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It is well known that natural organic matter (NOM) is the major precursor of disinfection by-products (DBPs) when inadequately removed NOM reacts with the disinfectant during chlorination and chloramination. Special interest in the DBP precursors is justified as it is essential to understand the reactivity and character of the precursors responsible for the formation of DBPs. This is vital in order to develop processes that will enhance precursor removal during drinking water treatment. The aim of this study was to investigate the impact of the characteristics of NOM within an oligotrophic water source on the formation of trihalomethanes (THMs) during drinking water treatment at Rand Water. Specific ultraviolet absorbance (SUVA) and molecular size distribution (MSD) were the main NOM characterisation techniques utilised during this study. The MSD was investigated by making use of high-performance size-exclusion chromatography (HPSEC). The MSD results showed a significant correlation between the high-molecular-weight (HMW) fraction of NOM and TTHM formation, specifically during the summer months. The positive correlation existing between SUVA and full scale NOM removal indicates that SUVA can be used to indicate NOM treatability during water treatment. A link between chloroform formation and the HMW fraction of NOM was also observed; however, the formation of bromodichloromethane (BDCM) was not due to the HWM fraction, as indicated by a weak regression coefficient. The results displayed are an indication that the aromatic fraction of NOM was the main precursor to TTHM formation, more prominently during summer.

Effective removal of natural organic matter (NOM) during water treatment is crucial as disinfection by-products (DBPs) such as trihalomethanes in the final drinking water are formed when residual NOM reacts with the disinfectant such as chlorine. This study compared the NOM removal efficiency by granular activated carbon (GAC) filtration, an ultrafiltration membrane and conventional water treatment plant. The NOM removal efficiency by GAC and submerged ultrafiltration process was conducted at pilot scale level and the conventional water treatment process assessment using a full scale water treatment plant. The performance of the three process train in removing NOM was conducted in parallel. On average, the conventional water treatment processes (coagulation, sedimentation and sand filtration) removed 61% and 24% NOM as indicated by UV254 and dissolved organic carbon (DOC) removal, respectively. A respective reduction of 73% and 25% of UV254 and DOC was achieved by ultrafiltration. The GAC filter column (preceded by a sand filter column) achieved UV254 removal of 86% and DOC removal of 28%. Conventional water treatment removed the hydrophobic high molecular weight (HMW) NOM fraction while GAC and ultrafiltration not only increased removal of HMW NOM, but substantially increased removal of the intermediate (IMW) and low molecular weight (LMW) NOM. Addition of GAC filtration to the conventional treatment process appeared superior to ultrafiltration and conventional treatment and increased the overall NOM removal efficiency.

In its natural environment, natural organic matter (NOM) is not problematic. However, during water treatment NOM does affect water quality specifically during the disinfection step, where if NOM is present it reacts with disinfectants resulting in the formation of disinfection by-products. To emphasize the importance of NOM monitoring during potable water treatment this study aimed to characterize NOM and evaluate NOM removal by a conventional water treatment plant considering seasonal trends. NOM was characterized by making use of NOM polarity and specific ultraviolet absorbance. NOM removal was monitored with high-performance size exclusion chromatography, dissolved organic carbon (DOC) and UV254 analyses. The polarity rapid assessment method indicated that the hydrophobic and hydrophilic NOM fractions within the surface water increased during a period of heavy rain when floods occurred, but conversely decreased during an average rain season. Although NOM character showed variability during the 5-year study period, seasonal relationship during high and low flow seasons between aromatic NOM and total trihalomethane (TTHM) formation was not evident. Aromatic NOM was not the only precursor to TTHM formation, which stresses the need to implement advanced NOM characterization techniques during NOM monitoring to study reactivity of the individual NOM fraction with the disinfectant used at the water treatment plant.

Natural organic matter (NOM) contributes to bacterial regrowth during potable water treatment and supply. Most conventional water treatment plants insufficiently remove the biodegradable dissolved organic (BDOC) NOM fraction. The presence of labile BDOC in water creates conducive conditions for bacterial regrowth. To reduce NOM and the bacterial regrowth potential (BRP) in water, the study aimed at establishing which of the NOM polarity fractions are biodegradable and if the BRP (enumerated according to the heterotrophic plate count [HPC]) method) can be correlated to biodegradability. Specific ultraviolet absorbance (SUVA) was used to characterise source and treated water NOM fractions (i.e. hydrophilic [Hpi], transphilic [Tpi] and hydrophobic [Hpo]) obtained through the modified polarity rapid assessment method (m-PRAM). The source and treated water SUVA values of the Hpi and Hpo were on average, 3.88 L/mg.m and 2.04 L/mg.m, respectively. The Hpi and Tpi fractions on the source and treated were the most biodegradable fractions, with mean BDOC values ranging between 29.22%, and 35.75 %. The high BDOC of the Tpi and Hpi NOM substantially contributed to BRP by up to 121.4 × 103-197.4 × 103 CFU/mL, respectively. The strong correlation (R2 > 0.96) between BRP and BDOC allows for the effective management of water treatment and supply processes, particularly for microbial control.

Due to the fluctuating quantity and quality of organic matter (OM) in surface waters, continuous characterisation and the evaluation of its propensity to form disinfection byproducts (DBPs) is essential. The characteristics of OM affects the removal efficiency and influences its reactivity with disinfectants to form DBPs. Research on DBPs is interesting because of their potential carcinogenic health risks. Although the link between DBP precursors such as natural organic matter (NOM) and DBP formation is well established, knowledge on the individual NOM fractions and other DBP precursors responsible for various DBPs is poor. Moreover, data on other precursors of DBPs has not been synthesized. The aim of this paper is therefore to review literature on the quantity and quality of NOM and other DBP precursors, evaluate the formation and treatability of the individual NOM fractions, and establish their influence on the DBPs formation. Possible removal processes for DBPs and their precursors, along with their economic feasibility were discussed. The key findings were: (1) certain fractions of NOM play a pivotal role in the formation of DBPs, (2) commonly used DBP control approaches include post-formation treatment, while targeting the removal of specific DBP precursors is hard to achieve, and (3) membrane technologies, enhanced coagulation, and advanced oxidation processes (AOPs) are effective in removing NOM, although AOP technologies are generally not economically feasible and still need further development and up-scaling. Future research should focus on: (1) toxicological studies to establish public health risks associated with specific emerging DBPs, (2) providing sufficient empirical data to determine whether to regulate currently unregulated DBPs, and (3) economic analyses to inform implementation of DBP precursor removal methods such as AOPs.

This paper proposes a three-parameter mathematical model to describe the particle size distribution in a water sample. The proposed model offers some conceptual advantages over two other models reported on previously, and also provides a better fit to the particle counting data obtained from 321 water samples taken over three years at a large South African drinking water supplier. Using the data from raw water samples taken from a moderately turbid, large surface impoundment, as well as samples from the same water after treatment, typical ranges of the model parameters are presented for both raw and treated water. Once calibrated, the model allows the calculation and comparison of total particle number and volumes over any randomly selected size interval of interest.