New developments in premise plumbing: Integrative hydraulic and water quality modeling

Abstract

Significant seasonal changes in chemical and microbiological water quality can occur in buildings at different fixture locations due to temperature and time dependent reaction rates. Here, a series of calibrated plumbing hydraulic‐water quality models were developed for the extensively monitored Retrofitted Net‐zero Energy, Water & Waste (ReNEWW) house in West Lafayette, Indiana, USA. The eight new models predict the absolute level of free chlorine, total trihalomethanes, copper, iron, lead, NO3− (nitrate‐nitrogen), heterotrophic plate count (HPC), and Legionella spp. concentration at each fixture for plumbing use, operational characteristics, and design layouts of the plumbing system. Model development revealed that the carrying capacity to describe Legionella spp. growth (and other organisms) under water usage and plumbing design conditions is lacking in the literature. Reducing simulated building water use by 25% prompted increased absolute concentrations of HPC and Legionella spp., each increasing by a factor of about 105. When the simulated service line length was increased, Legionella spp. concentrations increased by up to 106 gene copies /L in the Summer season. The proposed modeling framework can be used to support better planning, design, analysis, and operational decision‐making.

Characterizing stochastic water age in premise plumbing systems using conventional and advanced statistical tools

“…The results could differ for different homes, though the trends of reduced occupancy having a larger impact on water age than low flow devices are expected to hold, given the above discussion. Also, while simulated demands were used in this study, the same approach could be used for actual water demands and plumbing layouts, if known, as was done by Palmegiani et al 33 Although the water age trends were consistent across the analyses, examining the water age return period and the exceedance probabilities allows researchers to quantify the likelihood of a high water age event and make more informed decisions. This approach provides a way to compare different homes, plumbing systems, or water use scenarios, all of which can help inform decisions to maintain water quality.…”

“…Finally, we illustrate how the approaches can be used to assess the impact of the magnitude of water demands (i.e., scaling up or down the amount of water used as if with low flow fixtures) and the impact of home occupancy (i.e., the number of people in the home) to provide new insights on the relationship between water usage and water age. Although the examples are developed based on demand generators, a similar approach could be used if demands were known from actual demand monitoring, as was done by Palmegiani et al 33 This novel proposed approach can be used to investigate the impacts of changes…”

“…, the number of people in the home) to provide new insights on the relationship between water usage and water age. Although the examples are developed based on demand generators, a similar approach could be used if demands were known from actual demand monitoring, as was done by Palmegiani et al 33 This novel proposed approach can be used to investigate the impacts of changes in water usage in buildings to help mitigate water quality problems.…”

Comparing Actual and Designed Water Demand in Australian Multilevel Residential Buildings

“…It is unclear how the increased velocity in future systems would affect biofilm growth and water quality. However, new developments in water quality modeling presented by Palmegiani et al (2022) suggest the influence of pipe size on water quality can be evaluated. Another important factor is the impact of hydraulic transients, also known as water hammer.…”

Embracing Analytics in the Drinking Water Industry

“…Models are important because they serve as tools to aid in water infrastructure design, and instantly identify health risks associated with various water use patterns for different water systems and scenarios. The goal of water quality models is to combine hydraulic and water quality parameters to predict the concentration of various species that exist within water infrastructure over time (Palmegiani et al, 2022).…”