• Journal of Korean Society of Water and Wastewater
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• v.28 no.3
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• pp.287-297
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• 2014

It is important to predict chlorine decay with different water purification processes and distribution pipeline materials, especially because chlorine decay is in direct relationship with the stability of water quality. The degree of chlorine decay may affect the water quality at the end of the pipeline: it may produce disinfection by-products or cause unpleasant odor and taste. Sand filtrate and dual media filtrate were used as influents in this study, and cast iron (CI), polyvinyl chloride (PVC), and stainless steel (SS) were used as pipeline materials. The results were analyzed via chlorine decay models by comparing the experimental and model parameters. The models were then used to estimate rechlorination time and chlorine decay time. The results indicated that water quality (e.g. organic matter and alkalinity) and pipeline materials were important factors influencing bulk decay and sand filtrate exhibited greater chlorine decay than dual media filtrate. The two-component second-order model was more applicable than the first decay model, and it enabled the estimation of chlorine decay time. These results are expected to provide the basis for modeling chlorine decay of different water purification processes and pipeline materials.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.5
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• pp.601-607
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• 2007

In order to maintain constant residual chlorine in sedimentation basin, It is necessary to develop real time prediction model of residual chlorine considering water treatment plant data such as water qualities, weather, and plant operation conditions. Based on the operation data acquired from K water treatment plant, prediction models of residual chlorine in sediment basin were accomplished. The input parameters applied in the models were water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage. The multiple regression models were established with linear and non-linear model with 5,448 data set. The corelation coefficient (R) for the linear and non-linear model were 0.39 and 0.374, respectively. It shows low correlation coefficient, that is, these multiple regression models can not represent the residual chlorine with the input parameters which varies independently with time changes related to weather condition. Artificial neural network models are applied with three different conditions. Input parameters are consisted of water quality data observed in water treatment process based on the structure of auto-regressive model type, considering a time lag. The artificial neural network models have better ability to predict residual chlorine at sediment basin than conventional linear and nonlinear multi-regression models. The determination coefficients of each model in verification process were shown as 0.742, 0.754, and 0.869, respectively. Consequently, comparing the results of each model, neural network can simulate the residual chlorine in sedimentation basin better than mathematical regression models in terms of prediction performance. This results are expected to contribute into automation control of water treatment processes.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.1
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• pp.17-29
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• 2019

This study developed prediction models of chlorine bulk decay coefficient by each condition of water quality, measuring chlorine bulk decay coefficients of the water and water quality by water purification processes. The second-reaction order of chlorine were selected as the optimal reaction order of research area because the decay of chlorine was best represented. Chlorine bulk decay coefficients of the water in conventional processes, advanced processes before rechlorination was respectively $5.9072(mg/L)^{-1}d^{-1}$ and $3.3974(mg/L)^{-1}d^{-1}$, and $1.2522(mg/L)^{-1}d^{-1}$ and $1.1998(mg/L)^{-1}d^{-1}$ after rechlorination. As a result, the reduction of organic material concentration during the retention time has greatly changed the chlorine bulk decay coefficient. All the coefficients of determination were higher than 0.8 in the developed models of the chlorine bulk decay coefficient, considering the drawn chlorine bulk decay coefficient and several parameters of water quality and statistically significant. Thus, it was judged that models that could express the actual values, properly were developed. In the meantime, the chlorine bulk decay coefficient was in proportion to the initial residual chlorine concentration and the concentration of rechlorination; however, it may greatly vary depending on rechlorination. Thus, it is judged that it is necessary to set a plan for the management of residual chlorine concentration after experimentally assessing this change, utilizing the methodology proposed in this study in the actual fields. The prediction models in this study would simulate the reduction of residual chlorine concentration according to the conditions of the operation of water purification plants and the introduction of rechlorination facilities, more reasonably considering water purification process and the time of chlorination. In addition, utilizing the prediction models, the reduction of residual chlorine concentration in the supply areas can be predicted, and it is judged that this can be utilized in setting plans for the management of residual chlorine concentration.

