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Quantification of uncertainty in microbial data - reporting and regulatory implications

机译:量化微生物数据中的不确定性-报告和法规含义

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摘要

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.
机译:微生物污染物的法规通常与化学污染物的法规不同。微生物是通过经常容易遭受重大损失,导致回收率差异很大的技术来列举的。因此,针对微生物处理已经发展了几种基于处理技术的法规。但是,即使这些法规最终也需要一定程度地依赖微生物浓度数据。已经开发了统计方法来计算处理过程中微生物浓度和清除的置信区间,这些方法考虑了与微生物计数有关的各种误差。这些方法在此处用于证明方法错误与需要连续和/或频繁监测的基于浓度的法规的实用性之间的关系,表明基于处理技术的法规(如“长期2强化地表水处理规则”)的必要性,证明通过增加生物数量而不是通过改善方法回收率可以大大减少方法学不确定性,并提出了大约10种或更多生物体的采样目标,以显着降低与微生物定量相关的不确定性。

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