59 citations as recorded by crossref.

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5. Understanding nitrate dynamics in urbanized and forested river ecosystems: A study integrating natural-abundance and paired isotopes J. Zhang et al. https://doi.org/10.1016/j.jenvman.2025.125073
6. Isotopic compositions reveal the driving forces of high nitrate level in an urban river: Implications for pollution control H. Jiang et al. https://doi.org/10.1016/j.jclepro.2021.126693
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8. Backgrounds as a potentially important component of riverine nitrate loads S. Li et al. https://doi.org/10.1016/j.scitotenv.2022.155999
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12. Research on the traceability and treatment of nitrate pollution in groundwater: a comprehensive review Y. Liu et al. https://doi.org/10.1007/s10653-025-02412-0
13. Tracking riverine nitrate sources under changing land use pattern and hydrologic regime Y. Huang et al. https://doi.org/10.1016/j.marpolbul.2020.110884
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19. Regime shift in aerosol ammonium between the rainy and dry season: Perspective from stable isotopes in bulk deposition X. Zhou et al. https://doi.org/10.1016/j.apr.2022.101462
20. A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley, California K. Ransom et al. https://doi.org/10.5194/hess-22-2739-2018
21. Identifying nitrate sources in surface water, regolith and groundwater in a subtropical red soil Critical Zone by using dual nitrate isotopes H. Wu et al. https://doi.org/10.1016/j.catena.2020.104994
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23. Bayesian approach for simultaneous recognition of contaminant sources in groundwater and surface-water resources Y. Ju et al. https://doi.org/10.1016/j.coesh.2021.100321
24. Driving forces of nitrogen cycling and the climate feedback loops in the Yarlung Tsangpo River Basin, the highest-altitude large river basin in the world W. Liu et al. https://doi.org/10.1016/j.jhydrol.2022.127974
25. FRAME—Monte Carlo model for evaluation of the stable isotope mixing and fractionation M. Lewicki et al. https://doi.org/10.1371/journal.pone.0277204
26. Spatiotemporal variations of nitrate sources and dynamics in a typical agricultural riverine system under monsoon climate H. Jiang et al. https://doi.org/10.1016/j.jes.2020.03.007
27. Nitrate sources and biogeochemical processes identified using nitrogen and oxygen isotopes on the eastern coast of Hainan Island F. Chen et al. https://doi.org/10.1016/j.csr.2020.104209
28. From Soil to River: Revealing the Mechanisms Underlying the High Riverine Nitrate Levels in a Forest Dominated Catchment S. Li et al. https://doi.org/10.1016/j.watres.2023.120155
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30. Determining nitrate pollution sources in the Kabul Plain aquifer (Afghanistan) using stable isotopes and Bayesian stable isotope mixing model A. Zaryab et al. https://doi.org/10.1016/j.scitotenv.2022.153749
31. Combined Nitrogen‐Isotope and Cyclostratigraphy Evidence for Temporal and Spatial Variability in Frasnian–Famennian Environmental Change L. Percival et al. https://doi.org/10.1029/2021GC010308
32. Nitrogen Cycling Across a Salinity Gradient From the Pearl River Estuary to Offshore: Insight From Nitrate Dual Isotopes F. Chen et al. https://doi.org/10.1029/2022JG006862
33. Typhoon landfall track significantly changes coastal nitrogen cycling pathways by altering hydrodynamic regimes C. Chen et al. https://doi.org/10.1016/j.marpolbul.2025.119197
34. Constraining nitrogen sources to a seagrass-dominated coastal embayment by using an isotope mass balance approach D. Russell et al. https://doi.org/10.1071/MF21320
35. Identifying nitrogen sources to thermal tide pools in Kapoho, Hawai'i, U.S.A, using a multi-stable isotope approach T. Wiegner et al. https://doi.org/10.1016/j.marpolbul.2015.12.046
36. Seasonal nitrogen sources and its transformation processes revealed by dual-nitrate isotopes in Xiamen Bay, China Y. Shi et al. https://doi.org/10.1016/j.rsma.2024.103902
37. Monte Carlo Simulations as a Decision Support to Interpret δ15N Values of Nitrate in Groundwater L. Wild et al. https://doi.org/10.1111/gwat.12936
