Sewage is delivered to wastewater treatment plants (WWTPs) where benign microbial organisms within ‘activated sludge’ vessels contribute to the removal of harmful pathogens from the sewage. The activity and pathogen-removing ability of these helpful organisms is affected by many factors including temperature, numbers of fine particles, pH, ammonia, and the time available to remove the pathogens. Regulatory authorities require at least 90% (one log removal value, LRV) of the pathogens to be removed, but as WWTP operating conditions vary, the LRVs change. This problem led to recognition of the need to develop models capable of predicting relationships between plant operating parameters (such as temperature) and pathogen removal. This research reviewed published reports and datasets, then set up and ran an experimental activated sludge pilot plant to generate data about a range of operating conditions and pathogen removals. These datasets were used to develop models which had only a ‘poor’ predictive value for clostridia but were ‘good’ for giardia and ‘very good to excellent’ for the removal of other pathogens. These models need to be extended with more operating conditions but have the potential to be used to attribute LRVs and for future integration into online real-time monitoring.

E. coli bacteria naturally populate the gastrointestinal tract of humans and animals; they are usually harmless and are commonly excreted. Faeces can also contain harmful microscopic pathogens, and this has led to the assumption that if harmless E. coli are found in water, that the drinking water has been contaminated with faeces that might also have contained pathogens that pose a risk to public health. Using E. coli as an indicator of faecal contamination was recently challenged by the finding that some E. coli strains live, grow and bloom in the environment, and their presence in water might not mean that the water has been contaminated with harmful pathogens. This research examined the environmental conditions associated with E. coli bloom formation in the context of climate-change adaptation and developed multiplex PCR tests which allow the identification of environmental and faecal E. coli. This information was added to a Utility Response Protocol.

Cyanobacterial blooms in surface waters are a source of cells, taste and odour compounds, and a range of toxins. This research optimised treatment processes for the removal and control of cyanobacteria and their metabolites from a range of source waters. It was concluded that pre-chlorination is not advisable when cyanobacteria are present, but that in some situation’s potassium permanganate is a viable alternative. Although all three tested coagulants; ferric chloride, aluminium chlorohydrate and aluminium sulphate (alum) removed 90 to 95% of cells, alum at pH 6.3 was the most cost-effective. Maintaining pH > 6 reduced cell lysis and metabolite release. Since cyanobacteria in sludge remained viable for 2-3 weeks it was recommended that sludge detention in the clarifiers should be minimised.

Cyanobacterial blooms are a major problem for reservoir managers because of the large numbers of cells and the toxins they contain. These blue-green algae blooms have traditionally been treated with the algaecide copper sulphate, but this was expensive and unsustainable because it killed non-target species and left residual contaminants. This research examined and rejected alternatives: other copper-based algaecides, hydrogen peroxide, substances that trap cyanobacterial-growth supporting nutrients on the floor of the reservoir, and mechanical surface mixers. Laboratory experiments that tested the ability of ultrasound to prevent the photosynthetic cyanobacteria from floating at the depth that optimises light absorption were initially promising because the ultrasound reduced photosynthesis and metabolism and the blue-green algae died. Unfortunately, when an ultrasound system was deployed in a reservoir, the much larger volume of water attenuated and ‘absorbed’ the low-power ultrasound and led to the conclusion that sustainable, environmentally friendly levels of ultrasound do not provide effective control of blue-green algae. This rigorously conducted scientific study has generated useful information about methods which do not work, and resources can now be directed to promising new innovations.