This study investigated the impact of physicochemical parameters on geosmin production in Hope Valley reservoir during periods of absent pelagic cyanobacteria. Over 42 months, extracellular geosmin was consistently detected, with concentrations ranging from less than 4 ng/L to 37 ng/L during benthic cyanobacterial periods and increasing to 128 ng/L when pelagic cyanobacteria were active. Notably, four significant geosmin peaks occurred, predominantly between the October and December periods. A 20-year historical analysis corroborated these findings, revealing instances of geosmin in the absence of pelagic blooms. Factors such as phycocyanin, fluorescent dissolved organic matter, true colour, and alkalinity were identified as having a weak linear relationship with geosmin concentration, aligning with a principal component analysis. The evidence of sporadic detection of benthic cyanobacteria in the water column suggest that benthic cyanobacteria are likely to be the source of the geosmin. This infers that the physicochemical variables, while influential, are only part of a more complex ecological narrative. The total phosphorus concentration was ideal for benthic cyanobacterial growth (<0.02 mg/L) as higher total phosphorus concentration resulted in pelagic cyanobacterial blooms. The findings suggest that benthic and pelagic cyanobacteria will remain in competition for dominance each spring and summer. Consequently, further research into the shifts in benthic cyanobacterial diversity is needed to understand the geosmin production mechanisms in this environment.

A 12‐event survey of 8 water treatment plants (WTPs) was conducted to determine the impact of the 2021 summer (January) to winter (August) cyanobacterial challenge on WTP performance. High cyanobacterial numbers (>20,000 cells/mL) and high taste and odor (T&O) concentrations (>100 ng/L) were encountered. The summer to winter transition of this cyanobacterial challenge also saw the proliferation of Pseudanabaena blooms which challenged conventional WTPs and a breakthrough of cells was detected. This required further investigation into optimizing Pseudanabaena removal in WTP processes. WTP sampling determined that the sludge lagoons provided conducive conditions for cell accumulation and metabolite release. These cells and T&O compounds were recycled back into the head of the WTP through the supernatant return flows. In the most extreme case, 512 ng/L of T&O compounds was detected in the supernatant return. This study highlighted the need to understand the potential risks that treatment plants can encounter and ensure appropriate management during and after cyanobacterial events.

Cyanobacteria continue to contribute to the taste and odor issues (T&O) in the lower River Murray. A review on the cyanobacteria and T&O data collected in the last 22 years showed that there has been a shift in cyanobacterial community and subsequent T&O profiles. The increased numbers and changes in cyanobacteria occurrence have likely influenced the resultant T&O profiles. T&O challenges started occurring more frequently post-2015. Although the river has historically been affected by geosmin challenges, up to 999 ng/L of geosmin and 155 ng/L of 2-methylisoborneol (MIB) concentrations that have been detected along the river. Findings from this study showed that of the 22 water treatment plants investigated, the more advanced ultrafiltration membrane and granular activated carbon system treatment plants were able to mitigate most of the T&O challenges whereas the conventional water treatment plants were more likely to have T&O breakthrough instead.

The conventional drinking water treatment process involves disinfecting water at the final stage of treatment to ensure water is microbiologically safe at customer taps. Monochloramine is a popular disinfectant used in many water distribution systems (WDSs) worldwide. Understanding the factors that impact monochloramine decay in the WDS is critical for maintaining disinfection at the customer tap. While monochloramine residue moves through a WDS, it decays via several pathways including chemical, microbiological, and wall decay processes. The decay profile in these pathways is often site-specific and depends on various factors including treated water characteristics. In a water quality network model, the decay of a chemical species is often modelled using two parameters that represent bulk and wall decay kinetics. Typical bulk decay characteristics of monochloramine for a specific WDS can be easily established in the laboratory using grab sample tests, while in a real situation, wall decay is difficult to quantify. In this study, we compared two different approaches to model monochloramine decay in a WDS. In the first approach, the wall decay parameter was quantified using a parameter optimisation technique with monochloramine concentrations at different network locations simulated using a water quality network model. In the second approach, a data analytics model was developed using a machine learning algorithm. For both approaches, the model predicted monochloramine concentrations closely matched the observed data. Our study suggests that the data analytics model has a relatively higher accuracy in predicting monochloramine residual concentrations in a WDS.

