Estimation of Water Disinfection by Using Data Mining

• Autorzy: Bashayreh Esra'a , Manasrah Ahmad , Alkhalil Shahnaz , Abdelhafez Eman

Identyfikatory

DOI

10.12912/27197050/132088

• Języki publikacji: EN

Abstrakty

EN

In this study, the Artificial Neural Network (ANN) models and multiple linear regression techniques were used to estimate the relation between the concentration of total coliform, E. coli and Pseudomonas in the wastewater and the input variables. Two techniques were used to achieve this objective. The first is a classical technique with multiple linear regression models, while the second one is data mining with two types of ANN (Multilayer Perceptron (MLP) and Radial Basis Function (RBF). The work was conducted using (SPSS) software. The obtained estimated results were verified against the measured data and it was found that data mining by using the RBF model has good ability to recognize the relation between the input and output variables, while the statistical error analysis showed the accuracy of data mining by using the RBF model is acceptable. On the other hand, the obtained results indicate that MLP and multiple linear regression have the least ability for estimating the concentration of total coliform, E. coli and pseudomonas in wastewater.

Słowa kluczowe

EN

data mining; water disinfection; regression; artificial neural network

• Wydawca: Lubelski Oddział Polskiego Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology ; WNGB Wydawnictwo Naukowe
• Czasopismo: Ecological Engineering & Environmental Technology
• Rocznik: 2021
• Tom: Vol. 22, iss. 1
• Strony: 109--116
• Opis fizyczny: Bibliogr. 28 poz., rys., tab.

Twórcy

autor

Bashayreh Esra'a

• Department of Electrical Engineering, Communication and Computer, Al-Zaytoonah University of Jordan, Amman, Jordan

• https://orcid.org/0000-0003-4043-0999

autor

Manasrah Ahmad

• Department of Mechanical Engineering, Al-Zaytoonah University of Jordan, Amman, Jordan

• https://orcid.org/0000-0002-6736-6045

autor

Alkhalil Shahnaz

• Department of Mechanical Engineering, Al-Zaytoonah University of Jordan, Amman, Jordan

• https://orcid.org/0000-0002-1387-6883

autor

Abdelhafez Eman

• Department of Alternative Energy Technology, Al-Zaytoonah University of Jordan, Amman, Jordan

