Dynamics of Water Quality and Biofilm Formation in a Pilot Drinking Water Distribution System with and without Residual Disinfectants

Master Thesis (2020)
Author(s)

H. SHI (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

G.J. Medema – Mentor (TU Delft - Sanitary Engineering)

J.S. Vrouwenvelder – Graduation committee member (TU Delft - BT/Environmental Biotechnology)

Gang Liu – Graduation committee member (TU Delft - Sanitary Engineering)

Lihua Chen – Graduation committee member (TU Delft - Sanitary Engineering)

Faculty
Civil Engineering & Geosciences
Copyright
© 2020 Haoran Shi
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Haoran Shi
Graduation Date
30-11-2020
Awarding Institution
Delft University of Technology
Programme
['Civil Engineering | Environmental Engineering']
Faculty
Civil Engineering & Geosciences
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Abstract

Drinking water safety is of great concern all around the world. Two strategies can be pursued to maintain biological stable drinking water during distribution in the network: (i) without a residual disinfectant, in which bacterial growth is controlled by very low biodegradable nutrients in the water by extensive pre-treatment and a well-maintained network and (ii) with a residual disinfectant in the water during distribution. Independent of the strategy, maintaining water quality during the transportation processes has always been a challenge, and there is a need for a better understanding of the impact of biological stability strategies using systematic studies. In this study, the impact of no residual disinfectant, residual chlorine and residual monochloramine on chemical and microbial water quality were investigated. It is anticipated that studies with pilot distribution networks will lead to better control of drinking water safety, in terms of biological stability and DBPs formation. Meanwhile, computer models applied in this study fitted disinfectant decay kinetics, and appeared to correspond with the experimental data for THMs and biofilm formation, and hence provided more insights in terms of predicting the behaviour of the system in the future, while their accuracy can also be calibrated and verified by the future experimental data.

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