Journal article
Statistics of Microbial Disinfection
Water science and technology, v 21(3), pp 197-201
01 Mar 1989
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Engineering adequate disinfection processes and assessing risks associated with various disinfection options requires knowledge of kinetics of microbial inactivation as a function of design variables (e.g., dose, contact time). Often such information is obtained in batch studies and extrapolated to design conditions. By Monte Carlo techniques, we have shown that the use of a direct maximum likelihood evaluation for two types of data normally encountered, counts (PFU or CFU) and dilution experiments (MPN), leads to estimates of microbial inactivation rate parameters having lower bias and variance than other data reduction normally employed. This paper reviews the methodology of this technique and provides the theory for the computation of confidence limits for parameter estimates, and discusses how the data may be checked for consistency (goodness of fit determination).
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Details
- Title
- Statistics of Microbial Disinfection
- Creators
- Charles N. Haas - Illinois Institute of TechnologyBarbara Heller - Illinois Institute of Technology
- Publication Details
- Water science and technology, v 21(3), pp 197-201
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:A1989AE28300030
- Scopus ID
- 2-s2.0-0024399896
- Other Identifier
- 991019189026704721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Environmental
- Environmental Sciences
- Water Resources