Apportionment and uncertainty analysis of nitrate sources based on the dual isotope approach and a Bayesian isotope mixing model at the watershed scale

A multidisciplinary approach using hydrogeochemistry, δ15NNO3 isotopes, land use, and statistical tools in evaluating nitrate pollution sources and biochemical processes in Costa Rican volcanic aquifers

Nitrate pollution threatens the Barva and Colima multi-aquifer system, the primary drinking water source in the Greater Metropolitan Area of Costa Rica. In addressing nitrate contamination dynamics, this study proposes an integrated approach by combining multivariate statistical analyses, hydrochemical parameters, sewage discharge, and regional land-use and land-cover patterns to assess the extent and degree of contamination, dominant biogeochemical processes, and refine the interpretation of nitrate sources previously derived solely from δ15NNO3 information. Over seven years (2015-2022), 714 groundwater samples from 43 sites were analyzed for nitrate and major ions, including two sampling campaigns for dissolved organic and inorganic carbon, nitrite, ammonium, FeTotal, MnTotal, and δ15NNO3 analyses. The findings presented elevated nitrate concentrations in urban and agricultural/urban areas, surpassing the Maximum Concentration Levels on several occasions, and oxidizing conditions favoring mineralization and nitrification processes in unconfined Barva and locally confined Upper Colima/Lower Colima aquifers. Similar nitrate contents and spatial patterns in agricultural and urban zones in the shallow Barva aquifer suggest comparable contributions from nitrogen fertilizers and urban wastewaters despite the gradual increase in urban land cover and the reduction of agricultural areas. Isotopic analyses and dissolved organic carbon (DOC) indicate a shift in nitrate sources from agricultural to urban areas in both Barva and Colima aquifers. Principal Component and Hierarchical Cluster Analyses link land use, nitrate sources, and water quality. Three distinct sample clusters aligned with forest/grassland, agricultural/urban, and urban land use, emphasizing the impact of anthropogenic activities on groundwater quality, even in the deeper Colima aquifers. The study challenges nitrate isotope mixing models, enhancing accuracy in identifying pollution sources and assessing the spatial extent of contamination by incorporating DOC and other hydrochemical parameters. Similar outcomes, with and without the use of nitrate isotopes, reinforce the usefulness of the integrated approach, providing a practical and cost-effective alternative.

New insights into the controlling factors of nitrate spatiotemporal characteristics in groundwater of Dagu aquifer in Qingdao, China

Identifying spatiotemporal variation of groundwater NO3-N and its primary controlling factors are vital for groundwater protection. This study, under the data scarce conditions and based on time series monitoring data in Dagu aquifer, applied methods including hydrochemical ion ratio, multiple linear regression, support vector regression and grey relational analysis and dedicated to revealing primary controlling factors of temporal variation patterns of groundwater NO3-N. The results showed that agricultural and manure fertilizer are the main sources of NO3-N in north and central area (vegetable farming area), and that domestic sewage discharge and manure fertilizer are the main sources of NO3-N in south area (residential and grain planting area). In addition, results identified the dominant influencing factors of variation of NO3-N in different regions, with human wastewater discharge, nitrogen load amount and water-table depth being the dominant factors of variations of NO3-N in north area, human wastewater discharge being the main factor of variations of NO3-N in central area, and irrigation water and human wastewater being the leading factors of variations of NO3-N in south area. Moreover, types of controlling factors can influence the seasonal variations of NO3-N. NO3-N in vegetable farming area that dominantly affected by fertilization generally shows higher concentration and larger variation range of concentration during summer and autumn than that during spring. NO3-N which mainly affected by human wastewater discharge and manure inputs shows minimal seasonal variation of mean concentration. NO3-N in grain area influenced by irrigation could show more significant variations during spring and autumn than that during summer. The conclusions can enhance understandings of major influencing factors on NO3-N variation in local aquifer. Importantly, the dominant roles of water-table depth and irrigation in NO3-N variation of N2 site (vegetable planting area) and S5 site (grain planting area), respectively, were highlighted.

Dissolved N pollution and its biogeochemical constraints along a river-sea continuum of a typical dense oyster mariculture coastal water, northwest South China Sea

Dissolved nutrients, including nitrate (NO3--N) and its dual isotopes (δ15N-NO3- and δ18O-NO3-) were systematically studied along a river-sea continuum, wherein dense oyster mariculture is implemented, to constrain the pollution sources and biogeochemical cycling mechanisms of nitrogen (N). Total dissolved N, mainly composed of inorganic N, showed strong anthropogenic influence. Based on MixSIAR model results, N pollution was predominantly sourced from sewage/wastewater (55.9-64.3 %). Nutrient stoichiometry revealed DIP and DSi stress, and surface water in the riverine region was severely eutrophic. The occurrences of eutrophication and changes in nutrient stoichiometry were significantly related to N pollution sources in both summer and winter. N dynamics were controlled by anthropogenic activities and physical mixing. However, due to the insignificance of biological processes such as denitrification, phytoplankton assimilation, N2 fixation, and nitrification, including the lack of significant isotopic fractionation associated with these processes, and the poor fit of both the Rayleigh Model and Open system Model to the measured data, it is speculated that the several-fold reduction in N load and eutrophication along the river-sea continuum could be attributed to a combination of significant N removal by dense oyster mariculture and nutrient dilution due to physical mixing of river and seawater during winter and summer.

Tracing Nitrogen Sources and Transformation Characteristics in a Large Basin with Spatially Heterogeneous Pollution Distribution

This study used dual stable isotope analysis to examine nitrate sources and geographical distribution in the Liao River Basin (LRB), one of China's seven major river basins. During a normal hydrological season in April 2021, water samples were taken from the main streams of the Liao River (MLR), Shuangtaizi River (STR), Hun River (HR), Taizi River (TZR), and Daliao River (DLR). Monitoring results indicated that 93% of the water samples had a total nitrogen level exceeding the Class IV limit (1.5 mg/L) of the 'Environmental Quality Standards (EQS) for surface water', indicating a serious nitrogen pollution status. 71.3% of the total nitrogen on average was in the form of nitrate. The scatterplots of δD-H2O and δ18O-H2O showed that water in TZR and DLR were mainly affected by precipitation, while MLR, STR and HR were additionally impacted by evaporation and groundwater. The overall δ15N and δ18O of NO3- varied from 7.7‰ to 17.9‰ and 0.6‰ to 11.2‰, respectively. The correlations between δ15N-NO3- and δ18O-NO3-, along with attribution results from the Bayesian isotopic mixing model, indicated a predominant role of manure/sewage (MS) pollution in affecting river nitrate, accounting for 78% of total nitrate in MLR and 72% in DLR. A positive correlation between δ15N-NO3- and δ18O-NO3- in MLR indicated the occurrence of denitrification process. Overall, attribution results showed that the primary nitrate sources varied in different river systems within such a large basin, mainly due to spatially varied land use and human activities. Tailored nitrogen management strategies should be implemented to address the main anthropogenic pressures.

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.

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.

Microbial nitrogen transformations tracked by natural abundance isotope studies and microbiological methods: A review

Nitrogen is an essential nutrient in the environment that exists in multiple oxidation states in nature. Numerous microbial processes are involved in its transformation. Knowledge about very complex N cycling has been growing rapidly in recent years, with new information about associated isotope effects and about the microbes involved in particular processes. Furthermore, molecular methods that are able to detect and quantify particular processes are being developed, applied and combined with other analytical approaches, which opens up new opportunities to enhance understanding of nitrogen transformation pathways. This review presents a summary of the microbial nitrogen transformation, including the respective isotope effects of nitrogen and oxygen on different nitrogen-bearing compounds (including nitrates, nitrites, ammonia and nitrous oxide), and the microbiological characteristics of these processes. It is supplemented by an overview of molecular methods applied for detecting and quantifying the activity of particular enzymes involved in N transformation pathways. This summary should help in the planning and interpretation of complex research studies applying isotope analyses of different N compounds and combining microbiological and isotopic methods in tracking complex N cycling, and in the integration of these results in modelling approaches.

