Main Sources Of Nitrate Research Articles

Source identification of nitrate in groundwater of an agro-pastoral ecotone in a semi-arid zone, northern China: Coupled evidences from MixSIAR model and DOM fluorescence

In the extensive agro-pastoral ecotone of northern China, groundwater is a valuable resource, but it suffers from severe nitrate pollution. However, the extent of the contributions of agricultural and pastoral activities to nitrate accumulation in the groundwater of the region remains unclear. This study aimed to identify the main sources of groundwater nitrate in Chahannur Basin, a typical agro-pastoral ecotone in the semi-arid zone of northern China, using the MixSIAR model based on dual stable isotopes and dissolved organic matter (DOM) fluorescence. The hydrochemical and isotopic results showed that the groundwater has high concentrations of nitrate (up to 208.19 mg/L) with weak denitrification, and nitrate accumulation is mainly driven by mixed input from different sources. The MixSIAR model results indicated that the largest contributors to groundwater nitrate accumulation are manure & sewage, followed by soil nitrogen, chemical fertilizers, and atmospheric deposition. According to the DOM fluorescence characteristics, the groundwater is strongly affected by livestock and poultry waste, followed by soil humic substances. Moreover, the DOM fluorescence results further supported the MixSIAR model results based on the significant correlation between the contributions of nitrate sources and the percentages of fluorescent components, jointly confirming that the main source of nitrate in groundwater is manure and sewage, followed by soil nitrogen. These findings indicate that coupled evidences from the MixSIAR model and DOM fluorescence could be applied to identify the sources of nitrate in groundwater, and this coupling can provide valuable information for local authorities to achieve sustainable groundwater management.

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

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

Research Advances of Groundwater Nitrate Pollution and Source Apportionment in China

Groundwater nitrate (NO3-) contamination in China has become a serious environmental problem, especially in agricultural production areas, which greatly affects the safety of drinking groundwater and requires urgent attention. In this study, the main sources of groundwater nitrate in China were reviewed, including atmospheric deposition, soil nitrogen, agricultural fertilization, and fecal sewage, among which fecal sewage and agricultural fertilization were the main reasons for the excessive groundwater nitrate. The application of hydrochemical analysis, multivariate statistical analysis, stable isotope tracer method, and microbial source tracking in the source apportionment of groundwater nitrate was summarized. All types of source apportionment methods had certain limitations. It is suggested that a variety of methods should be used to identify the source of groundwater nitrate, and the contribution rate of different pollution sources should be calculated using multivariate statistical analysis and isotope quantitative analysis models. The source apportionment of nitrate pollution has undergone a process from qualitative to quantitative research. At present, the SIAR and MixSIAR models based on δ15N-NO3-and δ18O-NO3- have been used widely to analyze the source of nitrate. However, due to the overlap of isotope characteristic values of different input end-members, the difference in δ15N-NO3-and δ18O-NO3- values under different spatial and temporal changes, and the influence of isotope fractionation in the process of nitrogen migration and transformation, the results calculated by the model remain uncertain. It is necessary to further optimize the analytical method of the model to obtain the source of nitrate pollution and its contribution rate more accurately to further aid in the scientific management of groundwater resources.

Spatio-Temporal Variations in Nitrate Sources and Transformations in the Midstream of the Yellow River Determined Based on Nitrate Isotopes and Hydrochemical Compositions

Nitrate pollution is a major environmental problem threatening rivers, and nitrogen and oxygen isotopes have proved to be an effective means of analyzing the sources and transformations of nitrate in rivers. However, a low monitoring frequency cannot accurately reflect the changes in nitrate. In this study, the sources and transformations of nitrate in the middle reaches of the Yellow River and its tributaries during the dry season and the wet season were analyzed based on water quality parameters and nitrate isotopes. Stable isotope analysis conducted using the R (SIAR) model was used to estimate the proportions of different nitrate sources. The results showed that the main nitrate sources in the main stream were soil nitrogen (40.95–45.83%) and domestic sewage and manure (30.93–32.60%), respectively, with little variation between the dry season and wet season because of the large flow of the Yellow River. During the dry season, the nitrate sources of the two tributaries were mainly domestic sewage and manure (45.23–47.40%), followed by soil nitrogen (31.35–34.00%). However, the primary nitrate source of T2 (Qin River) became soil nitrogen (40.05%) during the wet season, a phenomenon that was mainly caused by the significant increase in river discharge and in soil erosion in the basin. During the wet season, the concentrations of total nitrogen (TN) and nitrate (NO3−) significantly decreased in the main stream and tributaries, and nitrification and denitrification processes occurred in both the main stream and tributaries of the Yellow River. In addition, the T2 tributary (Qin River) was also significantly affected by mixed dilution. High-frequency sampling can reflect the isotopic information of nitrate in the river more comprehensively, which helps us to understand the conversion process of nitrate more accurately.

