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Application of artificial neural networks for modeling of the treatment of wastewater contaminated with methyl tert-butyl ether (MTBE) by UV/H2O2 process.
J Hazard Mater. 2005 Oct 17; 125(1-3):205-10.JH

Abstract

During the last two decades, methyl tert-butyl ether (MTBE) has been widely used as an additive to gasoline (up to 15%) both to increase the octane number and as a fuel oxygenate to improve air quality by reducing the level of carbon monoxide in vehicle exhausts. The present work mainly deals with photooxidative degradation of MTBE in the presence of H2O2 under UV light illumination (30W). We studied the influence of the basic operational parameters such as initial concentration of H2O2 and irradiation time on the photodegradation of MTBE. The oxidation rate of MTBE was low when the photolysis was carried out in the absence of H2O2 and it was negligible in the absence of UV light. The addition of proper amount of hydrogen peroxide improved the degradation, while the excess hydrogen peroxide could quench the formation of hydroxyl radicals (OH). The semi-log plot of MTBE concentration versus time was linear, suggesting a first order reaction. Therefore, the treatment efficiency was evaluated by figure-of-merit electrical energy per order (E(Eo)). Our results showed that MTBE could be treated easily and effectively with the UV/H2O2 process with E(Eo) value 80 kWh/m3/order. The proposed model based on artificial neural network (ANN) could predict the MTBE concentration during irradiation time in optimized conditions. A comparison between the predicted results of the designed ANN model and experimental data was also conducted.

Authors+Show Affiliations

Petroleum Research Laboratory, Department of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz, Iran.No affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Evaluation Study
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

15996818

Citation

Salari, D, et al. "Application of Artificial Neural Networks for Modeling of the Treatment of Wastewater Contaminated With Methyl Tert-butyl Ether (MTBE) By UV/H2O2 Process." Journal of Hazardous Materials, vol. 125, no. 1-3, 2005, pp. 205-10.
Salari D, Daneshvar N, Aghazadeh F, et al. Application of artificial neural networks for modeling of the treatment of wastewater contaminated with methyl tert-butyl ether (MTBE) by UV/H2O2 process. J Hazard Mater. 2005;125(1-3):205-10.
Salari, D., Daneshvar, N., Aghazadeh, F., & Khataee, A. R. (2005). Application of artificial neural networks for modeling of the treatment of wastewater contaminated with methyl tert-butyl ether (MTBE) by UV/H2O2 process. Journal of Hazardous Materials, 125(1-3), 205-10.
Salari D, et al. Application of Artificial Neural Networks for Modeling of the Treatment of Wastewater Contaminated With Methyl Tert-butyl Ether (MTBE) By UV/H2O2 Process. J Hazard Mater. 2005 Oct 17;125(1-3):205-10. PubMed PMID: 15996818.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Application of artificial neural networks for modeling of the treatment of wastewater contaminated with methyl tert-butyl ether (MTBE) by UV/H2O2 process. AU - Salari,D, AU - Daneshvar,N, AU - Aghazadeh,F, AU - Khataee,A R, PY - 2005/03/09/received PY - 2005/05/18/revised PY - 2005/05/24/accepted PY - 2005/7/6/pubmed PY - 2006/2/24/medline PY - 2005/7/6/entrez SP - 205 EP - 10 JF - Journal of hazardous materials JO - J Hazard Mater VL - 125 IS - 1-3 N2 - During the last two decades, methyl tert-butyl ether (MTBE) has been widely used as an additive to gasoline (up to 15%) both to increase the octane number and as a fuel oxygenate to improve air quality by reducing the level of carbon monoxide in vehicle exhausts. The present work mainly deals with photooxidative degradation of MTBE in the presence of H2O2 under UV light illumination (30W). We studied the influence of the basic operational parameters such as initial concentration of H2O2 and irradiation time on the photodegradation of MTBE. The oxidation rate of MTBE was low when the photolysis was carried out in the absence of H2O2 and it was negligible in the absence of UV light. The addition of proper amount of hydrogen peroxide improved the degradation, while the excess hydrogen peroxide could quench the formation of hydroxyl radicals (OH). The semi-log plot of MTBE concentration versus time was linear, suggesting a first order reaction. Therefore, the treatment efficiency was evaluated by figure-of-merit electrical energy per order (E(Eo)). Our results showed that MTBE could be treated easily and effectively with the UV/H2O2 process with E(Eo) value 80 kWh/m3/order. The proposed model based on artificial neural network (ANN) could predict the MTBE concentration during irradiation time in optimized conditions. A comparison between the predicted results of the designed ANN model and experimental data was also conducted. SN - 0304-3894 UR - https://www.unboundmedicine.com/medline/citation/15996818/Application_of_artificial_neural_networks_for_modeling_of_the_treatment_of_wastewater_contaminated_with_methyl_tert_butyl_ether__MTBE__by_UV/H2O2_process_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0304-3894(05)00269-4 DB - PRIME DP - Unbound Medicine ER -