Systematic tracing of nitrate sources in a complex river catchment: An integrated approach using stable isotopes and hydrological models

Integrating stable isotopes and hydrological models to track nitrogen sources and transport pathways in plateau watersheds: a case study in Southwest China

Exogenous nitrogen inputs from agriculture and anthropogenic activities have dramatically altered the material cycling processes in the Plateau watershed, leading to a range of water pollution issues. Effective management of nitrogen pollution in water bodies is predicated on clarifying N export loads under different pathways in the watershed, as well as the contributions of different sources. Here, this study proposes an integrated framework that introduces multiple stable isotope techniques (δD-H2O, δ18O-H2O, δ15N-NO3- and δ18O-NO3-) based on the coupled Eckhardt's digital baseflow filter (ECK) and load estimation model (LOADEST). The integrated approach was applied for the first time in a typical plateau watershed in southwest China. Results showed that baseflow as the Fengyu River watershed (FRW) major hydrologic pathway, provides 69.6 % of the mean annual stream flow and 59.1 % of the mean annual NO3--N load. Furthermore, the FRW average annual TN and NO3--N export is 94.0 t and 55.1 t, respectively. The NO3--N was the primary form of N pollutant, with its average concentration in groundwater being 7 times that in river water. In groundwater, manure and sewage (M&S) and soil nitrogen (SN) contribution rates to NO3--N 53.6 %, and 37.2 %, respectively. While the river water shows low M&S (26.8 %) and high SN (61.5 %) characteristics. It can be seen that the baseflow is a key pathway for coupled water-nitrogen export from plateau agricultural watersheds. Blocking the migration of nitrogen-containing pollutants to groundwater is an important measure to control the degradation of the water environment in plateau watersheds from the root cause.

Artificial regulation affects nitrate sources and transformations in cascade reservoirs by altering hydrological conditions

Reservoirs are recognized as pivotal zones within the nitrate cycle, substantially modifying the source-sink dynamics of nitrate in fluvial systems. However, the impact of hydrological alterations induced by artificial regulation on nitrate sources and transformation processes in cascade hydropower reservoirs remains insufficiently comprehended. Consequently, we investigated the spatiotemporal characteristics of nitrate concentrations, δ15NNO3, δ18ONO3, δD, Δ17OH2O, relative water column stability (RWCS), runoff, and associated environmental factors within cascade reservoirs along the Wujiang River in Southwest China. The Bayesian stable isotope mixing model (MixSIAR) identified manure and sewage (M&S) as the predominant source of untreated nitrate (43.5 %) in the cascade reservoirs, with soil organic nitrogen (SON, 27.2 %), chemical fertilizer (CF, 18.5 %), and atmospheric precipitation (AP, 10.8 %) following in significance. However, evidence derived from δ15NNO3 and Δ17O isotopic values indicates that the contribution of nitrate produced by nitrification within the water body has been overlooked, accounting for 59 % in January, 40 % in July, and 24 % in October. Furthermore, the coupling of nitrification and assimilation emerged as the predominant process for nitrate transformation within the cascade reservoirs. This process was primarily regulated by RWCS and runoff (p < 0.01), indicating a substantial hydrological influence on the nitrogen cycle. This research quantifies the contribution of nitrate originating from the nitrification process within cascade reservoirs, while also addressing the limitations inherent in the traditional MixSIAR model. Additionally, it advances our comprehension of the impacts of hydrological conditions and thermal stratification on the nitrate cycle in reservoirs worldwide.

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.

Quantifying the environmental fate and source of nitrate contamination using dual-isotope tracing coupled with nitrogen cascade model on the basin scale

Nitrate (NO3-) contamination in riverine networks has threatened the environment and human health. Clarifying the NO3- source and environmental fate within the basin under different underlying surfaces is essential for water body protection, especially China's two mother rivers. A series of combination methods were established i.e., field survey, index measurements, isotope-tracing techniques, and material flow analysis in four typical basins to investigate the spatiotemporal variation and source of NO3- pollution and nitrogen cascade characteristics. The dual-isotope coupled with MixSIAR model revealed that manure and sewage were the major NO3- source in the irrigation basin (WY, 76.7 %), hilly mountainous basin (YC, 52.3 %), and plateau lake basin (DC, 48.7 %). However, for the plain-river network basin (CZ), soil leachate was the main source (55.5 %). In terms of the N losses to water within agri-environment system, livestock-breeding system in three basins made the biggest contribution among the systems, WY (77.3 %), YC (47.3 %), and DC (41.8 %). While in CZ, about 34.4 % of N was delivered from the crop-production system. The N cascade model verified the results of isotope-tracing techniques for each basin. The study provides new insight into NO3--tracing combining hydrogeochemical indicators, isotopic-tracing techniques, and material flow analysis and guides strategies for mitigating the negative impacts of NO3- pollution on aquatic environments on basin scale.

