Water age in drinking water systems is often used as a proxy for water quality but is rarely used as a direct input in assessing microbial risk. This study directly linked water ages in a premise plumbing system to concentrations of Legionella pneumophila via a growth model. In turn, the L. pneumophila concentrations were used for a quantitative microbial risk assessment to calculate the associated probabilities of infection (Pinf) and clinically severe illness (Pcsi) due to showering. Risk reductions achieved by purging devices, which reduce water age, were also quantified. The median annual Pinf exceeded the commonly used 1 in 10,000 (10-4) risk benchmark in all scenarios, but the median annual Pcsi was always 1-3 orders of magnitude below 10-4. The median annual Pcsi was lower in homes with two occupants (4.7 × 10-7) than with one occupant (7.5 × 10-7) due to more frequent use of water fixtures, which reduced water ages. The median annual Pcsi for homes with one occupant was reduced by 39-43% with scheduled purging 1-2 times per day. Smart purging devices, which purge only after a certain period of nonuse, maintained these lower annual Pcsi values while reducing additional water consumption by 45-62%.

Higher water ages are linked with water quality decline as chlorine dissipates, temperatures become more favorable for microbial growth, and metals and organic matter leach from the pipes. Water fixtures with automated purging devices can limit water age in premise plumbing systems, but also increase water use. To develop purging strategies that lower age while also minimizing water use, the stochastic nature of water demands must be considered. In this research, a hydraulic plumbing network model, with stochastic demands at fixtures, was used to compare water age and water use for five purging conditions: purging at regular intervals, \"smart\" purging (considering the time of last use), purging with different volumes of water, purging at different fixtures, and the purging with different levels of home occupancy. Higher purging frequency and volume resulted in lower water ages, but higher water use. Purging greatly reduced the variability in water ages, avoiding extreme ages entirely. Water age was minimized by scheduling the purging around occupancy behavior, such as before the occupants wake up or return from work. Scheduled purging used more water than smart purging. Purging after 12 h of nonuse used only 55% of the additional water required for purging every 12 h. Purging after 24 h of nonuse at the kitchen tap and shower used only 38% of the additional water required for purging every 24 h, while maintaining lower water ages and removing the variability in water ages. While larger purging volumes had a greater impact on water age, there were diminishing returns. Purging has a larger impact on low-occupancy homes because fixtures have less frequent use. Overall, this research provides a methodology to compare purging strategies that minimize both water age and water use. While the numerical results presented here are only valid for the specific layout and usage habits, they provide insights and trends applicable to other cases.