The impact of algal blooms on promoting in-situ N2O emissions: A case in Zhanjiang bay, China

Under the influence of many factors, such as climate change, anthropogenic eutrophication, and the development of aquaculture, the area and frequency of algal blooms have showed an increasing trend worldwide, which has become a challenging issue at present. However, the coupled relationship between nitrous oxide (N2O) and algal blooms and the underlying mechanisms remain unclear. To address this issue, 15N isotope cultures and quantitative polymerase chain reaction (qPCR) experiments were conducted in Zhanjiang Bay during algal and non-algal bloom periods. The results showed that denitrification and nitrification-denitrification were the two processes responsible for the in-situ production of N2O during algal and non-algal bloom periods. Stable isotope rate cultivation experiments indicated that denitrification and nitrification-denitrification were promoted in the water during the algal bloom period. The in-situ production of N2O during the algal bloom period was three-fold that during the non-algal bloom period. This may be because fresh particulate organic matter (POM) from the organisms responsible for the algal bloom provides the necessary anaerobic and hypoxic environment for denitrification and nitrification-denitrification in the degradation environment. Additionally, a positive linear correlation between N2O concentrations and ammonia-oxidizing bacteria (AOB) and denitrifying bacteria (nirK and nirS) also supported the significant denitrification and nitrification-denitrification occurring in the water during the algal bloom period. However, the algal bloom changed the main process for the in-situ production of N2O, wherein it shifted from denitrification during the non-algal bloom period to nitrification-denitrification during the algal bloom period. The results of our study will improve our understanding of the processes responsible for the in-situ production of N2O during the algal bloom period, and can help formulate effective policies to mitigate N2O emissions in the bay.

Tracing nitrate origins and transformation processes in groundwater of the Hohhot Basin's Piedmont strong runoff zone through dual isotopes and hydro-chemical analysis

Nitrate, which poses a serious threat to the drinking water supply, is one of the most prevalent anthropogenic groundwater contaminants worldwide. With the development of the chemical industry, the nitrate pollution of groundwater in the Piedmont strong runoff zone of the Hohhot Basin, which is the main groundwater extraction area, is becoming increasingly severe. The special hydrogeological and complex pollution conditions in the study area make it difficult to identify nitrate sources and transformation processes. In order to identify the results more accurately, this study combined water chemistry, multivariate statistical analysis and isotope tracer methods to determine the sources and transformation processes of nitrate in the study area. The results showed that the groundwater in the eastern part of the study area (ESA) was clearly affected by anthropogenic activities, and its nitrate was mainly from nitrification of ammonia in industrial wastewater, nitrate in industrial wastewater (the sum of the two contributions was 62.2 %), and nitrate in manure (20.5 %). The hydrogeochemical characteristics of groundwater in the western part of the study area (WSA) are the same as those of natural groundwater in the Piedmont strong-runoff zone. The nitrate in groundwater in the WSA was mainly derived from soil nitrogen (63.8 %) and ammonia fertilizer (28.8 %). Nitrification and denitrification occurred only locally in the aquifer of the study area and were more pronounced in the ESA. Meanwhile, the transformation processes of nitrate in groundwater in the ESA and WSA was significantly influenced by contamination with chlorinated hydrocarbon volatile organic compounds and hydrogeological conditions, respectively. These findings provide a scientific basis for the development of groundwater pollution prevention measures in the study area and guide the traceability of nitrate in groundwater in areas with similar hydrogeological and pollution conditions.

Storm-induced nitrogen transport via surface runoff, interflow and groundwater in a pomelo agricultural watershed, southeast China

The storm-induced export of nitrogen (N) from agricultural watersheds significantly impacts aquatic ecosystems, yet the mechanisms of source supply and transport behind N species remain unclear. Here, we investigated the hydrological factors influencing the timing and magnitude of river N species export in a Chinese pomelo agricultural watershed. We conducted continuous observations of watershed hydrology, N species, and their isotopic ratios along a soil-groundwater-river continuum during two storm events in 2018-2019. We found the export flux of river NO3-N covers ∼80% of the total N flux during storms, and the rest for other N species. Our results further revealed distinct pathways and timing of N transport among different N species, especially between ammonium N (NH4-N) and nitrate N (NO3-N). NH4-N in stormflow predominantly originates from sewage and soil leachate, rapidly transported via surface runoff and interflow. Orchard fertilization (contributed 41-56% based on SIAR analysis) was the major source of river NO3-N, which underwent initial dilution via surface runoff and subsequently became enriched through delayed discharge of soil leachate and groundwater. The variations in timing and magnitude of N transport between storms can be explained by antecedent conditions such as precipitation, soil N pools, and storm size. These findings emphasize the hydrological controls on N export from agricultural watersheds, and highlight the variations in source supply and transport pathways among different N species. The insights gained from this study hold significance for managing agricultural pollution and restoring impaired aquatic systems.

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).

Sources and seasonal variations of nitrate in the coastal multiple-aquifer groundwater of Beihai, southern China

Elevated nitrate (NO3-) loadings in groundwater may cause health effects in drinking water and nutrient enrichment of aquatic ecosystems. To reveal the sources and seasonal variations of NO3- in the coastal groundwater of Beihai, southern China, we carried out hydrochemical and isotopic (δ15N-δ18O in NO3-) investigations in the summer and winter, respectively, concerning multiple-aquifer groundwater, rainwater, seawater, and surface water. The sources of the main elements present in the waters were interpreted by ionic ratios. NO3- sources were identified by combined use of the δ15N values and δ18O values or NO3-/Na+ molar ratios, with estimations of the proportional contribution by the Bayesian stable isotope mixing model. Denitrification was interpreted along the flow paths. The results show groundwater main elements are originated primarily from silicate weathering, and secondarily from anthropogenic inputs and carbonate dissolution. Its qualities are largely affected by seawater intrusion along the coastline. Because of difference in the predominant minerals within the aquifers and in scale and extent of seawater intrusion, the groundwater displays distinct ionic ratio characters. NO3- concentrations are up to 33.9 mg/L, with higher loadings in the plains relative to along the coastline. Soil N, domestic sewage, rainwater, chemical fertilizers, and algae are NO3- sources, with average proportional contributions of 0.255, 0.221, 0.207, 0.202, and 0.116, respectively. In relation to the winter, higher production of NO3- from nitrification of soil N- and algae-derived ammonium induced by higher temperatures in the summer accounts for increases in groundwater NO3- loadings. In the rural areas, elevated loadings of NO3- in the winter may be due to larger infiltration fractions of sewage. Seasonal variations of atmospheric NO3- deposition and farming may also cause the dynamics. Our results improve the understanding of sources and seasonal dynamics of NO3- in coastal groundwater.

Identifying the external N and Hg inputs to the estuary ecosystem based on the triple isotopic information (δ15NNO3, Δ17ONO3 and δ18ONO3)

The supply and sources of N and Hg in the Geum estuary of the western coast of Korea were evaluated. Triple isotope proxies (δ15NNO3, Δ17ONO3 and δ18ONO3) of NO3- combined with conservative mixing between river and ocean waters were used to improve isotope finger-printing methods. The N pool in the Geum estuary was primarily influenced by the Yellow Sea water, followed by riverine discharge (821 × 106 mol yr-1) and atmospheric deposition (51 × 106 mol yr-1). The influence of the river was found to be greater for Hg than that of the atmosphere. The triple isotope proxies revealed that the riverine and atmospheric inputs of N have been affected by septic wastes and fossil fuel burning, respectively. From the inner estuary towards offshore region, the influence of the river diminishes, thus increasing the relative impact of the atmosphere. Moreover, the isotope proxies showed a significant influence of N assimilation in February and nitrification in May.

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.

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.

