• Journal of environmental and Sanitary engineering
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• v.9 no.1
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• pp.17-28
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• 1994

There are many possibilities that may lead to low quality of drinking water Recently, some unknown deposits in tap water raised a lot of public concern regarding the safety of drinking water in Seoul. We analyzed the quality of tap water from several areas of Seoul, including the area where public complaints about tap water were high. The results shows that the quality of tap water in Seoul was good, well below the environmental standards. Only the tap water from the area with high public complaints showed turbidity higher than that of other area. Also, result shows that component of deposit in tap water was Al, Fe, Mn, and Zn. Based on the research result we propose several measures that might help to reduce the amount of deposit in tap water as follows : 1 Using coagulant aid when coagulating or adjusting pH when filtering. 2. Replacing old water pipeline with new corrosive- resistant one. 3. Increasing water treatment efficiency by enhancing water treatment system such as automation of water treatment system adjusting production capacity, and improving operational condition of filler basin. 4. Chlorine disinfection at the distribution reservoir would help maintaining the same pH level and chlorine concentration throughout the water pipeline and reduce corrosion of pipe.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.723-728
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• 2019

Citizens' distrust of water pollution is very high in tap water that we routinely drink. In addition, water pollution accidents of tap water are difficult to predict and the risk is high, so real-time monitoring and management are needed. Therefore, it is necessary to introduce real-time water quality monitoring using the Internet of things(IoT). Residual chlorine is more persistent and economical than other disinfectants and it is easy to check residual effect, so it is mainly used as a disinfection index in waterworks. It can be monitored in real time by using IoT technology in order to secure the safety of tap water. In this study, we developed smart device for real-time water quality monitoring using amperometry sensor and analyzed its performance.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.2
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• pp.192-196
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• 2007

In this study, a formation of N-nitrosodimethylamine(NDMA), a disinfection by-product, was investigated as a result of monochloramine addition in water. The NDMA formation was studied in terms of pH, dimethylamine(DMA), monochloramine concentration, and nitrogen composition in monochloramine. At a fixed DMA concentration of 0.01 mM or 0.05 mM, the NDMA formed concentration was quite different when the monochloramine to DMA ratio is less or greater than 1. The NDMA formation increased with increasing pH and a ratio of nitrogen composition in monochloramine to total nitrogen composition. At pH 7 and 8, more than five times higher NDMA formation was produced as a result of five times increase in DMA concentration. It was likely that monochloramine could be related to stimulate NDMA formation, if monochloramine may be produced with chlorine disinfection, in water treatment systems.

• Journal of environmental and Sanitary engineering
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• v.6 no.1
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• pp.7-25
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• 1991

Until now, pure drinking water grnerally menas the water without taste, odor, general bacteria, coliform, and other exotic substance. Such a definition has been changing recently due to the finding of numerous other inorganic and organic substances unknown to us. 10 years ago, major causes of death were infectious agents and parasites contained in water, but recently, it has become apparent that some substances contained in drinking water cause cancer and heart diseases. We must drink about 2L of water everyday in order to maintain healthy condition. Waters used for drinking include tap water, well water, spring water, filtered water, etc., but the quality of drinking water has more polluted due to the industrial development and population increase. For example, industrial waste waters from industrial plants pollute the water supply sources ; toxic substances contained in the waste waters pollute the ground water sources by penetrating the geological strata, and municipal, livestock, public building waste waters also pollute the water supply sources. Sometimes, the polluted surface waters were announced to be polluted by various kinds of orgainc substance, and it is reported that the pollution of ground water by orga nic substances has few in number but high in its concectration comparing with those of surface water. As the water quality pollution level increases, so the amount of disinfectant also increase. For example, chlorine solution, one of widely used disinfectants, creates trihalomethane(THM), a carcinogen, and halogen compounds. According to Oliver, through chlorine disinfection process, humine substance and chlorine create bolatile organic halide and nonvolatile organic halide by chemical reaction. There are tens or hundreds filtering devices, but filtering principles and maintenance metjhods are different, so their efficiency tests are needed. According to Smith, the effeciency tests aginst over 30 Ameican filtering devices show that 10 devices can remove 85% of volatile organics and further studies on filtered waters are underway. In consideration of important impacts of polluted drinking water on national health, authors studied the state of water quality pollution against tap water used as drinking water, filtration device passed water, ground water, and conserved drinking water ; tested the efficiency of filtration devices for tap water ; tried to sep up the detection method by using ion chromatography based on negative ion and positive ion by using single column, and attemped the simple filtration method for general households.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.269-274
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• 2013