• Journal of Conservation Science
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• v.26 no.4
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• pp.397-406
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• 2010

The most ideal method to measure the water-soluble $Cl^-$ ion eluted from iron artifacts is conducting the analysis on desalting solution by Ion Chromatography. But most institutes related to cultural heritages use Cl meter by reason of lack of budget and experts. This study evaluated reliability and stability between Cl meter and Ion Chromatography by doing cross-validation with results from two methods to detect $Cl^-$ ion of desalting solution. From D.I water, extremely small quantities of $Cl^-$ ion was detected by the influence of remaining water-soluble $Cl^-$ ion at the electrode of Cl meter and water-soluble $Cl^-$ which remains in Sodium sesquicarbonate, components of reagent was detected as well. The first desalting solution had the most $Cl^-$ ions, $Cl^-$ ion slightly decreased from the second to the fourth desalting solution and tend to decrease again at the stage of dealkalified in D.I water. Each Cl meter has the standard deviation according to the measured numbers and the higher concentration of $Cl^-$ ion the desalting solution has, the wider the deviation is. But when the concentration of $Cl^-$ ion is low, it was stable to use Cl meter to detect the concentration of $Cl^-$ ion from iron artifacts because there is the small deviation, It is thought that conductivity meter method is not suitable for measuring $Cl^-$ ion, because the electrical conductivity of alkaline solution is too high to measure $Cl^-$ ion.

• Journal of Environmental Health Sciences
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• v.29 no.1
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• pp.8-15
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• 2003

In this study, chlorine dose at water storage tank was predicted to meet the recommended guideline for free chlorine residual in drinking water distribution system, using EPANET which is a computer program that performs extended Period simulation of hydraulic and water quality behavior within pressurized pipe networks. The results may be summarized as follows. The decay of chlorine residual by season varied considerably in the following order; in summer ($25^{\circ}C$) > spring and fall (15$^{\circ}C$) > winter (5$^{\circ}C$). For re-chlorination at water storage tank by season, season-varying chlorine dose was required at its maximum of 1.00 mg/l in summer and minimum of 0.40 mg/l in winter as free chlorine residual. The decay of chlorine residual through out the networks increased with water age spent by a parcel of water in the network except for some points with low water demand. In conclusion, the season-varying chlorine dose as well as the monitoring of water quality parameters at the some points which showed high decay of chlorine residual may be necessary to deliver the safe drinking water.

• Journal of Korean Society of Water and Wastewater
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• v.14 no.1
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• pp.108-116
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• 2000

Chlorine is widely used as a disinfectant in drinking-water systems throughout the world. Chlorine residual was used as an indicator for prediction of water quality in water distribution systems. The variation of chlorine residual in drinking water distribution systems of Suwon city was simulated using EPANET. EPANET is a computerized simulation model which predicts the dynamic hydraulic and water quality behavior within a water distribution system operating over an extended time period. Sampling and analysis were performed to calibrated the computer model in 1999 (Aug. Summer). Water quality variables used in simulations are temperature, roughness coefficient, pipe diameter, pipe length, water demand, velocity and so on. Extended water residence time affected water quality due to the extended reaction time in some areas. All area showed the higher concentration of chlorine residual than 0.2mg/l(standard). So it can be concluded that any area in Suwon city is not in biological regrowth problem. Rechlorination turned out to be an useful method for uniform concentration of free chlorine residual in distribution system. The cost of disinfectant could be saved remarkably by cutting down the initial chlorine concentration to the level which guarantees minimum concentration (0.2mg/l) throughout the distribution system.

• Journal of Korean Society of Water and Wastewater
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• v.12 no.3
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• pp.118-124
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• 1998

To use chlorine residual as an surrogate parameter of the water quality change during the transportation in the water distribution system(WDS), the correct prediction model of chlorine residual must be established in advance. This paper shows the procedure and the result of applying the water quality model to the field WDS. To begin with, hydraulic model was calibrated and verified using fluoride as an tracer. And chlorine residual was predicted through simulation of water quality model. This predicted value was compared with the observed value. With adjusting the bulk decay coefficient(kb) and the wall decay coefficient(kw) according to the pipewall environment, the predicted chlorine residual can represent the observed value relatively well.