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Abstract
Cyanobacterial blooms are a concern for water utilities due to the potential production of cyanotoxins and taste and odours. Current detection methods are slow and may not capture changes in bloom density which can prevent utilities in rapidly adjusting their treatment process. This project investigated using in situ fluorometers as a tool for real-time cyanobacteria monitoring and treatment adjustment. Four fluorometers were evaluated using different counts of cyanobacterial and green algal species to: 1) calibrate the fluorometers, 2) determine limit of detections, 3) quantify the measurement bias during simulated bloom events and 4) develop a correction method for chlorophyll-a interference based on the fluorometer response. Bench-scale and pilot trials were undertaken with fluorometers to determine the optimal treatment dose for the simulated bloom. Fluorometer accuracy was evaluated at 11 treatment plants to determine the suitability as a field detection tool. Finally, fluorometers were deployed at critical control points of 3 treatment plants for real-time monitoring.
Significant correlations were found between the phycocyanin response and cyanobacterial numbers for all fluorometers tested. The detection limits varied depending on the fluorometer and species tested. Green algae addition caused fluorometer measurement error to increase; the developed correction reduced the measurement error for almost all the fluorometers and species tested by 21% to 99%. Correction factors applied in the field reduced fluorometer measurement errors at sites that were dominated by a single cyanobacterial species, validating the protocol. Fluorometers tracked the growth phases of three cyanobacteria species based on cell count validation at the bench-scale. The calculated removal efficiencies were comparable between fluorometer measurements and cell counts (r > 0.85) for three cyanobacterial species. The optimal coagulant and PAC dose was determined for the simulated blooms. The fluorometers can track cyanobacterial trends throughout the critical control points during the pilot trials. Good correlation (r = 0.6) was found between corrected field fluorometer response and routine monitoring data; fluorometers detected the cyanobacterial cells entering the treatment plant in real-time. Fluorometers have a huge potential for cyanobacterial monitoring from the source and into treatment plants and as an aid for real-time chemical dose adjustment.