Literature DB >> 20873864

Disinfection model based on excess inactivation sites: implications for linear disinfection curves and the Chick-Watson dilution coefficient.

James N Jensen1.   

Abstract

Current disinfection models generally are either empirical modifications of Chick's law (linear survivor curves) or hit or site models modified from the radiation literature. In this paper, a general disinfection model is developed that assumes a large number of inactivation sites. From a probabilistic model of damaged site distribution, the normalized number of surviving organisms is described as the cumulative distribution function (cdf) of the normal distribution, with the independent variable equal to a measure of damage and the mean and variance equal and determined by dose-response submodels. Submodels were developed for chemical disinfectants without disinfectant demand, ultraviolet radiation, and chemical disinfectants with first-order disinfectant demand. This infinite site model reproduces linear, shouldering, and tailing survivor curves from literature data. In addition, it predicts Chick-Watson dilution coefficients in the range observed in the literature. The infinite site model offers the interpretation that linear, shoulder, tailing, and biphasic survivor curves and the apparent Chick-Watson dilution coefficient are ramifications of the normal cdf, rather than mechanistic laws.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20873864     DOI: 10.1021/es101818z

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  3 in total

Review 1.  Microbial Contamination of Drinking Water and Human Health from Community Water Systems.

Authors:  Nicholas J Ashbolt
Journal:  Curr Environ Health Rep       Date:  2015-03

2.  In vitro Susceptibility to β-Lactam Antibiotics and Viability of Neisseria gonorrhoeae Strains Producing Plasmid-Mediated Broad- and Extended-Spectrum β-Lactamases.

Authors:  Ilya Kandinov; Dmitry Gryadunov; Alexandra Vinokurova; Olga Antonova; Alexey Kubanov; Victoria Solomka; Julia Shagabieva; Dmitry Deryabin; Boris Shaskolskiy
Journal:  Front Microbiol       Date:  2022-06-20       Impact factor: 6.064

3.  Enumerating viable phytoplankton using a culture-based Most Probable Number assay following ultraviolet-C treatment.

Authors:  Hugh L MacIntyre; John J Cullen; Trina J Whitsitt; Brian Petri
Journal:  J Appl Phycol       Date:  2017-09-25       Impact factor: 3.215

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.