By Victor Stoica, Erik Kallen, John van Pol and Heinrich Wortche
Industrial wastewater quality monitoring is increasing in importance, due to enhanced legal requirements and the attempt to optimize industrial processes. For remote operations, field sampling and subsequent laboratory analysis of the samples is the method commonly used to obtain information on relevant water quality indicators.
Laboratory analysis allows for the detection of a broad spectrum of parameters through its high sensitivity and precision. However, the costs of highly-trained staff, travel time, accessibility of areas and laboratory costs limit sampling frequencies. Sampling provides snapshot-like information, with long intervals in between. Therefore, information is missing on the long-term history of indicators, such as the parameters and time scale of industrial operations and process cycles.
Self-sustained autonomously operating monitoring systems offer an alternative approach for monitoring remote areas. These combine an increasing number of sensors for detecting environmental parameters, with energy-saving, but powerful electronics and highly efficient micro-power stations.
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A remote monitoring system of this kind must be able to withstand harsh weather conditions, with temperatures varying from -45°C to 30°C. It must also withstand the impact of roaming wildlife, and storms and ice flow if mounted in water. It has to operate without access to the power grid and with limited radio communication. The latter imposes restrictions on the amount of data that can be transmitted from observation sites and the remote control capabilities of the devices.
The Remote Water Quality Monitoring system (RWQM), developed by INCAS in collaboration with INGU Solutions Inc., is a modular system designed for continuous all year remote operation under harsh conditions. It can house electrochemical, optical, physical and radiation sensor modules, measuring, for example, microbiological stability, the amount of nutrients and salts, the presence of radioactivity and the clarity of the treated industrial wastewater.
Case Study
From July to December 2014, an RWQM with two sensor modules (water and radiation) was set up in a creek in Northern Saskatchewan to continually monitor wastewater released by a mill that processes uranium ore. The initial trial was intended for a period of one month, allowing for the required monthly maintenance of the Intellisonde Water Sensor. However, during the trial it was decided to run into the winter months. This meant that water sensor data degraded over time and was switched off when the temperature went below zero. The radiation sensor remained operational during the complete period.
The RWQM power and control module is designed to support self-sufficient operation over long periods of time. A tree mounted solar panel provided power, and two large deep-cycle batteries were used to ensure continuous power during the night and periods of bad weather. The power and control module was configured to allow for two modes of operation: a standard mode and an energy saving mode.
In the standard mode, operated during the summer period, the RWQM runs its own measurement program, but can also be remotely accessed to perform enhanced measurements. During the winter period, the system was switched over to autonomous mode to minimize power consumption. Measurement frequency (typically several times per day) and the measurement period (typically 30 minutes per cycle) can be adjusted via remote access.
The system stores the data locally as well as uploading at regular intervals to the cloud. This allows for continuous data access without the need for accessing the RWQM and draining the system. All individual measurements and data transmitted by the RWQM are accessible at all times via a web interface which also displays the status of the system.
Conclusions
Developments in sensing and computing technology allow for novel water quality monitoring systems that are capable of year round monitoring in remote areas under harsh conditions. The Remote Water Quality Monitor is a system that has proven its functionality during a four month trial in Northern Saskatchewan. The embedded intelligence offers the flexibility to operate the system under widely varying environmental conditions with consistent performance. The radiation detector meets the required sensitivity limits for radio nuclide detection on ppm level, with effective measurement times below 30 minutes.
Victor Stoica is with INCAS. Erik Kallen, John van Pol and Heinrich Wortche are with INCAS and INGU-Solutions Inc.
