Models for estimation of the presence of non-regulated disinfection by-products in small drinking water systems
Among all the organic disinfection by-products (DBPs), only trihalomethanes (THMs) and haloacetic acids (HAAs) are regulated in drinking water, while most DBPs are not. Very little information exists on the occurrence of non-regulated DBPs, particularly in small water systems (SWS). Paradoxically, SWS are more vulnerable to DBPs because of a low capacity to implement adequate treatment technologies to remove DBP precursors. Since DBP analyses are expensive, usually SWS have difficulties to implement a rigorous characterization of these contaminants. The purpose of this study was to estimate non-regulated DBP levels in SWS from easy measurements of relevant parameters regularly monitored. Since no information on non-regulated DBPs in SWS was available, a sampling program was carried out in 25 SWS in two provinces of Canada. Five DBP families were investigated: THMs, HAAs, haloacetonitriles (HANs), halonitromethanes (HNMs), and haloketones (HKs). Multivariate linear mixed regression models were developed to estimate HAN, HK, and HNM levels from water quality characteristics in the water treatment plant, concentrations of regulated DBPs, and residual disinfectant levels. The models obtained have a good explanatory capacity since R 2 varies from 0.77 to 0.91 according to compounds and conditions for application (season and type of treatment). Model validation with an independent database suggested their ability for generalization in similar SWS in North America.
KeywordsSmall systems Non-regulated disinfection by-products Haloacetonitriles Halonitrometanes Haloketones Modeling
The authors thank all the voluntary municipalities and the water operators of the 25 SWS for their contribution. Many thanks also to the Department of Environment and Conservation of Newfoundland and Labrador and the Ministère du Développement Durable, de l’Environnement et de la Lutte contre les Changements Climatiques of Quebec for their support. The authors also thank all CREPUL members for their priceless help during the study.
Financial support for this project was received from Natural Sciences and Engineering Research Council of Canada (NSERC) through Res’EAU-WaterNET Research Network.
- Akaike, H. (1973). Information theory and extension of the maximum likelihood principle. In N. B. Petrov & F. Csaki (Eds.), Proceeding of the Second International Symposium on Information Theory (pp. 267–281). Budapest: Akademia Kiado.Google Scholar
- Carlson, M., & Hardy, D. (1998). Controlling DBPs with monocholoramine. Journal of American Water Works Association, 90, 95–106.Google Scholar
- Chowdhury, S., Champagne, P., & McLellan, P. J. (2009). Models for predicting disinfection byproduct (DBP) formation in drinking waters: a chronological review. Science of the Total Environment, 407(14), 4189–206.Google Scholar
- Crittenden, J. C., Rhodes Trussel, R., Hand, D. W., Howe, K. J., & Tchobanoglous, G. (2005). Water treatment: principles and design (2nd ed.). Wiley.Google Scholar
- Edwards, J. E., Henderson, S. B., Struck, S., & Kosatsky, T. (2012). Characteristics of small residential and commercial water systems that influence their likelihood of being on drinking water advisories in rural British Columbia, Canada: a cross-sectional study using administrative data. Journal of Water and Health, 10, 629–649.CrossRefGoogle Scholar
- Health Canada. (2012). Guidelines for Canadian Drinking Water Quality.Google Scholar
- Krasner, S. W., McGuire, M. J., Jacangelo, J. G., Patania, N. L., Reagan, K. M., & Aieta, E. M. (1989). The occurrence of disinfection by-products in US drinking water. Journal of American Water Works Association, 181, 41–53.Google Scholar
- Minalu, G., Aerts, M., Coenen, S., Versporten, A., Muller, A., Adriaenssens, N., et al. (2011). Application of mixed-effects models to study the country-specific outpatient antibiotic use in Europe: a tutorial on longitudinal data analysis. The Journal of Antimicrobial Chemotherapy, 22(6), 79–87.Google Scholar
- Ministère du Développement Durable, de l’Environnement et de la Lutte contre les Changements Climatiques, MDDELCC. (2012). Règlement sur la qualité de l’eau potable, Annexe 1.3.Google Scholar
- Plewa, M. J., Wagner, E. D., Jazwierska, P., Richardson, S. D., Chen, P. H., & McKague, B. A. (2004). Halonitromethane drinking water disinfection byproducts: chemical characterization and mammalian cell cytotoxicity and genotoxicity. Environmental Science & Technology, 38, 62–68.CrossRefGoogle Scholar
- Razali, N. M., & Wah, Y. B. (2011). Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. Journal of Statistical Modeling and Analytics, 2, 21–33.Google Scholar
- Rook, J. J. (1974). Formation of haloforms during chlorination of natural waters. Water Treatment Examination, 23, 234–243.Google Scholar
- Singer, P. C. (2002). Occurrence of haloacetic acids in chlorinated drinking water, water science and technology. Water Supply, 2(5–6), 487–492.Google Scholar
- US Environmental Protection Agency (2006). Initial distribution system evaluation guidance manual for the final stage 2 disinfectants and disinfection byproducts rule.Google Scholar
- White, G. C. (1992). Handbook of chlorination and alternative disinfectants. New York: Van Nostrand Reinhold.Google Scholar