TY - JOUR
T1 - Performance and process simulation of membrane bioreactor (MBR) treating petrochemical wastewater
AU - Huang, Shujuan
AU - Pooi, Ching Kwek
AU - Shi, Xueqing
AU - Varjani, Sunita
AU - Ng, How Yong
PY - 2020/12/10
Y1 - 2020/12/10
N2 - Mathematical modelling of biological treatment is an effective tool to predict effluent quality. Model calibration is critical to improve the accuracy of simulation, which is normally carried out by fine-tuning the values of parameters according to the practical data. It indicated that huge amount of practical date will be consumed, and it cannot predict the treatment performance of new wastewater. In this study, the main objective was to investigate the feasibility of application BioWin software coupled with determination of sensitive parameters to predict the treatment performance of membrane biological reactors (MBRs) treating real petrochemical wastewater (PW). Model calibrations, i.e., COD fractions of petrochemical wastewater and kinetic parameters of biomass, were carried out using the respirometry method and the relationship between observed and true growth yield coefficients of the three lab-scale MBRs which were operated under different solid retention time (SRT). All the three MBRs had good organic and ammonium removal, with removal efficiencies higher than 80% and 99.9%, respectively. Simulation using the calibrated model also obtained good fit for effluent COD concentration, effluent nitrate concentration and bioreactor's MLSS concentration of all the three MBRs. The mean absolute percentage errors (MAPE) of the simulation mostly were lower than 22%. The results indicated that it is feasible to using BioWin, incorporated with appropriate determination methods of sensitive parameters, to simulate and monitor the treatment performance of MBR treating petrochemical wastewater. This is more time-saving and effective than fine-tuning values of all parameters. This study provides a valuable reference for simulation of industrial wastewater treatment using BioWin. © 2020 Elsevier B.V.
AB - Mathematical modelling of biological treatment is an effective tool to predict effluent quality. Model calibration is critical to improve the accuracy of simulation, which is normally carried out by fine-tuning the values of parameters according to the practical data. It indicated that huge amount of practical date will be consumed, and it cannot predict the treatment performance of new wastewater. In this study, the main objective was to investigate the feasibility of application BioWin software coupled with determination of sensitive parameters to predict the treatment performance of membrane biological reactors (MBRs) treating real petrochemical wastewater (PW). Model calibrations, i.e., COD fractions of petrochemical wastewater and kinetic parameters of biomass, were carried out using the respirometry method and the relationship between observed and true growth yield coefficients of the three lab-scale MBRs which were operated under different solid retention time (SRT). All the three MBRs had good organic and ammonium removal, with removal efficiencies higher than 80% and 99.9%, respectively. Simulation using the calibrated model also obtained good fit for effluent COD concentration, effluent nitrate concentration and bioreactor's MLSS concentration of all the three MBRs. The mean absolute percentage errors (MAPE) of the simulation mostly were lower than 22%. The results indicated that it is feasible to using BioWin, incorporated with appropriate determination methods of sensitive parameters, to simulate and monitor the treatment performance of MBR treating petrochemical wastewater. This is more time-saving and effective than fine-tuning values of all parameters. This study provides a valuable reference for simulation of industrial wastewater treatment using BioWin. © 2020 Elsevier B.V.
KW - Membrane bioreactor
KW - Model calibration
KW - Petrochemical wastewater
KW - Simulation
KW - Solid retention time
UR - http://www.scopus.com/inward/record.url?scp=85089172776&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85089172776&origin=recordpage
U2 - 10.1016/j.scitotenv.2020.141311
DO - 10.1016/j.scitotenv.2020.141311
M3 - RGC 21 - Publication in refereed journal
C2 - 32791416
SN - 0048-9697
VL - 747
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 141311
ER -
