Effects of Graphene on the Transport of Quinolones in Porous Media

Author:

Cheng Zhou12,Mo Cehui1,Wu Ming134,Cao Huihui1,Hao Yanru1,Lu Guoping1,Li Qusheng5,Wu Jianfeng3,Wu Jichun3,Hu Bill X.6

Affiliation:

1. Guangdong Provincial Research Center for Environment Pollution Control and Remediation Materials, College of Life Science and Technology, Jinan University, Guangzhou 510632, China

2. Soil Environment Research Department, Guangdong Provincial Academy of Environmental Science, Guangzhou 510045, China

3. Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China

4. Guangdong Yixin Ecological Technology Co., Ltd., Guangzhou 510055, China

5. Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 510632, China

6. School of Water Conservancy and Environment, University of Jinan, Jinan 250022, China

Abstract

The effect of graphene (GN) on the transport of CIP and NOR in porous media is investigated by a combination of batch experiments, column experiments and mathematical models. The results obtained by batch experiments show that GN has great adsorption capacity to two antibiotic contaminants, and the maximum adsorption amounts based on the Langmuir model calculation are 270.67 mg/g and 178.36 mg/g, respectively. The column experiments suggest the mobility of CIP and NOR decreases with the mass fraction of GN packed in porous media, and the mass recovery rates of CIP and NOR increase with flow velocity. As the concentration of Na+ increases, the mobility of CIP and NOR is enhanced. However, Ca2+ has a significant enhancement effect on the mobility of CIP and NOR. Moreover, the transport processes of CIP and NOR in the column are predicted by a BDST mathematical model, and the calculated results are in good agreement with the experimental results. The relationships between kinetic parameters related to QNs’ mobility and GN content, flow velocity and ionic strength are obtained by a regression analysis, which can be used to predict the mobility of CIP and NOR in porous media.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Natural Science Foundation of Guangzhou City

National Key Research and Development Plan of China

Publisher

MDPI AG

Subject

Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry

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