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Estimating chloramine C × T for the synergistic inactivation of Cryptosporidium with ozone followed by chloramine
A statistical model was developed to account for the error in estimating the required chloramine concentration times time (C × T) to inactivate Cryptosporidium oocysts with ozone followed by chloramine in drinking water. Generally, either a modified in vitro excystation method or an animal infectivity method is used by researchers to investigate the inactivation kinetics of Cryptosporidium in sequential inactivation studies. Published data from three sequential inactivation studies were pooled to obtain a closed‐form formula for the required chloramine C × T to achieve a specified inactivation level of Cryptosporidium. In a previously published paper, a multiple linear regression analysis was used to calculate the required chloramine C × T using the same data in which uncertainties caused by factors such as lot variability and random error were not accounted for. This article proposes a mixed linear modeling approach that accounts for these uncertainties and thus generates higher C × T values than the values reported previously.
Estimating chloramine C × T for the synergistic inactivation of Cryptosporidium with ozone followed by chloramine
A statistical model was developed to account for the error in estimating the required chloramine concentration times time (C × T) to inactivate Cryptosporidium oocysts with ozone followed by chloramine in drinking water. Generally, either a modified in vitro excystation method or an animal infectivity method is used by researchers to investigate the inactivation kinetics of Cryptosporidium in sequential inactivation studies. Published data from three sequential inactivation studies were pooled to obtain a closed‐form formula for the required chloramine C × T to achieve a specified inactivation level of Cryptosporidium. In a previously published paper, a multiple linear regression analysis was used to calculate the required chloramine C × T using the same data in which uncertainties caused by factors such as lot variability and random error were not accounted for. This article proposes a mixed linear modeling approach that accounts for these uncertainties and thus generates higher C × T values than the values reported previously.
Estimating chloramine C × T for the synergistic inactivation of Cryptosporidium with ozone followed by chloramine
Sivaganesan, Mano (author)
Journal ‐ American Water Works Association ; 100 ; 120-125
2008-07-01
6 pages
Article (Journal)
Electronic Resource
English
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