Photocatalytic degradation of acetaminophen, ciprofloxacin and amoxicillin using UV/ZnO in a suspended photocatalytic reactor

被引:0
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作者
Karthika, V. [1 ]
Karthikeyan, S. [2 ]
Kathirvel, R. [2 ]
机构
[1] S.A. Engineering College, Department of Civil Engineering, Chennai,600 077, India
[2] Anna University, Department of Civil Engineering, Centre for Environmental Studies, Chennai,600 025, India
关键词
Biodegradation - Photocatalytic activity - Photodegradation - Photolysis - Ultraviolet spectrophotometers;
D O I
10.1088/1402-4896/ad804a
中图分类号
学科分类号
摘要
This study aims at evaluation of the photocatalytic degradation of pharmaceutical compounds acetaminophen (ATM), ciprofloxacin (CXN), and amoxicillin (AMX) using zinc oxide (ZnO) nano powder as a photocatalyst in a suspended reactor using a 16 W UV lamp. Operating parameters pH, catalyst dosage, and pollutant concentration were optimised for a working volume of 1.3 litres of model pharmaceutical compounds. The photo degradation efficiency was 95% at pH 6 after 5 h of irradiation for ATM, 98% at pH 6 after 2 h of irradiation for CXN, and 100% at pH 10 after 3 h of irradiation for AMX. The reaction kinetics for the degradation of ATM, CXN, and AMX followed pseudo-first order with the rate constants in the order of kAMX>kCXN>kATM 0.0321 min−1, 0.0232 min−1 and 0.0070 min−1 respectively. TOC (Total Organic Carbon) analysis was carried out for the model compounds, among which compound amoxicillin was found having a higher rate constant of about 0.0108 min−1, which is 1.2 times higher than ciprofloxacin and 2.5 times greater than acetaminophen. This study concludes that ZnO nano powder is efficient in degrading the model pharmaceutical compounds ATM, CXN, and AMX by utilising the UV light, which is evident from the results of the UV-vis spectrophotometer, HPLC analysis, and mineralisation study. In addition, ANOVA was performed on the results obtained from optimisation studies, which confirms the substantial influence of the operating parameters on the degradation of the compounds. © 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
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