Nitrification is a major challenge in chloraminated drinking water systems, resulting in undesirable loss of disinfectant residual. Consequently, heterotrophic bacteria growth is increased, which adversely affects the water quality, causing taste, odour, and health issues. Regular monitoring of various water quality parameters at susceptible areas of the water distribution system (WDS) helps to detect nitrification at an earlier stage and allows sufficient time to take corrective actions to control it. Strategies to monitor nitrification in a WDS require conducting various microbiological tests or assessing surrogate parameters that are affected by microbiological activities. Additionally, microbial decay factor (Fm) is used by water utilities to monitor the status of nitrification. In contrast, approaches to manage nitrification in a WDS include controlling various factors that affect monochloramine decay rate and ammonium substrate availability, and that can inhibit nitrification. However, some of these control strategies may increase the regulated disinfection-by-products level, which may be a potential health concern. In this paper, various strategies to monitor and control nitrification in a WDS are critically examined. The key findings are: (i) the applicability of some methods require further validation using real WDS, as the original studies were conducted on laboratory or pilot systems; (ii) there is no linkage/formula found to relate the surrogate parameters to the concentration of nitrifying bacteria, which possibly improve nitrification monitoring performance; (iii) improved methods/monitoring tools are required to detect nitrification at an earlier stage; (iv) further studies are required to understand the effect of soluble microbial products on the change of surrogate parameters. Based on the current review, we recommend that the successful outcome using many of these methods is often site-specific, hence, water utilities should decide based on their regular experiences when considering economic and sustainability aspects.

Major pathways of monochloramine disinfectant decay, kinetics involved, various influencing factors and the existing models to determine the chloramine decay in drinking water distribution systems are reviewed.

Calibration of a water distribution system (WDS) hydraulic model requires adjusting several parameters including hourly or sub-hourly demand multipliers, pipe roughness and settings of various hydraulic components. The water usage patterns or demand patterns in a 24-h cycle varies with the customer types and can be related to many factors including spatial and temporal factors. The demand patterns can also vary on a daily basis. For an extended period of hydraulic simulation, the modelling tools allows modelling of the variable demand patterns using daily multiplication factors. In this study, a linear modelling approach was used to handle the variable demand patterns. The parameters of the linear model allow modelling of the variable demand patterns with respect to the baseline values, and they were optimised to maximise the association with the observed data. This procedure was applied to calibrate the hydraulic model developed in EPANET of a large drinking water distribution system in regional South Australia. Local and global optimisation techniques were used to find the optimal values of the linear modelling parameters. The result suggests that the approach has the potential to model the variable demand patterns in a WDS hydraulic model and it improves the objective function of calibration.

Nitrification is a common issue observed in chloraminated drinking water distribution systems, resulting in the undesirable loss of monochloramine (NH2Cl) residual. The decay of monochloramine releases ammonia (NH3), which is converted to nitrite (NO2−) and nitrate (NO3−) through a biological oxidation process. During the course of monochloramine decay and the production of nitrite and nitrate, the spectral fingerprint is observed to change within the wavelength region sensitive to these species. In addition, chloraminated drinking water will contain natural organic matter (NOM), which also has a spectral fingerprint. To assess the nitrification status, the combined nitrate and nitrite absorbance fingerprint was isolated from the total spectra. A novel method is proposed here to isolate their spectra and estimate their combined concentration. The spectral fingerprint of pure monochloramine solution at different concentrations indicated that the absorbance difference between two concentrations at a specific wavelength can be related to other wavelengths by a linear function. It is assumed that the absorbance reduction in drinking water spectra due to monochloramine decay will follow a similar pattern as in ultrapure water. Based on this criteria, combined nitrate and nitrite spectra were isolated from the total spectrum. A machine learning model was developed using the support vector regression (SVR) algorithm to relate the spectral features of pure nitrate and nitrite with their concentrations. The model was used to predict the combined nitrate and nitrite concentration for a number of test samples. Out of these samples, the nitrified sample showed an increasing trend of combined nitrate and nitrite productions. The predicted values were matched with the observed concentrations, and the level of precision by the method was ± 0.01 mg-N L−1. This method can be implemented in chloraminated distribution systems to monitor and manage nitrification.

The spectra fingerprint of drinking water from a water treatment plant (WTP) is characterised by a number of light-absorbing substances, including organic, nitrate, disinfectant, and particle or turbidity. Detection of disinfectant (monochloramine) can be better achieved by separating its spectra from the combined spectra. In this paper, two major focuses are (i) the separation of monochloramine spectra from the combined spectra and (ii) assessment of the application of the machine learning algorithm in real-time detection of monochloramine. The support vector regression (SVR) model was developed using multi-wavelength ultraviolet-visible (UV-Vis) absorbance spectra and online amperometric monochloramine residual measurement data. The performance of the SVR model was evaluated by using four different kernel functions. Results show that (i) particles or turbidity in water have a significant effect on UV-Vis spectral measurement and improved modelling accuracy is achieved by using particle compensated spectra; (ii) modelling performance is further improved by compensating the spectra for natural organic matter (NOM) and nitrate (NO3) and (iii) the choice of kernel functions greatly affected the SVR performance, especially the radial basis function (RBF) appears to be the highest performing kernel function. The outcomes of this research suggest that disinfectant residual (monochloramine) can be measured in real time using the SVR algorithm with a precision level of ± 0.1 mg L−1.

