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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.
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Água Subterrânea , Poluentes Químicos da Água , Nitratos/análise , Isótopos de Nitrogênio/análise , Monitoramento Ambiental/métodos , Nitrogênio/análise , Solo , Esgotos , China , Qualidade da Água , Poluentes Químicos da Água/análise , Teorema de BayesRESUMO
Increased nitrogen (N) from urban stormwater runoff aggravates the deterioration of aquatic ecosystems as urbanisation develops. The sources and transport of nitrate (NO3-) in urban stormwater runoff were investigated by analysing different forms of N, water isotopes (δD-H2O and δ18O-H2O), and NO3- isotopes (δ15N-NO3- and δ18O-NO3-) in urban stormwater runoff in a residential area in Hangzhou, China. The results showed that the concentrations of total N and nitrate N in road runoff were higher than those in roof runoff. Moreover, high concentrations of dissolved organic N and particulate N led to high total nitrogen (TN) concentrations in road runoff (mean: 3.76 mg/L). The high δ18O-NO3- values (mean: + 60 ± 13.1) indicated that atmospheric deposition was the predominant NO3- source in roof runoff, as confirmed by the Bayesian isotope mixing model (SIAR model), contributing 84-98% to NO3-. Atmospheric deposition (34-92%) and chemical fertilisers (6.2-54%) were the main NO3- sources for the road runoff. The proportional contributions from soil and organic N were small in the road runoff and roof runoff. For the initial period, the NO3- contributions from atmospheric deposition and chemical fertilisers were higher and lower, respectively, than those in the middle and late periods in road runoff during storm events 3 and 4, while an opposite trend of road runoff in storm event 7 highlighted the influence of short antecedent dry weather period. Reducing impervious areas and more effective management of fertiliser application in urban green land areas were essential to minimize the presence of N in urban aquatic ecosystems.
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Nitratos , Poluentes Químicos da Água , Teorema de Bayes , China , Ecossistema , Monitoramento Ambiental/métodos , Isótopos/análise , Nitratos/análise , Isótopos de Nitrogênio/análise , Poluentes Químicos da Água/análiseRESUMO
Riverine nitrogen pollution is ubiquitous and attracts considerable global attention. Nitrate is commonly the dominant total nitrogen (TN) constituent in surface and ground waters; thus, stable isotopes of nitrate (δ15N/δ18O-NO3-) are widely used to differentiate nitrate sources. However, δ15N/δ18O-NO3- approach fails to present a holistic perspective of nitrogen pollution for many coastal-plain river networks because diverse nitrogen species contribute to high TN loads. In this study, multiple isotopes, namely, δ15N/δ18O-NO3-, δ18O-H2O, δ15N-NH4+, δ15N-PN, and δ15Nbulk/δ18O/SP-N2O in the Wen-Rui Tang River, a typical coastal-plain river network of Eastern China, were investigated to identify transformation processes and sources of nitrogen. Then, a stable isotope analysis in R (SIAR) model-TN source apportionment method was developed to quantify the contributions of different nitrogen sources to riverine TN loads. Results showed that nitrogen pollution in the river network was serious with TN concentrations ranging from 1.71 to 8.09 mg/L (mean ± SD: 3.77 ± 1.39 mg/L). Ammonium, nitrate, and suspended particulate nitrogen were the most prominent nitrogen components during the study period, constituting 45.4 %, 28.9 %, and 19.9 % of TN, respectively. Multiple hydrochemical and isotopic analysis identified nitrification as the dominant N cycling process. Biological assimilation and denitrification were minor N cycling processes, whereas ammonia volatilization was deemed negligible. Isotopic evidence and SIAR modeling revealed municipal sewage was the dominant contributor to nitrogen pollution. Based on quantitative estimates from the SIAR model, nitrogen source contributions to the Wen-Rui Tang River watershed followed: municipal sewage (40.6 %) ≈ soil nitrogen (39.5 %) > nitrogen fertilizer (9.7 %) > atmospheric deposition (2.8 %) during wet season; and municipal sewage (59.1 %) > soil nitrogen (30.4 %) > nitrogen fertilizer (4.1 %) > atmospheric deposition (1.0 %) during dry season. This study provides a deeper understanding of nitrogen dynamics in eutrophic coastal-plain river networks, which informs strategies for efficient control and remediation of riverine nitrogen pollution.
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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.