Identifying the hotspots of nitrate leaching and its key driving factors in the Yellow River Delta using DNDC model

The issue of nitrate leaching poses a substantial risk to the safety of groundwater resources. A critical aspect of mitigating this risk involves the quantification of the spatial heterogeneity of nitrate leaching and the identification of its primary drivers. In the present study, we developed a county-level DNDC database for the year 2020, specifically for the Yellow River Delta. This database was utilized to simulate the spatial distribution of nitrate leaching. Furthermore, we employed GWR to analyze the principal factors driving nitrate leaching. Our findings revealed considerable spatial variations in nitrate leaching, with an average value of 40.31 kg N ha-1. Wudi and Hekou emerged as areas of low risk for nitrate leaching, while the remaining 17 districts were identified as high-risk areas. The spatial heterogeneity of nitrate distribution was primarily attributed to the heterogeneity of the driving factors. The absolute values of the regression coefficients for these factors were ranked in the following order: clay content > pH > organic fertilizer > chemical fertilizer > rainfall > nitrogen deposition. Based on these findings, we propose an optimal management practice that involves a 20% reduction in the use of both chemical and organic fertilizers. This approach could potentially result in a 43.8% decrease in nitrate leaching, with a minimal 3% reduction in crop yield. The insights gained from our research offer a scientific foundation for the development of a management strategy that balances economic considerations with environmental protection.

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.

Utilization and applications of stable isotope analysis for wastewater treatment systems: A review

Stable isotopic analysis (SIA), traditionally crucial in ecological and geochemical studies, has recently expanded its applications to include wastewater management among other fields. This method is instrumental in verifying natural attenuation processes and deepening understanding of operations within engineering systems, such as groundwater, drinking water, and wastewater treatment. This review explores recent advancements in SIA, emphasizing its significance and potential applications in wastewater treatment. We highlight how this analysis can trace various sources within wastewater treatment processes, elucidate the mechanisms responsible for organic matter and nutrient removal in biological treatments, and facilitate the analysis of microbial communities. The review discusses a wide range of isotopic analytical methods, from bulk analysis and compound-specific approaches, covering sample preparation and extraction techniques. We also examine advanced tools like gas chromatography - isotope ratio mass spectrometer (IRMS) and liquid chromatography-IRMS which enhance the accuracy of source identification and address the limitations of bulk analysis. Literature shows a positive correlation between δ15N assimilation in activated sludge and nitrogen removal performance in reactors. Additionally, the review assesses the role of SIA in identifying active microbes involved in the degradation of specific pollutants in biological wastewater treatment. Finally, we discuss current limitations of SIA in wastewater treatment and propose potential research directions to broaden its applicability.

Integrative modeling of POPs output flux from soil at a regional scale: A comprehensive approach

Plot-scale natural attenuation models provide valuable insights into localized pollutant behavior but struggle to account for regional-scale hydrological processes. Existing research has predominantly concentrated on single processes, lacking comprehensive models to describe the output flux of persistent organic pollutants (POPs) by transport and transformation from soil at a regional scale. To address this gap, a model was developed by combining natural attenuation processes (e.g., degradation, volatilization, plant uptake) with hydrological transport processes (e.g., leaching, water washout, sediment transport). The model was validated using data from a petrochemical area in China and compared with the previous model (mass balance and neural networks model) to assess pollutant output flux. Results indicated that water washout was the dominant output pathway from soil for both Phenanthrene (Phe) (94.67 %) and Benzo(a)pyrene (BaP) (98.33 %). Phe exhibited a broader output flux range (0-67.8 mg∙m-2∙a-1) compared to BaP (0-12.9 mg∙m-2∙a-1), due to its higher volatility and solubility. Performance evaluation through 10-fold cross-validation yielded coefficient of determination (R2) values greater than 0.7 and root mean square error (RMSE) below 3 %, outperforming the previous model. Sensitivity analysis revealed that the soil organic carbon mass fraction (foc) was the most influential parameter at both a plot and regional scale. This study fills a gap in environmental research by providing a comprehensive model for accurate estimates of POPs output fluxes from soil.

