Water Treatment Process Control Research Articles

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.

Spatial and temporal variability in dissolved oxygen content of Asoro stream, in south western Nigeria

This study examined the spatial and temporal variation of dissolved oxygen (DO) concentration in Asoro stream, the self-recovery ability of the stream of the effluent discharges with a view to providing a baseline information on quality of water in Asoro stream. DO is a measure of the ability of water to sustain aquatic life, it is important in water pollution control and waste water treatment process control. Samples were collected from fifteen sampling points along the Asoro stream at 500 m intervals over a 5000 m stretch for twelve-months. The DO, Biochemical Oxygen Demand and some other physico-chemical parameters of water were determined using standard methods. The hydrographic characteristics of the stream were; width (0.8 to 5.8 m), depth (0.1 to 0.55 m), discharge (0.30 to 0.52 ms -1 ), flow rate 0.07 to 0.0.73 m 3 /s. The temporal variation in DO concentration in Asoro stream fluctuated from the first week of sampling to 25th week after with a peak range of concentration (7.46 mg/L to 10.12 mg/L) between 27th week and 39th week of sampling suggesting high level of organic pollution. The mean spatial distribution of DO at each station changed slightly between the point of brewery effluent discharge and 5000 m away. Regression analysis showed that there was no significant relationship (P≥ 0.05) between time (weeks) and DO concentration along Asoro stream. The study concluded that release of organic matter from industrial effluent affects the DO and BOD concentrations of Asoro stream. Keywords: Dissolved oxygen, Temporal, Spatial, Asoro stream, self- recovery

Contributions of spatial, temporal, and treatment impacts on natural organic matter character using fluorescence-based measures

The potential application of fluorescence spectroscopy for monitoring of organic matter concentration and character at four water treatment facilities was investigated. Results are presented showing impacts on natural organic matter (NOM) due to intake location on the same water body and from individual unit processes including ozonation, granular-activated carbon filtration, and coagulation/flocculation. For validation and comparison of fluorescence methods, organic matter was quantified and characterized using liquid chromatography-organic carbon detection (LC-OCD). Principal component analysis (PCA) and parallel factors analysis were used for dimensionality reduction and to represent individual organic components observed through fluorescence excitation-emission matrices. Fluorescence results generally agreed with LC-OCD characterization, indicating that complete treatment reduced organic concentrations and preferential removal of humic-like material was associated with coagulation/flocculation. PCA results indicated higher concentrations of humic-like material at the Island water treatment plant intake that was not well reduced by inline polyaluminum chloride coagulation and direct filtration. Through fluorescence spectroscopy, ozonation increased Rayleigh scattering, which is correlated to small colloidal/particulate concentrations. Full-scale results from four water treatment plants presented demonstrate that fluorescence methods can characterize NOM, providing similar identification of trends to LC-OCD, with possible online application and use in real-time water treatment process control.

Water recycling — forwards or backwards for public health?

Water recycling — forwards or backwards for public health?

Water recycling — forwards or backwards for public health?

Water recycling — forwards or backwards for public health?

Drinking water quality and treatment: the use of artificial neural networks

To improve drinking water quality while reducing operating costs, many drinking water utilities are investing in advanced process control and automation technologies. The use of artificial intelligence technologies, specifically artificial neural networks, is increasing in the drinking water treatment industry as they allow for the development of robust nonlinear models of complex unit processes. This paper highlights the utility of artificial neural networks in water quality modelling as well as drinking water treatment process modelling and control through the presentation of several case studies at two large-scale water treatment plants in Edmonton, Alberta.Key words: artificial neural networks, water treatment process control, water treatment modelling.

Real-Time Water Treatment Process Control with Artificial Neural Networks

The coagulation, flocculation, and sedimentation processes involve many complex physical and chemical phenomena and thus are difficult to model for process control with traditional methods. Proposed is the use of a neural network process control system for the coagulation, flocculation, and sedimentation processes. Presented is a review of influential control parameters and control requirements for these processes followed by the development of a feed forward neural network control scheme. A neural network process model was built based on nearly 2,000 sets of process control data. This model formed the major component of a software controller and was found to consistently predict the optimum alum and power activated carbon doses for different control actions. With minor modifications, the approach illustrated can be used for building control models for other water treatment processes.

Particle counters as tools for managing Cryptosporidium risk in water treatment

Outbreaks of waterborne cryptosporidiosis have been a major concern for the Water Industry in the UK and US over the past ten years. Management of risk from Cryptosporidium in water supplies relies heavily upon operation and control of water treatment processes to maximise oocyst removal. Difficulties in measuring oocyst concentrations in water supplies have led to evaluation of surrogate parameters with which to assess oocyst removal by treatment. Whilst turbidity measurement can give an indication of the risk of oocyst breakthrough from filters, a more sensitive indicator appears to be particle counts in filtered water. The paper gives a demonstration of the potential for particle counting as a tool for managing Cryptosporidium risk, and describe ways in which particle counting can be used for monitoring and controlling water treatment plant operation. With the present level of knowledge, the most suitable application for particle counting is as a diagnostic tool for the identification of operating conditions which reduce or minimise particle counts in filtered water at individual sites.

Particle counters as tools for managing Cryptosporidium risk in water treatment

Outbreaks of waterborne cryptosporidiosis have been a major concern for the Water Industry in the UK and US over the past ten years. Management of risk from Cryptosporidium in water supplies relies heavily upon operation and control of water treatment processes to maximise oocyst removal. Difficulties in measuring oocyst concentrations in water supplies have led to evaluation of surrogate parameters with which to assess oocyst removal by treatment. Whilst turbidity measurement can give an indication of the risk of oocyst breakthrough from filters, a more sensitive indicator appears to be particle counts in filtered water. The paper gives a demonstration of the potential for particle counting as a tool for managing Cryptosporidium risk, and describes ways in which particle counting can be used for monitoring and controlling water treatment plant operation. With the present level of knowledge, the most suitable application for particle counting is as a diagnostic tool for the identification of operating conditions which reduce or minimise particle counts in filtered water at individual sites.

Importance of speciation methods in analytical control of water treatment processes with application to fluoride removal from waste waters

Analytical methods of speciation for the control of water treatment processes, particularly for the removal of fluoride by aluminium hydroxide polymers as precipitant, have been discussed. It has been shown that combination of ultrafiltration with spectroscopic methods and fluoride ion-selective electrode offers a powerful means for the control of both the precipitant and pollutant, e.g. fluoride. 27Al n.m.r. has been used for the identification of hydrolytic products of aluminium(III) and the ultrafiltration technique has been applied for the separation of the active polymer. The hydrolytic products were also characterized by timed spectrometric method. The interaction between aluminium hydroxide polymer and fluoride was studied by means of fluoride ion-selective electrode, ultrafiltration and atomic absorption spectrometry. The usefulness of these speciation methods for choosing the best conditions for water treatment process is discussed. By applying them for the removal of fluoride, it was found that the fluoride levels can be brought down to less than 10 mg l −1, the limit set by Swiss regulatory body for discharge of waste water. The importance of using such speciation methods for evaluating the possible impact of the “products” of the water treatment (dissolved species in treated water, discharged solid) is also emphasized.

Operation and Control of Water Treatment Processes

Operation and Control of Water Treatment Processes