PMID- 37222890
OWN - NLM
STAT- MEDLINE
DCOM- 20230628
LR  - 20230628
IS  - 1614-7499 (Electronic)
IS  - 0944-1344 (Linking)
VI  - 30
IP  - 30
DP  - 2023 Jun
TI  - A response surface modeling and optimization of photocatalytic degradation of 
      2,4-dichlorophenol in water using hierarchical nano-assemblages of CuBi(2)O(4) 
      particles.
PG  - 75655-75667
LID - 10.1007/s11356-023-27774-9 [doi]
AB  - 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 (CuBi(2)O(4)) is applied 
      against a toxic emerging contaminant, 2,4-dichlorophenol (2,4-DCP) under an LED 
      light source (viible light lambda > 420 nm). A simple coprecipitation method was 
      adopted to synthesize CuBi(2)O(4) 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), CuBi(2)O(4) dosage 
      (catalyst dosge), contact time, and pH were the chosen as dependent factors, that 
      were optimized. However, under optimal conditions, the CuBi(2)O(4) 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(2)) 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, CuBi(2)O(4) 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.
CI  - (c) 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, 
      part of Springer Nature.
FAU - Rakshitha, Rajashekara
AU  - Rakshitha R
AD  - Department of Environmental Science, Faculty of Natural Science, JSS Academy of 
      Higher Education and Research, Mysuru, 570015, India.
FAU - Rajesh, Chethan
AU  - Rajesh C
AD  - Department of Environmental Science, Faculty of Natural Science, JSS Academy of 
      Higher Education and Research, Mysuru, 570015, India.
FAU - Gurupadayya, Bannimath
AU  - Gurupadayya B
AD  - Department of Pharmaceutical Chemistry, JSS College of Pharmacy, JSS Academy of 
      Higher Education and Research, Mysuru, 570015, India.
FAU - Devi, Sake Haridas Kameshwari
AU  - Devi SHK
AD  - Department of Polymer Science and Technology, JSS Sciences and Technology 
      University, Mysuru, 570006, India.
FAU - Pallavi, Nagaraju
AU  - Pallavi N
AD  - Department of Environmental Science, Faculty of Natural Science, JSS Academy of 
      Higher Education and Research, Mysuru, 570015, India. anupallavi@jssuni.edu.in.
LA  - eng
PT  - Journal Article
DEP - 20230524
PL  - Germany
TA  - Environ Sci Pollut Res Int
JT  - Environmental science and pollution research international
JID - 9441769
RN  - R669TG1950 (2,4-dichlorophenol)
RN  - 059QF0KO0R (Water)
RN  - 0 (Chlorophenols)
RN  - 0 (Phenols)
RN  - 0 (Environmental Pollutants)
SB  - IM
MH  - Water
MH  - *Chlorophenols/chemistry
MH  - Phenols/chemistry
MH  - *Environmental Pollutants
MH  - Catalysis
OTO - NOTNLM
OT  - 2,4-dichlorophenol
OT  - Advanced oxidation processes
OT  - Chlorophenols
OT  - Response surface methodology
EDAT- 2023/05/24 13:08
MHDA- 2023/06/28 06:42
CRDT- 2023/05/24 11:29
PHST- 2022/12/23 00:00 [received]
PHST- 2023/05/16 00:00 [accepted]
PHST- 2023/06/28 06:42 [medline]
PHST- 2023/05/24 13:08 [pubmed]
PHST- 2023/05/24 11:29 [entrez]
AID - 10.1007/s11356-023-27774-9 [pii]
AID - 10.1007/s11356-023-27774-9 [doi]
PST - ppublish
SO  - Environ Sci Pollut Res Int. 2023 Jun;30(30):75655-75667. doi: 
      10.1007/s11356-023-27774-9. Epub 2023 May 24.