In The Science of the total environment
The source and evolution of sulfate (SO42-) in groundwater from abandoned mines are widely concerned environmental issues. Herein, the major dissolved ions, multi-isotopes (δ34S, δ18Osulfate, δ2H and δ18Owater), machine learning (Self-organizing maps) and Bayesian isotope mixing model were used to identify the source and evolution of SO42- in an abandoned mine (Fengfeng mine, northern China) with a multi-layer groundwater system. Groundwater in the study area was mainly divided into three clusters (Cluster I, Cluster II and Cluster III), dominated by Na-SO4, Ca-SO4 and Ca-HCO3 types, respectively. According to δ2H and δ18Owater, groundwater in the study area mainly originated from atmospheric precipitation. δ34S, δ18Osulfate and SO42- suggested that bacterial sulfate reduction did not affect the SO42- isotopic composition. Dual SO42- isotopes, and MixSIAR model revealed that the main source of SO42- in the study area was pyrite oxidation/gypsum dissolution, accounting for an average of 57.4 % (gypsum), 71.24 % (pyrite oxidation) and 52.93 % (pyrite oxidation) of SO42- in the samples of Clusters I-III, respectively. Combined with the hydrochemical diagrams, the evolution of SO42- in different clusters of samples was derived. Cluster I was mainly gypsum dissolution; In contrast, Clusters II and III were mainly pyrite oxidation accompanied by carbonate dissolution, and Cluster II was also influenced by cation exchange. These findings will help in developing management strategies for protecting groundwater quality, which will provide a reference for the study of solute sources and S cycling in abandoned mines.
Mao Hairu, Wang Chenyu, Qu Shen, Liao Fu, Wang Guangcai, Shi Zheming
2022-Nov-19
Abandoned mine, Bayesian isotope mixing model, Stable isotope, Sulfate