Implication of self-organizing map, stable isotopes combined with MixSIAR model for accurate nitrogen control in a well-protected reservoir

Nitrogen pollution and eutrophication in reservoirs is a global environmental geochemical concern. Occasional algal blooms still exist in reservoirs that have undergone pollution treatment. The lack of quantitative evidence of nitrogen sources and fate limits long-term stable ecological safety management. This work applied an approach integrated zonal mapping, stable isotopes (δ18OH2O, δ15Nnitrate, δ18Onitrate, and δ13C-DIC) and a Bayesian isotope model to analyze regional and seasonal differences in the contribution and sources of nitrogen to a well-protected reservoir. The values of δ18Onitrate and the positive relationship between NO3− and δ13C-DIC suggested that nitrification was the primary NO3− production in the rivers. While Denitrification was present at only a few sites. Results of the MixSIAR model coupled the NO3−/Cl− indicator revealed that the domestic sewage contributed high riverine NO3− loading (68.6 ± 10.6 %) in the dry season. In the wet season, the main nitrate sources of upper watershed were ammonia and carbamide fertilizers (47.5 % and 40.3 %). While the domestic sewage was still the major contributor of downstream region (a dense residential area), indicating possible problems with rainwater and sewage drainage networks. The results implied that the colleting and treatment of sewages were the priority in downstream region, and non-point source pollution control and wastewater treatment plant upgrading were essential to control nitrate pollution in the two upstream regions. These findings provide new insights into precise nitrogen pollution traceability and identification of treatment priorities in the sub-region, and promote the management other well-protected watershed in similar need of further nitrogen contamination control.

Hydrochemical Evolution and Nitrate Source Identification of River Water and Groundwater in Huashan Watershed, China

The combined hydrochemical analysis, factor analysis, and isotopic signals of water and nitrate were applied to explore the hydrochemical origin and identify the sources and transformation of nitrate in river water and groundwater in the Huashan watershed. Additionally, a Bayesian isotope mixing model (SIAR) was employed for quantitative assessment of the nitrate sources. The results indicated that both river water and groundwater were dominated by HCO3-Ca and HCO3-Ca·Mg types; both originated from precipitation and were influenced by evaporation. The main constituent ions in the river water and groundwater primarily originated from carbonate and silicate dissolution, with the presence of cation exchange in the groundwater. The water chemistry of river water was greatly influenced by physicochemical factors, while that of groundwater was mainly controlled by water–rock interaction. NO3− in river water was mainly influenced by soil nitrogen (SN) and manure and septic wastes (MSWs), while NO3− in groundwater was jointly affected by ammonium fertilizers (AF), SN, and MSWs. With the exception of denitrification observed in the groundwater at the watershed outlet, denitrification was absent in both groundwater in the piedmont area and in river water. The SIAR model results demonstrated that the contribution rates of atmospheric precipitation (AP), AF, SN, and MSWs to river water were 12%, 21%, 25%, and 42%, respectively, while to groundwater, they were 16%, 27%, 10%, and 47%, respectively. Overall, MSWs were the main sources of nitrate in the river water and groundwater. It is necessary to prevent the leakage of MSWs when managing water resources.

