Photocatalytic oxidation of treated municipal wastewaters for the removal of phenolic compounds: Optimization and modeling using response surface methodology (RSM) and artificial neural networks (ANNs)

Journal of Chemical Technology and Biotechnology

Volumn 87, Issue 10, 2012, Pages 1385-1395

  Antonopoulou, Maria ^a   Papadopoulos, Vassilios ^a   Konstantinou, Ioannis ^a  

^a UNIVERSITY OF IOANNINA   (Greece)

Author keywords

Artificial neural networks (ANNs); Municipal wastewaters; Phenolic compounds; Photocatalysis; Response surface methodology (RSM)

Indexed keywords

CENTRAL COMPOSITE DESIGNS; FEED-FORWARD; HETEROGENEOUS PHOTOCATALYSIS; INITIAL CONCENTRATION; INPUT VARIABLES; IRRADIATION INTENSITY; MICROTOX BIOASSAY; MULTI-LAYERED; MUNICIPAL WASTEWATERS; OPTIMUM CONDITIONS; PERCEPTRON; PHENOLIC COMPOUNDS; PHOTO CATALYTIC DEGRADATION; PHOTOCATALYTIC OXIDATIONS; PSEUDO-FIRST-ORDER KINETIC MODELS; REMOVAL OF PHENOLIC COMPOUNDS; RESPONSE SURFACE METHODOLOGY; TIO; TOTAL ORGANIC CARBON; TPH REMOVALS; TREATED WASTEWATER;

BIOASSAY; DEGRADATION; NEURAL NETWORKS; OPTIMIZATION; PHENOLS; PHOTOCATALYSIS; PHOTODEGRADATION; SURFACE PROPERTIES; TITANIUM DIOXIDE;

WASTEWATER TREATMENT;

PHENOL DERIVATIVE; TITANIUM DIOXIDE;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; BIOASSAY; CONTROLLED STUDY; DEGRADATION; IRRADIATION; KINETICS; OXIDATION; PHOTOCATALYSIS; PROCESS OPTIMIZATION; REDUCTION; RESPONSE SURFACE METHOD; TOTAL ORGANIC CARBON; TOXICITY; WASTE WATER MANAGEMENT;

EID: 84866740896     PISSN: 02682575     EISSN: 10974660     Source Type: Journal    
DOI: 10.1002/jctb.3755     Document Type: Article

References (41)

