Factors Influencing Formation of Trihalomethanes in Drinking Water: Results from Multivariate Statistical Investigation of the Ontario Drinking Water Surveillance Program Database

被引:18
|
作者
Chowdhury, Shakhawat [1 ]
Champagne, Pascale [1 ]
McLellan, P. James [2 ]
机构
[1] Queens Univ, Dept Civil Engn, Kingston, ON K7L 3N6, Canada
[2] Queens Univ, Dept Chem Engn, Kingston, ON K7L 3N6, Canada
来源
基金
加拿大自然科学与工程研究理事会;
关键词
factors for trihalomethanes formation; multivariate statistical analysis; principal component analysis; simultaneous variation;
D O I
10.2166/wqrj.2008.022
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
The presence of trihalomethanes (THMs) in drinking water is an important issue in the context of their potential health effects. Numerous studies have developed models in the past three decades relating THMs concentrations to different factors (e. g., dissolved organic carbon [DOC], chlorine dose, pH, etc.). Previous studies characterized the importance of specific factors through controlled studies using synthetic water or source waters from a small number of water treatment plants. Few studies have reported looking for factors related to THMs formation system-wide across many different water supply systems, and in environments where many factors vary simultaneously. This study presents the results of a multivariate statistical analysis for 162 water supply systems in Ontario, Canada for 2000 to 2004. Principal component analysis (PCA) was applied to determine important factors and possible clusters of variation. PCA identified DOC, chlorine dose, pH, temperature, and reaction time as significant factors for THMs formation. Separate clusters were observed for DOC-colour; chlorine dose-total/free residual chlorine; and hardness-alkalinity. Each cluster indicated factors varying together and representing significant variation. Temperature and pH were found significant and uncorrelated throughout the analysis. The multivariate analysis is the first phase of a continuing investigation into THMs formation with the ultimate goal of developing a predictive model, which can be used to perform human health risk-cost balance studies for drinking water quality management.
引用
收藏
页码:189 / 199
页数:11
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