École Supérieure d'Aménagement du Territoire, Université Laval, 1628 Pavillon Félix-Antoine-Savard, Québec City, QC, Canada.
Water Res. 2011 Jan;45(1):337-47. doi: 10.1016/j.watres.2010.08.002. Epub 2010 Aug 11.
Disinfection byproducts (DBPs) in municipal supply water are a concern because of their possible risks to human health. Risk assessment studies often use DBP data in water distribution systems (WDS). However, DBPs in tap water may be different because of stagnation of the water in plumbing pipes (PP) and heating in hot water tanks (HWT). This study investigated occurrences and developed predictive models for DBPs in the PP and the HWT of six houses from three municipal water systems in Quebec (Canada) in a year-round study. Trihalomethanes (THMs) in PP and HWT were observed to be 1.4-1.8 and 1.9-2.7 times the THMs in the WDS, respectively. Haloacetic acid (HAAs) in PP and HWT were observed to be variable (PP/WDS = 0.23-2.24; HWT/WDS = 0.53-2.61). Using DBPs occurrence data from these systems, three types of linear models (main factors; main factors, interactions and higher orders; logarithmic) and two types of nonlinear models (three parameters Logistic and four parameters Weibull) were investigated to predict DBPs in the PP and HWT. Significant factors affecting DBPs formation in the PP and HWT were identified through numerical and graphical techniques. The R(2) values of the models varied between 0.77 and 0.96, indicating excellent predictive ability for THMs and HAAs in the PP and the HWT. The models were found to be statistically significant. The models were validated using additional data. These models can be used to predict DBPs increase from WDS (water entry point of house) to the PP and HWT, and could thereby help gain a better understanding of human exposure to DBPs and their associated risks.
市政供水中的消毒副产物（DBPs）因其对人类健康的潜在风险而受到关注。风险评估研究通常在供水管网系统（WDS）中使用 DBP 数据。然而，由于管道（PP）中的水停滞和热水箱（HWT）中的水加热，自来水中的 DBP 可能会有所不同。本研究在全年研究中，调查了魁北克（加拿大）三个市政供水系统的六所房屋的 PP 和 HWT 中 DBP 的发生情况，并建立了预测模型。分别观察到 PP 和 HWT 中的三卤甲烷（THMs）比 WDS 中的 THMs 高 1.4-1.8 倍和 1.9-2.7 倍。PP 和 HWT 中的卤乙酸（HAAs）变化不定（PP/WDS = 0.23-2.24；HWT/WDS = 0.53-2.61）。使用这些系统的 DBP 发生数据，研究了三种类型的线性模型（主要因素；主要因素、相互作用和更高阶；对数）和两种类型的非线性模型（三参数 Logistic 和四参数 Weibull），以预测 PP 和 HWT 中的 DBP。通过数值和图形技术确定了影响 PP 和 HWT 中 DBP 形成的显著因素。模型的 R²值在 0.77 到 0.96 之间变化，表明对 PP 和 HWT 中 THMs 和 HAAs 的预测能力非常出色。模型被发现具有统计学意义。使用额外的数据对模型进行了验证。这些模型可用于预测从 WDS（房屋进水点）到 PP 和 HWT 的 DBP 增加，从而有助于更好地了解人类对 DBP 的暴露及其相关风险。
