| Paper Title: | Statistical modelling AD for process optimization and bench-marking - A case study of E. coli inactivation across all Thames Water conventional sewage sludge treatment sites |
| Paper Topic: | Modelling & Control (Wastewater Systems) |
| Presenter Name: | Mr Jin Liu |
| Company/Organisation: | Imperial College London |
Paper Information :
Mesophilic anaerobic digestion (MAD) is the most-favoured process for sewage sludge treatment in the UK. It is a well-established approach to sludge stabilization, but the mechanisms responsible for pathogen removal are poorly understood. Operational data collected by Thames Water from conventional MAD sites were statistically scrutinised to examine the effects of primary and secondary digestion on the removal of the enteric indicator bacteria, Escherichia coli. The results showed that primary digestion conditions (specifically temperature) sublethally damaged E. coli and increased decay in secondary digestion and therefore over the whole digestion process. A similar analysis approach could be applied to the new big data analysis project jointly supported by five UK water companies for both pathogen reduction and biogas production optimisation.
