This scholarship aims to identify hotspots for mitigation of N2O emissions. N2O is emitted in nature during biological nitrogen removal and is produced by a consortium of microbes. When our current understanding of the biological processes is captured in mathematical models our prediction power becomes substantial. Process models for N2O describe, mechanistically, the key metabolic interactions driving N2O emissions, which are common across all the WWT technologies in Scotland. The benefits of mathematical modelling also include reducing the number of expensive monitoring campaigns across the almost two thousand WWTWs across Scotland.
The core biokinetic process model will include the metabolic reactions of autotrophic nitrifying and heterotrophic denitrifying communities, and liquid-to-gas mass-transfer of N2O. Model calibration will be carried out using a Bayesian approach including Markov Chain Monte Carlo algorithms. Model evaluations are carried out using full-scale measurements. The model will subsequently explored for individual scenario analysis to identify best- and worst-case operational conditions. Matlab® and Simulink® simulation software as well as Python tools will be developed.
Model structures will be reduced or expanded based on experimental observations and identifiability considerations. For example, trickling filters are ubiquitous and require a biofilm model to predict bacterial growth attached to the support material. The additional complexity of this geometry will only be considered based on identifiability metrics. For decentralised systems in rural communities with low data availability more simple statistical methods will be considered.
To obtain an accurate baseline value of the N2O emissions of a WWTW we need to capture the daily and seasonal patterns of municipal water use. The intrinsic dynamics of wastewater characteristics are monitored by WWTWs and are necessary inputs for model calibration. A setup to monitor full-scale and lab-scale N2O concentrations is available at the University of Glasgow. Short intensive campaigns for chemical analysis of WW components in the influent and effluent will be performed.
Within the University of Glasgow, in the James Watt School of Engineering, the project lies within the Water and Environment research group, including eight PIs (two RAEng research chairs, a RAEng early career research fellow), 15 PhDs and 13 PDRA. In recognition of their achievements and funding success, the Water and Environment group is located in the recently inaugurated Advanced Research Centre. The supervisory team has ample experience on N2O emissions, project supervision and project management.
Applicants are strongly advised to make an informal enquiry about the PhD to the primary supervisor well before the final submission deadline.
Applicants must send a completed Hydro Nation Scholarship application form and their Curriculum Vitae to Dr. Carlos Domingo-Felez (Carlos.Domingo-Felez@glasgow.ac.uk) by the final submission deadline of 10th January 2024.
The candidate must have a degree in environmental, chemical or biochemical related discipline, as well as excellent written and spoken communication skills. Previous experience with scientific programming (e.g. Matlab, Python, R) and/or bioreactor operation is also desirable but not essential. Candidates must be highly numerate and be willing to study any previously unknown underpinning areas of science that are required.