A novel mathematical template for developing fDOM probe fluorescence signal correction models for freshwaters.

The reliable application of field deployable fluorescent dissolved organic matter (fDOM) probes is hindered by several influencing factors which need to be compensated. This manuscript describes the corrections of temperature, pH, turbidity and inner filter effect on fluorescence signal of a commercial fDOM probe (fDOMs). For this, Australian waters with wide ranging qualities were selected, e.g. dissolved organic carbon (DOC) ranging from ∼1 to ∼30 mg/L, specific UV absorbance at 254 nm from ∼1 to ∼6 L/m/mg and turbidity from ∼1 to ∼ 350 FNU. Laboratory-based model calibration experiments (MCEs) were performed. A model template was developed and used for the development of the correction models. For each factor, data generated through MCEs were used to determine model coefficient (α) values by fitting the generated model to the experimental data. Four discrete factor models were generated by determination of a factor-specific α value. The α values derived for each water of the MCEs subset were consistent for each factor model. This indicated generic nature of the four α values across wide-ranging water qualities. High correlation between fDOMs and DOC were achieved after applying the four-factor compensation models to new data (r, 0.96, p < 0.05). Also, average biases (and %) between DOC predicted through fDOMs and actual DOC were decreased by applying the four-factor compensation model (from 3.54 (60.9%) to 1.28 (16.7%) mg/L DOC). These correction models were incorporated into a Microsoft EXCEL-based software termed EXOf-Correct for ready-to-use applications.

Using Surrogate Parameters to Enhance Monitoring of Community Wastewater Management System Performance for Sustainable Operations.

Community wastewater management systems (CWMS) are small-scale wastewater treatment systems typically in regional and rural areas with less sophisticated treatment processes and often managed by local governments or communities. Research and industrial applications have demonstrated that online UV-Vis sensors have great potential for improving wastewater monitoring and treatment processes. Existing studies on the development of surrogate parameters with models from spectral data for wastewater were largely limited to lab-based. In contrast, industrial applications of these sensors have primarily targeted large wastewater treatment plants (WWTPs), leaving a gap in research for small-scale WWTPs. This paper demonstrates the suitability of using a field-based online UV-Vis sensor combined with advanced data analytics for CWMSs as an early warning for process upset to support sustainable operations. An industry case study is provided to demonstrate the development of surrogate monitoring parameters for total suspended solids (TSSs) and chemical oxygen demand (COD) using the UV-Vis spectral data from an online UV-Vis sensor. Absorbances at a wavelength of 625 nm (UV625) and absorbances at a wavelength of 265 nm (UV265) were identified as surrogate parameters to measure TSSs and COD, respectively. This study contributes to the improvement of WWTP performance with a continuous monitoring system by developing a process monitoring framework and optimization strategy.

Current trends and future directions of global research on wastewater to energy: a bibliometric analysis and review.

This paper presents a structured bibliometric analysis and review of the research publications recorded in the Web of Science database from 2000 to 2023 to methodically examine the landscape and development of the 'wastewater to energy' research field in relation to global trends, potential hotspots, and future research directions. The study highlights three main research themes in 'wastewater to energy', which are biogas production through anaerobic digestion of sewage sludge, methane generation from microbial wastewater treatment, and hydrogen production from biomass. The analysis reveals activated sludge, biochar, biomethane, biogas upgrading, hydrogen, and circular economy as key topics increasingly gaining momentum in recent research publications as well as representing potential future research directions. The findings also signify transformation to SDGs and circular economy practices, through the integration of on-site renewables and biogas upgrading for energy self-sufficiency, optimising energy recovery from wastewater treatment systems, and fostering research and innovation in 'wastewater to energy' supported by policy incentives. By shedding light on emerging trends, cross-cutting themes, and potential policy implications, this study contributes to informing both knowledge and practices of the 'wastewater to energy' research community.

A comprehensive assessment of superabsorbent resin produced using modified quinoa husk and coal fly ash - Preparation, characterization and application.