Unravelling nitrate transformation mechanisms in karst catchments through the coupling of high-frequency sensor data and machine learning

Nitrate dynamics within a catchment are critical to the earth's system process, yet the intricate details of its transport and transformation at high resolutions remain elusive. Hydrological effects on nitrate dynamics in particular have not been thoroughly assessed previously and this knowledge gap hampers our understanding and effective management of nitrogen cycling in watersheds. Here, machine learning (ML) models were employed to reconstruct the annual variation trend in nitrate dynamics and isotopes within a typical karst catchment. Random forest model demonstrates promising potential in predicting nitrate concentration and its isotopes, surpassing other ML models (including Long Short-term Memory, Convolutional Neural Network, and Support Vector Machine) in performance. The ML-modeled NO3--N concentrations, δ15N-NO3-, and δ18O-NO3- values were in close agreement with field data (NSE values of 0.95, 0.80, and 0.53, respectively), which are notably challenging to achieve for process models. During the transition from dry to wet period, approximately 23.0 % of the annual precipitation (∼269.1 mm) was identified as the threshold for triggering a rapid response in the wet period. The modeled nitrate isotope values were significantly supported by the field data, suggesting seasonal variations of nitrogen sources, with precipitation as the primary driving force for fertilizer sources. Mixing of multiple sources appeared to be the main control of the transport and transformation of nitrate during the rising limb in the wet period, whereas process control (denitrification) took precedence during the falling limb, and the fate of nitrate was controlled by biogeochemical processes during the dry period.

Using surface runoff to reveal the mechanisms of landscape patterns driving on various forms of nitrogen in non-point source pollution

Non-point source (NPS) pollution directly threatens river water quality, constrains sustainable economic development, and poses hazards to human health. Comprehension of the impact factors on NPS pollution is essential for scientific river water quality management. Despite the landscape pattern being considered to have a significant impact on NPS pollution, the driving mechanism of landscape patterns on NPS pollution remains unclear. Therefore, this study coupled multi-models including the Soil and Water Assessment Tool (SWAT), Random Forest, and Partial Least Squares Structural Equation Modeling (PLS-SEM) to construct the connection between landscape patterns, NPS pollution, and surface runoff. The results suggested that increased runoff during the wet season enhances the link between landscape patterns and NPS pollution, and the explained NPS pollution variation by landscape pattern increased from 59.6 % (dry season) to 84.9 % (wet season). Furthermore, from the impact pathways, we find that the sink landscape pattern can significantly and indirectly influence NPS pollution by regulating surface runoff during the wet season (0.301*). Meanwhile, the sink and source landscape patterns significantly and directly impact NPS pollution during different seasons. Moreover, we further find that the percentage of paddy land use (Pad_PLAND) and grassland patch density (Gra_PD) metrics can significantly predict the dissolved total nitrogen (DTN) and nitrate nitrogen (NO3--N) variation. Thus, controlling the runoff migration process by guiding the rational evolution of watershed landscape patterns is an important development direction for watershed NPS pollution management.

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.

Exposure to zinc and dialkyldimethyl ammonium compound alters bacterial community structure and resistance gene levels in partial sulfur autotrophic denitrification coupled with the Anammox process

Dialkyldimethyl ammonium compound (DADMAC) is widely used in daily life as a typical disinfectant and often co-exists with the heavy metal zinc in sewage environments. This study investigated the effects of co-exposure to zinc (1 mg/L) and DADMAC (0.2-5 mg/L) on the performance, bacterial community, and resistance genes (RGs) in a partial sulfur autotrophic denitrification coupled with anaerobic ammonium oxidation (PSAD-Anammox) system in a sequencing batch moving bed biofilm reactor for 150 days. Co-exposure to zinc and low concentration (0.2 mg/L) DADMAC did not affect the nitrogen removal ability of the PASD-Anammox system, but increased the abundance and transmission risk of free RGs in water. Co-exposure to zinc and medium-to-high (2-5 mg/L) DADMAC led to fluctuations in and inhibition of nitrogen removal, which might be related to the enrichment of heterotrophic denitrifying bacteria dominated by Denitratisoma. Co-exposure to zinc and high concentration DADMAC (5 mg/L) stimulated the secretion of extracellular polymeric substances and increased the proliferation risk of intracellular RGs in sludge. This study provided insights into the application of PSAD-Anammox system and the ecological risks of wastewater containing zinc and DADMAC.

