Functionality of turbidity measurement under changing water quality and environmental conditions.

Turbidity is one of the key water quality parameters in environmental monitoring, water treatment or industrial process operation. Turbidity is however very challenging to measure reliably due to the many factors affecting the reading and functionality of the measurement device. In this paper, the results of the experiments to study the effects of changes in water quality and environmental condition to the readings of turbidity measurement devices are presented. The experiments were carried out in stable laboratory conditions where controlled changes were made to water pH, the temperature, salinity, colour, environment brightness and the mixing speed of the water. The study showed that even though the actual turbidity of the water remained constant the changes in other variables caused in the worst-case significant disturbances to the turbidity measurements. This knowledge is vital, for instance in monitoring or developing a robust model for forecasting regional turbidity in natural waters.

Monitoring a municipal wastewater treatment process using a trend analysis.

New monitoring methods are required to enhance the operation of a wastewater treatment process and to meet the constantly tightening regulations for the effluent discharges. An on-line optical monitoring device, that analyses the morphological parameters of the flocs, has been shown to be a potential tool for assessing the wastewater quality and the state of the activated sludge process. In this paper, the earlier presented trend analysis method is applied to the operating conditions, the treatment results and the optical monitoring variables of a full-scale biological wastewater treatment process. The trend episodes and the deviation indices resulted from the trend analysis provide warning of the changes in the monitored variables and the received information can be used as assistance in the treatment process operation and avoiding harmful environmental risks.

Comparison of modelling accuracy with and without exploiting automated optical monitoring information in predicting the treated wastewater quality.

Traditionally the modelling in an activated sludge process has been based on solely the process measurements, but as the interest to optically monitor wastewater samples to characterize the floc morphology has increased, in the recent years the results of image analyses have been more frequently utilized to predict the characteristics of wastewater. This study shows that the traditional process measurements or the automated optical monitoring variables by themselves are not capable of developing the best predictive models for the treated wastewater quality in a full-scale wastewater treatment plant, but utilizing these variables together the optimal models, which show the level and changes in the treated wastewater quality, are achieved. By this early warning, process operation can be optimized to avoid environmental damages and economic losses. The study also shows that specific optical monitoring variables are important in modelling a certain quality parameter, regardless of the other input variables available.

Modelling effluent quality based on a real-time optical monitoring of the wastewater treatment process.

A novel optical monitoring device was used for imaging an activated sludge process in situ during a period of over one year. In this study, the dependencies between the results of image analysis and the process measurements were studied, and the optical monitoring results were utilized to predict the important quality parameters for the wastewater treatment process efficiency: suspended solids, biological oxygen demand, chemical oxygen demand, total nitrogen and total phosphorous in biologically treated wastewater. The optimal subsets of variables for each model were searched using five variable selection methods. It was shown that online optical analysis results have clear dependencies on some process variables and the purification result. The model based on optical monitoring and process variables from the early stage of the treatment process can be used to predict the levels of important quality parameters, and to show the quality of the biologically treated wastewater hours in advance. This study confirms that the optical monitoring method is a valuable tool for monitoring a wastewater treatment process and receiving new information in real time. Combined with predictive modelling, it has the potential to be used in process control, keeping the process in a stable operating condition and avoiding environmental risks.

Early warning of changing drinking water quality by trend analysis.

Monitoring and control of water treatment plants play an essential role in ensuring high quality drinking water and avoiding health-related problems or economic losses. The most common quality variables, which can be used also for assessing the efficiency of the water treatment process, are turbidity and residual levels of coagulation and disinfection chemicals. In the present study, the trend indices are developed from scaled measurements to detect warning signs of changes in the quality variables of drinking water and some operating condition variables that strongly affect water quality. The scaling is based on monotonically increasing nonlinear functions, which are generated with generalized norms and moments. Triangular episodes are classified with the trend index and its derivative. Deviation indices are used to assess the severity of situations. The study shows the potential of the described trend analysis as a predictive monitoring tool, as it provides an advantage over the traditional manual inspection of variables by detecting changes in water quality and giving early warnings.

Real-time optical monitoring of the wastewater treatment process.

One activated sludge process line was optically monitored in situ by a novel image analysis equipment. The results of the image analysis were studied to find out dependencies to the process variables of the wastewater treatment plant (WWTP) and to the quality of the treated wastewater. The quality parameter of the treated wastewater, suspended solids, was modelled using the image analysis results. The model can be used for evaluating the performance of the WWTP and for the better control for stable effluent quality. It was shown that the results of the online optical monitoring reveal useful information from the process and can be used in forecasting the quality of biologically treated wastewater. The optical monitoring method together with process measurements has an important role in keeping the process in stable operating conditions and avoiding environmental risks.

Drinking water quality monitoring using trend analysis.

One of the common quality parameters for drinking water is residual aluminium. High doses of residual aluminium in drinking water or water used in the food industry have been proved to be at least a minor health risk or even to increase the risk of more serious health effects, and cause economic losses to the water treatment plant. In this study, the trend index is developed from scaled measurement data to detect a warning of changes in residual aluminium level in drinking water. The scaling is based on monotonously increasing, non-linear functions, which are generated with generalized norms and moments. Triangular episodes are classified with the trend index and its derivative. The severity of the situations is evaluated by deviation indices. The trend episodes and the deviation indices provide good tools for detecting changes in water quality and for process control.