Modeling of Petrochemical industries wastewater COD Removal with DOE&ANN

Document Type : Chemistry Article

Authors

1 semnan university

2 amirkabir university

Abstract

In this research, photocatalytic degradation method for COD(CHEMICAL OXYGEN DEMAND Value) removal has been introduced to treatment of petrochemical industries wastewater as an adaptable method and effective parameters in the process performance have been investigated. Therewith, by using commercial photocatalyst of titanium dioxide and empirical measurement of COD parameter, decrease percentage of this parameter of photocatalytic process during 90 minutes investigated via DOE&ANN method. To carry out experiments,A photocatalytic reactor with agitator used which UV-C lamps submerged within photocatalyst solution in the wastewater sample. Results of experiments at optimized conditions indicated that two models is in a good agreement with the consequences. These results demonstrated that photocatalyst concentration increase in the neutral pH state to optimized amount of 0.84 grams per liter under unlimited conditions and 2 grams per liter under limited conditions, causes removal increase of COD to 93 and 77 percent, respectively(from 180 to 90 and 294 respectively).

Keywords

Main Subjects

References

[1] G.S. Wang, H. Liau, H.W. Chen, H.C. Yang, "Characteristics of natural organic matter degradation in water by UV/ H2O2 treatment", Environmental Technology, Vol. 27, No. 3, 2006, pp. 277–287.
[2] C.E. Ellis, "Wet Air Oxidation of refinery spent caustic", Environmental Progress banner, Vol. 17, Issue 1, 2008, pp. 28–30.
[3] S. Mara, M. Carlos, "Wet Air Oxidation of Refinery Spent Caustic: A Refinery Case Study", NPRA Conference, San Antonio Texas, 2000.
[4] H. Shin, S.W. Hung, "Treatment of olefin plant spent caustic by combination of neutralization and fenton reaction", Water Research, Vol.35, No. 8, 2001, pp. 2017–2021.
[5] N. Rodriguez, K. Henrik, N. Patricio, "Spent caustic oxidation using electro-generated Fenton's reagent in a batch reactor", Journal of Environmental Science and Health, Part. A, Vol. 43, Issue 8, 2008, pp. 952–960.
[6] P. Nu ez, K. Henrik, N. Rodriguez, G. Claudia, "Electrochemical Generation of Fenton's Reagent to Treat Spent Caustic Wastewater", Separation Science and Technology, Vol. 44, Issue 10, 2008, pp. 2223–2233.
[7] Z.Z. Yu, D.Z. Sun, CH. Li, P.F. Shi, X.D. Duan, G.R. Sun, J.X. Liu, "UV-catalytic treatment of spent caustic from ethane plant with hydrogen peroxide and ozone oxidation", Journal of Environmental Science, Vol. 16, No. 2, 2004, pp. 272–275.
[8] A. Hawari, R. Hasanat, Abu-R. Ibrahim, O. Mabrouk, "A comparative study of the treatment of ethylene plant spent caustic by neutralization and classical and advanced oxidation", Journal of Environmental Management, Vol. 15, 2015, pp.105–112.
[9] S.H.Y. Abdulah, M.A. Abu-Hassan, Z. Zainon-Noor, A. Aris, "Optimization of photo-Fenton oxidation of sulfidic spent caustic by using response surface methodology", Journal of Environmental Science, Vol. 25, 2011, pp. 231–239.
[10] C. Chen. C. Ting, "Wet Air Oxidation and Catalytic Wet Air Oxidation for refinerey spent caustic degradation", Journal of Chemical Society of Pakistan, Vol.35, No. 2, 2013, pp. 74–81.
[11] M. Alaiezadeh, "Spent caustic wastewater treatment with electrical coagulation method", the first international conference oil, gas, petrochemical and power plant, Iran, June 2015.
[12] D.C. Montgomery, Design and analysis of experiments, 6rd Edition, John Wiley & Sons, 2012, pp. 1–638.
[13] S. Haykin, Neural Networks: A Comprehensive Foundation. 4th ed., Prentice Hall PTR, 2008.
[14] Standard methods for the examination of water and wastewater, in American Public Health Association (APHA): Washington, DC, USA, W.E. Federation and A.P.H. Association, Editors, 2015.
[15] U.I. Gaya, A.H. Abdullah, "Heterogeneous photocatalytic degradation of organic contaminants over titanium dioxide: A review of fundamentals, progress and problems", Journal of Photochemistry and Photobiology C: Photochemistry Reviews, Vol.9, Issue 1, 2008, pp.1–12.
]16[  ح. باقرپور، "شبیه سازی فرآیند سوخت بیودیزل حاصل از روغنهای پسماند با استفاده از شبکه عصبی"، مجله مدلسازی در مهندسی، دانشگاه سمنان، دوره 12، شماره 39، 1393، صفحه 143-149.
]17[ م. مهدی پور قاضی، "مدلسازی ریاضی و شبکه عصبی انتقال جرم در غشاهای مایع آمین گلایکول برای جداسازی دی اکسید کربن از هوا"، مجله مدلسازی در مهندسی، دانشگاه سمنان، دوره 14، شماره 47، 1395، صفحه 51-60.
 
 
Journal of Modeling in Engineering
Volume 16, Issue 54
October 2018
Pages 295-307

Files

History

  • Receive Date: 21 May 2017
  • Revise Date: 15 November 2017
  • Accept Date: 25 November 2017

Share

How to cite

Statistics