We are used with the alkaline ion water which an application field does to object for drinking water compare with the alkaline ion water which asked ion acid electrolysis so as to be very different. This is used with sterilization disinfection use by residual chlorine in case of strong acidity according to ph intensity, and in case of middle acidity use by washing and face washing, and mix with meal materials in case of weak acidity widely usable in cooking. Acid ion water generates as we electrolyze water. Chlorine gas and sodium hydroxide etc. was generated at electrolysis process, and we have toward sterilizing power. Derelicts such as chlorine, phosphorus, sulfur etc. are gathered from a negative ion, and we make acid ion water to + electrode direction in electrolysis. We used a diaphragm in order to disconnect too acid water and alkaline water. We implemented so that the acid water which it came down to three kinds of PWM voltage to PWM (pulse width modulation) control, and implementation method of ph intensity change authorized ph intensity between weak acidity to electrode in strong acidity as we used Microprocessor, and intensity was adjusted successively by PWM control was generated.

• YAKHAK HOEJI
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• v.21 no.4
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• pp.200-210
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• 1977

This investigation was undertaken from February 1976 to September 1976. The detergents in municipal sewages from the Chung Kae Stream, Ahn Yang Stream, and Bong Won Stream were determined at 1.5ppm, 0.93ppm, and 3.36ppm in average respectively. The concentrations of detergents determined in the Han river were 0.013ppm of Kwang Na Ru, 0.11ppm of Duk Do, 0.370ppm of Bo Kwang Dong, and 0.285ppm of Ka Yang Dong basin respectively. And the potable waters of Sung Book Ku and Sung Dong Ku from Ku Eu water pumping station located up-stream of the Han river were less polluted at 0.045ppm and 0.037ppm in average. Young Deung Po Ku and Su Dae Moon Ku had been relatively polluted at 0.181ppm and 0.133ppm. The coagulant, alum [$Al_{2}(SO_{4})_{3}$] could eliminated the small amount of detergent by coagulation. The eliminated rates were about 13% by 5ppm and 22.7% by 20ppm of aluminum sulfate in sewage contained 10ppm of turbidity. The sand and the charcoal adsorbed some detergent as the following Langmuir's equations: For the charcoal, m/x=0.029.$\times$1/Ce-11.43 For the charcoal, m/x=2.705log1/Ce-5.46 Where m: amount of snad and active carbon used(g) x: amount of detergent adsorbed from liquid(g) Ce:concentration in the liquid at equilibrium(miles) The adsorption effect of sand would be neglected. In the low concentration of detergent solution, one gram of active carbon adsorbed 0.263g of detergent. It was determined that one gram of chlorine reduced 5.5g pf DBS om keeping up 0.2ppm of residual chlorine by disinfection process with chlorine compound.

