2 times and 18.0 times higher On TP hillslope compared to the BF hillslope. The greatest soil N2O fluxes occurred during the PR period, while the lowest were observed during the DR period. Precipitation increased soil water content (SWC) and water-filled pore space, stimulating soil N cycling for N2O production. Fertilization activities and precipitation led to peak N concentration in leachate during the SR period. Additionally, soil wetness index (SWI) shaped spatial patterns of SWC, resulting in distinct spatial patterns of N2O emissions and nitrate leaching. Locations with higher SWI exhibited greater soil N2O flux and higher nitrate concentrations in leachate. This study emphasizes the significant effect of soil hydrological processes on soil N2O emissions and N leaching in hillslope ecosystems, providing valuable insights for N management in these environments.

Source-oriented health risk assessment of groundwater nitrate by using EMMTE coupled with HHRA model

Conventional concentration-oriented approaches for nitrate risk diagnosis only provide overall risk levels without identifying risk values of individual sources or sources accountable for potential health risks. Therefore, a hybrid model combining the end-member mixing model tool on Excel™ (EMMTE) with human health risk assessment (HHRA) was developed to assess the source-oriented health risks for groundwater nitrate, particularly in the Poyang Lake Plain (PLP) region. The results indicated that the EMMTE and the Bayesian stable isotope mixing model (MixSIAR) exhibited remarkable consistency in source apportionment of groundwater nitrate. The source contribution of groundwater nitrate in PLP was related to land use types, hydrogeological conditions, and soil properties. Notably, manure and sewage sources, contributing up to 53.4 %, represented the largest nitrate pollution sources, with a significant contribution of soil nitrogen and nitrogen fertilizers. The non-carcinogenic risk for four potential sources was below the acceptable threshold of 1. Given the factors including rainfall dilution and economic development, attention should be directed towards mitigating the health risks posed by manure and sewage. This study can verify the efficacy of EMMTE in source apportionment and offer valuable insights for decision-makers to regulate the largest sources of nitrate contamination and enhance groundwater management efficiency.

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.

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.

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).

Revealing the drivers and genesis of NO3-N pollution classification in shallow groundwater of the Shaying River Basin by explainable machine learning and pathway analysis method

Nitrate (NO3-N), as one of the ubiquitous contaminants in groundwater worldwide, has posed a serious threat to public health and the ecological environment. Despite extensive research on its genesis, little is known about the differences in the genesis of NO3-N pollution across different concentrations. Herein, a study of NO3-N pollution concentration classification was conducted using the Shaying River Basin as a typical area, followed by examining the genesis differences across different pollution classifications. Results demonstrated that three classifications (0-9.98 mg/L, 10.14-27.44 mg/L, and 28.34-136.30 mg/L) were effectively identified for NO3-N pollution using Jenks natural breaks method. Random forest exhibited superior performance in describing NO3-N pollution and was thereby affirmed as the optimal explanatory method. With this method coupling SEMs, the genesis of different NO3-N pollution classifications was proven to be significantly different. Specifically, strongly reducing conditions represented by Mn2+, Eh, and NO2-N played a dominant role in causing residual NO3-N at low levels. Manure and sewage (represented by Cl-) leaching into groundwater through precipitation is mainly responsible for NO3-N in the 10-30 mg/L classification, with a cumulative contribution rate exceeding 80 %. NO3-N concentrations >30 mg/L are primarily caused by the anthropogenic loads stemming from manure, sewage, and agricultural fertilization (represented by Cl- and K+) infiltrating under precipitation in vulnerable hydrogeological conditions. Pathway analysis based on standardized effect and significance further confirmed the rationality and reliability of the above results. The findings will provide more accurate information for policymakers in groundwater resource management to implement effective strategies to mitigate NO3-N pollution.

Selective adsorption of nitrate in water by organosilicon quaternary ammonium salt modified derived nickel-iron layered double hydroxide: Adsorption characteristics and mechanism

Nitrate (NO3-) is a widespread pollutant in the water environment. Due to its physicochemical properties, such as negative monovalent charge, traditional adsorption treatment processes have low selectivity for NO3- removal, resulting in low removal efficiency of NO3- by adsorbents in the presence of interfering ions. Therefore, to improve the adsorption selectivity and efficiency of NO3-. In this study, we used organosilicon quaternary modified derived nickel-iron layered double hydroxide (NiFe-MLDH/OQAS) for selective removal of NO3-. NiFe-MLDH/OQAS has a flowery globular structure, with interconnected nanosheets on the surface providing more adsorption sites for NO3-, which improves the adsorption rate and adsorption amount. What's more, the nitrate removal rate of NiFe-MLDH/OQAS only decreased by about 14.36% in the presence of the same concentration of interfering ions, and the maximum adsorption amount reached 61.05 mg/g, showing good selectivity and adsorption amount. Various characterization analyses indicate that the nitrate selectivity of NiFe-MLDH/OQAS is attributed to its unique layer spacing, as well as the abundant functional groups on the material surface. Finally, we demonstrated through experiments that NiFe-MLDH/OQAS has good cyclic regeneration ability and environmental safety. These findings demonstrate the great potential of NiFe-MLDH/OQAS for selective adsorption of NO3-.