Control of aliphatic halogenated DBP precursors with multiple drinking water treatment processes： Formation potential and integrated toxicity

The comprehensive control efficiency for the formation potentials（FPs） of a range of regulated and unregulated halogenated disinfection by-products（DBPs）（including carbonaceous DBPs（C-DBPs）, nitrogenous DBPs（N-DBPs）, and iodinated DBPs（I-DBPs）） with the multiple drinking water treatment processes, including pre-ozonation, conventional treatment（coagulation–sedimentation, pre-sand filtration）, ozone-biological activated carbon（O_3-BAC） advanced treatment, and post-sand filtration, was investigated. The potential toxic risks of DBPs by combing their FPs and toxicity values were also evaluated.The results showed that the multiple drinking water treatment processes had superior performance in removing organic/inorganic precursors and reducing the formation of a range of halogenated DBPs. Therein, ozonation significantly removed bromide and iodide,and thus reduced the formation of brominated and iodinated DBPs. The removal of organic carbon and nitrogen precursors by the conventional treatment processes was substantially improved by O_3-BAC advanced treatment, and thus prevented the formation of chlorinated C-DBPs and N-DBPs. However, BAC filtration leads to the increased formation of brominated C-DBPs and N-DBPs due to the increase of bromide/DOC and bromide/DON.After the whole multiple treatment processes, the rank order for integrated toxic risk values caused by these halogenated DBPs was haloacetonitriles（HANs）》haloacetamides（HAMs） 〉haloacetic acids（HAAs） 〉 trihalomethanes（THMs） 〉 halonitromethanes（HNMs） 》I-DBPs（I-HAMs and I-THMs）. I-DBPs failed to cause high integrated toxic risk because of their very low FPs. The significant higher integrated toxic risk value caused by HANs than other halogenated DBPs cannot be ignored.

Chloramine demand estimation using surrogate chemical and microbiological parameters

A 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.