Grant: Discovery Grants Program - Individual

The proposed research program explores the role of wastewater in addressing two of the most significant challenges facing society, namely the threats of respiratory viruses and climate change. Wastewater surveillance is now an accepted approach for monitoring the prevalence of viral diseases in society. However, there remain many open questions regarding the transport and decay of viral material within sewer systems. This research seeks to better understand the decay kinetics of viruses in wastewater using lab-scale experiments and modelling. New decay models will be incorporated into sewer hydraulic models, which will allow us to calculate the distribution of virus in response to various viral shedding scenarios. Some of the outcomes of this work are an improved ability to estimate the number of cases at a given time and the ability to model and correct for peak flow events due to high stormwater flows or snow melt. The conveyance and treatment of wastewater is responsible for a significant amount of greenhouse gas (GHG) emissions, especially when process emissions of methane and nitrous oxide are considered. Both are potent GHGs with global warming potentials of 25 and 265 times that of carbon dioxide, respectively. This research program seeks to better understand and model methane emissions in sewers and nitrous oxide emissions in biological treatment processes. With these models, one can optimize the processes with the goal of minimizing GHG emissions. This research also explores modelling wastewater treatment using photosynthetic microorganisms such as microalgae. Since these microorganisms consume carbon dioxide, they have the potential to enable carbon-negative wastewater treatment processes when end products that can store carbon over long periods are produced from the process biomass. Computational models of photobioreactors, which are specialized reactors used to cultivate photosynthetic microorganisms, will be developed and used to improve their efficiency. Modelling of wastewater treatment processes will employ computational fluid dynamics (CFD) methods. Novel approaches for reducing complexity of CFD simulations, including compartmental models derived using machine learning techniques will be explored. The proposed research will make progress toward improving quality of life for Canadians by reducing the burden of illness, through improved knowledge of respiratory virus prevalence, and by providing solutions for our significant GHG emissions. New knowledge regarding the transport of sediment and gases in sewer systems will be developed, which can benefit the design of wastewater collection systems. A better understanding of gas-liquid mass transfer in contaminated water matrices will be developed through the work on both activated sludge and photobioreactors; this knowledge can be applied in a wide range of process engineering applications where a gas is introduced into a reactor.