Abstract
Photocatalytic degradation, as an advanced oxidation process (AOPs), offers a great advantage to target persistent organic pollutants (POPs) in water. RSM in the present study which is statistical means for optimizing processes like photocatalysis with minimum laboratory experimentation. RSM has a history of being a potent design experiment tool for creating new processes, modifying their designs, and optimizing their performances. Herein, a highly sought-after, easily preparable, visible-light active, copper bismuth oxide (CuBi2O4) is applied against a toxic emerging contaminant, 2,4-dichlorophenol (2,4-DCP) under an LED light source (viible light λ > 420 nm). A simple coprecipitation method was adopted to synthesize CuBi2O4 and later analyzed with FESEM, EDX, XRD, FTIR, and spectroscopy to determine its intrinsic properties. Principally, the photocatalytic degradation investigations were based on response surface methodology (RSM), which is a commanding tool in the optimization of the processes. The 2,4-DCP concentration (pollutant loading), CuBi2O4 dosage (catalyst dosge), contact time, and pH were the chosen as dependent factors, that were optimized. However, under optimal conditions, the CuBi2O4 nanoparticle showed a remarkable photocatalytic performance of 91.6% at pH = 11.0 with a pollutant concentration of 0.5 mg/L and a catalyst dose of 5 mg/L within 8 h. The obtained RSM model showed a satisfactory correlation between experimental and predicted values of 2,4-DCP removal, with an agreeable probability value (p) of 0.0069 and coefficient of regression (R2) of 0.990. It is therefore anticipated that the study may open up new possibilities for formulating a plan to specifically target these organic pollutants. In addition, CuBi2O4 possessed fair reusability for three-consequent cycles. Hence, the as-synthesized nanoparticles applied for photocatalysis foster a fit-for-purpose and reliable system in the decontamination of 2,4 DCP in environmental samples, and also the study highlights the efficient use of RSM for environmental remediation, particularly in AOP implementation.
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Acknowledgements
R., Rakshitha gratefully acknowledges the Ministry of Tribal Affairs, New Delhi, India, for giving financial help via the “National Fellowship and Scholarship for Higher Education of S.T. Students,” broad Award No. 202021-NFST-KAR-00004. The JSS Academy of Higher Education and Research, Mysuru, provided a laboratory facility to the authors.
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RR executed the experiments, analyzed the obtained results, and prepared first draft of manuscript. CR supported in experimentation and curation of data. BMG and SHKD assisted in the interpretations of the results and validated th methodology for the study. NP hypothesized and supervised the study.
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Rakshitha, R., Rajesh, C., Gurupadayya, B. et al. A response surface modeling and optimization of photocatalytic degradation of 2,4-dichlorophenol in water using hierarchical nano-assemblages of CuBi2O4 particles. Environ Sci Pollut Res 30, 75655–75667 (2023). https://doi.org/10.1007/s11356-023-27774-9
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DOI: https://doi.org/10.1007/s11356-023-27774-9