About 200 million tons of coal fly ash (CFA) is not effectively used in China every year. To enhance the utilization of biomass waste quinoa husk (QH) and solid waste CFA and reduce the preparation cost of superabsorbent resin (SAR), a low-cost, biodegradable modified quinoa husk-g-poly (acrylic acid)/coal fly ash superabsorbent resin (MQH-g-PAA/CFA SAR) was synthesized using modified quinoa husk (MQH), acrylic acid and CFA and used to improve the drought resistance and fertilizer conservation ability of soil. The surface morphology and performance of SAR were characterized by Fourier transform infrared (FTIR) spectrometry, scanning electron microscopy (SEM), and thermogravimetric analysis (TGA), which provided evidence for improving the properties of SAR by grafting MQH and adding CFA. In addition, the synthesis conditions were studied and optimized, together with the contents of initiator, crosslinker, MQH, and CFA to acrylic acid as well as the neutralization degree of acrylic acid. After optimization, the optimum water absorbency of SAR in deionized water, tap water, and physiological saline was 1302, 356, and 91 g/g respectively. The swelling and water-retention mechanisms of SARs were analyzed by a dynamic model and the results were in good agreement with the experimental data. In the soil experiment, the addition of SAR improved the drought resistance ability of soil, and reduced the leaching loss of fertilizer in the soil (from 49.5 % to 36.7 %). Therefore, this material exhibits significant potential in the field of agriculture and offers a novel approach with economic benefit for the utilization of MQH and CFA.

Microbial Desalination Cell for Sustainable Water Treatment: A Critical Review.

In view of increasing threats arising from the shortage of fresh water, there is an urgent need to propose sustainable technologies for the exploitation of unconventional water sources. As a derivative of microbial fuel cells (MFCs), microbial desalination cell (MDC) has the potential of desalinating saline/brackish water while simultaneously generating electricity, as well as treating wastewater. Therefore, it is worth investigating its practicability as a potential sustainable desalination technology. This review article first introduces the fundamentals and annual trends of MDCs. The desalination of diverse types of solutions using MDCs along with their life cycle impact assessment (LCIA)  and economic analysis is studied later. Finally, limitations and areas for improvement, prospects, and potential applications of this technology are discussed. Due to the great advantages of MDCs, improving their design, building materials, efficiency, and throughput will offer them as a significant alternative to the current desalination technologies.

Development of a Knowledge Graph for Automatic Job Hazard Analysis: The Schema.

In the current practice, an essential element of safety management systems, Job Hazard Analysis (JHA), is performed manually, relying on the safety personnel's experiential knowledge and observations. This research was conducted to create a new ontology that comprehensively represents the JHA knowledge domain, including the implicit knowledge. Specifically, 115 actual JHA documents and interviews with 18 JHA domain experts were analyzed and used as the source of knowledge for creating a new JHA knowledge base, namely the Job Hazard Analysis Knowledge Graph (JHAKG). To ensure the quality of the developed ontology, a systematic approach to ontology development called METHONTOLOGY was used in this process. The case study performed for validation purposes demonstrates that a JHAKG can operate as a knowledge base that answers queries regarding hazards, external factors, level of risks, and appropriate control measures to mitigate risks. As the JHAKG is a database of knowledge representing a large number of actual JHA cases previously developed and also implicit knowledge that has not been formalized in any explicit forms yet, the quality of JHA documents produced from queries to the database is expectedly higher than the ones produced by an individual safety manager in terms of completeness and comprehensiveness.

Piezoresistivity and AC Impedance Spectroscopy of Cement-Based Sensors: Basic Concepts, Interpretation, and Perspective.

Cement-based sensors include conductive fillers to achieve a sensing capability based on the piezoresistivity phenomenon, in which the electrical resistivity changes with strain. The microstructural characterisation of cement-based sensors can be obtained using a promising non-destructive technique, such as AC impedance spectroscopy (ACIS), which has been recently used by many researchers. This paper reviews the fundamental concepts of piezoresistivity and ACIS in addition to the comparison of equivalent circuit models of cement-based sensors found in the literature. These concepts include piezoresistivity theory, factors affecting piezoresistivity measurement, resistance measurement methodology, strain/damage sensing, causes of piezoresistivity, theories of conduction, AC impedance spectroscopy theory, and the equivalent circuit model. This review aims to provide a comprehensive guide for researchers and practitioners interested in exploring and applying different techniques to self-sensing concrete.

Wastewater inflow time series forecasting at low temporal resolution using SARIMA model: a case study in South Australia.

Forecasts of wastewater inflow are considered as a significant component to support the development of a real-time control (RTC) system for a wastewater pumping network and to achieve optimal operations. This paper aims to investigate patterns of the wastewater inflow behaviour and develop a seasonal autoregressive integrated moving average (SARIMA) forecasting model at low temporal resolution (hourly) for a short-term period of 7 days for a real network in South Australia, the Murray Bridge wastewater network/wastewater treatment plant (WWTP). Historical wastewater inflow data collected for a 32-month period (May 2016 to December 2018) was pre-processed (transformed into an hourly dataset) and then separated into two parts for training (80%) and testing (20%). Results reveal that there is seasonality presence in the wastewater inflow time series data, as it is heavily dependent on time of the day and day of the week. Besides, the SARIMA (1,0,3)(2,1,2)24 was found as the best model to predict wastewater inflow and its forecasting accuracy was determined based on the evaluation criteria including the root mean square error (RMSE = 5.508), the mean absolute value percent error (MAPE = 20.78%) and the coefficient of determination (R2 = 0.773). From the results, this model can provide wastewater operators curial information that supports decision making more effectively for their daily tasks on operating their systems in real-time.