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

Accurate identification of riverine nitrate sources is required for preventing and controlling nitrogen contamination in agricultural watersheds. The water chemistry and multiple stable isotopes (δ¹⁵N-NO₃, δ¹⁸O-NO₃, δ²H-H₂O, and δ¹⁸O-H₂O) of the river water and groundwater in an agricultural watershed in China's northeast black soil region were analyzed to better understand the sources and transformations of riverine nitrogen. Results showed that nitrate is an important pollutant that affects water quality in this watershed. Affected by factors such as seasonal rainfall changes and spatial differences in land use, the nitrate concentrations in the river water showed obvious temporal and spatial variations. The riverine nitrate concentration was higher in the wet season than in the dry season, and higher downstream than upstream. The water chemistry and dual nitrate isotopes revealed that riverine nitrate came primarily from manure and sewage (M&S). Results from the SIAR model showed that it accounted for more than 40% of riverine nitrate in the dry season. The proportional contribution of M&S decreased during the wet season due to the increased contribution of chemical fertilizers and soil nitrogen induced by large amounts of rainfall. The δ²H-H₂O and δ¹⁸O-H₂O signatures implied that interactions occurred between the river water and groundwater. Considering the large accumulation of nitrates in the groundwater, restoring groundwater nitrate levels is essential for controlling riverine nitrate pollution. As a systematic study on the sources, migration, and transformations of nitrate/nitrogen in agricultural watersheds in black soil regions, this research can provide a scientific support for nitrate pollution management in the Xinlicheng Reservoir watershed and provide a reference for other watersheds in black soil regions in the world with similar conditions.

Unexpectedly high nitrate levels in a pristine forest river on the Southeastern Qinghai-Tibet Plateau

River nitrate (NO₃^-) pollution is a global environmental issue. Recently, high NO₃^- levels in some pristine or minimally-disturbed rivers were reported, but their drivers remain unclear. This study integrated river isotopes (δ¹⁸O/δ¹⁵N-NO₃^- and δD/¹⁸O-H₂O), ¹⁵N pairing experiments, and qPCR to reveal the processes driving the high NO₃^- levels in a nearly pristine forest river on the Qinghai-Tibet Plateau. The river isotopes suggested that, at the catchment scale, NO₃^- removal was prevalent in summer, but weak in winter. The pristine forest soils contributed more than 90 % of the riverine NO₃^-, indicating the high NO₃^- backgrounds. The release of soil NO₃^- to the river was "transport-limited" in both seasons, i.e., the NO₃^- production/stock in the soils exceeded the capacity of hydrological NO₃^- leaching. In summer, this regime and the NO₃^--plentiful conditions in the soils associated with the strong NO₃^- nitrification led to the high riverine NO₃^- levels. While the in-soil nitrification was weak in winter, the leaching of legacy NO₃^- resulted in the consistently high NO₃^- levels. This study provides insights into the reasons for high NO₃^- levels in pristine or minimally-disturbed rivers worldwide and highlights the necessity to consider NO₃^- backgrounds when evaluating anthropogenic NO₃^- pollution in rivers.

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

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

Source apportionment of nitrate in the Pearl River Estuary using δ15N and δ18O values and isotope mixing model

The mitigation of eutrophication in the Pearl River Estuary (PRE) has encountered numerous challenges in regards to source control. Herein, the isotope mixing model (SIAR) was used to quantify the primary nitrate sources in the PRE. The results showed that the nitrate levels were significantly higher in the high-flow season than in the low-flow season. Meanwhile, we found the most important nitrate sources were manure and sewage during the high-flow season, with a contribution ratio of 47 % in the low salt area (LSA) and 29 % in the high salt area (HSA). During the low-flow season, the primary nitrate sources were identified as reduced nitrogen fertilizer in the LSA and manure and sewage in the HSA, which accounted for 52 % and 44 %, respectively. Furthermore, we also suggest that a feasible measure might be to control the pollution caused in the PRE by manure and sewage as well as reduced nitrogen fertilizer.

EMMTE: An Excel VBA tool for source apportionment of nitrate based on the stable isotope mixing model

Dual nitrate stable isotopes combined with end-member mixing models are typically used to identify nitrate sources in fields of geochemistry and environmental science, which helps to quantitively depict the geochemical behaviors of nitrate and accurately control the sources of nitrate pollution in waters. Recently, various models with different computation principles, working efficiency, and operation difficulty have been developed and applied in the source apportionment of nitrate. In this paper, an end-member mixing model tool on Excel™, namely EMMTE, has been written with Visual Basic for Application (VBA) and built into a macro-enabled Excel™ spreadsheet. Monte Carlo simulation and constraint relative deviation between the observed and the predicted values were included in the working algorithm to solve the mass balance equation. After comparison with the internationally recognized Bayesian framework (mixing stable isotope analysis in R, MixSIAR) in different cases (three practical cases and one virtual case), the preliminary results showed that the contribution of various sources to groundwater nitrate calculated by EMMTE was highly consistent with that by MixSIAR and the performance of EMMTE seemed to be as good as that of MixSIAR as indicated by the higher goodness-of-prediction, lower root-mean-square error, and lower relative deviation. Therefore, EMMTE is applicable in the source apportionment of groundwater nitrate, and might also be extended to other water bodies and mixtures. It provides a simple, feasible, and user-friendly for front-line workers without experience with MixSIAR to quantitively source apportionment of nitrate in waters.

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

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

Tracking anthropogenic nitrogen-compound sources of surface and groundwater in southwestern Nile Delta: hydrochemical, environmental isotopes, and modeling approach

This research aims to assign the specific and potential sources that control migration and transformation mechanisms of ammonium/nitrate contaminants of surface and groundwater systems in the southwestern Nile Delta, Egypt. To achieve that, an integration of hydrogeochemistry, multiple environmental stable isotopes (δ²H-H₂O, δ¹⁸O-H₂O, δ¹⁵N-NH₄, and δ¹⁵N-NO₃) coupled with three-dimensional nitrogen transport numerical model (MODFLOW-MT3D) was done. A set of representative water samples (20 canals and drainage water) and 14 groundwater samples were collected and analyzed for physical, chemical, and stable isotope analysis. NH₄⁺ and NO₃^- concentrations in surface water samples varied from 0.29 to 124 mg/l and 0.52 to 39.67 mg/l, respectively. For groundwater samples, NH₄⁺ and NO₃^- concentrations varied from 0.21 to 1.75 mg/l and 0.33 to 32.8 mg/l, respectively. Total risk quotient (THQ) level of nitrate (oral and dermal effects) from drinking water exceeds unity for all water samples indicating a potential noncancer risk for the southwestern Nile Delta residents. The potential sources of nitrogen compound pollution are water from sewage treatment plants used for irrigation, sludge and animal manure, septic tanks, soil nitrogen, and artificial fertilizers according to results of δ¹⁵N values. Results of ammonium/nitrate modeling in shallow groundwater aquifers are compared with observed concentrations and are found to be in good agreement. Some recommendations are given to decrease nitrogen loads in the study area through suggested a need for adoption of N-fertilizer management practices and treatment of sewage water before to application in agricultural activities.

FRAME-Monte Carlo model for evaluation of the stable isotope mixing and fractionation

Bayesian stable isotope mixing models are widely used in geochemical and ecological studies for partitioning sources that contribute to various mixtures. However, none of the existing tools allows accounting for the influence of processes other than mixing, especially stable isotope fractionation. Bridging this gap, new software for the stable isotope Fractionation And Mixing Evaluation (FRAME) has been developed with a user-friendly graphical interface (malewick.github.io/frame). This calculation tool allows simultaneous sources partitioning and fractionation progress determination based on the stable isotope composition of sources/substrates and mixture/products. The mathematical algorithm applies the Markov-Chain Monte Carlo model to estimate the contribution of individual sources and processes, as well as the probability distributions of the calculated results. The performance of FRAME was comprehensively tested and practical applications of this modelling tool are presented with simple theoretical examples and stable isotope case studies for nitrates, nitrites, water and nitrous oxide. The open mathematical design, featuring custom distributions of source isotope signatures, allows for the implementation of additional processes that alternate the characteristics of the final mixture and its application for various range of studies.

