Technical report: modelling of chlorine residual for drinking water using parallel first order model / Nurul Afiqah Ahmad Nasrul, Farah Hanan Muhammad Hilmi and Tengku Syafiqah Tengku Mohamed Kamalludin

Setting the right amount of initial chlorine is important because if it is too low, the bacteria in the water will regrowth but if it is too high it can increase the carcinogenic effect. So, the water treatment company need to follow the World Health Organization (WHO) guideline to avoid this proble...

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Bibliographic Details
Main Authors: Ahmad Nasrul, Nurul Afiqah, Muhammad Hilmi, Farah Hanan, Tengku Mohamed Kamalludin, Tengku Syafiqah
Format: Student Project
Language:English
Published: 2016
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/110583/1/110583.pdf
https://ir.uitm.edu.my/id/eprint/110583/
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Summary:Setting the right amount of initial chlorine is important because if it is too low, the bacteria in the water will regrowth but if it is too high it can increase the carcinogenic effect. So, the water treatment company need to follow the World Health Organization (WHO) guideline to avoid this problem. In this study, the rate of chlorine decay, time taken for the chlorine to achieve minimum level and predictive chlorine residual are determined using the parallel first order model. The parallel first order decay model is model was first develop from first order decay model which consist of two different reaction rate (Haas & Karra, 1984). The data used in this project is the secondary data collected from Sungai Dua Treatment Plant Outlet, Penang. Chlorine residual data that was taken every day from five monitoring points. The reaction rate was obtained where the rate for fast reaction and slow reaction are 0.0108 and 0.0082 respectively. The predictive chlorine concentration formula for parallel first order is C(t) = l .86e-0-01081 (0.692) + l.86e-0·00821 (0.308). Tune taken for the chlorine to reach mini­mum level was obtained and the value is 227 hours. Thus, from the result obtain, it shows that mathematical modelling can be used to help in predicting and forecasting the chlorine concentration to ensure the quality of water distributed that compliance the guideline by WHO.