Characterising the Functional Microbial Ecology of Slow Sand Filters Through
Environmental Genomics
Sarah-Jane Haig
Today the water industry faces a huge challenge in supplying a sustainable, energy efficient
and safe supply of drinking water to an increasing world population. Slow sand filters (SSFs)
have been used for hundreds of years to provide a safe and reliable source of potable drinking
water, with minimal energy requirements. However, a lack of knowledge pertaining to the
treatment mechanisms, particularly the biological processes, underpinning SSF operation, has
meant SSFs are still operated as “black boxes”. This lack of knowledge pertaining to the
underlying ecology and ecophysiology limits the design and optimisation of SSFs.
This thesis represents the most comprehensive microbial community survey of full-scale
SSFs to-date. Using traditional microbiological methods alongside up-to-date molecular
techniques and extensive water quality analyses, specific taxa and community metrics are
linked to changes in water quality production. Furthermore, it has been verified that
laboratory- scale SSFs can mimic the microbial community and water quality production of
full-scale filters. This allowed rigorous experiments pertaining to operational differences,
pathogen and novel contaminant removal to be performed. This has revealed, for the first
time, that multiple trophic interactions within SSFs are integral to optimal performance.
This thesis has shown that SSFs are phylogenetically and metabolically diverse systems
capable of producing high quality water, with the ability to adapt to remove novel
contaminants. Using the information gathered, improvements to filter maintenance and
operation can be achieved. Future work will apply the microbial and macrobial community
dynamics and impact of novel contaminants on filter performance discovered in this thesis
into predictive models for water quality.