ZHANG L Y,MA Y Y,LI G W,et al.Research progress of stable isotopes in source analysis of nitrate pollution in water[J].Journal of Environmental Engineering Technology,2023,13(4):1373-1383. DOI: 10.12153/j.issn.1674-991X.20221103
Citation: ZHANG L Y,MA Y Y,LI G W,et al.Research progress of stable isotopes in source analysis of nitrate pollution in water[J].Journal of Environmental Engineering Technology,2023,13(4):1373-1383. DOI: 10.12153/j.issn.1674-991X.20221103

Research progress of stable isotopes in source analysis of nitrate pollution in water

  • Accurate identification of nitrate pollution sources in water bodies is crucial, and stable isotopes have been widely used in source analysis studies of nitrate pollution in water bodies. Still, there are few studies on the influence of isotope fractionation on the accuracy of source analysis results. The stable isotope analysis technology and its application in the analysis of nitrate pollution sources in water bodies were introduced, and by comparing the spatial and temporal variability of δ15N-NO3 and δ18O-NO3 in nitrogen transformations and the application of other technical methods in the source analysis of nitrate pollution, the limitations of the current stable isotope techniques in the source analysis of nitrate pollution were presented. The results showed that isotopic fractionation in nitrogen transformation had a strong influence on δ15N-NO3 and δ18O-NO3 in water, and the use of δ15N-NO3 and δ18O-NO3 of potential sources that met environmental characteristics was the key to ensure the accuracy of stable isotope model analysis results. Therefore, an in-depth study of microbial information related to nitrogen transformation in water bodies would help to further understand the characteristics of nitrate in migration transformation; the input of nitrate from soil layer or groundwater should be the key investigation end source for nitrate pollution source analysis in surface water bodies; the development of stable isotope models adapted to the geoclimatic characteristics of the study area in combination with machine learning was the future research direction to achieve accurate source tracing.
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