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.

Nitrate transformation and source tracking of Yarlung Tsangpo River using a multi-tracer approach combined with Bayesian stable isotope mixing model

Excessive levels of nitrate nitrogen (NO3--N) could lead to ecological issues, particularly in the Yarlung Tsangpo River (YTR) region located on the Qinghai Tibet Plateau. Therefore, it is crucial to understand the fate and sources of nitrogen to facilitate pollution mitigation efforts. Herein, multiple isotopes and source resolution models were applied to analyze key transformation processes and quantify the sources of NO3-. The δ15N-NO3- and δ18O-NO3- isotopic compositions in the YTR varied between 1.23‰ and 13.64‰ and -7.88‰-11.19‰, respectively. The NO3--N concentrations varied from 0.08 to 0.86 mg/L in the dry season and 0.20-1.19 mg/L during the wet season. Nitrification remained the primary process for nitrogen transformation in both seasons. However, the wet season had a widespread effect on increasing nitrate levels, while denitrification had a limited ability to reduce nitrate. The elevated nitrate concentrations during the flood season were caused by increased release of NO3- from manure & sewage (M&S) and chemical fertilizers (CF). Future endeavors should prioritize enhancing management strategies to improve the utilization efficiency of CF and hinder the direct entry of untreated sewage into the water system.

The interplay of hematite and photic biofilm triggers the acceleration of biotic nitrate removal

The soil-water interface is replete with photic biofilm and iron minerals; however, the potential of how iron minerals promote biotic nitrate removal is still unknown. This study investigates the physiological and ecological responses of photic biofilm to hematite (Fe2O3), in order to explore a practically feasible approach for in-situ nitrate removal. The nitrate removal by photic biofilm was significantly higher in the presence of Fe2O3 (92.5%) compared to the control (82.8%). Results show that the presence of Fe2O3 changed the microbial community composition of the photic biofilm, facilitates the thriving of Magnetospirillum and Pseudomonas, and promotes the growth of photic biofilm represented by the extracellular polymeric substance (EPS) and the content of chlorophyll. The presence of Fe2O3 also induces oxidative stress (•O2-) in the photic biofilm, which was demonstrated by electron spin resonance spectrometry. However, the photic biofilm could improve the EPS productivity to prevent the entrance of Fe2O3 to cells in the biofilm matrix and mitigate oxidative stress. The Fe2O3 then promoted the relative abundance of Magnetospirillum and Pseudomonas and the activity of nitrate reductase, which accelerates nitrate reduction by the photic biofilm. This study provides an insight into the interaction between iron minerals and photic biofilm and demonstrates the possibility of combining biotic and abiotic methods to improve the in-situ nitrate removal rate.

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.

Response of microbial communities to exogenous nitrate nitrogen input in black and odorous sediment

Since nitrate nitrogen (NO3--N) input has proved an effective approach for the treatment of black and odorous river waterbody, it was controversial whether the total nitrogen concentration standard should be raised when the effluent from the sewage treatment plant is discharged into the polluted river. To reveal the effect of exogenous nitrate (NO3--N) on black odorous waterbody, sediments with different features from contaminated rivers were collected, and the changes of physical and chemical characteristics and microbial community structure in sediments before and after the addition of exogenous NO3--N were investigated. The results showed that after the input of NO3--N, reducing substances such as acid volatile sulfide (AVS) in the sediment decreased by 80 % on average, ferrous (Fe2+) decreased by 50 %, yet the changing trend of ammonia nitrogen (NH4+-N) in some sediment samples increased while others decreased. High-throughput sequencing results showed that the abundance of Thiobacillus at most sites increased significantly, becoming the dominant genus in the sediment, and the abundance of functional genes in the metabolome increased, such as soxA, soxX, soxY, soxZ. Network analysis showed that sediment microorganisms evolved from a single sulfur oxidation ecological function to diverse ecological functions, such as nitrogen cycle nirB, nirD, nirK, nosZ, and aerobic decomposition. In summary, inputting an appropriate amount of exogenous NO3--N is beneficial for restoring and maintaining the oxidation states of river sediment ecosystems.