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

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

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

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

Impacts of anthropogenic groundwater recharge (AGR) on nitrate dynamics in a phreatic aquifer revealed by hydrochemical and isotopic technologies

Although anthropogenic groundwater recharge (AGR) can either elevate or decline the concentration of nitrate in the phreatic aquifer with high hydraulic conductivity, the long-term impact of AGR on nitrate dynamics in the phreatic aquifer and its reason is seldom disclosed. In this study, the hydrogen and oxygen stable isotopes (δ²H-H₂O and δ¹⁸O-H₂O) combined with mixing stable isotope analysis in R (MixSIAR) were used to group the study area into the dominant area of AGR by surface water (AGRSW) and the dominant area of natural groundwater recharged by precipitation (NGRP). Hydrochemical parameters and multiple stable isotopes, including δ²H-H₂O, δ¹⁸O-H₂O, δ¹⁵N-NO₃^-, δ¹⁸O-NO₃^-, and δ¹³C-DIC, were applied to explore the impacts of AGR on the concentration, biogeochemical processes, and main sources of nitrate. The results showed that AGR by surface water with low nitrate content can reduce nitrate pollution in groundwater. The characteristic of δ¹⁸O-NO₃^- value revealed that nitrification was the primary biogeochemical process of nitrogen in groundwater. AGR may enhance nitrification as indicated by the δ¹⁸O-NO₃^- value closer to the nitrification theoretical line. Dual nitrate stable isotopes and MixSIAR revealed that chemical fertilizer (CF), soil nitrogen (SN), and surface water (SW) contributed 10.88%, 49.92%, and 27.64% to nitrate in AGRSW groundwater, respectively, which was significantly different from their contributions to NGRP groundwater (p < 0.05). Notably, AGR significantly increased the contribution of SW but decreased the contribution of CF and SN in groundwater. This study provided a basis and guidance for groundwater quality assessment and pollution control in the phreatic aquifer with high hydraulic conductivity.

Backgrounds as a potentially important component of riverine nitrate loads

Nitrate (NO₃^-) is a major trigger for river eutrophication. While efforts have been made to understand the anthropogenic NO₃^- pollution in rivers, the role of background NO₃^- in determining NO₃^- loads remains to be studied. In this study, we used dual-isotopes (δ¹⁵N/δ¹⁸O-NO₃^-) and an isotope-mixing model to reveal the natural and anthropogenic processes regulating the NO₃^- loads in a forest river that acts as a headwater source for the China's South to North Water Transfer Project. Even though the basin is sparsely populated, the mean NO₃^--N concentration (0.6 ± 0.2 mg/L) was much higher than the median concentration of global rivers (0.3 ± 0.2 mg/L). Meanwhile, the δ¹⁵N-NO₃^- was extremely depleted (as low as -14.4‰). The correlations between the NO₃^- concentrations and isotopes indicate that the nitrification of different sources (i.e., soil organic nitrogen, chemical fertilizer, manure, and sewage) dominates the NO₃^- loads. Soil organic nitrogen accounted for c.a. 60% of the riverine NO₃^- in the high-flow season, which alone exceeds China's national standard. This finding clearly shows that high NO₃^- loads in rivers could not all be ascribed to direct anthropogenic inputs, and background NO₃^- could be critical triggers. Therefore, when evaluating the NO₃^- pollution of rivers, the background NO₃^- concentrations must be considered along with the actual NO₃^- loads. In the low-flow season, the contribution from manure and sewage (c.a. 34%) increases. This study highlights the potentially important role of background NO₃^- in regulating riverine NO₃^- loads, providing important implications for understanding high riverine NO₃^- loads worldwide.

APCS-MLR model: A convenient and fast method for quantitative identification of nitrate pollution sources in groundwater

Nitrate (NO₃^-) contamination in groundwater has diverse sources and complicated transformation processes. To effectively control NO₃^- pollution in groundwater systems, quantitative and accurate identification of NO₃^- sources is critical. In this work, we applied hydrochemical characteristics and isotope analysis to determine NO₃^- source apportionment. For the first time, the NO₃^- source contributions were calculated using hydrochemical indicators combined with multivariate statistical model (PCA-APCS-MLR). The results interpret that chemical fertilizers (58.11%) and natural sources (22.69%) were the primary NO₃^- sources in the vegetable cultivation area (VCA) which were rather close to the estimation by Bayesian isotope mixing model (SIAR). In particular, the contributions of chemical fertilizers in the VCA differed by only 3.79% between the two methods. Compared with previous approaches e.g. SIAR, the key advantage of the proposed PCA-APCS-MLR model is that it only requires the hydrochemical indicators which can be easily measured. A series of complicated experiments including measurement of isotope data of NO₃^- in groundwater, monitoring of in-situ pollution source information and calculation of isotopic enrichment factor can be simply avoided. The PCA-APCS-MLR model offers a much more convenient and faster method to determine the contribution rates of NO₃^- pollution sources in groundwater.

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

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

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

Nitrate (NO₃^-) contamination of surface water is a globally concern, especially in karstic regions affected by intensive agricultural activities. This study combines hydrochemistry, and environmental isotopes (δ²H_H2O, δ¹⁸O_H2O, δ¹⁵N_NO3, and δ¹⁸O_NO3) with a Bayesian isotope mixing model (Simmr) to reduce the uncertainty in estimating the contributions of different pollution sources. Samples were collected from 32 surface water sites in the Yufu River (YFR) watershed, North China, in September and December 2019. The results revealed that NO₃^--N was the predominant form of inorganic nitrogen that caused the deterioration of water quality in the watershed, accounting for approximately 58% of the total nitrogen (TN). The hydrochemical compositions and nitrate isotopes indicated that NO₃^- mainly originated from soil nitrogen (SN), ammonium fertilizer (AF), but nitrate fertilizer (NF), manure and sewage (M&S) and atmospheric precipitation (AP) were limited. The isotopic composition of nitrate in the upper reaches of the watershed was mainly affected by microbial nitrification, while the mixture of multiple sources was the dominant nitrogen transformation process in the mid-lower reaches of the watershed. Simmr model outputs revealed that SN (56.5%) and AF (29.5%) were the primary contributor to riverine NO₃^- pollution, followed by NF (7.1%), MS (3.6%), and AP (3.4%) sources. Moreover, an uncertainty index (UI₉₀) of the isotope mixing showed that SN (0.73) and AF (0.67) had the highest values, followed by NF (0.22), M&S (0.22) and AP (0.10). Chemical fertilizer and SN collectively contributed >50% of nitrate during the two sampling campaigns. These results indicated that reducing the application of nitrogen fertilizers and rational irrigation are the keys to alleviate of NO₃^- pollution. The study is helpful in understanding the source and transformation of riverine NO₃^- and effectively reducing NO₃^- pollution in karst agricultural rivers or watersheds.

Nitrate sources and nitrogen dynamics in a karst aquifer with mixed nitrogen inputs (Southwest China): Revealed by multiple stable isotopic and hydro-chemical proxies

The nitrate (NO₃^-) contamination of karst aquifers as an important drinking water reservoir is increasing globally. Understanding the behavior of nitrogen (N) in karst aquifers is imperative for effective groundwater quality management. This study combined multiple stable isotopes (δ²H-H₂O, δ¹⁸O-H₂O, δ¹³C-DIC, δ¹⁵N-NO₃, and δ¹⁸O-NO₃), including hydro-chemical data, with a tracer test and a Bayesian isotope mixing (SIAR) model to elucidate the NO₃^- sources and N cycling within the Babu karst aquifer in Guizhou Province, Southwest China. Nitrate isotopes and SIAR model revealed that manure and sewage, nitrogen fertilizer, and soil organic nitrogen were the three dominant NO₃^- sources in winter, contributing to 37%, 32%, and 31% to spring NO₃^-, and 38%, 31%, and 31% to surface water NO₃^-, respectively. The δ¹⁸O-NO₃ values of sampled waters ranging from 0.3‰ to 13.7‰ (mean of 7.7 ± 3.0‰; N = 63) and the significant negative correlations between δ¹⁵N-NO₃ and δ¹³C-DIC in the spring waters (P < 0.01) revealed that nitrification was the primary N transformation process in the Babu watershed. Whereas, denitrification might still occur locally, confirmed by the enriched values of δ¹⁵N-NO₃ (14.3 ± 7.6‰; N = 6) and high denitrification extent (46.6 ± 22.2%; N = 6) in the springs from residential areas, and by elevated δ¹³C-DIC (-11.2 ± 0.6‰; N = 26) and δ¹⁵N-NO₃ values (18.9 ± 5.2‰; N = 26) in the boreholes. During the base flow period, point-inputs of the AMD-impacted stream and sewage waters, and short transit time (<5 days) were conducive to nitrification processes in the karst conduit, resulting in elevated NO₃^- concentration and NO₃^-/Cl^- ratio at the watershed outlet. Approximately 50% of NO₃^- flux at the outlet was derived from nitrification, indicating that a significant extent of nitrification occurred in the NH₄⁺-contaminated karst conduit, which may be a new NO₃^- source to receiving rivers and lakes. This study provided an integrated method for exploring the N dynamics in contaminated karst aquifers. Moreover, the study highlighted that the point N sources control required particular attention for groundwater protection and restoration.

