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DOI: https://doi.org/10.4491/eer.2020.402
Multi-linear regression model for chlorine consumption by waters
Guocheng Zhu1, Shanshan Zhang1, Yongning Bian1, and Andrew S Hursthouse2
1Hunan Provincial Key Laboratory of Shale Gas Resource Utilization, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China
2School of Computing, Engineering & Physical Sciences, University of the West of Scotland, Paisley, PA1 2BE UK
Corresponding Author: Guocheng Zhu ,Tel: +0731-58290269, Fax: +0731-58290269, Email: zgc945ahhn@163.com; zhuguoc@hnust.edu.cn
Received: July 8, 2020;  Accepted: September 2, 2020.
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ABSTRACT
In drinking water treatment, disinfection is a key step to ensure the safety of water quality and people's health but little is known of the relationship between chlorine consumption and water matrix properties from varied sources (BWM). In this study, we measured the fluorescence from fractions of NOM (FFN) for the relevant BWM. This included the evaluation of three components: the chlorine-dependence factor (CDF) (DOC and NH3-N), the BWM (such as NO3-, NO2- and turbidity), and FFN (I-V fluorescence fractions). Multi-linear regression model was used to fit the data. Results showed that when using the CDF, BWM and FNN, in the prediction of chlorine consumption showed the (R2) values were 0.72, 0.71 and 0.41, respectively. While the FNN did not fit the model well it did enhance the model using CDF by 11.26%. The FNN is not effective in enhancement of the BWM response to the model. Combination of the CDF, BWM and FNN or that of the CDF and BWM were both effective in prediction of chlorine consumption.
Keywords: Chlorine consumption | Fluorescence | Model | Water
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