Quantifying and assessing nitrogen sources and transport in a megacity water supply watershed: Insights for effective non-point source pollution management with mixSIAR and SWAT models

The expansion and intensification of human activities have resulted in excessive nitrogen (N) in rivers, causing worldwide concern. To effectively manage agricultural non-point source pollution and ensure a safe drinking water supply in watersheds, it is crucial to trace and quantify the primary sources and spatial distribution patterns of N. In response to the challenge of unclear sources and agricultural non-point source pollution, this study utilised the Bayesian isotope mixing model and Soil and Water Assessment Toolmodel to identify the dominant nitrate sources and transformation processes. These models were employed to quantify N retention by the mainstream and tributaries in the Bai River Basin, which directly impacts the safety of drinking water in Beijing. Total N (TN) concentrations in the Yunzhou Reservoir (4.22 ± 0.04 mg.L˗1) and Miyun Reservoir (2.88 ± 0.62 mg.L˗1) inlets in autumn and winter were V class (2 mg.L˗1) category as per GB 3838–2002 standards. This implies higher risks of eutrophication and algal blooms exceeding the standards at individual points and seasons in the Bai River. Fertilisers were the main nitrate source in the Bai River Basin, contributing 44.6% during the dry season and 62.9% during the wet season, suggesting that nitrate is more susceptible to leaching and runoff during rainy periods. Rainfall was not a major contributor, with only 3.2% and 2.9% originating from the Hebei and Beijing areas of the Bai River, respectively. Annually, the Bai River Basin exports loads of approximately 629.3 t.a˗1 of TN and 433.7 t.a˗1 of organic N (Org-N) from the Bai River Basin land to the river. The TN and Org-N loads at the final destination in the Miyun Reservoir were 521.3 t.a˗1 and 100.3 t.a˗1, respectively. Of the exported TN and Org-N, 17.16% and 76.87%, respectively, were retained in the river network. Consequently, N transformation occurred in the Bai River, with nitrification–denitrification being particularly dominant. Nitrification was more evident in the nitrate-enriched river.

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

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

Identification and apportionment of groundwater nitrate sources in Chakari Plain (Afghanistan).

The Chakari alluvial aquifer is the primary source of water for human, animal, and irrigation applications. In this study, the geochemistry of major ions and stable isotope ratios (δ2H-H2O, δ18O-H2O, δ15N-NO3̄, and δ18O-NO3̄) of groundwater and river water samples from the Chakari Plain were analyzed to better understand characteristics of nitrate. Herein, we employed nitrate isotopic ratios and BSIMM modeling to quantify the proportional contributions of major sources of nitrate pollution in the Chakari Plain. The cross-plot diagram of δ15N-NO3̄ against δ18O-NO3̄ suggests that manure and sewage are the main source of nitrate in the plain. Nitrification is the primary biogeochemical process, whereas denitrification did not have a significant influence on biogeochemical nitrogen dynamics in the plain. The results of this study revealed that the natural attenuation of nitrate in groundwater of Chakari aquifer is negligible. The BSIMM results indicate that nitrate originated mainly from sewage and manure (S&M, 75‰), followed by soil nitrogen (SN, 13‰), and chemical fertilizers (CF, 9.5‰). Large uncertainties were shown in the UI90 values for S&M (0.6) and SN (0.47), whereas moderate uncertainty was exhibited in the UI90 value for CF (0.29). The findings provide useful insights for decision makers to verify groundwater pollution and develop a sustainable groundwater management strategy.

Microencapsulated and Ready-to-Eat Beetroot Soup: A Stable and Attractive Formulation Enriched in Nitrate, Betalains and Minerals

Beetroot is a tuber rich in antioxidant compounds, i.e., betanin and saponins, and is one of the main sources of dietary nitrate. The aim of the present study was to microencapsulate a ready-to-eat beetroot soup by lyophilization using different encapsulating agents, which supply the required amount of bioactive nutrients. Particle size distributions ranged from 7.94 ± 1.74 to 245.66 ± 2.31 µm for beetroot soup in starch and from 30.56 ± 1.66 to 636.34 ± 2.04 µm in maltodextrin. Microparticle yields of powdered beetroot soup in starch varied from 77.68% to 88.91%, and in maltodextrin from 75.01% to 80.25%. The NO3- and total betalain contents at a 1:2 ratio were 10.46 ± 0.22 mmol·100 g-1 fresh weight basis and 219.7 ± 4.92 mg·g-1 in starch powdered beetroot soup and 8.43 ± 0.09 mmol·100 g-1 fresh weight basis and 223.9 ± 4.21 mg·g-1 in maltodextrin powdered beetroot soup. Six distinct minerals were identified and quantified in beetroot soups, namely Na, K, Mg, Mn, Zn and P. Beetroot soup microencapsulated in starch or maltodextrin complied with microbiological quality guidelines for consumption, with good acceptance and purchase intention throughout 90 days of storage. Microencapsulated beetroot soup may, thus, comprise a novel attractive strategy to offer high contents of bioaccessible dietary nitrate and antioxidant compounds that may aid in the improvement of vascular-protective effects.

