A response surface modeling and optimization of photocatalytic degradation of 2,4-dichlorophenol in water using hierarchical nano-assemblages of CuBiO particles.

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 (CuBiO) 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 CuBiO 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), CuBiO dosage (catalyst dosge), contact time, and pH were the chosen as dependent factors, that were optimized. However, under optimal conditions, the CuBiO 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 (R) 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, CuBiO 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.