Climate change and drinking water quality: Predicting high trihalomethane occurrence in water utilities supplied by surface water. (October 2019)

• Record Type: Journal Article
• Authors: Cool, Geneviève; Delpla, Ianis; Gagnon, Pierre; Lebel, Alexandre; Sadiq, Rehan; Rodriguez, Manuel J.
• Is Part Of: Environmental modelling & software. Volume 120(2019)
• Publication Date: 2019-10
• Subjects: Drinking water -- Trihalomethanes -- Climate change -- Multilevel regression models; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2019.07.004
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract : This study estimates the impact of future variations in temperature and precipitation ― associated with climate change scenarios ― on the probability of total Trihalomethanes (TTHM) concentrations exceeding a threshold in drinking water. 108 drinking water utilities (DWUs) located in the Province of Quebec (Canada) were selected for this study. Temperature and precipitation variations from the period 2006–2009 to three predicted periods (2010–2039, 2040–2069, and 2070–2099) were estimated using two climate models and three emission scenarios. The probability of TTHM threshold exceedances was calculated using a multilevel logistic regression model based on three variables (treatment type, temperature, and precipitation) and three hierarchical levels (TTHM samples, DWUs and source water ecosystem). Results showed a low but significant increase in the probability of TTHM threshold exceedances over time (between 1.9% and 4.7%). There was also a significant probability difference between seasons (up to 30%) and between treatment types (between 25% and 40%). Highlights: Low increase in TTHM exceedances probability over time (+1.9–4.7%) was found. An increase in intra-annual variability in probabilities with time was observed. There is large differences between seasons (up to 30%) and treatment types (25–40%). DWUs using advanced treatment are more resilient than DWUs using chlorination only.