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Frontiers of Environmental Science & Engineering

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Front. Environ. Sci. Eng.    2015, Vol. 9 Issue (3) : 534-544    https://doi.org/10.1007/s11783-014-0660-2
RESEARCH ARTICLE
Simulation of long-term nutrient removal in a full-scale closed-loop bioreactor for sewage treatment: an example of Bayesian inference
Zheng LI1,Rong QI1,Wei AN1,Takashi MINO2,Tadashi SHOJI3,Willy VERSTRAETE4,Jian GU5,Shengtao LI5,Shiwei XU5,Min YANG1,*()
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
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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.
Keywords activated sludge model      Bayesian inference      biological nutrient removal      closed-loop bioreactor      oxidation ditch      denitrifying polyphosphate accumulating organisms     
Corresponding Author(s): Min YANG   
Online First Date: 21 February 2014    Issue Date: 30 April 2015
 Cite this article:   
Zheng LI,Rong QI,Wei AN, et al. Simulation of long-term nutrient removal in a full-scale closed-loop bioreactor for sewage treatment: an example of Bayesian inference[J]. Front. Environ. Sci. Eng., 2015, 9(3): 534-544.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-014-0660-2
https://academic.hep.com.cn/fese/EN/Y2015/V9/I3/534
Fig.1  Model structure of the closed-loop oxidation ditch process
name symbol percentage/% method/equation
total COD TCOD 100 measurement
inert soluble COD SI 2.0 SI = 0.9 CODeff,sol
readily biodegradable soluble COD SS 29.2 SS = CODinf,sol-SI
volatile fatty acids, VFA, in COD SA 16.9 measurement
fermentable, readily biodegradable COD SF 12.3 SF = SS-SA
slowly biodegradable particulate COD XS 57.1 XS = BCOD-SS
inert particulate COD XI 11.7 XI = TCOD-SI-SS-XS
Tab.1  COD fractions relative to the total COD in the effluent from grit chamber
parameter unit rel. std. prior mean prior SD max. posterior
KA,PAO g COD·m-3 0.5 4 2 1.9
KMAX g P·g COD-1 0.2 0.34 0.068 0.54
K O 2 , A U T g O2·m-3 0.2 0.5 0.1 0.14
K O 2 , H E T g O2·m-3 0.5 0.2 0.1 0.36
ηfe – 0.2 0.4 0.08 0.55
η N O 3 , H E T , – 0.2 0.8 0.16 0.90
η N O 3 , P A O , – 0.2 0.6 0.12 0.31
qPHA* d-1 0.5 3 1.5 3.5
qPP* d-1 0.5 1.5 0.75 1.8
μAUT* d-1 0.2 1 0.2 1.7
μPAO* d-1 0.5 1 0.5 1.3
YPO4 g P·g COD-1 0.05 0.4 0.02 0.44
Tab.2  Parameters for the dynamic calibration with Bayesian inference
Fig.2  Measurements (circles) and model predictions (solid lines) of ammonium, nitrate and phosphate concentrations in the effluent. The correlation coefficients between prediction and measured data in the right panel are: ammonium: R2 = 0.862, nitrate: R2 = 0.884, phosphate: R2 = 0.718
Fig.3  Measurements (light bars) and prediction (dark bars) of phosphate concentrations in the system
WWTP process type VFA uptake rate/(mg·g-1 VSS·h-1) P-release rate/(mg·g-1 VSS·h-1) P-release/VFA uptake ratio/(g P·g-1 COD) aerobic P-uptake rate/(mg·g-1 VSS·h-1) anoxic P-uptake rate/(mg·g-1 VSS·h-1) anoxic/aerobic P-uptake rate
this study OD 21.1 7.8 0.37 0.99 1.94 2.1
Hardenberg a) BCFS 21.9 17.4 0.38 19.2 5.9 0.31
Deventer a) BCFS 19.2 9.6 0.45 9.0 2.1 0.23
Holten b) modified UCT 47 16 0.50 13 6 0.46
Genemuiden c) modified UCT 7–31 5–9 0.40 4–6 1.2–1.6 0.2–0.4
Katwoude a) Phoredox 13.5 11.1 0.33 8.0 1.9 0.23
Hoek vanHolland a) Phoredox 21.3 20.9 0.38 9.1 4.4 0.48
Venlo a) Phoredox 11.2 10.6 0.38 6.2 0.6 0.9
HaarlemWaarderpolder SidestreamP-stripping 9.0 a), 23 d) 10.4 a), 6 d) 0.40 a), 0.31 d) 9.8 a), 2.2 d) 3.3 a), 1.7 d) 0.34 a), 0.8 d)
Tab.3  Comparison of simulated PAO activities with the measurements from other full-scale systems
Fig.4  PAO activities in the anaerobic, anoxic and aerated compartments calculated with the simulated process rates. The black and dark gray bars represent the anaerobic and anoxic compartments, and the light gray and white bars represent the anoxic and aerobic activities in the aerated compartment of the reactor respectively
Fig.5  Nitrogen removal by denitrification in the anoxic and aerated compartments calculated with the simulated process rates. The dark bar represents the denitrification by heterotrophic organisms, and the light bar represents the denitrification by the process of anoxic Poly-P storage of PAO
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[1] Supplementary Material Download
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