Modeling
Evaluating the impact of extreme weather events on biological wastewater treatment processes using modeling
Climate change is increasing the frequency of intense wet weather, placing considerable stress on wastewater treatment plants. The surge in high-flow events threatens to push operational plant capacities to their limits, particularly for older infrastructure. This will potentially also lead to biomass loss from biological treatment processes and even plant malfunctions. Current models often struggle to predict these transient high flows due to their sporadic occurrence and limited data. To address this, we are developing predictive models specifically designed to capture high flows. These models leverage monitoring data from routine plant operations and apply extreme value analysis to focus on the high-flow variations. This approach helps the model focus on these critical flows which are hoped to provide a more precise prediction of high-impact flows. By tailoring models to capture such irregularities, we aim to improve the ability of models to forecast and respond to extreme flows, thereby reducing the risk of overflows and operational strain.
We are also developing resilience-oriented process models and life cycle assessment (LCA) models of wet weather management strategies. Resilience-oriented process models are calibrated with data from facilities with strict nitrogen discharge requirements. By simulating how these technologies can manage wet weather surges while optimizing existing infrastructure, these models provide valuable insights into treatment resilience under varying conditions. LCA models of wet weather management strategies will evaluate trade-offs between system resiliency and other outputs such as increased energy demands, higher chemical use, potential GHG emissions, and the risk of discharging partially treated water. This analysis is vital for developing wet weather management practices that align with long-term environmental objectives.
Researcher
- Isaac Musaazi
Funding
- National Science Foundation
Collaborators
- Lauren Stadler
- Li Liu
- Andrew Shaw
Quorum sensing in MABR
Novel and Sustainable Nitrogen Removal in Wastewater using MABR
Nutrient removal in wastewater treatment is essential for mitigating water pollution, protecting aquatic ecosystems, and meeting regulatory standards that are becoming stricter nowadays. Excess nutrients—primarily nitrogen and phosphorus—from untreated or inadequately treated wastewater can lead to environmental problems like eutrophication, which depletes oxygen in water bodies, disrupts ecosystems, and promotes the growth of harmful algal blooms.
Currently the traditional nitrogen removal processes are widely applied in municipal and industrial wastewater treatment, however, often in separate tanks, which demands land and space. In addition, during the denitrification stage, additional organic compounds (e.g., acetate) need to be added to provide heterotrophic denitrifying organisms with carbon source, which increases the carbon footprint of wastewater treatment plants (WWTPs). The membrane aerated biofilm reactor (MABR) is an emerging and advanced technology for nitrogen removal, where oxygen diffuses from inside of gas permeable membranes to the bulk liquid. It is easier to control oxygen load and diffusion in MABR, which makes efficient and simultaneous nitrification and denitrification possible.
Researcher
- Yuchen Zhang
Quorum sensing in Nitrogen cycle
Functional and transcriptional effects of autoinducers on rate of nitrogen transformation
Nitrification, driven by ammonia-oxidizing and nitrite oxidizing bacteria/archaea, is a crucial step in nitrogen cycle for ammonia and nitrite oxidation respectively. However, lengthy startups of biological nutrient removal due to slow growing nitrifying communities could be energy intensive and rate-limiting step for wastewater treatment systems. Quorum sensing (QS) based microbial interactions emerge as a promising strategy for bioreactors to accelerate the start-up and overcome challenges arising from insufficient microbial aggregates.
The current project focuses on the ecological role of QS mediated autoinducers (AIs) in shaping nitrifying communities and their performance via quantifying the transcription of various downstream genes, metabolic activities, and taxonomic composition. New insights will be provided for potential nitrifying mechanism by interlinking the AIs level with the functional genes including ammonia monooxygenase (amoA), nitrite oxidoreductase (nxrA), hydroxylamine oxidoreductase (Hao), nitrite reductase (nirK), etc.
Researcher
- Hira Waheed
Funding
- National Science Foundation