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The sequencing batch reactor (SBR) is a wastewater treatment option feasible for low flows. The objective of this research was to optimize SBR by varying its operational parameters, viz. (i) settling time and (ii) reaction time. The study was conducted in two phases. In Phase 1, raw wastewater was fed into the SBR after conventional settling, while in Phase 2 raw wastewater was fed into the SBR after coagulation-flocculation-sedimentation. A bench-scale model was set up and domestic wastewater was used for this study. Performance of the treatment system was evaluated through 5-day biochemical oxygen demand (BOD), chemical oxygen demand (COD) and total suspended solids (TSS). The results demonstrated that reaction time was reduced to 4 h in Phase 2 compared to 10 h in Phase 1. The BOD, COD and TSS removal efficiencies observed in Phase 1 were 80%, 80% and 73%, respectively, and for Phase 2 the removal efficiencies were 74%, 75% and 80% respectively. National Environmental Quality Standards (NEQS) were met in both cases and the treatment cost per cubic metre of wastewater for Phase 2 was 2.5 times lower compared to Phase 1.

Disinfection is used to deactivate pathogens in drinking water. However, disinfectants react with natural organic matter present in water to form disinfection by-products (DBPs). While a few of these DBPs have been studied extensively and are regulated in many countries, new unregulated DBPs (UR-DBPs) have also recently been identified in drinking water. The UR-DBPs are considered to be more toxic than regulated DBPs (R-DBPs). To understand the occurrence of UR-DBPs in a water distribution network (WDN), this research presents an approach to predicting the behaviour of emerging UR-DBPs such as dichloroacetonitrile (DCAN), trichloropropanone (TCP), and trichloronitromethane (TCNM) in WDNs. Water quality data, generated by sampling and laboratory analysis of 12 small communities, was used to develop predictive models. A framework was also proposed alongside the predictive models to estimate the concentration of emerging UR-DBPs under limited water quality sampling information. Moreover, the relationship between emerging UR-DBP concentrations and their identified predictors was further observed and evaluated by developing contour profiles. DCAN and TCP predictive models have coefficient of determination ( R 2 ) > 85%, whereas for TCNM model, the R 2 was > 65%. Water quality parameters including water temperature, turbidity, conductivity, and dissolved organic carbon concentrations were identified as key predictors. Similarly, trichloroacetic acid and bromodichloromethane were identified as key predictors among DBP families, to predict the occurrence of emerging UR-DBPs. Developed models and relationships between the UR-DBPs and predictors can help water utilities and regulators to manage the occurrence of UR-DBPs in small WDNs.

The City of White Rock, Canada has been facing challenges of elevated concentrations of arsenic and manganese in its drinking water supply. A pilot water treatment study was conducted to explore effective contaminant removal solutions for human health risk mitigation. The arsenic and manganese removal performance of four treatment processes, including ozonation-manganese greensand filtration (OSF), OSF-iron-based granular media adsorption (OSFIA), the Burgess Iron Removal Method (BIRM), and BIRM-iron-based granular media adsorption (BIA) were evaluated. The non-cancer health risks and the incremental lifetime cancer risks (ILCR) posed by arsenic in different water sources were also assessed. The results show that OSFIA treatment achieved the highest arsenic and manganese removal. An average arsenic removal rate of 68.5% (initial concentration = 9.3 μg/L) was observed using OSFIA during two months of treatment, while manganese (initial concentration = 133.9 μg/L) can be completely removed. The arsenic removal was mainly be attributed to the adsorption of iron-based granular media. The mean values of non-cancer health risks of arsenic exposure due to oral intake of treated water were identified to be lower than the critical threshold for different age groups. In addition, the probability of critical ILCR occurrence can be greatly reduced. Based on the results from the pilot study, OSFIA was selected to construct a full-scale water treatment plant. Arsenic and manganese concentrations in the effluent from the plant can be reduced to a low-to-undetectable level, achieving negligible health risks to the residents of the city.