• Journal of Environmental Health Sciences
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• v.32 no.1 s.88
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• pp.53-59
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• 2006

This study was carried out to investigate the physicochemical characteristics with the elapsed time of $1\~10$ minutes after adding green tea leaves in the tap water. The results are summarized as follows: 1. $UV_{254}$ measurement increased sharply in direct opposition to increasing conductivity slowly. It is expected that the water soluble organic matters were better extracted than minerals. 2. Residual chlorine decay coefficients evaluated by assuming first-order reaction was increased in proportion to adding weights of green tea leaves. 3. In DBP formation experiments, residual chlorine decreased when reaction time was elapsed. whereas DBPs such as HAAs and THMs increased with the passing of time. From these results, it was showed that residual chlorine decay was related with the formation of DBPs. Therefore, use of boiled tap water in preparation of green tea is suggested if the residual chlorine in the tap water is high.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.5
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• pp.311-321
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• 2020

In this study, a model to optimize residual chlorine concentrations in a water supply system was developed using a multi-objective genetic algorithm. Moreover, to quantify the effects of optimized residual chlorine concentration management and to consider customer service requirements, this study developed indices to quantify the spatial and temporal distributions of residual chlorine concentration. Based on the results, the most economical operational method to manage booster chlorination was derived, which would supply water that satisfies the service level required by consumers, as well as the cost-effectiveness and operation requirements relevant to the service providers. A simulation model was then created based on an actual water supply system (i.e., the Multi-regional Water Supply W in Korea). Simulated optimizations were successful, evidencing that it is possible to meet the residual chlorine concentration demanded by consumers at a low cost.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.147-154
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• 2014

In this study, chlorine modeling technique based on fuzzy system is proposed to reduce the carcinogenic substance and decide the optimal chlorine injection rate, which is affected by chlorine evaporation rate in sedimentation basin according to detention time, weather and water quality. The additional chlorine meter is installed in the inlet part of sedimentation to reduce the feedback time and implement cascade control, which leads to maintaining the residual chlorine concentration decided by fuzzy rule. It helps to take a preemptive action about long time delay, the characteristics of the disinfection process, and reduce the variation of residual chlorine rate by 7.3 times and the chlorine consumption by 40,000 dollars. It made a significant contribution to supply hygienically safe drinking water.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.6
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• pp.587-597
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• 2017

This study aimed to develop a method to optimize residual chlorine concentrations in the process of providing water supply. To this end, this study developed a model capable of optimizing the chlorine input into the clearwell in the purification plant and the optimal installation location of rechlorination facilities, and chlorine input. This study applied genetic algorithms finding the optimal point with appropriate residual chlorine concentrations and deriving a cost-optimal solution. The developed model was applied to SN purification plant supply area. As a result, it was possible to meet the target residual chlorine concentration with the minimum cost. Also, the optimal operation method in target area according to the water temperature and volume of supply was suggested. On the basis of the results, this study derived the most economical operational method of coping with water pollution in the process of providing water supply and satisfying the service level required by consumers in the aspects of cost effectiveness. It is considered possible to appropriately respond to increasing service level required by consumers in the future and to use the study results to establish an operational management plan in a short-term perspective.

• Journal of Korean Society on Water Environment
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• v.27 no.3
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• pp.334-341
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• 2011

The free residual chlorine of tap water samples, collected from 266 faucets on the water pipe network in Daegu City, was between 0.1 and 0.79 mg/L. On microorganic tests, general bacteria and the coliform goup were not detected and thus the tap water was turned out to be fit to drink. In particular, samples of which free residual chlorine was 0.1 mg/L and over were cultured in R2A agar media at $25^{\circ}C$ for 7 days, and as a result heterotrophic bacteria were detected in 65.9% of samples; (1). The closer tap water got to the faucet from the stilling basin, the lower residual chlorine concentration became but the more the bacterial count became. And, more bacteria were detected in the R2A agar medium than in the PCA medium. (2). In the case of separated strains, most colonies were reddish or yellowish. 16S rRNA sequence was identified as Methylobacterium sp. and Williamsia sp., and yellow strain was identified as Sphingomonas sp., Sphingobium sp., Novosphingobium sp., Blastomonas sp., Rhodococcus sp. and Microbacterium sp. White strain was identified as Staphylococcus sp. (3). Sterilized tap water in polyethylene bottles was inoculated with separated strain and was left as it was for 2 months. As a result, bio-film was observed in tap water inoculated with Methylobacterium sp. and Sphingomonas sp. It was found that heterotrophic bacteria increased when free residual chlorine was removed from tap water in the water pipe network. Thus, there is a need to determine a base value for heterotrophic bacteria in order to check the cleanliness of tap water in the water pipe network.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.1
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• pp.61-72
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• 2014