Applications of Online UV-Vis Spectrophotometer for Drinking Water Quality Monitoring and Process Control: A Review.

Water quality monitoring is an essential component of water quality management for water utilities for managing the drinking water supply. Online UV-Vis spectrophotometers are becoming popular choices for online water quality monitoring and process control, as they are reagent free, do not require sample pre-treatments and can provide continuous measurements. The advantages of the online UV-Vis sensors are that they can capture events and allow quicker responses to water quality changes compared to conventional water quality monitoring. This review summarizes the applications of online UV-Vis spectrophotometers for drinking water quality management in the last two decades. Water quality measurements can be performed directly using the built-in generic algorithms of the online UV-Vis instruments, including absorbance at 254 nm (UV254), colour, dissolved organic carbon (DOC), total organic carbon (TOC), turbidity and nitrate. To enhance the usability of this technique by providing a higher level of operations intelligence, the UV-Vis spectra combined with chemometrics approach offers simplicity, flexibility and applicability. The use of anomaly detection and an early warning was also discussed for drinking water quality monitoring at the source or in the distribution system. As most of the online UV-Vis instruments studies in the drinking water field were conducted at the laboratory- and pilot-scale, future work is needed for industrial-scale evaluation with ab appropriate validation methodology. Issues and potential solutions associated with online instruments for water quality monitoring have been provided. Current technique development outcomes indicate that future research and development work is needed for the integration of early warnings and real-time water treatment process control systems using the online UV-Vis spectrophotometers as part of the water quality management system.

Review of Nitrification Monitoring and Control Strategies in Drinking Water System.

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.

Stormwater monitoring using on-line UV-Vis spectroscopy.

Stormwater runoff contains a myriad of pollutants, including faecal microbes, and can pose a threat to urban water supplies, impacting both economic development and public health. Therefore, it is a necessity to implement a real-time hazard detection system that can collect a substantial amount of data, assisting water authorities to develop preventive strategies to ensure the control of hazards entering drinking water sources. An on-line UV-Vis spectrophotometer was applied in the field to collect real-time continuous data for various water quality parameters (nitrate, DOC, turbidity and total suspended solids) during three storm events in Mannum, Adelaide, Australia. This study demonstrated that the trends for on-line and comparative laboratory-analysed samples were complimentary through the events. Nitrate and DOC showed a negative correlation with water level, while turbidity and total suspended solids indicated a positive correlation with water level during the high rainfall intensity. The correlations among nitrate, DOC, turbidity, total suspended solids and water level are the opposite during low rainfall intensity. Nitrate, one of the main pollutants in stormwater, was investigated and used as a surrogate parameter for microbial detection. However, the microbiological data (Escherichia coli) from captured storm events showed poor correlations to nitrate and other typical on-line parameters in this study. This is possibly explained by the nature of the stormwater catchment outside of rain events, where the sources of bacteria and nutrients may be physically separated until mixed during surface runoff as a result of rainfall. In addition, the poor correlations among the microbiological data and on-line parameters could be due to the different sources of bacteria and nutrients that were transported to the stormwater drain where sampling and measurement were conducted.

Innovative method of utilising hydrogen peroxide for source water management of cyanobacteria.

The treatment and control of cyanobacterial blooms using copper-based algaecides in water reservoirs have historically been used; however, due to the adverse impact of copper on the environment, water authorities have been researching and studying new and innovative ways to control cyanobacterial blooms. Hydrogen peroxide has been investigated as an environmentally friendly alternative, and this research aims to determine the impact of water quality on its effectiveness based on the decay characteristics in different water samples. Natural water samples from South Australian reservoirs and river were used to evaluate hydrogen peroxide decomposition and provide a better strategy for water operators in using it as an algaecide. Our experiments show the dependency of hydrogen peroxide decomposition not only on water quality but also on the initial hydrogen peroxide dose. A higher initial hydrogen peroxide dose can trigger the increase of pH, leading to increased consumption of hydrogen peroxide. In addition, the hydrogen peroxide decomposition is significantly accelerated with the rise of copper concentration in water samples. Moreover, it is found that UV light can also affect the decomposition rate of hydrogen peroxide. The hydrogen peroxide decay is more significant under UV light for the samples with lower hydrogen peroxide concentrations. Our study also shows the impact of dissolved organic carbon (DOC) on hydrogen peroxide decomposition is not substantial. The study also presents a modelling method to optimise hydrogen peroxide application based on water quality characteristics. Our findings can provide knowledge for the water industry to produce a suitable model which can be used to optimise the application of hydrogen peroxide for the control of cyanobacteria.