1. 2-photocatalysis as a tertiary treatment of naturally treated wastewater. Catal Today 76: 279-289 (2002).
2. Busca G, Berardinelli S, Resini C and Arrighi L, Technologies for the removal of phenol from fluid streams: a short review of recent developments. J Hazard Mater 160: 265-288 (2008).
3. Environment Canada, Canadian Environmental Protection Act, Priority substances List Assessment report: Phenol, 1999. www.ec.gc.ca.
4. Ho DP, Vigneswaran S and Ngo HH, Photocatalysis-membrane hybrid system for organic removal from biologically treated sewage effluent. Sep Purif Technol 68: 145-152 (2009).
5. Konstantinou IK and Albanis TA, Photocatalytic transformation of pesticides in aqueous titanium dioxide suspensions using artificial and solar light: intermediates and degradation pathways. Appl Catal B: Environ 42: 319-335 (2003).
6. 2-assisted photocatalytic degradation of azo dyes in aqueous solutions: kinetic and mechanistic investigations. A review. Appl Catal B: Environ 49: 1-14 (2004).
7. Konstantinou IK, Sakkas VA and Albanis TA, Photocatalytic degradation of the herbicides propanil and molinate over aqueous TiO2 suspensions. Identification of intermediates and the reaction pathway. Appl Catal B: Environ 34: 227-239 (2001).
8. 2 nanoparticles: effect of dye molecular structure and response surface approach. J Mol Catal A: Chem 333: 73-84 (2010).
9. Zou L and Zhu B, The synergestic effect of ozonation and photocatalysis on color removal from reused water. J Photochem Photobiol A: Chem 196: 24-32 (2008).
10. Klavarioti M, Mantzavinos D and Kassinos D, Removal of residual pharmaceuticals from aqueous systems by advanced oxidation processes. Environ Int 36: 402-417 (2009).
11. 2 in a solar pilot plant. Appl Catal B: Environ 103: 294-301 (2011).
12. Ahmed S, Rasul MG, Brown R and Hashib MA, Influence of parameters on the heterogeneous photocatalytic degradation of pesticides and phenolic contaminants in wastewater: A short review. J Environ Manage 92: 311-330 (2011).
13. nd edn. John Wiley & Sons, New York (2002).
14. Fox RJ, Elgardt D and Davis SC, Bayesian credible intervals of response surface optima. J Stat Plan Inf 139: 2498-2501 (2009).
15. Sleiman M, Vildozo D, Ferronato C and Chovelon JM, Photocatalytic degradation of azo dye Metanil Yellow: Optimization and kinetic modeling using a chemometric approach. Appl Catal B: Environ 77: 1-11 (2007).
16. Sakkas VA, Calza P, Medana C, Villioti AE, Baiocchi C, Pelizzetti E, et al, Heterogeneous photocatalytic degradation of the pharmaceutical agent salbutamol in aqueous titanium dioxide suspensions. Appl Catal B: Environ 77: 135-144 (2007).
17. Khataee AR and Kasiri MB, Artificial neural networks modeling of contaminated water treatment processes by homogeneous and heterogeneous nanocatalysis. J Mol Catal A: Chem 331: 86-100 (2010).
18. Secula MS, Suditu GD, Poulios I, Cojocaru C and Cretescu I, Response surface optimization of the photocatalytic decolorization of a simulated dyestuff effluent. Chem Eng J 141: 18-26 (2008).
19. Durán A, Monteagudo JM, San Martín I and Sánchez-Romero R, Photocatalytic treatment of IGCC power station effluents in a UV-pilot plant. J Hazard Mater 167: 885-891 (2009).
20. 2: optimization and modelling using the response surface methodology. Environ Chem Lett 7: 45-49 (2009).
21. 2/UV system: Optimization and modeling using a responsesurface methodology (RSM) based on the central composite design. Dyes Pigments 75: 533-543 (2007).
22. Almeida BM, Santelli RE, Oliveiraa LP, Villar LS and Escaleiraa LA, Response surface methology (RSM) as a tool for optimization in analytical chemistry. Talanta 76: 965-977 (2008).
23. Huitao L, Ketai W, Hongping X, Xingguo C and Zhicte H, Application of experimental design and artificial neural networks to separation and determination of active components in traditional chinese medicinal preparations by capillary electrophoresis. Chromatographia 55: 579-583 (2002).
24. Garcia SF, Sanchez MJ and Rodriguez-Delgado MA, Optimization of the separation of a group of triazine herbicides by micellar capillary electrophoresis using experimental design and artificial neural networks. Electrophoresis 25: 1042-1050 (2004).
25. Boti VI, Sakkas VA and Albanis TA, An experimental design approach employing artificial neural networks for the determination of potential endocrine disruptors in food using matrix solid-phase dispersion. J Chromatogr A 1216: 1296-1304 (2009).
26. Papadopoulos VD, Beligiannis GN and Hela DG, Combining experimental design and artificial neural networks for the determination of chlorinated compounds in fish using matrix solid-phase dispersion. Appl Softw Comput 11: 5155-5164 (2011).
27. nd edn. Prentice Hall International (1998).
28. rd edn. Prentice Hall International (2008).
29. Gimeno O, Carbajo M, Lopez MJ, Melero JA, Beltran F and Rivas FJ, Photocatalytic promoted oxidation of phenolic mixtures: an insight into the operating and mechanistic aspects. Water Res 41: 4672-4684 (2007).
30. Youssefi S, Emam-Djomeh Z and Mousavi SM, Comparison of artificial neural network (ANN) and response surface methodology (RSM) in the prediction of quality parameters of spray-dried pomegranate juice. Drying Technol 27: 910-927 (2009).
31. Salaices M, Serrano B and de Lasa HI, Photocatalytic conversion of phenolic compounds in slurry reactors. Chem Eng Sci 59: 3-15 (2004).
32. Liotta LF, Gruttadauria M, Di Carloc G, Perrini G and Librando V, Heterogeneous catalytic degradation of phenolic substrates: catalysts activity. J Hazard Mater 162: 588-606 (2009).
33. Roig B, Gonzalez C and Thomas O, Monitoring of phenol photo-degradation by ultraviolet spectroscopy. Spectrochim Acta A 59: 303-307 (2003).
34. Moreira RFPM, Sauer TP, Casaril L and Humeres E, Mass transfer and photocatalytic degradation of leather dye using TiO2/UV. J Appl Electrochem 35: 821-829 (2005).
35. Fotiadis C, Xekoukoulotakis PN and Mantzavinos D, Photocatalytic treatment of wastewater from cottonseed processing: effect of operating conditions, aerobic biodegradability and ecotoxicity. Catal Today 124: 247-253 (2007).
36. Kuo CH and Huang CH, Aqueous phase ozonation of chlorophenols. J Hazard Mater 41: 31-45 (1995).
37. Arslan-Alaton I and Akmehmet Balcioglu I, Biodegradability assessment of ozonated raw and biotreated pharmaceutical wastewater. Arch Environ Contam Toxicol 43: 425-431 (2002).
38. Ferreira F, Carvalho L, Pereira R, Antuness SC, Marques M, Goncalves F, et al, Biological and photo-fenton treatment of olive oil mill wastewater. Global Nest J 10: 419-425 (2008).
39. Martins RC, Rossi AF and Quinta-Ferreira RM, Fenton's oxidation process for phenolic wastewater remediation and biodegradability enhancement. J Hazard Mater 180: 716-721 (2010).
40. Zazo JA, Casas JA, Molina CB, Quintanilla A and Rodriguez JJ, Evolution of ecotoxicity upon Fenton's oxidation of phenol in water. Environ Sci Technol 41: 7164-7170 (2007).
41. Santos A, Yustos P, Rodríguez S, Vicente F and Romero A, Kinetic modeling of toxicity evolution during phenol oxidation. Ind Eng Chem Res 48: 2844-2850 (2009).