本powerpoint演示文稿首先简要概述了风险分析和敏感性分析。研究目的是:开发QMRA蒙特卡罗模型，以评估 与隐孢子虫和 饮用水中的贾第虫， 之前:包括SCADA数据， 现在:开发CT模型来评估臭氧氧化性能； 根据微生物风险比较不同的治疗方案 减少 评估停药期对患者的影响 估计风险； 和 完成敏感性分析，以评估 响应模型上每个输入参数的可变性 （风险）。方法论 目标包括: 使用植物A和B的组合数据来表示 污染源； 扩大臭氧氧化模型的适用范围； 验证流程中一个流程停机的影响 多重障碍的情况； 证明存在多重障碍是合理的； 完成敏感性分析以评估影响 响应模型上每个输入参数的 根据他们的敏感程度对他们进行分类；和 敏感性分析是决策的关键步骤 关于建设和发展的决定 QMRA模型的改进。演示结论表明:在正常运行和 各种处理工艺的临时停工期； 紫外线消毒性能大大降低了微生物风险， 比优化直接过滤更重要；紫外线的平均风险是， 但是，受停堆期（不是第90个）的显著影响 百分位）； 风险评估中必须包括允许的停机时间， 尤其是当只有一个障碍存在时；对于这种情况，敏感性分析确定了 风险估计差异的主要来源。 这些输入的不确定性应该是至关重要的 对于已审核的: 更好地估计原水中寄生虫的发生，剂量反应 感染性卵囊的关系和比例； 将孢子去除作为指标的全面验证 去除寄生虫的方法；和 评估移除或移除之间的相关性 寄生虫的灭活及其浓度。包括数字。

This powerpoint presentation begins by providing a brief overview of risk analysis and sensitivity analysis. Study objectives were to: develop a QMRA Monte Carlo model to assess the relative risk of infection associated with the presence of Cryptosporidium and Giardia in drinking water, Before: Including SCADA data, Now : Developing a CT model to evaluate ozonation performance; compare different treatment scenarios based on microbial risk reduction; assess the impact of treatment shutdown periods on the estimated risk; and, complete a sensitivity analysis to estimate the effect of the variability of each input parameter on the response's model (risk). Methodology objectives included: using combined data of plants A and B to represent the source contamination; broadening the applicability of the ozonation model; verifying the impact of one process downtime in the case of multiple barriers; justifying the presence of multiple barriers; completing sensitivity analysis to estimate the effect of each input parameter on the response model and to classify them according to their degree of sensibility; and, sensitivity analysis is a key step in making decisions concerning construction and improvement of the QMRA model. Presentation conclusions indicate the following: multi-barriers minimize the overall risk during normal operation and temporary shutdown periods of various treatment processes; UV disinfection performance considerably reduces microbial risk, more so than optimizing direct filtration; mean risk with UV is, however, significantly influenced by shutdown periods (not 90th percentile); allowed downtime duration must be included in risk assessment, especially when only one barrier is present; and, for this case, the sensitivity analysis identified the main sources of variance of the risk estimates. The uncertainty on these inputs should be critically reviewed for: a better estimation of parasite occurrence in raw water, dose-response relationship and fraction of infectious oocysts; a full-scale validation of the use of spore removal as an indicator of parasite removal; and, an assessment of the correlation between the removal or inactivation of parasites and their concentration. Includes figures.