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As part of the Long-Term 2 Enhanced Surface Water Treatment Rule (LT2ESWTR), the United States Environmental Protection Agency (USEPA) is in the process of developing a "CT" table for the inactivation of Cryptosporidium with ozone at drinking water treatment plants. The common approach to developing a Ct table includes two primary steps (Clark et al., 2002): fitting available data with a microbial inactivation model to determine the value of the model parameter; and, the use of statistical analysis to develop an uncertainty factor that would then be applied to the CT values calculated by the model. The need for the uncertainty factor is driven primarily by the observation that significant scatter in the inactivation results exists. How the variability is applied, and the sources of that variability, are two critical contributors to this analysis. Clark et al. (2002) described the modeling approach, and presented one approach for determining the value of the uncertainty factor. As a compliment to the statistical analysis of Clark et al. (2002), the USEPA is exploring a modified approach that attempts to delineate between the scatter resulting from the uncertainty in the value of the model parameter itself, and that resulting from experimental and analytical errors inherent to the methods used experimentally. The variation in the model parameter value is primarily caused by unpredictable effects of water matrix and variability in oocyst resistance to the disinfectant. It is important to note that when ozone inactivation is applied in full scale treatment plants, the variability due to analytical and experimental errors will not be a factor. The variability observed due to uncertainty in the disinfection parameter, K10, will be a factor in the full-scale inactivation processes. Therefore, it follows that the uncertainty factor should be limited to one that captures the uncertainty in the model parameter value, but excludes the error caused by the experimental and analytical methods used in the inactivation experiments. This paper presents an approach for partitioning the overall variability into the two types of errors. Using the data presented by Oppenheimer et al. (2000), the authors partitioned the variability in the data set and calculated the percent of the variability due to analytical and experimental error and that portion of the variability due to differences in water matrices and oocyst resistance to the disinfectant. This document details how this task was conducted and presents its outcome. As noted in the introductory section, the development of the Ct table is comprised of two steps. The first is the determination of the value of the kinetic model parameter as a function of water temperature, and the second is the development of an uncertainty factor. Includes 6 references, tables, figures.

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Edition: Vol. - No. Published: 09/22/2002 Number of Pages: 12File Size: 1 file , 310 KB