Chloramine demand estimation using surrogate chemical and microbiological parameters

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dc.contributor.authorMoradi, S.
dc.contributor.authorLiu, S.
dc.contributor.authorChow, C.
dc.contributor.authorvan Leeuwen, J.
dc.contributor.authorCook, D.
dc.contributor.authorDrikas, M.
dc.contributor.authorAmal, R.
dc.date.issued2017
dc.description.abstractA model is developed to enable estimation of chloramine demand in full scale drinking water supplies based on chemical and microbiological factors that affect chloramine decay rate via nonlinear regression analysis method. The model is based on organic character (specific ultraviolet absorbance (SUVA)) of the water samples and a laboratory measure of the microbiological (Fm) decay of chloramine. The applicability of the model for estimation of chloramine residual (and hence chloramine demand) was tested on several waters from different water treatment plants in Australia through statistical test analysis between the experimental and predicted data. Results showed that the model was able to simulate and estimate chloramine demand at various times in real drinking water systems. To elucidate the loss of chloramine over the wide variation of water quality used in this study, the model incorporates both the fast and slow chloramine decay pathways. The significance of estimated fast and slow decay rate constants as the kinetic parameters of the model for three water sources in Australia was discussed. It was found that with the same water source, the kinetic parameters remain the same. This modelling approach has the potential to be used by water treatment operators as a decision support tool in order to manage chloramine disinfection.
dc.description.statementofresponsibilitySina Moradi, Sanly Liu, Christopher W.K. Chow, John van Leeuwen, David Cook, Mary Drikas, Rose Amal
dc.identifier.citationJournal of Environmental Biology, 2017; 57:1-7
dc.identifier.doi10.1016/j.jes.2017.01.010
dc.identifier.issn0254-8704
dc.identifier.issn1878-7320
dc.identifier.urihttp://hdl.handle.net/2440/110162
dc.language.isoen
dc.publisherElsevier
dc.rights© 2017 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
dc.source.urihttps://doi.org/10.1016/j.jes.2017.01.010
dc.subjectChloramine demand; drinking water treatment plants; modelling
dc.titleChloramine demand estimation using surrogate chemical and microbiological parameters
dc.typeJournal article
pubs.publication-statusPublished

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