Risk assessment and source identification of coastal groundwater nitrate in northern China using dual nitrate isotopes combined with Bayesian mixing model

ABSTRACT

Due to the intensive and complicated human activities, the identification of nitrate pollution source of coastal aquifer is usually a challenge. This study firstly adopted stable isotope technique and stable isotope analysis in R (SIAR) model to identify the nitrate sources and contribution proportions of different sources in typical coastal groundwater of northern China. The results showed that about 91.5% of the groundwater samples illustrated significantly high nitrate concentrations exceeding the maximum WHO drinking water standard (50 mg/l), reflecting the high risk of groundwater nitrate pollution in the coastal area. A total of 57 sampling sites were classified into three groups according to hierarchical cluster analysis (HCA). The δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻ values of groundwater samples from Group C (including nine samples) were much higher than those from Group A (including 40 samples) and Group B (including 8 samples). SIAR results showed that NH₄⁺ fertilizer was the dominant nitrate source for groundwater samples of Groups A and B while manure and sewage (M&S) served as dominant source for Group C. This study provided essential information on the high risk and pollution sources of coastal groundwater nitrate of northern China.

KEYWORDS:

• groundwater nitrate pollution
• source identification
• dual nitrate isotopes
• hierarchical cluster analysis
• stable isotope analysis in R model

Acknowledgments

The authors would like to thank the reviewers for their valuable suggestions on the manuscript.

Additional information

Funding

This work was supported by One Hundred-Talent Plan of Chinese Academy of Sciences (Grant numbers of Y629041021 and Y610061033), National Natural Science Foundation of China (No. 41671319), Two-Hundred Talents Plan of Yantai (Y739011021), and Research Program of CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation (No. 1189010002).