Spatial distribution and sources of nutrients at two coastal developments in South Kohala, Hawai'i

Nutrient sources to coastal waters with coral reefs are not well-characterized. This study documented spatial distributions of nutrients within coastal waters along two developments with coral reefs, and identified nutrient sources through nutrient mixing plots, δ¹⁵N measurements in macroalgal tissue, and NO₃^- stable isotope mixing models. Nutrients decreased from fresh groundwaters to offshore waters, with some surface waters higher in concentrations than benthic ones. Conservative and non-conservative mixing between fresh and ocean waters occurred, the latter suggestive of local nutrient sources and biological removal. δ¹⁵N in macroalgal tissue and NO₃^- concurred that fresh groundwater, ocean water, and fertilizers were dominant nutrient sources. Benthic salinity and NO₃^- + NO₂^- concentrations illustrated that submarine groundwater discharge delivered nutrients to reefs in pulses ranging from minutes to days. Information generated from this study is imperative for developing management actions to improve water quality and make coral reefs more resilient to stressors.

Varying water column stability controls the denitrification process in a subtropical reservoir, Southwest China

Reservoirs are regarded as hotspots of nitrogen transformation and potential sources of nitrous oxide (N₂O). However, it remains unclear how the hydrological conditions due to dam construction control the processes of nitrogen transformation in reservoir waters. To address this issue, we examined the spatial-temporal characteristics of nitrate concentrations, δ¹⁵N-NO₃^-, δ¹⁸O-NO₃^-, δ¹⁸O-H₂O, relative water column stability (RWCS), and related environmental factors in a subtropical eutrophic reservoir (Hongfeng Reservoir, HFR), Southwest China. We found that denitrification was the most important nitrogen transformation process in the HFR and that higher denitrification intensity was associated with increased RWCS in summer, which suggested hydrological control of the denitrification process. In contrast, low RWCS conditions favored the nitrification process in the HFR in winter. Additionally, dissolved oxygen (DO; p < 0.05) and nitrate concentrations (p < 0.01) had significant impacts on the denitrification rate. We also found that the spatiotemporal RWCS variations were a prerequisite for regulating DO/nitrate stratification and the coupling/decoupling of nitrification-denitrification at the local and global scales. This study would advances our knowledge of the impacts of RWCS and thermal stratification on nitrogen transformation processes in reservoirs.

Determination of the nitrogen isotope enrichment factor associated with ammonification and nitrification in unsaturated soil at different temperatures

For nitrogen (N) migration and transformation from unsaturated soil to groundwater, the N stable isotope (δ¹⁵N) was modified due to the isotope fractionation effect. To quantitatively evaluate the N cycle in groundwater systems, the determination of isotope fractionation is decisive. In this research, for the first time, incubation experiments were conducted to quantitatively investigate the N isotope enrichment factor (ϵ_p/s) associated with ammonification in unsaturated soil. Under weak isotopic fractionation, the Rayleigh function cannot be directly applied during ammonification. Thus, we proposed a different method calculating the ϵ_p/s values during ammonification, which were -0.03‰ for 15 °C and -2.34‰ for 30 °C. Moreover, for the first time, experimental equipment is presented to explore the isotopic fractionation effects under the co-occurrence of nitrification and volatilization. The results indicated that the isotope effect of volatilization during nitrification can be ignored in this study, and the ϵ_p/s values during nitrification were -10.59 and -6.81‰ at 15 and 30 °C, respectively. This work provides a novel arrangement determining the crucial parameters for identifying nitrate pollution sources in groundwater systems.

Nitrate sources and transformations along a mountain-to-plain gradient in the Taizi River basin in Northeast China

Fifty-seven riverine samples in three typical regions, namely, upper mountainous (zone 1), middle hilly (zone 2), and lower plain (zone 3) regions, were collected in May (low flow) and August (high flow) of 2016, and chemical parameters and isotopes were analyzed to enrich the knowledge of riverine nitrate sources and transformations in the Taizi River basin. Results showed that NO₃^- concentrations in zone 3 were the highest, followed by zones 2 and 1. NO₃^-/Cl^- molar ratios and nitrate dual isotopes indicated that NO₃^- was mainly from chemical fertilizer (CF) in zones 1 (57.0%) and 2 (43.1%) according to a Bayesian mixing model (SIAR) and mixed sources of CF, nitrification of soil organic nitrogen (SON), and manure and sewage (M&S) in zone 3 (92.8%), during the high-flow season. NO₃^- was mainly from CF and SON in zones 1 (76.7%) and 2 (74.0%), during the low-flow season. NO₃^-sources were different in the three rivers of zone 3 mainly due to various urban inputs. Contributions of CF, SON, and M&S increased by 13%, 8.3%, and 7.5% in zones 1, 2, and 3, respectively, from the low-flow to the high-flow season. NO₃^- in the Taizi River was mainly influenced by nitrification in soils, while no significant denitrification was found in the three zones. Measures for reducing NO₃^- inputs to rivers should be considered by improving effectively utilizing rate of chemical fertilizer and inhibit nitrification.

Seasonal Sources and Cycling of Nitrogen Revealed by Stable Isotopes in the Northeastern Beibu Gulf, China

Isotope measurements were performed on dissolved nitrate (NO3−) and ammonium (NH4+) in the coastal waters of the northeastern Beibu Gulf, China, to investigate the seasonal nitrate sources and their biogeochemical processes, which are due to the rapid development of local industrialisation and urbanisation. The high N/P ratio observed in the coastal bay during both fall and spring suggests that P is a limiting nutrient, which in turn indicates that increasing P causes conditions favourable for algal blooms. Higher nutrient concentrations and δ15N-NO3− and δ15N-NH4+ values were found in the nearshore area in the fall, suggesting that nutrients originated mainly from land-based pollution. A Bayesian isotope mixing model was used to calculate the contribution of potential NO3− sources and the results showed that in the nearshore area, NO3− originated mainly from manure and sewage (58%). In the spring, however, in addition to the impact of urban sewage effluents, the exchange of sediment and water was another important factor causing higher nutrient concentrations and positive NO3− isotopes in the nearshore area. There were lower concentrations of nutrients and an increase in δ15N-NO3− and δ15N-NH4+ values in the offshore area in the fall, and the NO3− loss in the surface water was mainly caused by the process of assimilation. However, the exchange of sediment and water was the dominant factor causing higher nutrient concentrations (except for NO3−) and positive dual nitrate isotopes but lower NO3− concentration in the offshore area during the spring. Overall, isotope analysis of NO3− and NH4+ helps to illustrate the major sources of the former and their biological transformation in the northeastern Beibu Gulf.

