Manuel J. Rodriguez

Spatial and temporal evolution of trihalomethanes in three water distribution systems

Spatial and seasonal changes in trihalomethane (THM) concentrations were investigated in three distribution systems of Quebec (Canada) which are supplied by different surface waters and which use a variety of physicochemical treatment strategies. The investigation was based on an intensive 25-week sampling programme, undertaken at a time of year when the temperature of southern Quebec surface waters exceeds 4 degrees C (April-November). THMs and other water quality and operational parameters were monitored at points along the distribution system--between the treatment plant and the system extremities--which represented variable residence times of water. Results showed that THM concentrations vary significantly (from 1.5 to 2 times, depending on the utility) between finished waters as they leave the plant and water at the system extremities. When water temperature exceeds 15 degrees C, spatial THM variations are particularly high (from 2 to 4 times, depending on the utility). The development of multivariate regression models showed that water temperature was a better predictor of THM seasonal variability than chlorine dose, surrogates of natural organic matter and pH. Also, initial THM formation (in finished waters leaving the plant) was a good predictor of THM levels at distribution system extremities.

Disinfection byproducts in Canadian provinces: associated cancer risks and medical expenses.

Chlorination for drinking water forms various disinfection byproducts (DBPs). Some DBPs are probably linked to human cancer (e.g., bladder, colorectal cancers) and other chronic and sub-chronic effects. This emphasizes the need to understand and characterize DBPs in drinking water and possible risks to human health. In this study, occurrences of DBPs throughout Canada were investigated. Trihalomethanes (THMs) were observed to be highest in Manitoba followed by Nova Scotia and Saskatchewan, while haloacetic acids were highest in Nova Scotia followed by Newfoundland and Labrador. Based on the characterization of DBPs, risk of cancer from exposure to THMs was predicted using ingestion, inhalation and dermal contact pathways of exposure. In Canada, approximately 700 cancer cases may be caused by exposure to THMs in drinking water. Medical expenses associated with these cancer incidents are estimated at some

Trihalomethanes in drinking water of greater Québec region (Canada): occurrence, variations and modelling.

140 million/year. Expense may be highest in Ontario (∼

Assessing empirical linear and non-linear modelling of residual chlorine in urban drinking water systems

47 million/year) followed by Quebec (∼

Variability of chlorination by-product occurrence in water of indoor and outdoor swimming pools

25 million/year) due to a greater population base. This paper suggests improvements in water treatment, source protection and disinfection processes, and caution in the use of alternative disinfectants to reduce DBPs. Finally, elements are provided to mitigate risks and reduce cost estimates in future studies.

Estimation of chlorination by-products presence in drinking water in epidemiological studies on adverse reproductive outcomes: A review

The levels of trihalomethanes (THMs) – the main species of by-product from water chlorination – were monitored in thedistribution systems of the five major drinking water utilitiesof the greater area of Québec City in order to investigate andmodel their occurrence on a spatial and seasonal basis. Data forTHMs and other water quality and operational parametersassociated with their formation were generated through a 16 monthsampling program involving several sites representing variablewater residence times, from the plant to the system extremity.The results demonstrate that the differences in measured THMlevels between the five utilities are mainly due to the variablequality of raw waters, the type of water treatment process beingused and the type and levels of applied disinfectant. Dependingon the utility, average THM levels were from 1.3 to 2.5 timeshigher in the system extremities than in the water leaving thetreatment plant. Also, average levels of THMs measured in summerat the distribution system extremities were, depending on theutility, from 2.5 to 5 times higher than the average levelsmeasured in winter. The seasonal differences were found to besignificantly greater than those observed by others in waterutilities in the United States and Europe and are explained inlarge part by the considerable changes, over the year, in thequality and temperature of surface waters in Southern Québec. Forthe five utilities under study, multivariate regression modelswere developed in order to predict spatial and seasonalvariations of THMs. Both residual chlorine demand and temperaturewere found to be better, statistically, as predictors for THMoccurrence. The usefulness of the developed models for routineand long term water quality management, as well as for assessmentof human exposure to THMs, are also discussed.

