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Simulation of the improving effect of graphene visible‐light photocatalysis using the MIKE11 model of an urban landscape river in the Chaohu Lake Basin, China.

Authors :
Xiong, Hongbin
Liu, Tianxin
Wang, Haiyun
Feng, Chenxiao
Source :
Natural Resource Modeling; Aug2022, Vol. 35 Issue 3, p1-18, 18p
Publication Year :
2022

Abstract

We selected the Tanchong River in Hefei as the site to test the efficacy of graphene visible‐light photocatalysis (GVLP), a new water treatment technology to improve water quality in black‐odorous rivers in urban landscapes. A model coupling the hydrodynamic force and water quality of the Tanchong River was constructed using the MIKE11 model. The numerical simulation method was used to model the concentrations of the main pollutants—chemical oxygen demand (COD), ammonia nitrogen (NH3–N) and total phosphorus (TP) concentrations. The simulation of water quality in the river section treated by GVLP was verified by the Tanchong River water quality improvement project experiment. The results showed that the MIKE11 model can effectively simulate the effect of GVLP technology on water quality improvement. The removal rates of the main pollutants'—COD, NH3–N, and TP by GVLP were 43.9%, 82.1%, and 76.8%, respectively, thus proving GVLP's viability as a treatment for controlling water pollution in similar black‐odorous rivers. Recommendations for Resource Managers: Described the treatment effect of a new type of water environment treatment technology—graphene photocatalysis technology in actual black‐odorous water. Experiments verified that the technology has a good treatment effect on black‐odorous rivers.MIKE11 model can be used to simulate the pollutant control effect of graphene visible‐light photocatalysis treatment technology in urban landscape rivers, and the simulation results can be used in the design optimization of the actual engineering projects. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08908575
Volume :
35
Issue :
3
Database :
Complementary Index
Journal :
Natural Resource Modeling
Publication Type :
Academic Journal
Accession number :
158392945
Full Text :
https://doi.org/10.1111/nrm.12344