Formation and modeling of disinfection by-products in Newfoundland communities

For the past few years, the presence of disinfection by-products (DBPs) especially chlorinated DBPs has become a health concern. This will be an important and particular concern at the water utilities. As standards are becoming very strict, water utilities have to adjust their operation strategies t...

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Bibliographic Details
Main Author: Boyalla, Rajya Lakshmi
Format: Thesis
Language:English
Published: Memorial University of Newfoundland 2004
Subjects:
Online Access:https://research.library.mun.ca/10188/
https://research.library.mun.ca/10188/1/Boyalla_RajyaLakshmi.pdf
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Summary:For the past few years, the presence of disinfection by-products (DBPs) especially chlorinated DBPs has become a health concern. This will be an important and particular concern at the water utilities. As standards are becoming very strict, water utilities have to adjust their operation strategies to comply with the new regulations while maintaining residual chlorine, which should ensure an acceptable microbiological quality. This study was aimed at finding the parameters affecting the formation of these DBPs, studying the kinetics of DBPs formation during the chlorination of raw water and developing models to predict the formation of DBPs. Gas chromatograph with an ECD detector was used for the analysis of the samples. Four compounds of trihalomethanes (THMs) Chloroform, dibromochloromethane, bromodichloromethane, bromoform, four compounds of Haloacetonitriles (HANs) dichloroacetonitrile, trichloroacetonitrile, bromochloroacetonitrile, dibromoactonitrile along with two compounds of Haloketones (HKs) 1,1- dichloropropanone and 1,1,1- trichloropropanone were analysed. Chloroform, dichloroactonitrile and 1,1,1- trichloropropanone dominated among the DBPs. TOC, pH, chlorine dosage and reaction time were the important parameters which where affecting the formation of these DBPs. The models to predict the formation of THMs, HANs and HKs were developed with coefficient of correlations of 0.77, 0.685 and 0.681 respectively. Data fit software was used to develop these models.