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.
The residence time of water in residential building water systems is a critical factor regarding water quality at end use. Published literature has highlighted the importance of water age in these systems and its relationship with pathogenic bacteria such as Legionella pneumophila. However, tools to measure water age in such plumbing systems are typically repurposed from other applications and include limitations that make them inappropriate for some plumbing systems. This work presents a novel means of estimating water age by assuming these systems operate without mixing. Data for this study was collected from a full-scale home equipped with an extensive array of flow meters to monitor water use. Further, 408 individual water quality samples were collected to ascertain water quality changes that take place in the plumbing. Model results show weak correlation with EPANET 2.2 (ρ = 0.666), a commonly used hydraulic modeling software. The results of the water age model were also evaluated with several variable selection tools. These analyses indicate that this method's water age results are a statistically significant (p < .05) predictor of Legionella concentrations. Model results from this approach could be used in plumbing design and/or operation to assist in managing Legionella risks.
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