38. Multiple isotopes reveal the driving forces of nitrogen cycling from freshwater to brackish water A. Zhang et al. https://doi.org/10.1016/j.scitotenv.2023.165396
39. Key biogeochemical processes and source apportionment of nitrate in the Bohai Sea based on nitrate stable isotopes K. Yu et al. https://doi.org/10.1016/j.marpolbul.2024.116617
40. Carbon-nitrogen association influences response of the microplankton food web to enrichment J. Guo et al. https://doi.org/10.3354/ame01993
41. Tracing the contributions of different nitrate sources associated with submarine groundwater discharge in coastal seawaters off Jeju Island, Korea J. Park et al. https://doi.org/10.1016/j.marchem.2024.104382
42. Comparative Study of Nitrogen Cycling Between a Bay With Riverine Input and a Bay Without Riverine Input, Inferred From Stable Isotopes C. Chen et al. https://doi.org/10.3389/fmars.2022.885037
43. Nitrogen pollution and sources in an aquatic system at an agricultural coastal area of Eastern China based on a dual-isotope approach Y. Li et al. https://doi.org/10.1007/s11356-019-05665-2
44. Nitrate source apportionment using a combined dual isotope, chemical and bacterial property, and Bayesian model approach in river systems Y. Xia et al. https://doi.org/10.1002/2016JG003447
45. Translocation of isotopically distinct macroalgae: A route to low-cost biomonitoring? D. Gröcke et al. https://doi.org/10.1016/j.chemosphere.2017.06.082
46. A stable isotope approach and its application for identifying nitrate source and transformation process in water S. Xu et al. https://doi.org/10.1007/s11356-015-5309-6
47. Quantification of nitrate sources and fates in rivers in an irrigated agricultural area using environmental isotopes and a Bayesian isotope mixing model Y. Zhang et al. https://doi.org/10.1016/j.chemosphere.2018.05.164
48. Isotopic Constraint on the Sources and Biogeochemical Cycling of Nitrate in the Jiulong River Estuary X. Wang et al. https://doi.org/10.1029/2020JG005850
49. Dissolved N pollution and its biogeochemical constraints along a river-sea continuum of a typical dense oyster mariculture coastal water, northwest South China Sea S. Felix Dan et al. https://doi.org/10.1016/j.jhazmat.2024.136207
50. Research Progress on Stable Nitrogen Isotope Tracing of Atmospheric Nitrate Sources C. DUAN et al. https://doi.org/10.3724/EE.1672-9250.2024.52.065
51. Nitrogen sources and cycling revealed by dual isotopes of nitrate in a complex urbanized environment A. Archana et al. https://doi.org/10.1016/j.watres.2018.06.004
52. Confirming the Source of High-Sulfate Concentrations in Dead Horse Creek, Winkler, Manitoba, Canada, Using a Dual-Isotope Bayesian Probability Mixing Model A. Dubinsky et al. https://doi.org/10.1007/s11270-020-04887-2
53. Multiple Isotopes Reveal a Hydrology Dominated Control on the Nitrogen Cycling in the Nujiang River Basin, the Last Undammed Large River Basin on the Tibetan Plateau H. Jiang et al. https://doi.org/10.1021/acs.est.1c07102
54. Triple oxygen isotopic evidence for atmospheric nitrate and its application in source identification for river systems in the Qinghai-Tibetan Plateau X. Xia et al. https://doi.org/10.1016/j.scitotenv.2019.06.204
55. Isotopic evidence for the shift of nitrate sources and active biological transformation on the western coast of Guangdong Province, South China Q. Lao et al. https://doi.org/10.1016/j.marpolbul.2019.04.026
56. Temporal variability of particle flux and its components in the Gotland Basin, eastern Baltic Sea O. Beltran-Perez et al. https://doi.org/10.3389/feart.2023.1171917
57. Mechanistic Characterization of Nitrate Transport and Transformation in Typical Semiarid River-Lake Systems, Northwest China: Implications by Dual Nitrogen–Oxygen Stable Isotopes A. Dong et al. https://doi.org/10.1021/acsestwater.5c01191
58. Quantitative assessment of nitrate sources in Jiaozhou Bay and its terrestrial inflows using nitrate stable isotope techniques H. Feng et al. https://doi.org/10.1016/j.marpolbul.2025.118203
59. Hydrological regulation of nitrate sources and transformation pathways in a sandy subterranean estuary constrained by dual isotopes A. Zidan et al. https://doi.org/10.1016/j.csr.2026.105705