Simulation of spatial and temporal variation of nitrate leaching in the vadose zone of alluvial regions on a large regional scale

Excessive use of fertilizers presents a significant threat to groundwater safety. To mitigate nitrate leaching and ensure the sustainable utilization of groundwater resources, it is crucial to quantify the spatial heterogeneity of nitrogen leaching and its drivers. Therefore, accurate modeling of deep nitrate leaching at large regional scales is necessary. In this study, we have created a computational framework to analyze the transport of unsaturated zone water and nitrate at a regional scale. The framework is based on a process-oriented, watershed-scale computational model that segments the study area into a grid system, with each grid modeled using Richards-based advection-diffusion equations for water and solutes. The research model estimated nitrate nitrogen leaching, accumulation, and denitrification in the vadose zone of agricultural fields in the Baiyangdian watershed, which is a typical agricultural region with complex land use and soil deposition conditions in the North China Plain. The results showed that there were significant spatial differences in nitrate N leaching, denitrification and accumulation with values of 0-388 kg/ha/year, 30-177 kg/ha/year and 75-4778 kg/ha. Groundwater recharge in the wheat/maize, vegetable, and cotton area exhibited a negative correlation with nitrate N accumulation while showing a positive correlation with nitrate N leaching. Nitrate nitrogen distribution indicated spatial heterogeneity, attributable mainly to the heterogeneity in soil texture, structure, and land use. With nitrate nitrogen leaching and denitrification levels reaching 327-388 kg/ha/year and 133-175 kg/ha/year, respectively, vegetable fields pose a direct threat to groundwater. Meanwhile, wheat/maize fields showed the greatest nitrate nitrogen accumulation, ranging from 624 to 4778 kg/ha. This excessive buildup of nitrate in these fields presents a potential hazard to groundwater quality. Soil texture in the root zone had a greater influence on the amount of nitrate leaching and denitrification than soil texture below the root zone. Deeper soil texture (>2 m) was found to mainly control total nitrate accumulation in the vadose zone. To assess nitrate leaching, denitrification, and accumulation at a regional scale within the deep vadose zone, a process-oriented model was developed, considering the intricate associations among land usage, soil texture, and biochemical reactions.

The effects of heavy rain on the fate of urban and agricultural pollutants in the riverside area around weirs using multi-isotope, microbial data and numerical simulation

The increase in extreme heavy rain due to climate change is a critical factor in the fate of urban and agricultural pollutants in aquatic system. Nutrients, including NO3- and PO43-, are transported with surface and seepage waters into rivers, lakes and aquifers and can eventually lead to algal blooms. δ15N-NO3-, δ18O-NO3-, and δ11B combined with hydrogeochemical and microbial data for groundwater and surface water samples were interpreted to evaluate the fate of nutrients in a riverside area around weirs in Daegu, South Korea. Most of the ions showed similar concentrations in the groundwater samples before and after heavy rain while concentrations of major ions in surface water samples were diluted after heavy rain. However, Si, PO43-, Zn, Ce, La, Pb, Cu and a number of waterborne pathogens increased in surface water after heavy rain. The interpretation of δ11B, δ15N-NO3-, and δ18O-NO3- values using a Bayesian mixing model revealed that sewage and synthetic fertilizers were the main sources of contaminants in the groundwater and surface water samples. δ18O and SiO2 interpreted using the Bayesian mixing model indicated that the groundwater component in the surface water increased from 4.4 % to 17.9 % during the wet season. This is consistent with numerical simulation results indicating that the direct surface runoff and the groundwater baseflow contributions to the river system had also increased 6.4 times during the wet season. The increase in proteobacteria and decrease of actinobacteria in the surface water samples after heavy rain were also consistent with an increase of surface runoff and an increased groundwater component in the surface water. This study suggests that source apportionment based on chemical and multi-isotope data combined with numerical modeling approaches can be useful for identifying main hydrological and geochemical processes in riverside areas around weirs and can inform suggestions of effective methods for water quality management.

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.

Current trends and challenges in the analysis of marine environmental contaminants by isotope ratio mass spectrometry

An increasing number of organic and inorganic pollutants are being detected in the marine environment, posing a severe threat to the ecosystem and human health, even in trace concentrations. Isotope ratio mass spectrometry (IRMS) is one of the critical methods for determining the origin and fate of environmental pollutants and characterising their transformation processes. It has been used for a relatively long time for ecological monitoring of some well-studied industrial hydrocarbons at contaminated sites. However, the method still faces many analytical challenges. This review provides a comprehensive overview of recent technical advances concerning IRMS analysis of various contaminants and discusses typical pitfalls encountered in marine environment analysis. Particular attention is given to the study of sampling techniques and sample preparation for examination, often the keys to successful research given the complexity of marine matrices and the diverse and numerous nature of contaminants. Prospects for developing IRMS to monitor pollution sources and pollutant transformation in the marine environment are outlined.

