Paper/Poster/Presentation Title
A mathematical model for GHG from SB-MBR: calibration by an innovative protocol
Keywords
Uncertainty; greenhouse gases; wastewater; membrane.
Location
Session B1: Data Assimilation Techniques for Uncertainty Reduction
Start Date
13-7-2016 3:10 PM
End Date
13-7-2016 3:30 PM
Abstract
A mathematical model to quantify greenhouse gases (GHG) (carbon dioxide, CO2 and nitrous oxide, N2O) for a membrane bioreactor (MBR) is presented. The model has been applied to a pilot plant with a pre-denitrification MBR scheme. The pilot plant was cyclically filled with real saline wastewater according to the fill-draw-batch operation. The model was calibrated by adopting a specific protocol based on extensive field dataset. Standardised Regression Coefficient (SRC) method was adopted to select the most influential model factors to be calibrated. Results related to SRC method show that among the important model factors a key role is played by the half saturation coefficients related with the nitrogen removal processes (kN2O, kNO) and by the model factors affecting the oxygen transfer rate in the aerobic and MBR tank (k2,2 and k2,3). In terms of uncertainty, it was found that for the gaseous model outputs (SGHG,N2O,1 and SGHG,N2O,2) only the 7% and the 12% of the measured data lays outside the bands showing an accurate model prediction in case a wide data set is available.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
A mathematical model for GHG from SB-MBR: calibration by an innovative protocol
Session B1: Data Assimilation Techniques for Uncertainty Reduction
A mathematical model to quantify greenhouse gases (GHG) (carbon dioxide, CO2 and nitrous oxide, N2O) for a membrane bioreactor (MBR) is presented. The model has been applied to a pilot plant with a pre-denitrification MBR scheme. The pilot plant was cyclically filled with real saline wastewater according to the fill-draw-batch operation. The model was calibrated by adopting a specific protocol based on extensive field dataset. Standardised Regression Coefficient (SRC) method was adopted to select the most influential model factors to be calibrated. Results related to SRC method show that among the important model factors a key role is played by the half saturation coefficients related with the nitrogen removal processes (kN2O, kNO) and by the model factors affecting the oxygen transfer rate in the aerobic and MBR tank (k2,2 and k2,3). In terms of uncertainty, it was found that for the gaseous model outputs (SGHG,N2O,1 and SGHG,N2O,2) only the 7% and the 12% of the measured data lays outside the bands showing an accurate model prediction in case a wide data set is available.
