Interlinkages between operational conditions and direct and indirect greenhouse gas emissions in a moving bed membrane biofilm reactor

Abstract

Nitrous oxide (N2O) can be emitted during wastewater treatment contributing to the global warming due to its high global warming potential,. During the last ten years, several efforts have been provided to improve knowledge on: key mechanisms, operating factors and influent features affecting the N2O production/emission. However, the knowledge on the investigated issues is not completely mature. Indeed, in terms of mathematical modelling, literature shows that a reliable model has not yet been established due to the huge data set required and the complexity of the mechanistic models indicated as the most accurate. In this work, the first attempt to perform a multiregression analysis is presented with the final aim to get a simple and easy tool for N2O estimation from wastewater treatment plant. The multiregression analysis has been performed by testing both simple and complex equations by means of Monte Carlo simulations. Data acquired from an University Cape Town moving bed membrane bioreactor pilot plant have been adopted. The pilot plant has been operated at different sludge retention times. Results of the simple linear regression analysis show that such approaches are suitable to predict N2O flux emitted from each tank of the plant and dissolved in the permeate. For some tested cases, a high efficiency (obtained comparing simulated and measured data) was obtained (e.g., 0.96 for N2O-N dissolved in the effluent). The results show that the dependence with the available measured data changes with the operational conditions. Conversely, results related to the complex multiregression analysis reveal that no unique equation valid for different operational conditions can be established.