Including operational data in QMRA model: development and impact of model inputs

Abstract

A Monte Carlo model, based on the Quantitative Microbial Risk Analysis approach (QMRA), has been developed to assess the relative risks of infection associated with the presence of Cryptosporidium and Giardia in drinking water. The impact of various approaches for modelling the initial parameters of the model on the final risk assessments is evaluated. The Monte Carlo simulations that we performed showed that the occurrence of parasites in raw water was best described by a mixed distribution: log-Normal for concentrations . detection limit (DL), and a uniform distribution for concentrations , DL. The selection of process performance distributions for modelling the performance of treatment (filtration and ozonation) influences the estimated risks significantly. The mean annual risks for conventional treatment are: 1.97E 2 03 (removal credit adjusted by log parasite ¼ log spores), 1.58E 2 05 (log parasite ¼ 1.7 £ log spores) or 9.33E 2 03 (regulatory credits based on the turbidity measurement in filtered water). Using full scale validated SCADA data, the simplified calculation of CT performed at the plant was shown to largely underestimate the risk relative to a more detailed CT calculation, which takes into consideration the downtime and system failure events identified at the plant (1.46E 2 03 vs. 3.93E 2 02 for the mean risk).

Global Distribution, Public Health and Clinical Impact of the Protozoan PathogenCryptosporidium

“…The QMRA model was recently applied to assess the relative risks of infection associated with the presence of Cryptosporidium and Giardia in drinking water in Canada [152]. The assessment of the final risk in the contamination of the water plants resulted considerably affected by the selection of treatment performance model (filtration and ozonation).…”

Application of Quantitative Microbial Risk Assessment at 17 Canadian Water Treatment Facilities

“…To conduct risk calculations, it is assumed that all pathogens are infectious; recoveries of Cryptosporidium and Giardia are 40% and 69%, respectively (Jaidi et al 2009); and that 1 L of unboiled water is consumed per person per day (Health Canada 2012). Protozoan data were recovery‐corrected before entering (oo)cyst concentrations into the model.…”

“…The dose of ingested organisms (D) is calculated for each pathogen according to Eq 4, where C SW represents the concentration of microorganisms in the source water, R the recovery of the analytical method, I fraction the infectious fraction, and V the volume of unboiled water ingested daily. To conduct risk calculations, it is assumed that all pathogens are infectious; recoveries of Cryptosporidium and Giardia are 40% and 69%, respectively (Jaidi et al 2009); and that 1 L of unboiled water is consumed per person per day (Health Canada 2012). Protozoan data were recovery-corrected before entering (oo)cyst concentrations into the model.…”

Microbial risk assessment for recreational use of the Chicago Area Waterway System

“…In the past, MRA has been used to assess the risks from microorganisms in drinking water (Haas 1983;Regli et al 1991;Jaidi et al 2009). In addition, MRA methodology to assess microbial risks for a variety of activities and microorganisms has been studied Haas et al 1996;Crabtree et al 1997;Haas et al 1999;Pouillot et al 2004) and used by the US EPA and international agencies such as World Health Organization (Parkin 2008) to quantitatively assess the health risks during use of recreational waters that receive effluent discharges (Soller et al 2003).…”

“…The probabilistic approach (one-dimensional, based on both variability and uncertainty) selected for this risk impact analysis is Monte Carlo simulation using Crystal Ball s Pro software operating on a personal computer (Jaidi et al 2009). …”