Design WWTPs with Minimal N2O Emissions and Best Effluent Quality

Abstract: Two WWTPs, one in Sweden currently in the final design stage, and one in The Netherlands undergoing a renovation plan, are making use of the integration of mechanistic activated sludge models for biological wastewater treatment with Computational Fluid Dynamics (CFD) to understand the effect of operational and design changes. INTRODUCTION Designing wastewater treatment plants (WWTPs) with the goal of minimizing nitrous oxide (N2O) emissions in addition to ensuring the required effluent quality is the latest objective to assure utilities and global population's sustainable future. N2O emissions from WWTPs can be minimized implementing advanced operational strategies that promote efficient nitrogen removal while minimizing N2O production. The complexity of N2O formation in bioreactors makes it difficult to use general guidelines for measurements and mitigation. In addition to this, the root causes of N2O formation cannot be understood by only measuring more. Integrating sensors with mechanistic models can be much more informative (Domingo-Félez and Smets, 2019). This allows tailoring effective mitigation strategies along with industry-wide learning. Mechanistic models are well established in the biological water treatment sector and can be used to accelerate decisions on both placement of N2O sensors and N2O mitigation itself. In this work, mechanistic activated sludge models for biological wastewater treatment integrated with Computational Fluid Dynamics (CFD) were used to understand the effect of operational and design changes of a bioreactor in two WWTPs: One currently in the final design stage in Sweden, and one undergoing a renovation plan in The Netherlands. METHODS The WWTP in Sweden will be built for removal of N and P and is configured as a sequence of treatment steps separated by baffles with the possibility of directing the influent stream in four points of the treatment train at the same time depending on the influent flow and concentrations (Figure 1, top). The WWTP in The Netherlands is a carrousel configuration with pre-denitrification in need of revamping to make sure the treatment capacity is improved for coping with future effluent requirements. The hydraulic model used for the CFD simulations was a 2-phase Eulerian model (air-liquid). The oxygen mass transfer from gas to liquid was modelled according to the Henry's equilibrium considering temperature and pressure, and the relative equilibrium concentration between the phases in presence of the biological activity. The biological activity was modelled via the ASM-N2O developed by AM-Team from the available literature (inter alia: Bellandi, 2018, Guo, 2014; Hiatt and Grady, 2008; Peng et al., 2015; Spérandio et al., 2016). RESULTS The WWTP in Sweden was modelled in several operational scenarios including dry and wet weather conditions. In Figure 1 are reported the N2O emissions in the gas phase as a result of the biological activity treating a flow expected in the short -term operation (2027) and in the long term (2025) considering population growth. Increasing influent flow and concentrations can result in increasing emissions in the long-term (Figure 1, bottom), therefore, plant operation needs to adapt to changing environmental and social conditions. For the Dutch plant, the integrated simulation CFD-biokinetics helped understanding the limitations of the current design (Figure 2, top), and to explore practical solutions of new design changes (Figure 2, bottom) while keeping a close look at the implications in terms of effluent quality and N2O emissions. Conclusions As there are no unique solutions for reducing N2O emission from water treatment, tailored mitigation strategies should be designed for each plant to be effective across the whole operational domain. The integration of CFD-biokinetics allows to test and refine design changes by simulating their direct effect on both the effluent quality and the N2O emissions. The WWTP in Sweden is currently being simulated with an extended scenario set to understand operational alternatives as well as best location for monitoring emissions. Anticipating design improvement is the key for achieving fast and deep understanding of bioreactor's potential in achieving the best effluent quality with minimal N2O emissions. Thinking of the three Es (Energy, Effluent, Emissions) already at the design stage is now possible with simulation tools.