• AWWA ACE70606

AWWA ACE70606

Estimating the Risk of Virus Intrusion into the Distribution System

American Water Works Association , 11/01/2009

Publisher: AWWA

File Format: PDF

$12.00$24.00


Low pressure transients can be mechanisms for intrusion of microbial contaminants into the distribution system. Prior research has demonstrated episodes of negative pressure (-16 psi) in drinking water systems following planned or unplanned pump shutdowns. This poster paper models the risk of infection from these negative pressure events and evaluates mitigation options. A quantitative microbial risk assessment (QMRA) model developed estimates of norovirus and rotavirus concentrations in untreated sewage based on a Monte Carlo analysis of censored published values. The volume of sewage that could intrude into the system was based on a logarithmic distribution of the duration of negative pressure transients and an estimate of the distribution leakage. The dilution of the intrusion volume was calculated based on the distribution of flow in the system and resulted in an estimation of the final virus concentration. Dose response data for norovirus and rotavirus along with known estimates of water consumption were used to estimate the risk of infection based on the distribution of customers (demand) within the system. Sensitivity analysis showed that the coincidence of consumption (the probability of consuming the slug of contaminated water) has the strongest influence on risk and was related to the duration of the negative pressure event. Estimates of the disinfectant demand due to the intruded diluted sewage, and virus inactivation, showed that maintenance of free chlorine residuals nearly eliminated the risk, but viruses persisted for more than 24 hours in chloraminated systems. A single event in an undisinfected system could pose significant risk (>1/10,000 annual risk of infection), but data on electrical power interruptions showed that pump shutdowns could happen as frequently as once per month. Overall the QMRA model was useful for organizing known data, estimating data gaps, and testing hypotheses for future research.

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