Nitrite Oxidation Across the Full Oxygen Spectrum in the Ocean

AbstractFixed nitrogen limits primary productivity in most areas of the surface ocean. Nitrite oxidation is the main source of nitrate, the most abundant form of inorganic fixed nitrogen. Even though known as an aerobic process, nitrite oxidation is not always stimulated by increased oxygen concentration, and nitrite oxidation occurs in layers of oxygen minimum zones (OMZs) where oxygen is not detectable. Nitrite‐oxidizing bacteria, known since their original isolation as aerobes, were also detected in these layers. Whether and how nitrite oxidation is occurring in the anoxic seawater is debated. Here, we reassess recent advances in marine nitrite oxidation in OMZ regions using previous work and new data sets we collected in two Pacific OMZs. We analyze the complex relationship between nitrite oxidation and oxygen. We discuss potential mechanisms explaining nitrite oxidation in different layers of OMZs based on recent findings and propose future directions to resolve the controversial question of apparently anaerobic nitrite oxidation in anoxic layers.

Unveiling the nitrogen transport and transformation in different karst aquifers media

Karst aquifers, a significant source of drinking water worldwide, are vulnerable to anthropogenic pollutants because of their special hydrogeological conditions. However, distinguishing the nitrogen transformation process is difficult owing to the heterogeneity of karst media. Therefore, the process of nitrogen transformation in different karst aquifer media remains poorly understood. In this study, multiple stable isotopic and physicochemical indicators are combined, the sources of water and nitrogen are analysed, and the degree of openness and redox conditions of different media are discussed to elucidate the nitrate sources and N transformation in groundwater with different degrees of openness. Water isotopes indicate local meteoric groundwater origin. However, different karst aquifer media have different degrees of openness, resulting in the highest deuterium–oxygen isotope values in surface water, followed by conduit water, fissure water, and isolated cave water. Based on the evidence from isotope and physicochemical indicators, different karst aquifer media have different redox processes. Isolated cave water environments were under anoxic conditions dominated by sulfate reduction reactions. Fissure water was under temporary anoxic or sub-anoxic conditions dominated by denitrification reactions. Conduit water and karst surface water were between micro-oxygen and oxidising conditions, and nitrification was the key process. This phenomenon was observed because the diversity of karst media produces different conservation conditions and openness. The nitrate isotope and Bayesian mixing model indicate that the main sources of nitrate in karst groundwater in the study area are mostly associated with manure and sewage wastes, and a few are from soil organic nitrogen, atmospheric deposition, and chemical fertilizer. This study helps identify the migration and transformation patterns and processes of nitrogen in different karst aquifer media, providing a scientific basis for the restoration and remediation of contaminated karst groundwater.

Determination of nitrate sources in a karst plateau reservoir based on nitrogen and oxygen isotopes

ABSTRACT Investigating the sources, migration and proportional contribution of nitrate is essential to effectively protect water quality. δ 15N-NO3 –, δ 18O-NO3 – and Stable Isotope Analysis in R (SIAR) were used to qualitatively and quantitatively analyse nitrate sources in the Pingzhai Reservoir water body. The values of δ 15N-NO3 – and δ 18O-NO3 – in water vary with season. Soil organic nitrogen and chemical fertilisers are the main sources of nitrate in autumn, while domestic sewage and livestock manure are the primary sources of nitrate in winter and spring. The SIAR results showed that chemical fertilisers, livestock manure, sewage, and soil organic nitrogen had the highest proportional contribution. In autumn, the proportional contribution of chemical fertilisers to river and reservoir were 47 and 51 %. During winter, the proportional contributions of livestock manure and sewage to river and reservoir were 53 and 68 %, respectively, and in spring 49 and 68 %, respectively. Considering the fragility of karst ecosystems, strict measures should be formulated for the use of chemical fertilisers and standards for sewage discharge should be raised. Control nitrogen input from agricultural activities and prevent water quality deterioration.