Development of an Optical Method to Monitor Nitrification in Drinking Water.

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.

Evaluation of the impact of suspended particles on the UV absorbance at 254 nm (UV254) measurements using a submersible UV-Vis spectrophotometer.

There is an increasing need to use online instrumentation for continuous monitoring of water quality. However, industrial applications using online instruments, such as submersible UV-Vis spectrophotometers, may require the use of alternative techniques to remove particle effect rather than performing a physical filtration step. Some submersible UV-Vis spectrophotometers have built-in generic particle compensation algorithms to remove the filtration step. This work studied the influence of suspended particles on the measurements of a submersible UV-Vis spectrophotometer as well as the performance of the built-in particle compensation technique under laboratory-controlled conditions. Simulated water samples were used in the combinations of standard particles from laboratory chemical and natural particles extracted from water systems with ultrapure water and treated water from a drinking water treatment plant. Particle contributions to the UV absorbance at 254 nm (UV254) measurements of water samples varied differently when particle types or concentrations changed. The compensated UV254, measured by the submersible instrument using the built-in generic particle compensation algorithms, was compared with laboratory UV254, analysed by the bench-top instrument with the physical filtration method. The results indicated that the built-in generic compensation algorithms of the submersible UV-Vis spectrophotometer may generate undercompensated UV254 or overcompensated UV254 for various surface waters. These findings provide in-depth knowledge about the impact of suspended particles on the measurements of submersible UV-Vis spectrophotometers; source water dependence; and why site-specific calibration is often needed to get accurate measurements.

Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach.

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.

Durability of Fibre-Reinforced Calcium Aluminate Cement (CAC)-Ground Granulated Blast Furnace Slag (GGBFS) Blended Mortar after Sulfuric Acid Attack.

Concrete wastewater infrastructures are important to modern society but are susceptible to sulfuric acid attack when exposed to an aggressive environment. Fibre-reinforced mortar has been adopted as a promising coating and lining material for degraded reinforced concrete structures due to its unique crack control and excellent anti-corrosion ability. This paper aims to evaluate the performance of polyethylene (PE) fibre-reinforced calcium aluminate cement (CAC)-ground granulated blast furnace slag (GGBFS) blended strain-hardening mortar after sulfuric acid immersion, which represented the aggressive sewer environment. Specimens were exposed to 3% sulfuric acid solution for up to 112 days. Visual, physical and mechanical performance such as water absorption ability, sorptivity, compressive and direct tensile strength were evaluated before and after sulfuric acid attack. In addition, micro-structure changes to the samples after sulfuric acid attack were also assessed by X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) to further understand the deterioration mechanism. The results show that overall fibre-reinforced calcium aluminate cement (CAC)-based samples performed significantly better than fibre-reinforced ordinary Portland cement (OPC)-based samples as well as mortar samples in sulfuric acid solution in regard to visual observations, penetration depth, direct tensile strength and compressive reduction. Gypsum generation in the cementitious matrix of both CAC and OPC-based systems was the main reason behind the deterioration mechanism after acid attack exposure. Moreover, laboratory sulfuric acid testing has been proven for successfully screening the cementitious material against an acidic environment. This method can be considered to design the service life of concrete wastewater pipes.

Recycling drinking water treatment sludge into eco-concrete blocks with CO2 curing: Durability and leachability.

Drinking water treatment sludge (DWTS) can be recycled into low-strength concrete blocks for construction use. The sodium sulfate resistance and leaching behaviours of the DWTS-derived blocks are investigated in this study. The experimental results show that the addition of DWTS degrades the sodium sulfate resistance of the concrete blocks, however CO2 curing compensates for such property, especially in the case of blocks incorporating 30% DWTS. The improvement can be attributed to the formation of crystalline CaCO3 during CO2 curing for microstructure refinement evidenced by X-ray Computed Tomography and Scanning Electron Microscopy. Leaching analyses show that Cu and Al concentrations increased with increasing DWTS content, and CO2 curing adversely increased the leachability of metals due to the decrease of pH, especially at early leaching stage. Nevertheless, the total leaching concentrations of Cu and Al after 60-day test is far below the prescribed limitations, regardless of samples subject to air curing or CO2 curing. In summary, sludge-derived blocks exposed to CO2 curing are safe and behave well in aggressive environments. Therefore, this study showcases a green technology that successfully recycling DWTS into value-added and durable concrete blocks with low environmental impacts.