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Nitratos , Poluentes Químicos da Água , Nitratos/análise , Isótopos de Nitrogênio/análise , Esgotos , Rios , Fertilizantes/análise , Esterco/análise , Estuários , Monitoramento Ambiental/métodos , Poluentes Químicos da Água/análise , Nitrogênio/análise , ChinaRESUMO
Nitrogen (N) loss by surface runoff inevitably results in severe N pollution and eutrophication of aquatic ecosystems. In this study, surface runoff from different land uses in the East Tiaoxi River watershed was collected, and the N concentrations, sources and losses were measured using the dual isotope (δ15N-NO3- and δ18O-NO3-), a Bayesian isotopic mixing (SIAR) model and Soil Conservation Service Curve Number (SCS-CN) method. The results showed that the N concentrations in surface runoff from agricultural lands were higher than those from urban areas and forestlands, and nitrate (NO3-), particulate nitrogen (PN) and dissolved organic nitrogen (DON) were the major forms of N in surface runoff in the East Tiaoxi River watershed. The total loss rate of total nitrogen (TN) from surface runoff in the East Tiaoxi River watershed was 5.38 kg·ha-1·a-1, with NO3--N (46%) contributing the most to TN loss. The TN, and NO3--N loss rates in surface runoff from tea planting lands (21.08 kg·ha-1·a-1, 11.98 kg·ha-1·a-1) and croplands (16.93 kg·ha-1·a-1, 10.96 kg·ha-1·a-1) were high, those from vegetable lands and urban areas were medium, and those from economic and natural forestlands were low in the East Tiaoxi River watershed. The NO3--N contributions of chemical fertiliser (CF), soil N (SN), sewage/manure (SM), and atmospheric deposition (AD) in surface runoff in the East Tiaoxi River watershed were 124.32 × 103, 104.84 × 103, 82.25 × 103 and 58.69 × 103 kg·a-1, respectively. The N pollutant losses in surface runoff from agricultural lands (croplands with rice growing, vegetable lands and tea planting lands) were responsible for most of the N pollutants being transported into the East Tiaoxi River systems.
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Poluentes Ambientais , Poluentes Químicos da Água , Nitrogênio/análise , Teorema de Bayes , Ecossistema , Poluentes Químicos da Água/análise , Monitoramento Ambiental/métodos , Solo , Rios , Chá , China , Nitratos/análise , Isótopos de Nitrogênio/análiseRESUMO
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.
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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.
Assuntos
Rios , Poluentes Químicos da Água , Teorema de Bayes , China , Ecossistema , Monitoramento Ambiental/métodos , Humanos , Nitratos/análise , Nitrogênio/análise , Isótopos de Nitrogênio/análise , Óxidos de Nitrogênio , Esgotos , Incerteza , Poluentes Químicos da Água/análiseRESUMO
Excessive quantities of nitrates in the aquatic environment can cause eutrophication and raise water safety concerns. Therefore, identification of the sources of nitrate is crucial to mitigate nitrate pollution and for better management of the water resources. Here, the spatiotemporal variations and sources of nitrate were investigated by stable isotopes (δ15N and δ18O), hydrogeochemical variables (e.g., NO3- and Cl-), and exogenous microbial signals (i.e., sediments, soils, domestic and swine sewage) in an agricultural watershed (Changle River watershed) in China. The concentration ranges of δ15N- and δ18O-NO3- between 3.03-18.97 and -1.55-16.47, respectively, suggested that soil nitrogen, chemical fertilizers, and manure and sewage (M&S) were the primary nitrate sources. Bayesian isotopic mixing model suggested that the major proportion of nitrate within the watershed (53.12 ± 10.40% and 63.81 ± 15.08%) and tributaries (64.43 ± 5.03% and 76.20 ± 4.34%) were contributed by M&S in dry and wet seasons, respectively. Community-based microbial source tracking (MST) showed that untreated and treated domestic wastewater was the major source (>70%) of river microbiota. Redundancy analysis with the incorporation of land use, hydrogeochemical variables, dual stable isotope, and exogenous microbial signals revealed domestic wastewater as the dominant cause of nitrate pollution. Altogether, this study not only identifies and quantifies the spatiotemporal variations in nitrate sources in the study area but also provides a new analytical framework by combining nitrate isotopic signatures and community-based MST approaches for source appointment of nitrate in other polluted watersheds.