Modeling of heterotrophic bacteria counts in a water distribution system

Abstract To evaluate the performance of chlorine disinfection in drinking water plants, managers use as an indicator the concentrations of residual chlorine within the distribution system. Because of the residence time of water in storage tanks and in distribution pipelines, data that reflect residual chlorine concentrations for a given applied dose are only available after a certain time delay. Consequently, applied chlorine doses that are either too high or too low are often identified too late for an operators reaction (either decreasing or increasing the applied doses) to be effective. To improve effectiveness in this area, modelling of residual chlorine appears to be an interesting alternative. This paper presents the application of two empirical models for simulating and forecasting residual chlorine concentrations within urban water systems. The first is a linear autoregressive model with external inputs, known as ARX; the second is a non-linear artificial neural network (ANN) model. The development of both models is founded on representative data from two Canadian drinking water systems. The results demonstrate the potential of an ANN model, which has a unique ability to detect non-linear complex relationships between data. In evaluating all the given data, simulation results show a similar performance for the linear and non-linear models. However, for specific water treatment conditions (very high and very low chlorine doses), the ANN model gives better predictions than the ARX model. Strategies designed to identify more representative data for future research are also proposed.

Maternal exposure to drinking-water chlorination by-products and small-for-gestational-age neonates.

Swimming is one of the most popular aquatic activities. Just like natural water, public pool water may contain microbiological and chemical contaminants. The purpose of this study was to study the presence of chemical contaminants in swimming pools, in particular the presence of disinfection by-products (DBPs) such as trihalomethanes (THMs), haloacetic acids (HAAs) and inorganic chloramines (CAMi). Fifty-four outdoor and indoor swimming pools were investigated over a period of one year (monthly or bi-weekly sampling, according to the type of pool) for the occurrence of DBPs. The results showed that DBP levels in swimming pools were greater than DBP levels found in drinking water, especially for HAAs. Measured concentrations of THMs (97.9 vs 63.7 μg/L in average) and HAAs (807.6 vs 412.9 μg/L in average) were higher in outdoor pools, whereas measured concentrations of CAMi (0.1 vs 0.8 mg/L in average) were higher in indoor pools. Moreover, outdoor pools with heated water contained more DBPs than unheated pools. Finally, there was significant variability in tTHM, HAA9 and CAMi levels in pools supplied by the same municipal drinking water network, suggesting that individual pool characteristics (number of swimmers) and management strategies play a major role in DBP formation.

Spatial variations of human health risk associated with exposure to chlorination by-products occurring in drinking water.

Chlorination of drinking water is essential to prevent waterborne disease. However, chlorine reacts with organic matter present in surface waters to form various by-products. In the last decade, several epidemiological studies have been conducted to determine the connection between exposure to these chlorination by-products (CBPs) and human health defects, such as adverse reproductive outcomes. However, the methodology used to assess exposure of pregnant women in these studies had serious limitations, particularly in relation to determining CBP presence in the subjects tap water. The purpose of this paper is to critically review of methods used to evaluate the CBP presence in a subjects tap water for exposure assessment purposes in epidemiological studies focused on adverse reproductive outcomes and CBPs in drinking water. Interest is directed more precisely at space-time features related to CBPs for an optimal estimation of their presence in a subjects tap water.

Spatio-temporal variability of non-regulated disinfection by-products within a drinking water distribution network.

Heterotrophic plate count (HPC) constitutes a common indicator for monitoring of microbiological water quality in distribution systems (DS). This paper aims to identify factors explaining the spatiotemporal distribution of heterotrophic bacteria and model their occurrence in the distribution system. The case under study is the DS of Quebec City, Canada. The study is based on a robust database resulting from a sampling campaign carried out in about 50 DS locations, monitored bi-weekly over a three-year period. Models for explaining and predicting HPC levels were based on both one-level and multi-level Poisson regression techniques. The latter take into account the nested structure of data, the possible spatiotemporal correlation among HPC observations and the fact that sampling points, months and/or distribution sub-systems may represent clusters. Models show that the best predictors for spatiotemporal occurrence of HPC in the DS are: free residual chlorine that has an inverse relation with the HPC levels, water temperature and water ultraviolet absorbance, both having a positive impact on HPC levels. A sensitivity analysis based on the best performing model (two-level model) allowed for the identification of seasonal-based strategies to reduce HPC levels.