Imperial College London
Alternate

ProfessorStephenSmith

Faculty of Engineering, Department of Civil and Environmental Engineering

Professor of Bioresource Systems
 
 
 
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Contact

 

+44 (0)20 7594 6051s.r.smith

 
 
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Assistant

 

Miss Judith Barritt +44 (0)20 7594 5967

 
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Location

 

229Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Liu:2017:10.1111/wej.12271,
author = {Liu, J and Gao, Y and Pearce, P and Shana, A and Smith, SR},
doi = {10.1111/wej.12271},
journal = {Water and Environment Journal},
pages = {498--507},
title = {Statistical modelling anaerobic digestion for process optimization and bench-marking: a case study of E. coli inactivation across all Thames Water conventional sewage sludge treatment sites},
url = {http://dx.doi.org/10.1111/wej.12271},
volume = {31},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Untreated sewage sludge potentially contains a wide range of enteric pathogens that present a risk to human health. Mesophilic anaerobic digestion (MAD) is the most-favoured process for sewage sludge treatment in the United Kingdom. It is a well-established approach to sludge stabilisation, 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, by using the IBM SPSS statistical software package for ANOVA, post-hoc and multiple regression analysis. The results showed that the process temperature conditions at the MAD plants were equivalent to or exceeded the minimum estimated by the analysis necessary to comply with the 2 log10 removal standard for E. coli. The results also showed that primary digestion conditions (specifically temperature) sublethally damaged E. coli and increased decay in secondary digestion and therefore over the whole digestion process.
AU  - Liu,J
AU  - Gao,Y
AU  - Pearce,P
AU  - Shana,A
AU  - Smith,SR
DO  - 10.1111/wej.12271
EP  - 507
PY  - 2017///
SN  - 1747-6593
SP  - 498
TI  - Statistical modelling anaerobic digestion for process optimization and bench-marking: a case study of E. coli inactivation across all Thames Water conventional sewage sludge treatment sites
T2  - Water and Environment Journal
UR  - http://dx.doi.org/10.1111/wej.12271
UR  - http://hdl.handle.net/10044/1/48509
VL  - 31
ER  -
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