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Updated: Jun 8, 2025

Removal of Trace Elements by Cupric Oxide Nanoparticles from Uranium In Situ Recovery Bleed Water and Its Effect on Cell Viability
Published on: June 21, 2015
A bidirectional kinetic reaction model to predict uranium distribution in permeable reactive bio-barrier with
Fuxin Zheng1, Yanguo Teng1, Jinsheng Wang2
1Engineering Research Center for Groundwater Pollution Control and Remediation of Ministry of Education of China, College of Water Sciences, Beijing Normal University, Beijing, 100875, China.
Abstract:
The use of permeable reactive bio-barriers (Bio-PRBs) is a developing method for remediation of uranium groundwater pollution. However, some remediation effects are difficult to estimate when because of the subsurface environment. Advanced knowledge of uranium migration and reactions in Bio-PRBs is crucial for successful practical application. In this study, a bidirectional kinetic reaction model was developed for predicting uranium reduction in a Bio-PRB system. The research demonstrates that the model is able to predict the uranium migration and rapidly evaluate the Bio-PRBs performance. The results show that contact period and microbial growth are the key factors that affect the remediation performance of Bio-PRBs. Microbial growth could lead to a decrease in hydraulic conductivity (K). The hydraulic conductivity loss in the free microorganisms (FM) group was 0.8-2.3 m/d, which was significantly smaller than the immobilized microorganism (IM) group (0.8-5.2 m/d). Compared to the IM group, the simulation results reveal that longer contact reaction period improves the remediation performance of SO42- and uranium by 32.6% and 21.7%, respectively. The bidirectional reaction between microorganisms and pollutants leads to a decrease in the remediation efficiency. In addition, the model can be used to design standard Bio-PRBs for real field of uranium contanminated groundwater. To meet the remediation goal of groundwater, the width of IM group needs to be increased to 250 cm while 500 cm for FM group. Therefore, IM-PRBs save costs significantly. The model has successfully optimized Bio-PRBs and predicted uranium contaminant-plume evolution and microbial growth inhibition in different Bio-PRBs.
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