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Frontiers of Environmental Science & Engineering >> 2015, Volume 9, Issue 3 doi: 10.1007/s11783-014-0660-2

Simulation of long-term nutrient removal in a full-scale closed-loop bioreactor for sewage treatment: an example of Bayesian inference

1. State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100086, China.2. Socio-Cultural Environmental Studies, the University of Tokyo, Kashiwa City 277-8563, Japan.3. Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry, Chiba 270-1194, Japan.4. Laboratory of Microbial Ecology and Technology (LabMET), Ghent University, Gent 9000, Belgium.5. Beijing Drainage Group Co. Ltd, Beijing 100044, China

Accepted: 2014-02-21 Available online: 2015-04-30

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Abstract

In this study, the performance of nitrogen and phosphorus removal in a full-scale closed-loop bioreactor (oxidation ditch) system was simulated using the ASM2d model. Routine data describing the process for two years were compiled for calibration and validation. To overcome the identifiability problem, the classic Bayesian inference approach was utilized for parameter estimation. The calibrated model could describe the long-term trend of nutrient removal and short-term variations of the process performance, showing that the Bayesian method was a reliable and useful tool for the parameter estimation of the activated sludge models. The anoxic phosphate uptake by polyphosphate accumulating organisms (PAO) contributed 71.2% of the total Poly-P storage, which reveals the dominance of denitrifying phosphorus removal process under the oxygen limiting conditions. It was found that 58.7% of the anoxic Poly-P storage and denitrification by PAO in the reactor was achieved in the aerated compartment, implying that the PAO’s anoxic activity was significantly stimulated by the low dissolved oxygen (DO) level in this compartment due to the oxygen gradient caused by brush aerator.

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