The effect of age on larkspur poisoning of cattle is unknown. An experiment consisting of oral dosing of dried, ground, Delphinium barbeyi to ten Angus steers as yearlings, and again at two years was performed. There was a significant difference between the responses of yearling and two year old steers (P = 0.0015), with yearling steers being more susceptible. These results suggest that the adverse response of Angus cattle to larkspur is age-dependent.

This paper reports the effects of pre-oxidation processes including ozone and ultraviolet (UV) irradiation prior to chloramination on microbiologically assisted monochloramine decay. Water samples with varying water qualifies were pre-oxidated by ozone and UV irradiation, followed by determination of chemical and microbiological monochloramine decay (F-m). Both ozone and UV could effectively improve the reduction of microbial-like compounds responsible for monochloramine decay in treated water samples. Reductions in F-m values were observed for ozone contact times (Ct) greater than 5 mg min/L and UV doses greater than 30 mJ/cm(2). However, UV was less effective than ozone in reducing F-m values in raw water samples. Complete removal of the microbiological component of the decay for raw water samples was not found either with ozone (even with Ct of 50 mg min/L) or UV (even with UV dose of 120 mJ/cm(2)). The effects of pre-oxidation processes on chemical (k(c)) and microbial (k(m)) decay coefficients were assessed. Increasing both ozone Ct and UV dose ahead of chloramine did not affect the chemical decay component, but they changed the microbiological component of decay. Changes in organic matter after ozonation were also characterized using three-dimensional fluorescence excitation-emission matrix (3D-FEEM) spectroscopy, and correlations between 3D-FEEM spectroscopy results and F-m values were found. Intensifies of humic-like, fulvic-like, microbial protein-like and aromatic protein-like substances were reduced by pre-ozonation. Based on the 3D-FEEM results, we can confirm that the slowdown of monochloramine decay rate is due to the reduction of marine humic-like substances and soluble microbial protein-like compounds by pre-ozonation.

Ipomoea asarifolia has been associated with a tremorgenic syndrome in livestock. Recently indole diterpene compounds were identified in I. asarifolia, some of which have been shown to cause a tremorgenic syndrome. In this study, the tremorgenic nature of I. asarifolia was assessed using a mouse model. Adult mice were fed rodent chow containing 10, 15, 20 and 25% endophyte infected (E+), or 25% endophyte free (E-), I. asarifolia for 14 days. The mice fed E+ chow developed a tremorgenic syndrome as characterized by visually observed muscle tremors and an inability to traverse a balance beam, whereas the mice fed E- chow did not develop tremors and had similar muscle coordination to control mice. A lactating mouse model was also used to determine if the compounds can be transferred to nursing pups via the milk. Nursing pups were exposed via their mother's milk for 21 days, from post-natal day 0–21. The pups from dams exposed to E+ chow developed a similar tremorgenic syndrome. Data presented in this study demonstrate that the tremorgenic compounds in I. asarifolia are endophyte derived. Additionally, both adult mice and nursing pups are good models for studying the tremorgenic nature of I. asarifolia and related plants.

Zinc is a heavy metal that is essential for human health at trace levels. Zinc also has antibacterial properties and these were investigated on microbiological mediated monochloramine decay (measured as a microbial decay factor, Fm) occurring in chloraminated drinking water. Water samples displaying rapid chloramine decay were obtained using a field based novel design pilot-plant distribution system (PDS), located at the Tailem Bend water treatment plant, South Australia. The PDS comprised 1 kL tanks each holding 900m of polyethylene tubing with sampling points at 300m intervals. Flow rates were applied to achieve hydraulic retention times (HRTs) that simulated those of the full-scale distribution system. Total (k(t)) and microbiological mediated (k(m)) decay rates were determined for chloraminated waters as these passed through the PDS. Highest Fm values (2.1 +/- 0.7) were found for waters collected at the outflow of the PDS pipework, demonstrating increase in microbiological mediated monochloramine decay with increased HRT. Zinc (0.6-60 mg/L) added to water samples was found to lower k(t), k(m) and consequently Fm, as its concentration was increased. Mathematical models (R-2 > 0.9 and Ttest value > 0.8) were developed that describe reductions in monochloramine decay rates with the zinc addition. Reduction in kt and Fm in response to zinc were found to have an inverse correlation with initial microbial activity in the chloraminated waters. Zinc concentration below drinking water aesthetic limits (< 3.0 mg/L, ADWG) was also found to lower the monochloramine decay rate, indicating potential benefit at such levels in chloraminated distribution systems.