Utilization of drinking water treatment sludge in concrete paving blocks: Microstructural analysis, durability and leaching properties.

The management of abundant drinking water treatment sludge (DWTS) in landfill remains an important issue. The reuse of DWTS as construction material could contribute to the development of greener concrete product and to mitigating the detrimental environment effect from excessive production of DWTS. This paper investigates the potential of using DWTS as sand replacement in Concrete Paving Blocks (CPB). Five CPB mixtures were designed and the replacement ratios of sand by DWTS were 0%, 5%, 10%, 15%, and 20%, by weight. Properties of CPB such as compressive strength, water absorption, abrasion resistance, sulfate attack and metal leachability were determined. The results indicated that above 10% of DWTS, the replacement was detrimental to such properties of the CPB. Microstructure analysis proved the addition of DWTS could result in ettringite formation and the interfacial transition zone (ITZ) between the cement matrix and DWTS was more porous than that of sand. In addition, the metal leachability test of CPB demonstrated that the addition of high-copper DWTS into CPB was safe.

The key factors and removal mechanisms of sulfadimethoxazole and oxytetracycline by coagulation.

The effects of coagulant dosage, alkalinity, turbidity, ionic strength, and dissolved organic matter (DOM) on the removal of sulfadimethoxazole (SMZ) and oxytetracycline (OTC) by coagulation were studied and the reaction mechanisms of the coagulation process were revealed in this research. From our results, alkalinity, turbidity, ionic strength, and DOM had different effects on the removal of antibiotics. The SMZ and OTC removals were improved with increase in poly-aluminum chloride (PACl) dosage, whereas the turbidity had less influence on the removal of SMZ and OTC because the adsorption of SMZ and OTC to kaolin was low, confirmed by a control when no PACl added. The hydrolysate of PACl played a more important role than turbidity in SMZ and OTC removals. The SMZ and OTC removals were significantly increased with the increase in alkalinity, which provided a suitable condition in situ for coagulant to form more optimal species of hydrolysate. The ionic strength, which was adjusted by NaNO3, also had a positive effect on the removal of SMZ but no obvious effect on the OTC removal. Furthermore, DOM had a higher effect on the removal of SMZ than that of OTC. In another word, if a water plant wants to improve the removal of SMZ and OTC by coagulation unit, PACl hydrolysate, alkalinity, and DOM are the three key factors to be considered primarily. Moreover, an experiment for the recovery of antibiotics from the flocs was done and the results showed that OTC and SMZ were removed by different mechanisms. The OTC was removed via complexation formed through the reaction between OTC and coagulant while the SMZ was removed through the pathway of adsorption and inter-particle bridging to the surface of coagulant hydrolysate.

The development and evaluation of a microstill with conductance detection for low level ammonia monitoring in chloraminated water.

Monitoring low levels of ammonia in chloraminated water can be challenging but is important for effectively managing potable water disinfection. The lower the concentration of free ammonia that can be determined, the tighter the control at the disinfection point, which supports better maintenance of chloramine residuals in the distribution system. In this study a micro-distillation technique was used to selectively separate ammonia into a boric acid solution allowing determination by conductance (i.e., micro-distillation and conductance measurement instrument - Micro-DCMI). The optimised technique had a linear calibration range of 0.01-60 mg NH3 L-1 with a limit of detection (LOD) of 0.014 mg L-1 and limit of quantification (LOQ) of 0.045 mg L-1. With the optimum operational parameters of 80 °C distillation temperature, 0.3 L min-1 air flow rate, 0.1 mol L-1 boric acid concentration and 8 min pre-concentration time, a sample throughput of 7 samples per hour was achieved. A laboratory comparison between Micro-DCMI and the standard ammonia selective electrode method was conducted on water samples obtained from a chloraminated drinking water distribution system. The results showed that the ratios of the free ammonia values determined by Micro-DCMI and an ammonia selective electrode were between 0.82 and 1.2 for 11 water samples. A custom-built automated analytical system was evaluated at a water treatment plant in Australia and the results compared favourably with the in plant online ammonia ion selective analyser. This study indicated that the Micro-DCMI method was a simple, robust and low cost online monitoring system suitable for determining low concentration ammonia to manage chloramination.