Use of a Bayesian isotope mixing model to estimate proportional contributions of multiple nitrate sources in surface water

2012 ◽  
Vol 161 ◽  
pp. 43-49 ◽  
Author(s):  
Dongmei Xue ◽  
Bernard De Baets ◽  
Oswald Van Cleemput ◽  
Carmel Hennessy ◽  
Michael Berglund ◽  
...  
2021 ◽  
Vol 778 ◽  
pp. 146297
Author(s):  
Yasheng Shi ◽  
Cai Li ◽  
Zanfang Jin ◽  
Yongqi Zhang ◽  
Jiazheng Xiao ◽  
...  

2020 ◽  
Vol 700 ◽  
pp. 134517 ◽  
Author(s):  
Widad Fadhullah ◽  
Nur Syahirah Yaccob ◽  
M.I. Syakir ◽  
Syahidah Akmal Muhammad ◽  
Fu-Jun Yue ◽  
...  

2020 ◽  
Author(s):  
Juan Antonio Torres-Martinez ◽  
Abrahan Mora ◽  
Peter S.K. Knappett ◽  
Nancy Ornelas-Soto ◽  
Jürgen Mahlknecht

<p>Groundwater quality deterioration by nitrate pollution due to the intensive use of fertilizers in agriculture, release of untreated urban sewage and industrial wastewater, and atmospheric deposition is a worldwide concern. The urbanized and industrialized Monterrey valley has a long record of elevated nitrate concentrations in groundwater with multiple potential pollution sources. This study aimed to fingerprint different sources and transformation processes of nitrate pollution in Monterrey using a suite of chemical and isotopic tracers (δ<sup>2</sup>H-H<sub>2</sub>O, δ<sup>18</sup>O-H<sub>2</sub>O, δ<sup>15</sup>N-NO<sub>3</sub>, δ<sup>18</sup>O-NO<sub>3</sub>) combined with a Bayesian isotope mixing model. The results suggest that soil nitrogen and sewage were the most important nitrate sources. However, the concentrations of nitrate were controlled by denitrification processes in the transition and discharge zones. The approach followed in this study is useful for establishing effective pollution management strategies in contaminated aquifers.</p>


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