• https://orcid.org/0000-0001-9480-7582

Bibliografia

• 1. Ahmad A., M. Hamdan, E. Abdelhafez, E. Turk, J. Ibbini & N. Abu Shaban (2019) Water Disinfection by Solar Energy. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects Journal, DOI: 10.1080/15567036.2019.1666182.
• 2. Barlow, M., and T. Clarke (2017) Blue gold: the battle against corporate theft of the world’s water. Routledge.
• 3. Boyle, M., et al. (2008) Bactericidal effect of solar water disinfection under real sunlight conditions. Appl. Environ. Microbiol. 74, 10, 2997-3001.
• 4. Burhan, D. (2015) Solar water disinfection considerations: Using ultraviolet light methods to make water safe to drink, IJISET - International Journal of Innovative Science, Engineering & Technology 2, 253–64.
• 5. Castro-Alférez, M., et al. (2017) Mechanistic modeling of UV and mild-heat synergistic effect on solar water disinfection. Chemical Engineering Journal 316, 111-120.
• 6. Dawney, B., and J.M. Pearce (2012) Optimizing the solar water disinfection (SODIS) method by decreasing turbidity with NaCl. Journal of Water, Sanitation and Hygiene for Development 2, 2, 87-94.
• 7. Figueredo-Fernández, M., S. Gutiérrez-Alfaro, A Acevedo-Merino, and M.A. Manzano (2017) Estimating lethal dose of solar radiation for enterococcus inactivation through radiation reaching the water layer. Application to Solar Water Disinfection (SODIS). Solar Energy 158, 303-310.
• 8. Giannakis, S., E. Darakas, A.Escalas-Cañellas, and C. Pulgarin (2015) Temperature-dependent change of light dose effects on E. coli inactivation during simulated solar treatment of secondary effluent. Chemical Engineering Science 126, 483-487.
• 9. Gutiérrez‐Alfaro, S., A. Acevedo, M. Figueredo, M. Saladin, and M.A. Manzano (2017) Accelerating the process of solar disinfection (SODIS) by using polymer bags. Journal of Chemical Technology & Biotechnology 92, 2, 298-304.
• 10. Haider, H. (2017) Exposure Period Assessment for Solar Disinfection (Sodis) under Uncertain Environmental Conditions: A Fuzzy Rule-Based Model. International Journal of Water Resources and Arid Environments, 6.
• 11. Hernández C.D., J.M. Rodríguez, X.D. Galván, J.O. Medel, and M.R.J. Magaña (2015) Optimal use of chlorine in water distribution networks based on specific locations of booster chlorination: Analyzing conditions in Mexico. Water Science and Technology: Water Supply 16, 2, 493-505.
• 12. Islam, Md, A.K. Azad, Md Akber, M. Rahman, and I. Sadhu (2015) Effectiveness of solar disinfection (SODIS) in rural coastal Bangladesh. Journal of water and health 13, 4, 1113-1122.
• 13. Keeratipibul, S., A. Phewpan, and C. Lursinsap (2011) Prediction of coliforms and Escherichia coli on tomato fruits and lettuce leaves after sanitizing by using Artificial Neural Networks. LWT-Food Science and Technology 44, 1, 130-138.
• 14. Keogh, M.B., K. Elmusharaf, P. Borde, and K.G. McGuigan (2017) Evaluation of the natural coagulant Moringa oleifera as a pretreatment for SODIS in contaminated turbid water. Solar energy, 158, 448-454.
• 15. Lawrie, K., A. Mills, M. Figueredo-Fernández, S. Gutiérrez-Alfaro, M. Manzano, and M. Saladin (2015) UV dosimetry for solar water disinfection (SODIS) carried out in different plastic bottles and bags. Sensors and Actuators B: Chemical 208, 608-615.
• 16. Meierhofer, R., and M. Wegelin (2002) Solar water disinfection: a guide for the application of SODIS. Report by SANDEC (Water & Sanitation in Developing Countries) at EAWAG (Swiss Federal Institute for Environmental Science and Technology).
• 17. Hamdan M. and S. Darabee (2017) Enhancement of solar water disinfection using nanotechnology. International Journal of Thermal & Environmental Engineering 15, 2, 111-116.
• 18. Oates, P.M., P. Shanahan, and M.F. Polz (2003) Solar disinfection (SODIS): simulation of solar radiation for global assessment and application for pointof-use water treatment in Haiti. Water Research 37, 1, 47-54.
• 19. Padowski, J.C., S.M. Gorelick, B.H. Thompson, S. Rozelle, and S. Fendorf (2015) Assessment of human–natural system characteristics influencing global freshwater supply vulnerability. Environmental Research Letters 10, 10, 104014.
• 20. Polo, D., I. García-Fernández, P. Fernández-Ibáñez, and J.L. Romalde (2015) Solar water disinfection (SODIS): Impact on hepatitis A virus and on a human Norovirus surrogate under natural solar conditions. Int. Microbiol 18, 1, 41-49.
• 21. Sahel, S. Mulaw, N. Belachew, H. Gebretsadik, and G. Gebregziabher (2017) The Effect of Bottle Scratches and Lime Juice on Natural Solar Radiation Disinfection (SODIS) Techniques on Different Bacterial Colonies at ShoaRobit and Surrounding Rural Kebeles. American Journal of Life Sciences 5, 2, 57-64.
• 22. Shekoohiyan, S., S. Rtimi, G. Moussavi, S. Giannakis, and C. Pulgarin (2019) Enhancing solar disinfection of water in PET bottles by optimized in-situ formation of iron oxide films. From heterogeneous to homogeneous action modes with H2O2 vs. O2–Part 1: Iron salts as oxide precursors. Chemical Engineering Journal 358, 211-224.
• 23. Sift, M., S. Wagner, and M. Hessling (2016) Investigations on Temperature Effects and Germ Recovery for Solar Water Disinfection (SODIS). International Journal of Applied Sciences and Biotechnology 4, 4, 430-435.
• 24. Stubbé, S.ML, et al. (2016) Household water treatment and safe storage–effectiveness and economics., Drinking Water Engineering and Science 9. 1, 9-18.
• 25. Vivar, M., N. Pichel, M. Fuentes, A. López-Vargas (2017) Separating the UV and thermal components during real-time solar disinfection experiments: The effect of temperature. Solar Energy 146, 334-341.
• 26. Water, a shared responsibility – Report 2 (2006) World Water Assessment Programme (WWAP), New York, US.
• 27. Wu, W., G.C. Dandy, and H.R. Maier (2014) Optimal control of total chlorine and free ammonia levels in a water transmission pipeline using artificial neural networks and genetic algorithms. Journal of Water Resources Planning and Management 141, 7, 04014085.
• 28. Zounemat-Kermani, M., A. Ramezani-Charmahineh, J. Adamowski, and O. Kisi (2018) Investigating the management performance of disinfection analysis of water distribution networks using data mining approaches. Environmental monitoring and assessment 190, 7, 397.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).