Water Journal : Water Journal April 2015
water APRIL 2015 150 water Business A NEW INSIGHT INTO WATER TREATMENT In critical water analysis and water- quality monitoring environments, the ability to rapidly detect, identify and quantify nuisance algae or problem particulate matter in real-time is essential in providing high levels of customer satisfaction. A rare influx of nutrients into Standley Lake, Westminster, Colorado, triggered a surprise algae bloom that quickly affected the taste and odour of the city’s drinking water. Thriving on nutrient-rich water, the Stephanodiscus algae population soared then quickly plummeted. However, the metabolites generated from the algae’s demise sped through the treatment process before testing procedures could detect their presence. Several nearby cities using the same water supply also experienced similar conditions that affected their drinking water quality. City staff had been detecting and identifying nuisance algae by counting cells and using an inverted microscope to examine 1-mL settled-water samples. The manual process required as much as several days for a sample to settle before analysis could be performed, and generated data weren’t available for months. The traditional microscopes and slides method is time consuming, has the potential for missing target algal cells and an inability to efficiently test large samples for minute populations. The delay hindered the city’s efforts to find and treat algae before it could bloom and threaten water quality. In Massachusetts, at Wachusett Reservoir, an algal bloom caused a barrage of angry complaints to the Water Resources Authority. Their monitoring process was tedious, time-consuming, labour–intensive and depended heavily on the skill and experience of the person doing the test. Other challenges were that the bloom could occur between the sample rounds and the fact that not all algae inhabiting the reservoir posed a threat that warrants treatment. The bloom was treated successfully with copper sulfate; however, customers’ confidence in their drinking water had been shaken. With industry-leading image quality combined with automated statistical pattern recognition software, the FlowCam imaging particle analysis system is an important tool for detecting, identifying, and quantifying algae or problem particulate matter in water treatment process. FlowCAM greatly reduces the time it would take to perform the same analyses using manual microscopy, while yielding higher statistical significance to the data due to higher throughput. Measurements can take place more frequently, with less manual hours, ensuring closer monitoring with cost savings. FlowCAM measures and stores over 40 unique parameters for every particle imaged, giving it the ability to automatically differentiate and enumerate many different algal types using powerful image recognition techniques. And since every particle image is stored, the quantified FlowCAM results are easily verified qualitatively by interactively viewing the images. In Pueblo, at Colo Reservoir, there was an imminent threat of invasive mussels, which multiply so rapidly they can destroy lake ecology, compromise water treatment infrastructure, and contribute to nuisance growth. Ideally, mussels should be detected at the larval veliger stage before they can become entrenched. FlowCAM is equally effective for detecting, counting and identifying zooplankton, invasive mussel veligers and various particulates in a single water sample processed at the same time. FlowCAM offers cross-polarising filters that reveal particles and microorganisms that exhibit birefringence such as sugars, starches, fibres and mussel veligers. In addition, FlowCAM can be used by water and wastewater professionals who deal with other water quality issues on a daily basis. For example, when the hatch of a water storage tank at the Massachusetts Water Resources Authority (MWRA) blew off, protocols were triggered that included draining and refilling the tank and then performing a series of tests including coliform, colour, odour and turbidity before the tank could be returned to service. As test samples were run through the FlowCAM, very small, geometrically shaped particles were found that were suspected to be concrete sediments suspended in the new batch of water. This information led to the discovery that the tank had been improperly filled from a neighbouring water tank rather than from the distribution system. FlowCAM will be featured by Kenelec Scientific at Stand Z11 at Ozwater. For more information please contact 1300 73 22 33 or visit www.kenelec.com.au. COLORADO WWTP REDUCES ANNUAL OPERATING EXPENSES BY ALMOST $300,000 In 2003, Littleton/Englewood was managing all of its plant data with a manual process. Technicians at five different locations would fill data into paper reports that were compiled into a larger reporting spreadsheet. Those larger sheets were then compiled by analysts and entered into a database through custom-developed Excel sheets. The process resulted in inconsistent and inaccurate data that couldn’t be graphed for analysis over time. Automated data collection was limited to lab‐generated data, and did not include operations or field data such as flow indications or pump status. As a result, during the ’90s, LEWWTP averaged two permit violations per year. The manual system didn’t help troubleshoot the causes of the violations or provide information to help prevent them. A collaborative team consisting of the database analyst, process specialist, IT Department, technology consultant, and SCADA, LIMS and business service Samples from the Danube River.
Water Journal February 2015
Water and CSG