Spatial variability of nitrate pollution and its sources in a hilly basin of the Yangtze River based on clustering

Nitrate (NO₃^-) pollution is a serious global problem, and the quantitative analysis of its sources contributions is essential for devising effective water-related environmental-protection policies. The Shengjin Lake basin, located in the middle to lower reaches of the Yangtze River in China was selected as the research area in our study. We first grouped 29 surface water samples and 33 groundwater samples using cluster analysis, and then analyzed potential nitrate sources for each dataset of δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- isotope values by applying a Bayesian isotope-mixing model. Our results show that the nitrogen pollution in the surface-ground water in the study area seriously exceeded to class V of the Environmental Quality Standard of Surface Water of China. The NO₃^- in surface water from the mid-upper reaches of the drainage basin mainly originates from soil nitrogen (SN) and chemical fertilizer (CF), with contribution rates of 48% and 32%, respectively, and the NO₃^- in downstream areas mainly originates from CF and manure and sewage (MS), with contribution rates of 48% and 33%, respectively. For the groundwater samples, NO₃^- mainly originates from MS, CF, and SN in the mid-upper reaches of the drainage basin and the northside of Dadukou near the Yangtze River, with contribution rates of 34%, 31%, and 29%, respectively, whereas NO₃^- in the lower reaches and the middle part of Dadukou mainly originates from MS, with a contribution rate of 83%. The nitrogen conversion of surface water in lakes and in the mid-upper reaches is mainly affected by water mixing, while the groundwater and surface water in the lower plains are mainly affected by denitrification. The method proposed in this study can expand the ideas for tracking nitrate pollution in areas with complex terrain, and the relevant conclusions can provide a theoretical basis for surface and groundwater pollution control in the hilly basin of Yangtze River.

Identifying nitrogen sources in intensive livestock farming watershed with swine excreta treatment facility using dual ammonium (δ15NNH4) and nitrate (δ15NNO3) nitrogen isotope ratios axes

We proposed a novel approach based on dual ammonium and nitrate nitrogen isotope ratios (δ¹⁵N_NH4 and δ¹⁵N_NO3, respectively) axes to identify nitrogen sources in intensive livestock farming watersheds, especially those with swine excreta treatment facilities. The δ¹⁵N_NH4 and δ¹⁵N_NO3 values in water samples were measured monthly in 2016-2017. Soil and mineral fertilizers, sewage, sewage effluent, manure, and swine effluents were the five sources considered to identify nitrogen sources. The results showed that nitrogen pollution from agricultural activities was well reflected by the seasonal δ¹⁵N_NH4 and δ¹⁵N_NO3 patterns in the river, and microbial nitrification was suggested as the dominant nitrogen transformation process in the river. This study revealed that δ¹⁵N_NH4 and δ¹⁵N_NO3 axes provided better results than the traditionally used nitrate oxygen (δ¹⁸O_NO3) and δ¹⁵N_NO3 axes for identifying nitrogen sources in agricultural watersheds with swine excreta treatment facilities. The mixing model results showed that stream water was severely contaminated with swine effluents (e.g., a mean minimum contribution of 31%), thus affecting the quality of the mainstream (p = 0.068 < 0.10). This study was the first successful application of dual δ¹⁵N_NH4 and δ¹⁵N_NO3 axes to better understand nitrogen sources in intensive livestock farming watersheds with swine excreta treatment facilities.

Ozone profile retrievals from TROPOMI: Implication for the variation of tropospheric ozone during the outbreak of COVID-19 in China

During the outbreak of the coronavirus disease 2019 (COVID-19) in China in January and February 2020, production and living activities were drastically reduced to impede the spread of the virus, which also caused a strong reduction of the emission of primary pollutants. However, as a major species of secondary air pollutant, tropospheric ozone did not reduce synchronously, but instead rose in some region. Furthermore, higher concentrations of ozone may potentially promote the rates of COVID-19 infections, causing extra risk to human health. Thus, the variation of ozone should be evaluated widely. This paper presents ozone profiles and tropospheric ozone columns from ultraviolet radiances detected by TROPOospheric Monitoring Instrument (TROPOMI) onboard Sentinel 5 Precursor (S5P) satellite based on the principle of optimal estimation method. We compare our TROPOMI retrievals with global ozonesonde observations, Fourier Transform Spectrometry (FTS) observation at Hefei (117.17°E, 31.7°N) and Global Positioning System (GPS) ozonesonde sensor (GPSO₃) ozonesonde profiles at Beijing (116.46°E, 39.80°N). The integrated Tropospheric Ozone Column (TOC) and Stratospheric Ozone Column (SOC) show excellent agreement with validation data. We use the retrieved TOC combining with tropospheric vertical column density (TVCD) of NO₂ and HCHO from TROPOMI to assess the changes of tropospheric ozone during the outbreak of COVID-19 in China. Although NO₂ TVCD decreased by 63%, the retrieved TOC over east China increase by 10% from the 20-day averaged before the lockdown on January 23, 2020 to 20-day averaged after it. Because the production of ozone in winter is controlled by volatile organic compounds (VOCs) indicated by monitored HCHO, which did not present evident change during the lockdown, the production of ozone did not decrease significantly. Besides, the decrease of NO_x emission weakened the titration of ozone, causing an increase of ozone.

Climatic and anthropogenic driving forces of the nitrogen cycling in a subtropical river basin

To date, basin-scale understanding of nitrogen (N) cycling is lacking, which undermines riverine N pollution control efforts. Applying a multiple-isotopic approach, this study provided insights into the impacts of climate and anthropogenic activities on the N cycling at a basin scale. The isotopic compositions of the river water were regulated by a simple mixing process in winter, while unconservative processes (nitrification and denitrification) occurred in warm seasons. Denitrification dominated the N transformations in summer, while coupled nitrification-denitrification in soils after fertilization was responsible for the isotopic fractionations in spring and autumn. While at least 58.7% of the nitrate (NO₃^-) was removed from the basin, the NO₃^- loadings in the river remained high, suggesting that the ecosystem services could not balance the anthropogenic pollution. After correcting the isotopic fractionations, the sources of the riverine NO₃^- were quantified by a Markov chain Monte Carlo isotope mixing model. The contributions of point sources versus non-point sources changed dynamically with the precipitation and fertilization patterns. In summer and autumn, the soil organic N and chemical fertilizer dominated the riverine NO₃^-, with total contributions of 75.9% and 74.6%, respectively. The contributions from sewage and manure significantly increased during spring (47.9%) and winter (50.2%). Overall, the annual NO₃^- fluxes were from SON (28.7%), CF (28.1%), DS (18.2%), MA (23.9%), and AP (1.1%). In addition, we presented the large uncertainties in source apportionment that arose from the ignorance of isotope fractionations, highlighting the importance of considering the effect of isotopic fractionations in N source apportionment studies.

A machine learning model to assess the ecosystem response to water policy measures in the Tagus River Basin (Spain)

Anthropogenic activities are seriously endangering the conservation of biodiversity worldwide, calling for urgent actions to mitigate their impact on ecosystems. We applied machine learning techniques to predict the response of freshwater ecosystems to multiple anthropogenic pressures, with the goal of informing the definition of water policy targets and management measures to recover and protect aquatic biodiversity. Random Forest and Gradient Boosted Regression Trees algorithms were used for the modelling of the biological indices of macroinvertebrates and diatoms in the Tagus river basin (Spain). Among the anthropogenic stressors considered as explanatory variables, the categories of land cover in the upstream catchment area and the nutrient concentrations showed the highest impact on biological communities. The model was then used to predict the biological response to different nutrient concentrations in river water, with the goal of exploring the effect of different regulatory thresholds on the ecosystem status. Specifically, we considered the maximum nutrient concentrations set by the Spanish legislation, as well as by the legislation of other European Union Member States. According to our model, the current nutrient thresholds in Spain ensure values of biological indices consistent with the good ecological status in only about 60% of the total number of water bodies. By applying more restrictive nutrient concentrations, the number of water bodies with biological indices in good status could increase by almost 40%. Moreover, coupling more restrictive nutrient thresholds with measures that improve the riparian habitat yields up to 85% of water bodies with biological indices in good status, thus proving to be a key approach to restore the status of the ecosystem.

