Predictive model for disinfection by-product in Alexandria drinking water, northern west of Egypt

Abstract

Chlorine has been utilized in the early stages of water treatment processes as disinfectant. Disinfection for drinking water reduces the risk of pathogenic infection but may pose a chemical threat to human health due to disinfection residues and their by-products (DBP) when the organic and inorganic precursors are present in water. In the last two decades, many modeling attempts have been made to predict the occurrence of DBP in drinking water. Models have been developed based on data generated in laboratory-scale and field-scale investigations. The objective of this paper is to develop a predictive model for DBP formation in the Alexandria governorate located at the northern west of Egypt based on field-scale investigations as well as laboratory-controlled experimentations. The present study showed that the correlation coefficient between trihalomethanes (THM) predicted and THM measured was R (2)=0.88 and the minimum deviation percentage between THM predicted and THM measured was 0.8 %, the maximum deviation percentage was 89.3 %, and the average deviation was 17.8 %, while the correlation coefficient between dichloroacetic acid (DCAA) predicted and DCAA measured was R (2)=0.98 and the minimum deviation percentage between DCAA predicted and DCAA measured was 1.3 %, the maximum deviation percentage was 47.2 %, and the average deviation was 16.6 %. In addition, the correlation coefficient between trichloroacetic acid (TCAA) predicted and TCAA measured was R (2)=0.98 and the minimum deviation percentage between TCAA predicted and TCAA measured was 4.9 %, the maximum deviation percentage was 43.0 %, and the average deviation was 16.0 %.

Human health risk estimation and predictive modeling of halogenated disinfection by- products (chloroform) in swimming pool waters: a case study of Dhanbad, Jharkhand, India

“…Other statistical parameters like mean square error of prediction (MSEP) and percentage error were also low for linear model compared to non-linear model. Previous research investigations are showed the applicability of linear model over non-linear models to predict the THMs levels in drinking water supplies [1,30,56]. Thus, the overall observation and validation indicated that MLR approach can prove to useful for swimming pool management to pre-assess the concentration level of THMs in pool water, and also to implement control practices for their regulation.…”

“…Dose-response study was conducted by determining the average daily dose (ADD, mg kg-day −1 ) for the pathways mentioned above using Eq. (1)(2)(3).…”

“…Over the years, several empirical and kinetics based predictive models [1,44] has been developed to determine the concentration levels of THMs in drinking water supplies. However, limited information is available with respect to swimming pool water.…”