Quantification of uncertainty in microbial data—reporting and regulatory implications

Abstract

Microbial contaminants are often regulated differently than chemical contaminants. Microorganisms are enumerated by techniques that are frequently susceptible to considerable losses, resulting in highly variable recoveries. Accordingly, several treatment technique‐based regulations have evolved for microbial treatment. However, even these regulations ultimately require some reliance on microbial concentration data. Statistical approaches have been developed for the calculation of confidence intervals for microbial concentrations and removals by treatment processes, and these approaches take into account the various errors associated with microbial enumeration. The approaches were used here to demonstrate the relationship between methodological error and the practicality of concentration‐based regulations that require continuous and/or frequent monitoring, demonstrate the necessity of treatment technique‐based regulations such as the Long Term 2 Enhanced Surface Water Treatment Rule, demonstrate that methodological uncertainty is more substantially reduced by increasing organism count than by improving methodological recovery, and propose sampling targets of approximately 10 or more organisms to appreciably reduce the uncertainty associated with microbial quantification