Identification of Nitrate Source of Surface Water in a Typical Peri-urban Watershed in the Tableland of the Loess Plateau, China

With the rapid development of industry and agriculture, nitrate pollution in surface water has become one of the serious environmental problems in the Loess Plateau region. In this study, Yanwachuan watershed, a typical suburban watershed in the gully region of a loess plateau, was selected as the research area. Using hydrochemical data and nitrogen and oxygen bistable isotopes, combined with the SIAR model, the contribution rates of different pollution sources of nitrate in surface water in the dry season and wet season were quantitatively identified, and the main reasons for seasonal differences in different pollution sources were clarified. The results showed that inorganic nitrogen mainly existed in the form of NO3--N and NO2--N, and the average concentration of NO3--N and NO2--N in the wet season was higher than that in the dry season, whereas NH4+-N showed the opposite characteristics. Nitrification was the main process of nitrate transformation in the surface water of the basin. In the wet season, the main sources of nitrate were manure and sewage, whereas in the dry season, manure, sewage, and soil N leaching were the dominant sources, followed by ammonium fertilizer. The contribution proportion of different pollution sources to nitrate in surface water of the watershed showed significant seasonal differences. The sewage had the highest contribution, accounting for 31.40% and 65.66% in the dry season and rainy season, respectively, and the contribution of sewage to NO3- in the wet season was much higher than that in the dry season. The increase in residential water consumption in summer led to a large amount of sewage discharge into the watershed.

Rapid nitrification involving comammox and canonical Nitrospira at extreme pH in saline-alkaline lakes.

Nitrite-oxidizing bacteria (NOB) catalyse the second nitrification step and are the main biological source of nitrate. The most diverse and widespread NOB genus is Nitrospira, which also contains complete ammonia oxidizers (comammox) that oxidize ammonia to nitrate. To date, little is known about the occurrence and biology of comammox and canonical nitrite oxidizing Nitrospira in extremely alkaline environments. Here, we studied the seasonal distribution and diversity, and the effect of short-term pH changes on comammox and canonical Nitrospira in sediments of two saline, highly alkaline lakes. We identified diverse canonical and comammox Nitrospira clade A-like phylotypes as the only detectable NOB during more than a year, suggesting their major importance for nitrification in these habitats. Gross nitrification rates measured in microcosm incubations were highest at pH10 and considerably faster than reported for other natural, aquatic environments. Nitrification could be attributed to canonical and comammox Nitrospira and to Nitrososphaerales ammonia-oxidizing archaea. Furthermore, our data suggested that comammox Nitrospira contributed to ammonia oxidation at an extremely alkaline pH of 11. These results identify saline, highly alkaline lake sediments as environments of uniquely strong nitrification with novel comammox Nitrospira as key microbial players.

Nitrate containing vegetables and dietary nitrate and nonalcoholic fatty liver disease: a case control study

BackgroundVegetables is the main sources of dietary nitrate. Studies suggested the potential link between nitrate content of vegetables and reduce the risk of chronic diseases. We aimed to assess the association between nitrate-containing vegetables (NCVs) with odds of nonalcoholic fatty liver diseases (NAFLD) in Iranian adults.MethodThis case-control study was performed on a total of 225 newly diagnosed NAFLD cases and 450 controls aged 20–60 years. Individuals’ dietary intakes were determined using a valid and reliable food frequency questionnaire.ResultsThe mean ± SD age and BMI of participants were 38.1 ± 8.8 years and 26.8 ± 4.3 kg/m2, respectively. In the fully adjusted model, the odds of NAFLD were decreased across tertiles of total NCVs [(adjusted OR: 0.20, 95%CI: 0.10–0.40), (Ptrend < 0.001)] and low-nitrate vegetables [(adjusted OR: 0.22, 95%CI: 0.11–0.48), (Ptrend < 0.001)]. Our results showed that each one SD increments in nitrate content of vegetables (adjusted OR: 0.73, 95%CI: 0.55–0.97) and nitrate content of fruits (adjusted OR: 0.59, 95%CI: 0.36–0.97) was associated with reduced odds of NAFLD (P < 0.05). However, there was a positive association between each one SD increments in nitrate content of dairy products and meats and processed meats with odds of NAFLD (adjusted OR: 1.34, 95%CI: 1.03–1.74), (P < 0.05).ConclusionOur finding suggested that a higher intake of vegetable nitrate may be related to a decrease the odds of NAFLD.