Identification of nitrate sources and transformations in basin using dual isotopes and hydrochemistry combined with a Bayesian mixing model: Application in a typical mining city

The external nitrogen load input caused by human activities exacerbates the eutrophication process of aquatic ecosystems in mining areas, causing water quality problems. However, knowledge of the sources and environmental behavior of nitrate in the surface water of mining areas is still very limited. This study investigated the nitrate content and spatiotemporal variation characteristics of surface water in the Linhuan mining area, identified the sources and transformation processes of nitrate using isotopes and hydrochemistry, and evaluated the contribution rates of different potential nitrate sources based on a Bayesian mixing model. The nitrogen pollution in the surface water in the mining area seriously exceeded class Ⅴ of the Environmental Quality Standard of Surface Water of China (GB3838-2002). The NO₃^- content ranged from 0.87 to 3.41 mg/L, showing obvious seasonal and spatial differences. Isotope and NO₃^-/Cl^- analysis indicated that nitrate in the subsidence area water (SAW) was mainly derived from chemical fertilizer (NF) and soil organic nitrogen (NS), while nitrate in the mainstream of the Huihe River water (HRW) was mainly derived from manure/sewage (MS). The nitrate in the tributary of the Baohe River water (BRW) was mainly derived from soil NS, and nitrification was a nitrogen conversion pathway in the soil. The results of the Bayesian mixing model showed that the main sources of nitrate in the BRW, HRW and SAW were NF (34.5%), MS (68.8%) and NF (40.8%) in the wet season, and NS (33.4%), MS (70.9%) and NF (58.1%) in the dry season, respectively. The results of this study provide a new integrated method for the identification of nitrate pollution sources in mining areas, and this method can be used to improve the biogeochemical information of nitrogen in the aquatic ecosystems of mining areas and help formulate relevant measures to reduce water nitrogen pollution.

Identification of the sources and fate of NO3--N in shallow groundwater around a plateau lake in southwest China using NO3- isotopes (δ15N and δ18O) and a Bayesian model

Pollution by NO₃^--N seriously threatens the quality of shallow groundwater (SG) around Erhai Lake, which is the 2^nd largest source of freshwater in the plateau area in southwest China; further, NO₃^--N affects the lake water quality and human health. We collected SG samples during the dry and wet seasons in 2018 and 2019, and the potential NO₃^--N sources and their fates were identified in SG by NO₃^- isotopes and hydrochemical methods. Our results showed that the NO₃^--N concentrations in the SG in the wet season in farmland were far higher than those in the dry season in residential areas. The high variation in δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- (from -12.78‰ to +18.10‰ and -27.62‰ to +23.07‰, respectively, in the farmland and from -5.34‰ to +34.54‰ and -20.04‰ to +17.47‰, respectively, in the residential area) indicated multiple NO₃^--N sources in the SG. The NO₃^--N in the farmland mainly originated from chemical nitrogen fertilizer (NF, 36%), soil nitrogen (SN, 33%) and manure and sewage (M&S, 24%) in the dry season and from SN (61%) and NF (33%) in the wet season. The NO₃^--N in the residential area mainly originated from M&S (57%), SN (23%) and NF (14%) in the dry season and from SN (50%), NF (25%) and M&S (24%) in the wet season. Nitrogen transformation was dominated by denitrification in the SG. The most polluted SG area was observed on the east bank of Erhai Lake, NO₃^--N mainly originated from NF. But the NO₃^--N pollution slowed down from high altitude to lakeside and had multiple NO₃^--N sources on the west bank of Erhai Lake. The SG was contaminated by nitrogen from NF, SN and M&S along the flow path and flowed into Erhai Lake. Therefore, reducing soil nitrogen concentrations and chemical nitrogen fertilizer applications and improving sewage facilities are significant ways to mitigate nitrate pollution in the SG.

Tracking nitrate and sulfate sources in groundwater of an urbanized valley using a multi-tracer approach combined with a Bayesian isotope mixing model

Over the past decades, groundwater quality has deteriorated worldwide by nitrate pollution due to the intensive use of fertilizers in agriculture, release of untreated urban sewage and industrial wastewater, and atmospheric deposition. Likewise, groundwater is increasingly polluted by sulfate due to the release of domestic, municipal and industrial wastewaters, as well as through geothermal processes, seawater intrusion, atmospheric deposition, mineral dissolution, and acid rain. The urbanized and industrialized Monterrey valley has a long record of elevated nitrate and sulfate concentrations in groundwater with multiple potential pollution sources. This study aimed to track different sources and transformation processes of nitrate and sulfate pollution in Monterrey using a suite of chemical and isotopic tracers (δ²H-H₂O, δ¹⁸O-H₂O, δ¹⁵N-NO₃, δ¹⁸O-NO₃ δ³⁴S-SO₄, δ¹⁸O-SO₄) combined with a probability isotope mixing model. Soil nitrogen and sewage were found to be the most important nitrate sources, while atmospheric deposition, marine evaporites and sewage were the most prominent sulfate sources. However, the concentrations of nitrate and sulfate were controlled by denitrification and sulfate reduction processes in the transition and discharge zones. The approach followed in this study is useful for establishing effective pollution management strategies in contaminated aquifers.

Nitrate contamination and source apportionment in surface and groundwater in Ghana using dual isotopes (15N and 18O-NO3) and a Bayesian isotope mixing model

The rising food production to meet the growing human population has led to increased anthropogenic inputs of nutrients such as NO₃^- in groundwater and aquatic environments. Nitrate concentrations, hydrochemistry, and isotope data (δ¹⁸O-H₂O, δ²H-H₂O, ¹⁵N-NO₃, and δ¹⁸O-NO₃) from boreholes (BH), hand dug wells (HDW), and surface water (SW) were analyzed. The objectives of the study were to identify potential nitrate sources and their proportional contributions using an isotope mixing model (SIAR). The results showed that NO₃^- concentrations in the BH, HDW, and SW were heterogeneous and controlled by localized anthropogenic activities. The hydrochemistry and dual isotope (¹⁵N-NO₃ and ¹⁸O-NO₃) identified manure/sewage as the dominant source of NO₃^- in the groundwater, while the SW showed a complex signature overlapping in the areas of manure/septic, chemical fertilizer, and soil nitrogen. The SIAR analysis showed that sewage/manure contributed about 66%, 68%, and 55% of NO₃^- in the BH, HDW, and SW, respectively. In the study area, the NO₃^- source contribution based on the mean probable estimate (MPE) were in the order S&M > SN > CF > P. Shortcomings and the uncertainties associated with the SIAR to guide future studies have also been discussed. The study also highlighted the use of hydrochemistry, environmental isotopes, and Bayesian isotope mixing models for NO₃^- source identification and apportionment. This is to enable effective planning, farming practices, and sewage disposals to safeguard groundwater quality and control the eutrophication in rivers to meet safe drinking water demand.

Spatiotemporal variations of nitrate sources and dynamics in a typical agricultural riverine system under monsoon climate

Nitrogen pollution is a serious environmental issue in the Danjiangkou Reservoir region (DRR), the water source of the South-to-North Water Diversion Project of China. In this research, seasonal surveys and a bi-weekly time series survey were conducted in the Qihe River Basin, one of the most densely populated agricultural basins in the DRR. Hydrochemical compositions (NO₃^- and Cl^-), dual isotopes (δD-H₂O, δ¹⁸O-H₂O, δ¹⁵N-NO₃^-, and δ¹⁸O-NO₃^-), and a Markov Chain Monte Carlo isotope mixing model were jointly applied to unravel the sources, migrations, and transformations of the nitrate (NO₃^-) in the basin. It was revealed that the mixing between different sources was the main process controlling the isotopic compositions of the riverine NO₃^- in the upper-middle reaches. In contrast, denitrification occurred in the lower reaches. For the first time, the sources of NO₃^- were quantified at a basin scale in the DRR. Overall, the river transported 484.2 tons/year of NO₃-N to the reservoir, of which 32.6%, 36.4%, 28.0%, and 3.0% was from soil organic nitrogen, chemical fertilizer, residential sewage and atmospheric precipitation, respectively. The NO₃-N fluxes of the different sources were regulated by the monsoon climate and anthropogenic activities. For example, high precipitation and intense fertilization resulted in severe nonpoint source pollution. Denitrification thrived in soils and reservoirs in wet seasons. Temperature could regulate the migration, nitrification and denitrification processes. Based on the results, we suggest that the management strategies dealing with nitrogen pollution issue in the DRR should follow the specific spatiotemporal characteristics of NO₃^- sources, migration and transformation mechanisms.