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Nitratos , Poluentes Químicos da Água , Animais , Teorema de Bayes , China , Monitoramento Ambiental , Nitratos/análise , Isótopos de Nitrogênio/análise , Isótopos de Oxigênio/análise , Rios , Suínos , Águas Residuárias/análise , Poluentes Químicos da Água/análiseRESUMO
Multiple isotopes (C, N, and O) and hydrochemical data were used to trace the sources and fate of nitrate in ground and surface waters of the Babu subterranean stream watershed in Guizhou Province. The origin of nitrate in the water samples was also quantitatively analyzed by the SIAR model. Approximately 38% of the groundwater samples were not drinkable because the nitrate exceeded the drinking water standard, thereby indicating that the groundwater was seriously polluted by nitrate. The ranges of δ15N-NO3, δ18O-NO3, and δ18O-H2O in groundwater were 2.30-30.33 (mean of 9.68), 2.65-13.73 (mean of 6.64), and -8.83﹣-7.37 (mean of -8.18), respectively. Based on the stable isotopic compositions (δ15N-NO3, δ18O-NO3, and δ18O-H2O), nitrification was the dominant process in the basin. The nitric acid produced by nitrification promoted the dissolution of carbonate rocks, thereby leading to a significantly negative correlation (P<0.001) between the carbon isotope of dissolved inorganic carbon (δ13CDIC) and δ15N-NO3 and indicating that δ13CDIC, combined with δ15N-NO3, is effective in exploring the fate of nitrate in karst groundwater. The nitrate in the ground and surface waters mainly originated from soil N, manure and sewage, and ammonium nitrogen fertilizer. The results of the SIAR model showed that the contributions of soil N, manure and sewage, and ammonium nitrogen fertilizer were 36.19%, 33.71%, and 30.10% in groundwater, respectively, and 39.15%, 36.08%, and 24.77% in surface water, respectively. Therefore, it would be more effective to reduce the nitrate recharge flux in groundwater by simultaneously removing nitrate and ammonium nitrogen during wastewater treatment and by adopting scientific fertilization technology in agricultural areas.
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Different land uses have different impacts on the water quality of the region. Multiple isotopes (δD-H2O, δ18O-H2O, δ15N-NO3-, and δ18O-NO3-) and the SIAR (stable isotope analysis in R) model were applied to identify the nitrate sources and estimate the proportional contributions of multiple nitrate sources in a river in a typical urban area (the Grand Canal, Hangzhou) and a river in a typical forest and agricultural area (Yuying Riveri). The results indicated that there were different degrees of nitrogen pollution in the Grand Canal and Yuying River; NO3--N and NH4+-N are the predominant forms of nitrogen in the Grand Canal, and the primary form of nitrogen in Yuying River was NO3--N. There was an obvious linear relationship between the hydrogen and oxygen isotopes (R2=0.78). The δD-H2O and δ18O-H2O values for the Grand Canal and Yuying River were distributed along the local meteoric waterline, indicating that precipitation served as the primary water source in these rivers. All of the δ18O-NO3- values of the Grand Canal and Yuying River were lower than 15 . It was revealed that nitrification, rather than denitrification, was the primary N cycling process in the two rivers. The δ15N-NO3-/δ18O-NO3- ratios of some of the samples from the Grand Canal ranged from 1.3 to 2.1, accompanied by low concentrations of DO and NO2-, indicating that denitrification existed in some sections of the Grand Canal. The δ15N-NO3- values of the samples from the Grand Canal (average:6.1) were higher than those from the Yuying River (average:2.3). The NO3- source contributions differed significantly between the Grand Canal and Yuying River. The contributions of NO3- sources in the Grand Canal were sewage/manure (37.0%) > soil nitrogen (35.7%) > chemical fertilizer (19.1%) > precipitation (8.2%), and those in the Yuying River were chemical fertilizer (46.1%) > soil nitrogen (22.8%) > precipitation (17.3%) > sewage/manure (13.8%). The contribution of the sewage/manure was substantially increased in the Grand Canal in the urban area with stronger human activities primarily due to the sporadic discharge of domestic sewage and urban runoff. Chemical fertilizer is the main NO3- source in the Yuying River near the forest and agricultural area, suggesting that the nitrogen pollution caused by agricultural non-point sources was extremely serious. The contribution of precipitation decreased in the areas of substantial human activities. The isotopic fractionation produced by denitrification was affected by the contributions of the NO3- sources, which were calculated by SIAR model. Sewage/manure and chemical fertilizer produced significant impacts, followed by soil nitrogen and precipitation.
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Nitrate (NO3-) contamination has become a dominant international problem in the aquatic environment, so identifying the sources and transformations of NO3- is the basis for improving water quality. Since the Jing River is the largest tributary of the Wei River, to understand its water quality, this study collected surface water samples from the Shaanxi section of the Jing River during the dry season. The potential sources of NO3- were analyzed by hydrochemical and bi-isotopic methods, and the SIAR model was used to estimate the proportional contribution of each source. Results indicated that NO3--N was the main form of inorganic nitrogen in this area, and the average total nitrogen content was 10.23 mg·L-1, which showed that nitrogen pollution was highly serious; the transformation process of nitrogen in this study area was mainly nitrification; The results of Bayesian model showed that manure and sewage contributed to the most NO3- (64.39%) in the dry season, followed by soil nitrogen, which was 26.35%. These results help to adopt better nitrogen management measures to meet the national environmental quality standards for surface water.