Identification of nitrogen pollution sources and transport transformation processes in groundwater of different landforms using C, H, N, and O isotope techniques: an example from the lower Weihe River.

Nitrogen pollution in groundwater is an environmental issue of global concern. Identifying nitrogen pollution sources and determining migration and transformation processes are the major ways to prevent and control nitrogen pollution in the groundwater on a regional scale. In this study, groundwater in the lower Wei River was investigated by combining multi-isotope tracing techniques with the SIAR hybrid model (source resolution) to trace the nitrate sources and their contribution rate to nitrogen pollution in groundwater of different geomorphological units, considering types of geomorphology as the units. The multi-isotope tracing technique allows dynamic analysis of nitrate sources, and the combination of this technology can improve the accuracy of nitrogen source traceability. The results indicated that the pH of the water bodies in the study area ranged from 6.83 to 8.01, which is neutral and weakly alkaline. The nitrogen pollution was mainly due to nitrates. The significant factors affecting nitrogen migration in groundwater are the geomorphological type, the chemical characteristics of the groundwater, and the age of the groundwater. Nitrogen migration and transformation processes in the study area were dominated by nitrification, and sources of nitrate pollution were mainly animal manure and domestic sewage (32.6%), followed by atmospheric deposition (26.8%), soil nitrogen (20.9%), and chemical fertilizer (19.7%). The main sources of nitrate in groundwater from river flats, alluvial plains, and loess tableland were animal manure and domestic sewage (43.7%), animal manure and domestic sewage (59.1%), and atmospheric deposition (55.5%), respectively. The result is mainly related to the different structural characteristics of various geomorphic units and the intensity of human activities. This study can provide a theoretical basis for the relevant agencies to develop plans to combat groundwater pollution.

The Relationship Between Nitrate and Potential Density in the Ocean South of 30°S

AbstractAs a main source of nitrate for the pycnocline in the global ocean, the ocean south of 30°S plays a pivotal role in the global marine biogeochemical cycle. Nitrate in the pycnocline often shows a more stable relationship with density than with depth. Hence, it is important to understand the nitrate structure and its relationship with density in the ocean south of 30°S. In the present study, the nitrate‐density relationship and the mechanisms for its variability are studied based on the data from more than 60,000 profiles. Through analysis, we find that nitrate is approximately linearly correlated with potential density in the nitracline, except for the western boundary current zones. The upper bounds of the nitracline depend on the mixed layer and euphotic layer depth. The lower bounds are related to the depth of maximum nitrate, which mainly vary meridionally with sharp changes near the Subantarctic Front. The diapycnal gradients of nitrate also show meridional variability, with large magnitudes corresponding to thick Subantarctic Mode Water, low diapycnal mixing in the nitracline, and high biological uptake in the euphotic layer. The nitrate‐density relationship can be applied to predict nitrate concentrations based on the observed temperature and salinity profiles and support some detailed studies on the physical‐biogeochemical interactions. Two examples show that the predicted nitrate data could help better resolve the effects of ocean circulations and mesoscale eddies on nitrate than the existing observed nitrate profiles.

