On the use of coprostanol to identify source of nitrate pollution in groundwater

Research output: Contribution to journalArticle


Investigation of contaminant sources is indispensable for developing effective countermeasures against nitrate (NO3 ) pollution in groundwater. Known major nitrogen (N) sources are chemical fertilizers, livestock waste, and domestic wastewater. In general, scatter diagrams of δ18O and δ15N from NO3 can be used to identify these pollution sources. However, this method can be difficult to use for chemical fertilizers and livestock waste sources due to the overlap of δ18O and δ15N ranges. In this study, we propose to use coprostanol as an indicator for the source of pollution. Coprostanol can be used as a fecal contamination indicator because it is a major fecal sterol formed by the conversion of cholesterol by intestinal bacteria in the gut of higher animals. The proposed method was applied to investigate NO3 pollution sources for groundwater in Shimabara, Nagasaki, Japan. Groundwater samples were collected at 33 locations from March 2013 to November 2015. These data were used to quantify relationships between NO3-N, δ15N-NO3 , δ18O-NO3 , and coprostanol. The results show that coprostanol has a potential for source identification of nitrate pollution. For lower coprostanol concentrations (<30 ng L−1) in the nitrate-polluted group, fertilizer is likely to be the predominant source of NO3 . However, higher concentration coprostanol samples in the nitrate-polluted group can be related to pollution from livestock waste. Thus, when conventional diagrams of isotopic ratios cannot distinguish pollution sources, coprostanol may be a useful tool.


External organisations
  • Nagasaki University
  • Kumamoto University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Water Treatment


  • Coprostanol, Groundwater, Nitrate pollution, Stable isotopes
Original languageEnglish
Pages (from-to)663-668
Number of pages6
JournalJournal of Hydrology
Publication statusPublished - 2017 Jul 1
Publication categoryResearch