Fluorescence excitation-emission matrix spectroscopy coupled with parallel factor analysis (FEEM/PARAFAC) was applied to characterise natural organic matter (NOM) present in nitrified and non-nitrified waters from different sampling sites in a drinking water distribution system in Australia. Each excitation-emission matrix (EEM) data set of nitrified and non-nitrified water samples were successfully decomposed into a three component PARAFAC model (C-1, C-2, and C-3). The spectral shapes of these components were compared with those identified earlier in other studies from the OpenFluor database. While C-1 and C-2 exhibited similar fluorescence spectra in both non-nitrified and nitrified sampling locations, there were some fluorescence peaks in C-3 for nitrified water samples that were not present in non-nitrified water samples. Both C-1 and C-2 in each PARAFAC model for nitrified and non-nitrified water samples showed striking similarities with components previously listed as humic-like compounds. While C-3 for non-nitrified water samples also consisted of terrestrial humic-like compounds, C-3 in PARAFAC model for nitrified water samples represented protein-like material produced as a result of microbiological activity. The fluorescence peaks that appeared only in nitrified sampling locations are related to the formation of microbial-like compounds associated with nitrification. These results indicate that PARAFAC modelling of EEM data can be used to investigate nitrification and water quality changes in chloraminated drinking water distribution systems.

Four chemically similar alkaloids, anabasine, anabaseine, epibatidine and dimethylphenylpiperazinium (DMPP), are potent nicotinic acetylcholine receptor agonists of fetal muscle nicotinic acetylcholine receptors in human TE-671 cells. Based on results with these cells, we hypothesized that the alkaloids would completely inhibit ultrasound-monitored fetal movement in a goat model. Different, single doses of anabasine, anabaseine, epibatidine, DMPP, or saline control were administered I.V. to pregnant goats on day 40 of gestation and the number of fetal movements per 5 min sample was measured by ultrasound at times 0, 0.5, 1, 2, 4 and 8 h. The differences among does in fetal movements were more consistent at dosing and following recovery for doses of anabasine above 0.125 mg/kg compared to the other compounds and dosages. Anabasine actions were dose-dependent with an IC50 value of ∼0.1 mg/kg, and, at a dose of 0.8 mg/kg, completely inhibited fetal movement for 1.5 h after dosing. Anabaseine, epibatidine, and DMPP failed to completely inhibit fetal movement in day 40 pregnant goats at doses predicted to be effective. These results suggest that while experiments with TE-671 cells provide valuable information and predictions of the actions of plant alkaloids on fetal movement, in vivo experiments are still required in order to determine the ability of an alkaloid to inhibit fetal movement in livestock species. Moreover, other pharmacological properties such as receptor differences between mammalian species and differences in the pharmacokinetic properties of the alkaloids also are likely to weaken teratologic predictions based solely on the in vitro data.

The safety of drinking water in Australia is ensured using a risk management framework embedded within the Australian Drinking Water Guidelines (ADWG). This framework includes elements for hazard identification, risk assessment, risk mitigation, verification of barrier performance and monitoring for any changes to the hazards that influence source water quality. The next revision of the ADWG will incorporate Health-Based Targets (HBTs) for achieving microbiologically safe drinking water. This incorporates Quantitative Microbial Risk Assessment and the metric of Disability Adjusted Life Year (DALY) to define safety, with a target of 1×10−6 Disability Adjusted Life Year (1 microDALY) set as the maximum tolerable disease burden from drinking water, which in the case of Cryptosporidium is <1.3×10−5oocysts/L. The resulting product water specification, in combination with knowledge of pathogen challenges in source waters, allows the determination of the treatment requirements to ensure public safety. The ADWG revision provides default removal values for Cryptosporidium for particular treatment processes, such as conventional coagulation and dual media filtration. However, these values are based on assumptions regarding treatment plant design, operation and water quality. To properly manage risk and demonstrate compliance with the guidelines, water utilities may need to validate treatment performance for Cryptosporidium removal. A particular limitation is the absence of Cryptosporidium surrogates for full-scale filter validation. This paper will provide an overview of risk-based management of drinking water safety in Australia, the development of health-based targets for microbial pathogens and the evaluation of Cryptosporidium surrogates for conventional coagulation and dual media filtration.