Measurement of ordinary heterotrophic organism active biomass in activated sludge mixed liquor: Evaluation and comparison of the quantifying techniques

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Abstract

Ordinary heterotrophic organism (OHO) active biomass plays key roles in biological wastewater treatment processes. However, due to the lack of measurement techniques, the OHO active biomass exists hypothetically within the design and simulation of biological wastewater treatment processes. This research was purposed to develop a quick and easy quantifying technique for the OHO active biomass applying a modified batch aerobic growth test. Two nitrification-denitrification activated sludge systems, with 10- and 20-day sludge ages, were operated to provide well-cultured mixed liquor to the batch tests. A steady state design model was firstly applied to quantify the "theoretical" OHO active biomass concentration of the two parent systems. The mixed liquor from the parent systems was then inoculated to a batch growth test and a batch digestion test to estimate the "measured" OHO active biomass concentration in the mixed liquor. The measured OHO active biomass concentrations with the batch growth test and the batch digestion test were compared to the theoretical concentrations of the parent system. The measured concentrations with the batch growth test were generally smaller than the theoretical concentrations. However, the measured concentrations with the batch aerobic digestion tests showed a good correlation to the theoretical concentrations. Thus, a different microbial growth condition (i.e., a higher food/biomass ratio) in the batch growth test, compared to the parent system or the batch digestion test, was found to cause underestimation of the OHO active biomass concentrations. © 2014 Korean Society of Environmental Engineers.

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Lee, B. J., Wentzel, M., Ekama, G., Choi, Y. Y., & Choi, J. W. (2014). Measurement of ordinary heterotrophic organism active biomass in activated sludge mixed liquor: Evaluation and comparison of the quantifying techniques. Environmental Engineering Research, 19(1), 91–99. https://doi.org/10.4491/eer.2014.19.1.091

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