Applying DBP models to full‐scale plants

Westerhoff, Paul; Debroux, Jean; Amy, Gary L.; Gatel, D.; Mary, Véronique; Cavard, J.

doi:10.1002/j.1551-8833.2000.tb08912.x

Cited by 32 publications

(14 citation statements)

References 10 publications

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“…The chlorine demand is generally determined to satisfy the actual needs of the water disinfection in the plants and distribution systems (Sung et al, 2000). As such, chlorine demand has been incorporated into certain modeling approaches (Westerhoff et al, 2000;Clark et al, 2001). However, the readily oxidizable substances such as Fe 2+ , Mn 2+ and S 2-in water can also exhibit a chlorine demand (Gang et al, 2002;MOE, 2004), which may not be associated with THMs formation.…”

Section: Chlorine Dosementioning

confidence: 99%

“…In Ferryland water, TOC has been found strongly correlated (r 2 = 0.94) to THMs (Figure 3 (i)), while in Bonavista water TOC exhibited a lower correlation (r 2 = 0.76) with THMs ( Figure 3 (iii)). Dissolved organic carbon is generally more representative of the soluble organic carbon fraction than TOC, and increase in DOC generally led to increase in THMs formation (Muller, 1998;Westerhoff et al, 2000). (Figure 4 (i-iii)).…”

Section: Total and Dissolved Organic Carbonmentioning

confidence: 99%

“…Trihalomethanes are formed during water treatment when NOM in water reacts with chlorine in the treatment plants and/or residual chlorine in the water distribution systems. A significant amount of research has been performed to characterize THMs formation and their associated health risks (Rodriguez et al, 2000;2002;Clark et al, 2001;Stevens et al, 1976;Engerholm and Amy, 1983;Amy et al, 1987;Black et al, 1996;Gang et al, 2002;Sohn et al, 2004;Rathbun, 1996;King et al, 2000;Westerhoff et al, 2000). A number of studies have developed models to predict THMs formation, some of which are listed in Table 1.…”

Section: Introductionmentioning

confidence: 99%

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An investigation on parameters for modeling THMs formation

Chowdhury

Champagne²

2013

Global NEST Journal

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Reactions between natural organic matter (NOM) and chlorine during disinfecting drinking water form trihalomethanes (THMs) and other chlorinated by products (CBPs), some of which are possible carcinogen to human health. A number of models have been developed to predict THMs formation since the discovery of THMs in drinking waters. A fraction of these models used a total of 22 different parameters while individual models used 3 to 8 parameters. Some existing models incorporated more than one parameter from total organic carbon (TOC), dissolved organic carbon (DOC) and UV absorption capacity at 254 nm (UV 254 ), while all of these three characterize NOM in water; thus, there exist a possibility of illconditioned coefficient estimation. This paper presents the results of an experimental investigation on different parameters from four water supply systems in Newfoundland, Canada. Strong correlations were found among total organic carbon (TOC), dissolved organic carbon (DOC) and UV absorption capacity at 254 nm (UV 254 ). This study along with the past studies identified pH, temperature and reaction time as significant for THMs formation; however, some existing models ignored these parameters. Although these models have good performance in predicting THMs formation in respective environmental conditions, some models might suffer weakness from mathematical point of view; thus needs to be carefully applied. This study recommends using one parameter from TOC, DOC and UV 254 and chlorine dose, pH, temperature and reaction time for future modeling.

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Section: Chlorine Dosementioning

confidence: 99%

Section: Total and Dissolved Organic Carbonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An investigation on parameters for modeling THMs formation

Chowdhury

Champagne²

2013

Global NEST Journal

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“…This kind of model has been chosen due to the fact that, according to Kulkarni and Chellam [9], DBP mass concentrations are typically modeled empirically by linearly regressing each of the water quality parameters influencing DBP formation. In addition, log-linear power functions are extensively employed to model THM and Haloacetic acid (HAA) formation [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Feasibility Study of a Simple and Low-Cost Device for Monitoring Trihalomethanes Presence in Water Supply Systems Based on Statistical Models

Rivadeneyra

García-Ruiz

Delgado-Ramos

et al. 2014

Water

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This paper describes a new method for predicting trihalomethanes (THMs) presence in networks of water supply systems, using a low-cost device that permits a fast monitoring of concentrations without need of complex analysis made in laboratories. This method, based on statistical models, allows the estimation of THM concentration by monitoring parameters whose determination is direct and easy, and therefore, THM presence can be carried out in real-time. These parameters values are introduced in a multiple regression model resulting in the concentration of THMs levels. This model has taken into account parameters compulsory in water quality analysis and it has been shown that six parameters are enough to determine accurately THM concentration. In addition, the feasibility of a low-cost device that directly gives THM concentration is demonstrated. This device can be easily designed to be transported to different points of the water supply network where it is intended to make control campaigns.

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“…Log-linear power functions are extensively employed to model THM and HAA formation e.g. [9]. For our study, multiple regression model analysis was used.…”

Section: Introductionmentioning

confidence: 99%

A model for predicting THM presence in networks of water supply systems

Osorio

Ribes²,

González‐Martínez

et al. 2011

WIT Transactions on the Built Environment

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The European normative, implemented in the Spanish national legislation in 2003, reduced the acceptable maximum concentration of THMs in drinking water, from 150 to 100 µ/L. This implies that many existent facilities could not achieve this requirement. Generally speaking, the problems related to THMs in the area studied occur in certain periods during the year, mainly in summer. The present concentration of trihalomethanes (THM) in networks samples of water supply systems was predicted based on a set of easy parameters measured continuously at the site, which evidently did not include THM concentration. Consequently, when these values started being high, it was possible to take necessary measures (e.g. to modify the water source, reduce chlorination, etc.) to prevent higher values which are not permitted by law. The analysis of disinfection by-products is expensive and to develop a simple tool that will allow measuring the concentrations of trihalomethanes, particularly in small, poorly resourced water supplies is therefore a worthy intention. Other studied aspects have been the season of sampling or the sampling point. Data of drinking water supply systems coming from four regions in Spain have been used. In total 893 complete analyses have been managed. For obtaining the model, a statistical analysis of multiple regression and diverse Anova tests have been carried out.

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Applying DBP models to full‐scale plants

Cited by 32 publications

References 10 publications

An investigation on parameters for modeling THMs formation

An investigation on parameters for modeling THMs formation

Feasibility Study of a Simple and Low-Cost Device for Monitoring Trihalomethanes Presence in Water Supply Systems Based on Statistical Models

A model for predicting THM presence in networks of water supply systems

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