Model development and system optimization to minimize greenhouse gas emissions from wastewater treatment plants

As greenhouse gas emissions (GHG) reduction has drawn considerable attention, various methods have been established to estimate greenhouse gas emissions from wastewater treatment plants (WWTPs). In order to establish a design and operational strategy for GHG mitigation, accurate estimates are essential. However, the existing approaches (e.g. the IPCC protocol and national greenhouse gas inventories) do not cover emissions from all sources in WWTPs and are not sufficient to predict facility-level emissions. The ultimate goal of this research was to improve the quantification of GHG emissions from WWTPs. This was accomplished by creating a new mathematical model based on an existing activated sludge model. The first part of the research proposed a stepwise methodology using elemental balances in order to derive stoichiometry for state variables used in a mass balance based whole-plant wastewater treatment plant model. The two main advantages of the elemental balance method are the inclusion of carbon dioxide (CO2) into the existing model with no mass loss and ease of tracking elemental pathways. The second part of the research developed an integrated model that includes (1) a direct emission model for onsite emissions from treatment processes and (2) an indirect emission model for offsite emissions caused by plant operation. A sensitivity analysis of the proposed model was conducted to identify key input parameters. An uncertainty analysis was also carried out using a Monte Carlo simulation, which provided an estimate of the potential variability in GHG estimations. Finally, in the third part, the research identified an optimal operational strategy that resulted in minimizing operating costs and GHG emission, while simultaneously treating the wastewater at better levels. To do this, an integrated performance index (IPI) was proposed to combine the three criteria. The IPI was then incorporated into an optimization algorithm. The results obtained in this research demonstrated that the variation of GHG emissions is significant across the range of practical operational conditions. With system optimization, however, WWTPs have the potential to reduce GHG emissions without raising operating costs or reducing effluent quality. Further research should include a mechanistic examination of processes that produce methane (CH4) in the wastewater treatment stream and nitrous oxide (N2O) in the sludge treatment stream.