PREDICTION OF NITRATE CONCENTRATION IN GROUNDWATER USING MLR AND AGRICULTURAL INDICATORS

Environmental pollution results in the degradation of all segments of nature. Groundwater, as one of thesignificant sources of drinking water at the global level, is increasingly exposed to various types of pollutants thatare mainly the result of anthropogenic action. Nitrate are one of the pollutants that can persist for a long time ingroundwater and their concentrations can reach high levels. Namely, the fact that groundwater is used for variouspurposes such as: irrigation, food production, drinking, special attention is focused on monitoring the concentrationof nitrate in groundwater. In this sense, EU legislation also prescribed a standard for drinking water in terms ofnitrate concentration in order to avoid possible threats to human health. The main sources of nitrate in groundwaterare agricultural activities, which primarily involve the use of chemical fertilizer, animal farms, waste water fromindustries that produce chemical fertilizer. In this paper, the prediction of average annual concentrations of nitrate ingroundwater at the national level was performed. Bearing in mind the mentioned sources of nitrate in groundwater, atotal of seven agricultural indicators were selected in this paper, which were assumed to contribute to higher nitrateconcentrations, namely: the area used for agriculture, meat production on farms, the balance of indicators - whichrepresents the total potential environmental risk caused by excess or deficit of N and P in agricultural soils, areaused for organic agricultural production, consumption of chemical fertilizer, sale of pesticides and percentage ofpopulation associated with at least secondary wastewater treatment. The prediction was made using multiple linearregression, where agricultural indicators were used as input parameters, i.e. independent variables, a total of seven,while the dependent variable was the average annual concentration of nitrate in groundwater at the national level. Inthis paper, five EU countries were selected for nitrate prediction: Belgium, Bulgaria, the Czech Republic, Germanyand France. For the development of the MLR (Multiple linear regression) model, available data from 2011 to 2015were used for all eight variables. Before developing the model, a correlation analysis was first performed todetermine whether the selected independent variables were correlated with the dependent variable. The results of thecorrelation analysis showed that there is a significant correlation between the independent and dependent variables.The developed MLR model showed good prediction results with a value of coefficient of determination R2 - 0.96.The results of the one year prediction by the MLR model showed satisfactory results, the biggest deviations betweenthe measured and model predicted values are in the case of Germany and France. Based on the obtained results, itcan be concluded that the MLR model can be applied as one of the alternatives in the assessment of nitrateconcentration in groundwater.

Sources and transformations of nitrate in Qixiangcuo Lake and its inflow rivers in the northern Tibetan Plateau.

Human activities and climate change input more reactive nitrogen into alpine lakes. Alpine saline lakes are usually located in endorheic watersheds at high-altitude areas, with no other drainage methods than evaporation, and are prone to accumulate nutrients. Meanwhile, alpine saline lakes are usually oligotrophic and sensitive to reactive nitrogen inputs, and even modest reactive nitrogen inputs may have significant effects on them, such as eutrophication. Nitrate is the main form of reactive nitrogen in lakes; therefore, clarifying the sources and transformations of nitrate in alpine saline lakes is important to prevent or mitigate eutrophication in alpine saline lakes. In this study, the sources and transformations of nitrate in Qixiangcuo Lake and its inflow rivers in the northern Tibetan Plateau were identified using dual nitrate isotopes and hydrochemistry. The results show that (1) the ranges of NO3- concentrations, δ15N - NO3-, and δ18O - NO3- values were 3.6 ~ 26.1μg/L, - 10.5 to + 6.0‰, and - 10.4 to + 9.2‰ in Qixiangcuo Lake and 194.4 ~ 728.1μg/L, + 5.8 ~ + 8.8‰, and - 1.9 to + 2.4‰ in its inflow rivers, respectively. The NO3- concentrations and δ15N - NO3- values were significantly lower in Qixiangcuo Lake than in its inflow rivers (P < 0.05). (2) The main sources of nitrate in both surface water and bottom water of Qixiangcuo Lake were ammonium in atmospheric deposition (mean probability estimate (MPE) 41.0% and 32.2%, respectively) and livestock manure (MPE 28.9% and 21.7%, respectively). The main sources of nitrate in the inflow rivers of Qixiangcuo Lake were domestic sewage (MPE 35.7%) and livestock manure (MPE 29.6%). (3) The main nitrogen transformation process in Qixiangcuo Lake was nitrification. The conservative mixing of multiple sources controlled the nitrate concentration and isotopic composition of Qixiangcuo Lake. Improvement in grazing area planning and the installation of sewage treatment facilities are effective measures to prevent eutrophication in Qixiangcuo Lake and its inflow rivers.