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Quantitative microbial risk assessment (QMRA) is increasingly applied to estimate drinking water safety. In QMRA the risk of infection is calculated from pathogen concentrations in drinking water, water consumption and dose response relations. Pathogen concentrations in drinking water are generally low and monitoring provides little information for QMRA. Therefore pathogen concentrations are monitored in the raw water and reduction of pathogens by treatment is modelled stochastically with Monte Carlo simulations. The method was tested in a case study with Campylobacter monitoring data of rapid sand filtration and ozonation processes. This study showed that the currently applied method did not predict the monitoring data used for validation. Consequently the risk of infection was over estimated by one order of magnitude. An improved method for model validation was developed. It combines non-parametric bootstrapping with statistical extrapolation to rare events. Evaluation of the treatment model was improved by presenting monitoring data and modelling results in CCDF graphs, which focus on the occurrence of rare events. Apart from calculating the yearly average risk of infection, the model results were presented in FN curves. This allowed for evaluation of both the distribution of risk and the uncertainty associated with the assessment.

The decimal elimination capacity (DEC) of slow sand filtration (SSF) for Cryptosporidium parvum was assessed to enable quantitative microbial risk analysis of a drinking water production plant. A mature pilot plant filter of 2.56m(2) was loaded with C. parvum oocysts and two other persistent organisms as potential surrogates; spores of Clostridium perfringens (SCP) and the small-sized (4-7microm) centric diatom (SSCD) Stephanodiscus hantzschii. Highly persistent micro-organisms that are retained in slow sand filters are expected to accumulate and eventually break through the filter bed. To investigate this phenomenon, a dosing period of 100 days was applied with an extended filtrate monitoring period of 150 days using large-volume sampling. Based on the breakthrough curves the DEC of the filter bed for oocysts was high and calculated to be 4.7log. During the extended filtrate monitoring period the spatial distribution of the retained organisms in the filter bed was determined. These data showed little risk of accumulation of oocysts in mature filters most likely due to predation by zooplankton. The DEC for the two surrogates, SCP and SSCD, was 3.6 and 1.8log, respectively. On basis of differences in transport behaviour, but mainly because of the high persistence compared to the persistence of oocysts, it was concluded that both spores of sulphite-reducing clostridia (incl. SCP) and SSCD are unsuited for use as surrogates for oocyst removal by slow sand filters. Further research is necessary to elucidate the role of predation in Cryptosporidium removal and the fate of consumed oocysts.

To determine the disinfection efficacy of ozonation, water companies can apply several disinfection calculation methods. The goal of this study was to evaluate the use of the T10 and continuous stirred tank reactor (CSTR) method to extrapolate inactivation rates of ozone sensitive microorganisms observed in laboratory tests to full-scale ozonation in drinking water treatment. The inactivation efficacy of the ozonation at the Amsterdam water treatment works was assessed by determining Escherichia coli concentrations in large volume samples before and after ozonation over a period of 1 year. The inactivation of dosed E. coli WR1 was tested in a bench-scale dissolved ozone plug flow reactor (DOPFR) on the same feed water as the full-scale ozonation in which a concentrated ozone solution in Milli-Q water was dosed. Applying the T10 method on the inactivation rates observed in the DOPFR strongly overestimated the inactivation capacity of the full-scale ozonation. The expected inactivation based on the CSTR method (LT2ESWTR) approached the observed inactivation at full-scale. Therefore, the CSTR method should be preferred to calculate inactivation of ozone sensitive organisms such as E. coli, viruses, Giardia and Campylobacter by full-scale ozonation.