Riverine nitrate source apportionment using dual stable isotopes in a drinking water source watershed of southeast China

It is crucial to quantitatively track riverine nitrate (NO₃^-) sources and transformations in drinking water source watersheds for preventing current and future NO₃^- pollution, and ensuring a safe drinking water supply. This study identified the significant contributors to riverine NO₃^- in Zhaoshandu reservoir watershed of Zhejiang province, southeast China. To achieve this goal, we used hydrochemistry parameters and stable isotopes of NO₃^- (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-) accompanied with a Markov Chain Monte Carlo mixing model to estimate the proportional contributions of riverine NO₃^- inputs from atmospheric deposition (AD), chemical nitrogen fertilizer (NF), soil nitrogen (SN), and manure and sewage (M&S). Results indicated that the main form of riverine nitrogen in this region was NO₃^-, constituting ~60% of the total nitrogen mass on average (total organic nitrogen ~37% & ammonium ~3%). Variations in the isotopic signatures of NO₃^- demonstrated that microbial nitrification of NF, SN and M&S was the primary nitrogen transformation process within the Zhaoshandu reservoir watershed, whereas denitrification was minimal. A classical dual isotope bi-plot incorporating chloride concentrations suggested NF, SN and M&S were the major contributors of NO₃^- to the river. Riverine NO₃^- source apportionment results were further refined using the Markov Chain Monte Carlo mixing model, which revealed that AD, NF, SN and M&S contributed 7.6 ± 4.1%, 22.5 ± 12.8%, 27.4 ± 14.5% and 42.5 ± 11.3% of riverine NO₃^- at the watershed outlet, respectively. Finally, uncertainties associated with NO₃^- source apportionment were quantitatively characterized as: SN > NF > M&S > AD. This work provides a comprehensive approach to distinguish riverine NO₃^- sources in drinking water source watersheds, which helps guide implementation of management strategies to effectively control NO₃^- contamination and protect drinking water quality. SUMMARY OF THE MAIN FINDING FROM THIS WORKS (CAPSULE): We utilized NO₃^- stable isotope analysis and a Markov Chain Monte Carlo mixing model to quantify riverine nitrate pollution sources in a drinking water source watershed in Zhejiang province, southeast China. Markov Chain Monte Carlo mixing model output showed that NF, SN and M&S were the dominant sources of riverine NO₃^- during the sampling period in Zhaoshandu watershed. Uncertainty analysis characterized the variation strength associated with contributions of individual nitrate sources and indicated the greatest uncertainty for SN, followed by NF, M&S and AD.

Sources and transformations of nitrate constrained by nitrate isotopes and Bayesian model in karst surface water, Guilin, Southwest China

Surface water suffering from nitrate (NO₃^-) contamination in karst area is not only harmful to human health as drinking water but can also affect the process of carbonate rock weathering, so it is crucial to trace the sources and transformations of NO₃^- in karst surface water. In this study, an investigation of water chemical data and NO₃^- isotopes (δ¹⁵N and δ¹⁸O) was used to elucidate the transformations of NO₃^- and quantify a proportional apportionment of NO₃^- sources of individual potential sources (incl. soil organic nitrogen (SON), atmospheric precipitation (AP), manure and sewage wastes (M&S), and chemical fertilizer (CF)) in the Lijiang River (typical karst surface water), Guilin, Southwest China. δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- values of water samples from the Lijiang River range from 2.14 to 13.50‰ (mean, 6.59‰) and from - 2.44 to 6.97‰ (mean, 3.76‰), respectively. A positive correlation between Cl^- and NO₃^- but no correlations between NO₃^- and δ¹⁵N-NO₃^- or δ¹⁸O-NO₃^- are found and the δ¹⁸O-NO₃^- values fitted the theoretical δ¹⁸O-NO₃^- values produced from nitrification, suggesting that the genesis of NO₃^- in waters of the Lijiang River is affected by nitrification processes and the mixing process has a major effect on NO₃^- transportation. Results of the Bayesian stable isotope mixing model show that the M&S and SON are the main NO₃^- source through the whole year (accounting for ~ 61% and 65% of the total NO₃^- in the wet and dry season, respectively), followed by CF (~ 29%). Furthermore, we find that nitrification of nitrogen in fertilizers, soil, and manure and sewage can promote the carbonate rock weathering. The estimated contribution of such nitrification to the weathering of carbonate rocks accounts for about 11% of the total carbonate rock weathering flux (calculated by HCO₃^-) in the Lijiang River. This finding indicates that the weathering of carbonate rock is probably affected by nitrogen nitrification processes in karst catchment.

Nitrate source apportionment in groundwater using Bayesian isotope mixing model based on nitrogen isotope fractionation

Accurate identification of nitrate (NO₃^-) sources is critical to address the issue of groundwater pollution. The nitrogen (N) isotopic enrichment factor (ɛ_p/s) is an important parameter to explain the N cycle and determine the proportional contribution of NO₃^- sources. Considering the isotopic fractionation effects in N transformation processes, this study quantitatively analyzed the NO₃^- sources in groundwater using stable isotopes (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-) and the Bayesian isotope mixing model (SIAR). For the first time, the ɛ_p/s values (0.0‰, -8.7‰, -8.7‰, and 14.7‰) of atmospheric deposition (AD), soil nitrogen (SN), chemical fertilizers (CF), and manure and sewage (M&S) were calculated to determine the NO₃^- source apportionment in groundwater. It was proved that the isotopic fractionation effect could produce a more accurate NO₃^- source apportionment. We also found that the NO₃^- source contributions were closely related to the cropping system. In the vegetable cultivation area, CF (54.32%) and SN (37.75%) were the dominant NO₃^- source, while in the grain cultivation area, NO₃^- pollution was largely influenced by SN (33.67%), CF (33.27%), and M&S (30.16%). According to this study, the isotope fractionation is strongly recommended for NO₃^- source apportionment in groundwater system.

Isotopic and chemical evidence for nitrate sources and transformation processes in a plateau lake basin in Southwest China

In recent decades, multiple occurrences of algal blooms have substantially deteriorated water quality, especially for the nutrient budget in plateau lakes. Specifically, NO₃^- pollution has critically threatened groundwater quality, thus increasing human health risk if groundwater serves as a drinking source. To identify the origin and fate of NO₃^- in a plateau lake basin, we utilized nitrate isotope natural abundance and water chemistry information under land use frameworks and groundwater flow information. In December 2018, we collected water samples from aquifers (n = 33), rivers (n = 2), soil (n = 7), and lakes (n = 4) in Chenghai Lake basin, Southwest China. Our results showed that nearly 41% of groundwater samples failed to meet the drinking water standard of WHO and China (GB/T 5749-2006) of 50 mg/L for NO₃^- during the dry season. The high variation of δ¹⁵N-NO₃^- (from -3.3 to +41.3‰) and δ¹⁸O-NO₃^- (from -6.4 to +13.6‰) indicated multiple N sources and N cycling processes. Our analysis revealed that 16%-80% of nitrate in groundwater was derived from accumulated soil N, whereas 13%-76% was contributed from manure/landfill leachate. The contribution from atmospheric nitrogen deposition to aquifers was less than 3%. Manure/landfill and soil nitrogen were the primary N sources, contributing for 38.9% and 35.3% to N loading in lake. As for river water, soil nitrogen contributed for 69.7% and 37.2% in R1 and R2, respectively. The denitrification process significantly affects nitrate attenuation of N sources in aquifers. An increasing trend in NO₃^- concentration was noticed along the groundwater flow path (A-A') from mountain area to lake. Among different pathways, distinct nitrate sources loading downwards to the aquifers were observed in massive farmlands and residential areas. Thus, the information on both land-use and groundwater flow pathways is indispensable for modelling nitrate sources and transformation processes using the dual isotope approach.