• Food Science of Animal Resources
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• v.38 no.3
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• pp.487-497
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• 2018

Controlling of microorganisms in the industrial process is important for production and distribution of hatching and table eggs. In the previous study, we reported that chlorine dioxide ($ClO_2$) gas of a proper concentration and humidity can significantly reduce the load of Salmonella spp. on eggshells. In this study, we compared microbial reduction efficacy on egg's surface using hatching eggs and table eggs, internal quality of table eggs, and hatchability after both the conventional method (washing and UV expose, fumigation with formalin) and $ClO_2$ gas disinfection. Application of 40 ppm $ClO_2$ gas to the table and hatching eggs, respectively, reduced the aerobic plate count (APC) with no statistical difference compared with the conventional methods. Additionally, we didn't observed that any significant difference in albumin height, Haugh unit (HU), and yolk color, this result confirms that 40 ppm $ClO_2$ had no effect on the internal quality of the table eggs, when comparing with the UV treatment method. The hatchability of hatching eggs was not statistical different between formaldehyde fumigation and 80 ppm $ClO_2$ gas treatment, though the value was decreased at high concentration of 160 ppm $ClO_2$ gas. From these results, we recommend that $ClO_2$ gas can be used as a safe disinfectant to effectively control egg surface microorganisms without affecting egg quality.

• Bulletin of the Korean Chemical Society
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• v.25 no.10
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• pp.1525-1530
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• 2004

Mutagen X (MX) exists in our drinking water as the bi-products of chlorine disinfection. Being one of the most potent mutagen, it attracted much attention from many researchers. MX and its analogs are synthesized and modeled by quantitative structure activity relationship (QSAR) methods. As a result, factors affecting this class of compounds have been found to be steric and electrostatic effects. We tried to collect all the data available from the literature. With both CoMFA and CoMSIA various combinations of physiochemical parameters were systematically studied to produce reasonable 3-dimensional models. The best model for CoMFA gave $q^2$ = 0.90 and $r^2$ = 0.97, while for CoMSIA $q^2$ = 0.85 and $r^2$ = 0.94. So the models seem to be reasonable. Unlike previous result of CoMFA, in our case steric parameter alone gave the best statistics. Although the steric contribution was found to be the most important in both CoMFA and CoMSIA, steric parameter along with electrostatic parameter produced slightly better model in CoMSIA. Overall, steric contribution is clearly the most important single factor. However, when we compare chlorine and bromine substitution, chlorine substitution can be more mutagenic. This indicates that other factors such as electrostatic effect also influence the mutagenicity. From the contour maps, steric contribution seems to be focused on rather small area near C6 substituent of the furanone ring, rather than C3 substituent. Therefore the locality of steric contribution can play a significant role in mutagenicity.

• YAKHAK HOEJI
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• v.24 no.2
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• pp.87-95
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• 1980

Chlorination to polluted water can produce chlorocompounds which may impair human health. It has been discussed that chlorophenols would be one of undesirable substances in drinking water. This study was undertaken to investigate the production mechanism of chlorophenols by chlorination in the disinfection of water and to determine pollution levels of phenols as precursor of chlorophenols and chloropbenols in some sewage, stream water and tap water in the vicinity of Seoul from January to September, 1979. By chlorination with hyperchlorite to phenols in distilled water, o-chlorophenol was predominantly produced at the concentration of less than 10ppm of free chlorine. o-Chlorophenol, 2,6-dichlorophenol and 2,4-dichlorophenol were also produced by chlorination with the concenration from 20 to 100ppm of free chlorine. From the concentration of 100ppm of free chlorine to 200ppm, o-Chlorophenol was vanished and 2,6-dichlorophenol and 2,4-dichlorophenol were determined. Phenols originated from night soil, municipal sewage and stream were determined at 49.15 ppm. 0.095 ppm and 0.003 ppm in average respectively. About 87 and 88 percent of phenols in sewage and night soil were biodegradated by aeration for 10 days and 74 and 51 percent of phenols in sewage and night soil by spontaneous settling for 10 days. From the tap water in Seoul during summer, 1979, chlorophenols were identified; they were average 0.042 ppb of o-chlorophenol, 0.033 ppb of 2, 6-dichlorophenol and 0.003 ppb of 2, 4-dichlorophenol respectively. With the above result and discussion, it is considered that chlorophenols should be controlled from the source as well as chlorination in water purification.

• 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.