SENTRY technology was installed at an Organica Food Chain Reactor with combined returned MLSS in Budapest, Hungary. The sensor was installed in the influent and effluent of the treatment facility. The key goal of the installation was to validate the SENTRY platform could be used as a replacement for and improvement to traditional manual wastewater sampling. Local sampling was performed by Organica personnel to determine the correlation between the Microbial Electron Transfer (MET) value of the sensor and TBOD5, TCOD and fCOD.
The Organica wastewater treatment plant consists of a primary clarifier, two anoxic tanks, six aerobic tanks, clarification, post nitrification and post denitrification. The plant treats as much as 80,000 m3/day, approximately 1/3rd of the municipal flow from Budapest.
The sensor was demonstrated to be a functional tool for the on-site operator in understanding key process factors, such as (1) real-time influent and effluent water quality monitoring, (2) daily and weekly trend identification, (3) identifying process upset events.
The major conclusions from the case study are outlined as follows:
(1) Organic load correlation: SENTRY data correlated well with TCOD/fCOD/TBOD5, with R2 ranging from 0.61 to 0.82 for the influent and R2 from 0.49 to 0.51 for the effluent. Combined influent and effluent data further increased this correlation.
(2) Organic loading pattern identification: The sensor identified the days of the week with the highest organic strength in the influent (Wednesday - Friday) and time of day with highest organic strength (after 5pm). The lowest organic strength in the influent occurred on Monday (also it was low on the weekend) and typically was lowest around noon. This information can be tied into understanding when the wastewater treatment process is underloaded or overloaded (or just at an improper carbon/nitrogen loading) and allows decisions to be made intelligently around things like plant down times, best times to schedule internal recycles, times for additional material to be received from offsite, etc. The real time data gives operations the maximum time period possible to respond and react to changes in the incoming wastewater. October 24th, 29th, 30th and 31st were flagged due to high changes in MET on these days. Discoloured water and precipitation events were of note during imbalance event identification. Working with the on-site team these events were tracked to rain events or incoming water with an unusual color. Understanding what exactly happens on days of these will inform plant decision makers with this critical information showing wastewater conditions are changing and impacting biological performance. Smoothing out these events or moving them to more favorable time periods could significantly improve plant performance. Understanding what exactly happens on these days will inform plant decision makers with critical information showing wastewater conditions are changing and impacting biological performance. Smoothing out these events or moving them to more favorable time periods could significantly reduce operational costs.
(3) Sample frequency and real-time insight: Data from SENTRY could be used to reduce the quantity of on-site water quality analysis, saving costs for the facility while simultaneously providing an improved monitoring solution for the process.
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