Study on effluent organic matter (EfOM) characteristic and removal efficiency is required, because EfOM is important in regard to the stability of effluents reuse, quality issues of artificial recharge and water conservation of aqueous system. UV technology is widely used in wastewater treatment. Many reports have been conducted on microbial disinfection and micro pollutant reduction with UV treatment. However, the study on EfOM with UV has limited because low/medium pressure UV lamp is not sufficient to affect refractory organics. The high intensity of pulsed UV would mineralize EfOM itself as well as change the characteristics of EfOM. Chlorine demand and DBPs formation is affected on the changed amounts and properties of EfOM. The objective of this study is to investigate the effect on EfOM, chlorine residual, and chlorinated DBPs formation with low pressure and pulsed UV treatment. The removal of organic matter through low pressure UV treatment is insignificant effect. Pulsed UV treatment effectively removes/transforms EfOM. As a result, the chlorine consumption is changed and chlorine DBPs formation is decreased. However, excessive UV treatment caused problems of increasing chlorine consumption and generating unknown by-products.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.1
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• pp.86-93
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• 2006

In the drinking water treatment, the aesthetic and color problem are caused by the manganese which is occurring and present in the surface, lake and ground water. The most common treatment processes for removing manganese are known for oxidation followed by filtration. In this study, the manganese sand process was used for removing manganese with river bank filtrate as a source. In the manganese sand process, the residual chlorine and pH are important factors on the continuous manganese oxidation. In addition, space velocity (SV) and alum dosage are play a role of manganese removal. Even though manganese removal increased with increasing chlorine concentration, the control of residual chlorine is actually difficult in this process As the results of tests, the residual chlorine concentration as well as manganese removal were effectively achieved at pH 7.5. The optimum attached manganese concentration on manganese sand was confirmed to 0.3mg/L by the experimental result of a typical sand converting to manganese sand.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1197-1210
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• 2022

Recently, users' complaints on drinking water quality are increasing according to emerging interest in the drinking water service issues such as pipe aging and various water quality accidents. In the case of drinking water quality complaints, not only the water pollution but also the inconvenience on the chlorine residual for disinfection are included, thus various efforts, such as rechlorination treatment, are being attempted in order to keep the chlorine concentration supplied evenly. In this research, for a more accurate water quality simulation of water distribution network, the water quality reaction coefficients were estimated, and an optimization method of chlorination/ rechlorination scheduling was proposed consideirng satisfaction of water quality standards and chlorine residual equalization. The proposed method was applied to a large-scale real water network, and various chlorination schemes were comparatively analyzed through the grid search algorithm and optimized based on the suitability and uniformity of supplied chlorine residual concentration.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.5
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• pp.411-419
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• 2018

The residual chlorine concentration is an essential factor to secure reliable water quality in the water distribution systems. The chlorine concentration decays along the pipeline system and the main processes of the reaction can be divided into the bulk decay and the wall decay mechanisms. Using EPANET 2.0, it is possible to predict the chlorine decay through bulk decay and wall decay based on the pipeline geometry and the hydraulic analysis of the water distribution system. In this study, we tried to verify the predictability of EPANET 2.0 using data collected from experimental practices. We performed chlorine concentration measurement according to various Reynolds numbers in a pilot-scale water distribution system. The chlorine concentration was predicted using both bulk decay model and wall decay model. As a result of the comparison between experimental data and simulated data, the performance of the limited $1^{st}$-order model was found to the best in the bulk decay model. The wall decay model simulated the initial decay well, but the overall chlorine decay cannot be properly predicted. Simulation also indicated that as the Reynolds number increased, the impact of the wall.