Assuntos
Rios , Poluentes Químicos da Água , Teorema de Bayes , China , Monitoramento Ambiental , Nitratos/análise , Isótopos de Nitrogênio/análise , Poluentes Químicos da Água/análiseRESUMO
To increase crops yields, applying large amounts of fertilizers has become increasingly common in agricultural regions, resulting in NO3--N groundwater pollution. Agricultural non-point pollution is the main source of groundwater NO3--N pollution. To ensure drinking water safety and quality, it is crucial to clarify the sources of NO3--N pollution in agricultural regions. In this study, 35 sampling sites were randomly selected in the Qingdao agricultural area in 2009 and 2019. The spatial distribution of NO3--N concentration was analyzed by the inverse distance weighting method (IDW). The nitrogen and oxygen isotopes were used as a tool to trace sources of NO3--N and the SIAR model was used to quantify contribution proportion of pollution sources. The results showed that the concentration of NO3--N (average) in groundwater in Qingdao has been reduced from 38.49 mg·L-1 in 2009 to 22.37 mg·L-1 in 2019, but it is still higher than the maximum allowable concentration of NO3--N in drinking water set by the World Health Organization (WHO). The NO3--N concentration gradually increased from south to north both in 2009 and 2019. The cross diagram of δ15N-NO3- and δ18O-NO3- show that the main sources of NO3--N in groundwater in Qingdao are chemical fertilizers, soil nitrogen, and manure and sewage. Water isotopes indicate that precipitation was the main source of groundwater in Qingdao. The SIAR model results indicated that the contribution of each source ranked as follows:manure and sewage (47.42%) > soil nitrogen (27.80%) > chemical fertilizer (14.32%) > atmospheric nitrogen depositions (10.43%). From 2009 to 2019, the quality of groundwater in Qingdao has been improved, but NO3--N pollution still cannot be ignored. According to the results, prevention and control should be made to ensure the safety of drinking water and the sustainable development of agriculture.
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Água Subterrânea , Poluentes Químicos da Água , Agricultura , Monitoramento Ambiental , Fertilizantes/análise , Nitratos/análise , Isótopos de Nitrogênio/análise , Poluentes Químicos da Água/análiseRESUMO
Underground rivers are an important source of groundwater in karst area. Recently, nitrate pollution of underground rivers has become a serious issue. To identify the sources of nitrate in Guancun typical karst underground river basin, stable isotope techniques (δ15N-NO3-, δ18O-NO3-, and δ18O-H2O) were applied in this study. The contribution rates of different nitrate sources in groundwater were quantitatively identified based on the stable isotope analysis in R (SIAR) model, and the influence of land use type on nitrate distribution and source in watershed water was clarified. The results showed that â nitrate mainly came from fertilizers, soil organic nitrogen, and manure/sewage based to the isotopic composition of nitrate nitrogen and oxygen isotopes. It was revealed that non-point sources significantly contributed to nitrate in waters of the Guancun underground river basin. â¡ Nitrification dominated the formation process of nitrate in groundwater, and the initial values of nitrogen and oxygen isotopes were not affected by fractionation. ⢠Based on SIAR, the contribution of different sources to nitrate in water in the basin varied seasonally, and the contributions of fertilizer, soil organic nitrogen, and manure/sewage to nitrate were 57.07%, 34.06%, and 8.87% in the wet season and 34.14%, 33.02%, and 32.84% in the dry season, respectively. Overall, the present study quantitatively evaluated the temporal variations of nitrate sources in a typical karst groundwater river basin and provided a theoretical foundation for prevention and control management of non-point source pollution and watershed management in karst areas.
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To identify the sources and transformation processes of nitrate in surface water and groundwater in a karst basin, water samples were collected in the Songbai Mountain Reservoir basin during the normal and dry seasons. The spatio-temporal distribution, sources, and transformation processes of nitrate in the waters were analyed using a hydrochemical and stable isotopic (δ15N-NO3-, δ18O-NO3-, and δ18O-H2O) multi-tracing approach. The contribution rates of different nitrate sources in surface and groundwater were estimated based on the SIAR model. The results showed that NO3--N and NH4+-N were the main species of dissolved inorganic nitrogen in the waters. The over standard rate of NO3--N in groundwater was 7.89% in the normal season and 16.67% in the dry season. Temporally, the nitrate concentrations of waters in the dry season were higher than those in the normal season. Spatially, the nitrate concentrations of groundwater around dryland areas (from the Kailun River to the Songbai Mountain Reservoir) were higher than those of paddy fields (Ganhe River), and the nitrate concentrations of surface water in dryland and construction sites (Kailun River) were generally high. Nitrification was the dominant process in the waters. The nitrate in the waters mainly came from soil organic nitrogen, manure/sewage, and chemical fertilizers; their contribution rates to nitrate were 36.7%, 34.7%, and 28.6% for surface water and 39.9%, 34.9%, and 25.2% for groundwater, respectively. Nitrate pollution in the waters was mainly affected by agricultural activities and the discharge of sewage; appropriate control measures such as water and fertilizer regulation for farmland and treatment of rural sewage should be strengthened.