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Theoretical considerations and modeling of chemical inactivation of microorganisms: inactivation of Giardia Cysts by free chlorine.

作者信息

Fernando W J N

机构信息

School of Chemical Engineering, Universiti Sains Malaysia, Seri Ampangan, 14300, Nibong Tebal, Pulau Pinang, Malaysia.

出版信息

J Theor Biol. 2009 Jul 21;259(2):297-303. doi: 10.1016/j.jtbi.2009.03.026. Epub 2009 Mar 29.

Abstract

Chemical inactivation of microorganisms is a common process widely employed in many fields such as in treatment of water, preservation in food industry and antimicrobial treatments in healthcare. For economy of applications and efficiency of treatment establishment the minimum dosage of breakpoint in the chemical application becomes essential. Even though experimental investigations have been extensive, theoretical understanding of such processes are demanding. Commonly employed theoretical analyses for the inactivation of microorganisms and depletion of chemicals include kinetics expressing the rates of depletion of chemical and microorganisms. The terms chemical demand (x) and specific disinfectant demand (alpha) are often used in theoretical modeling of inactivation. The value of specific disinfectant demand (alpha) has always been assumed to be a constant in these models. Intracellular concentration built up within the cells of the microorganisms during inactivation could lead to possible weakening effects of microorganisms thereby requiring lower doses as disinfection proceeds makes the assumption of constant alpha inaccurate. Model equations are formulated based on these observations co-relating the parameters alpha and x with a progressive inactivation (N/N(0)). The chemical concentration (C) is also presented in terms of the inactivation time (t) and the survival ratio (N/N(0)) for given pH and temperature conditions. The model is examined using experimentally verified Ct data of Giardia Cysts/chlorine system. The respective values of x for different survival ratios were evaluated from the data using MatLab software. Proposed model correlating for the disinfectant demand (x) with the survival ratio (N/N(0)) fits satisfactorily with those evaluated from data. The rate constants for different pH and temperature conditions are evaluated which showed compatibility with the Arrhenius model. The dependence of frequency factors with pH indicated compatibility with accepted models. The Ct values regenerated with the kinetic data shows a very accurate fit with published data.

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