The distinct phases of fresh-seawater mixing intricately regulate the nitrogen transformation processes in a high run-off estuary: Insight from multi-isotopes and microbial function analysis

Excessive anthropogenic nitrogen inputs lead to the accumulation of nitrogen, and significantly impact the nitrogen transformation processes in estuaries. However, the governing of nitrogen during its transport from terrestrial to estuary under the influence of diverse human activities and hydrodynamic environments, particularly in the fresh-seawater mixing zone, remains insufficient researched and lack of basis. To address this gap, we employed multi-isotopes, including δ15N-NO3-, δ18O-NO3-, δ15N-NH4+, and δ15N-PN, as well as microbial function analysis, to investigate the nitrogen transformation processes in the Pearl River Estuary (PRE), a highly anthropogenic and terrestrial estuary. Principle component analysis (PCA) confirmed that the PRE could clearly partitioned into three zone, e.g., terrestrial area (T zone), mixing area (M zone) and seawater area (S zone), in terms of nitrogen transportation and transformation processes. The δ15N-NO3- (3.38±0.60‰) and δ18O-NO3- (6.35±2.45‰) results in the inner estuary (T area) indicate that NO3-attributed to the domestic sewage and groundwater discharge in the river outlets lead to a higher nitrification rate in the outlets of the Pearl River than in the reaching and seawater intrusion areas, although nitrate is rapidly diluted by seawater after entering the estuary. The transformation of nitrogen in the T zone was under significant nitrogen fixation (0.61 ± 0.22 %) and nitrification processes (0.0043 ± 0.0032 %) (presumably driven by Exiguobacterium sp. (14.1 %) and Cyanobium_PCC-6307 (8.1 %)). In contrast, relatively low δ15N-NO3- (6.83 ± 1.24‰) and high δ18O-NO3- (22.13±6.01‰) imply that atmospheric deposition has increased its contribution to seawater nitrate and denitrification (0.53±0.13 %) was enhanced by phytoplankton/bacterial (such as Psychrobacter sp. and Rhodococcus) in the S zone. The assimilation of NH4 results from the ammonification of NO3- reduces δ15N-NH4+ (5.36 ± 1.49‰) and is then absorbed by particulate nitrogen (PN). The retention of nitrogen when fresh-seawater mixing enhances the elevation of δ15N-NH4+ (8.19 ± 2.19‰) and assimilation of NH4+, leading to an increase in PN and δ15N-PN (6.91 ± 1.52‰) from biological biomass (mainly Psychrobacter sp. and Rhodococcus). The results of this research demonstrate a clear and comprehensive characterization of the nitrogen transformation process in an anthropogenic dominated estuary, highlighting its importance for regulating the nitrogen dissipation in the fresh-seawater mixing process in estuarine ecosystems.

Spatio-temporal analysis of the sources and transformations of anthropogenic nitrogen in a highly degraded coastal basin in Southeast China

Nitrogen transport from terrestrial to aquatic environments could cause water quality deterioration and eutrophication. By sampling in the high- and low-flow periods in a highly disturbed coastal basin of Southeast China, hydrochemical characteristics, nitrate stable isotope composition, estimation of potential nitrogen source input fluxes, and the Bayesian mixing model were combined to determine the sources and transformation of nitrogen. Nitrate was the main form of nitrogen. Nitrification, nitrate assimilation, and NH4+ volatilization were the main nitrogen transformation processes, whereas denitrification was limited due to the high flow rate and unsuitable physicochemical properties. For both sampling periods, non-point source pollution from the upper to the middle reaches was the main source of nitrogen, especially in the high-flow period. In addition to synthetic fertilizer, atmospheric deposition and sewage and manure input were also major nitrate sources in the low-flow period. Hydrological condition was the main factor determining nitrate transformation in this coastal basin, despite the high degree of urbanization and the high volume of sewage discharge in the middle to the lower reaches. The findings of this study highlight that the control of agricultural non-point contamination sources is essential to pollution and eutrophication alleviation, especially for watersheds that receive high amounts of annual precipitation.