• Journal of Korean Society of Environmental Engineers
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• v.22 no.3
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• pp.505-510
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• 2000

In this study the effects of pre-chlorination on the coagulation of water which contain Microcystis aeruginosa. were investigated on the laboratory scale. We prepared the sample of $10^5cell/mL$ Microcystis aeruginosa and then applied 0.2, 1.0, 10 mg-Cl/L chlorine on the sample After reaction period(1 minute and 1 hour), each sample was coagulated. As a result, after 0.4 mg-Al/L coagulant dose, turbidities of all samples were below 2 mg-Kaolin/L. Turbidity was not affected by chlorine dose. As the dose of chlorine was increased, the residual aluminum was decreased, but result of $UV_{254}$ was adverse.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 1997.10a
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• pp.67-67
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• 1997

정수공정은 "원수 -1 침사지 1 전염소 -1 전오존 -1 침전지 1 여과지 1 후오존 1 GAC 4 후염소 1 가정수"로 이루어져 있으며 전처리 공정으로 염 소와 오존을 주입하게 되는데, 여기서 전염소 처리 공정으로 인해 잔류 유리염 소가 수중의 유기물질과 반웅하여 유해성 유기염소 화합물 (i.e.. Trihalomethane, Haloacetonitriles, Chlorophenol 등)을 생성하는 것으로 알려져 있다. 이러한 이유로 고도 정수처리 공정에서는 강한 산화력을 지닌 대체 산화 제로서 오존을 이용하고 있다. 전오존 처리공정은 OOC와 탁도 제거에 있어 응 집제 주입량을 감소시키는 것과 더불어 전오존 효과 (산화, 생분해 증대, 살균 등)를 얻을 수 있는 것으로 알려져 왔다. 그러나 낙동강과 같이 유기물이 많은 원수에 과다한 오존이 주입되면 수중 의 유기물이 저분자화 또는 응집이 어려운 오존 산화물로 변화하여 응집제의 소비가 많아지게 된다. 실제, 오존을 응집 효과에 대해서 pilot plant로 운전한 결과 전오존에 의해 입자성 물질의 제거 효율은 향상된 반면에 유기물 제거는 뚜렷한 효과를 볼 수 없었다고 보고되었다 (류, 1997). 본 연구에서는 물금 지역의 원수와 응집-침전 공정까지 거치는 각각의 처 리수에 대해서 전처리가 응집에 미치는 영향을 천연유기물질 (NOM)의 조성 변화로 파악하였다. 그 방법으로 천연유기물질 (NOM)을 XAD-1, -4 수지를 이 용하여 소수성 물질 (hydrophobic components)과 친수성 물질 (hydrophilic components)로 분리 및 농축하여 용존 유기물이 처리 과정에서 어떻게 변화하 는지를 조사하여 개선된 상수 처리 시스템을 설계하는데 기초 자료를 제공하고 수질 관리 분야에서도 적용하고자 하였다. 상수원수인 물금 지역의 소수성 물질(hydrophobic components)은 75~80%, 친수성 물질(hydrophilic components)은 30~33%정도의 분포를 보였고, 전염소 및 전오존 공정을 거친 처리수에서는 각각 62.2-62.8%, 43.9~49.0% 및 50~ 55%, 40~57% 정도의 분포를 보였다. 그리고 웅집-침전을 거친 처리수에서는 그 분포가 77~82%, 24-48%였다. 전주리 공정을 통하여 소수성 물질(byoghobic components)의 분포가 감 소하는 것을 볼 때 전염소 및 전오존 처리가 용존유기물의 응집에는 오히려 역 효과를 나타내는 것으로 판단된다. 것으로 판단된다.

• Proceedings of the Membrane Society of Korea Conference
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• 2003.05a
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• pp.129-132
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• 2003

• Journal of Korean Society of Environmental Engineers
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• v.33 no.12
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• pp.893-899
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• 2011

The occurrence of THMs, the characteristics of THMs formation and removal of THMs were investigated. The treatment train of M plant consists of prechlorination, flocculation, sedimentation, filtration, ozonation, activated carbon and postchlorination. The study of THM formation indicated that about 92% of the THMs were formed in the flocculation/sedimentation/filtration process which affected by prechlorination. The formation of THMs was highly correlated to $KMnO_4$ consumption and water temperature in raw water. The regression model had showed 0.72~0.80 of determination coefficient so it could be used to predict the amount of THMs formation in finished water. Compared to the prechlorination process, the THMs formation was reduced in interchlorination process. With the addition of PAC, fewer THMs were formed in PAC-chlorination process than in chlorination-PAC process. Our results showed that air stripping could be used to remove the existing THMs.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.10
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• pp.556-560
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• 2017

This research carried out to evaluate the disadvantage of pre-chlorination and the effect of polyamine as coagulant aids for treating the blooming water with Microcystis sp.. Pre-chlorination on blooming water makes the colony of Microcystis sp. to the smaller size. Coagulation with polyamine advanced treatment efficiency not only turbidity but also particulate matters especially less then $5{\mu}m$ size for the blooming water compared with using alum alone. Particle count was more sensitive than turbidity on water quality management of settlement and filtrate.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 1999.04a
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• pp.113-115
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• 1999

• Proceedings of the Membrane Society of Korea Conference
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• 2002.11a
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• pp.154-157
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• 2002

• Journal of Korea Water Resources Association
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• v.30 no.3
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• pp.235-245
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• 1997

A pilot scale study for removing odor and trihalomethane formation potential (THMFP) was investigated in the standard water treatment plant equipped with ozone oxidation and granular activated carbon (GAC) adsorption processes. The removal efficiency of dissolved organic carbon (DOC) in the pilot scale standard water treatment process (PSWTP) was about 25%, however, no more removal in the ozone oxidation process. On a GAC after 30 days operation, DOC removal efficiency was about 75%. Odor removal efficiency was about 30% in PSWTP, 60% in ozone oxidation, and almost complete in well as DOC. Mid-1 and 2 that showed breakthrough in odor inducing material as well as DOC. Mid-1 and 2 chlorination was able to reduce trihalomethanes (THM) by 25% compared to prechloringation, while postchlorination alone could reduce them by 30%.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.7
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• pp.721-728
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• 2008

DBPs(Disinfection By-Products) are most formed through the reactions between chlorine and NOM(Natural Organic Matter) in water treatment. In this study, occurrence of DBPs including THMs(Trihalomethanes) is evaluated. Also, influencing factors by the seasons and raw water quality were investigated for correlation among them and the characteristics of THMs formation by prechlorination process. This study investigated the operation condition for THMs removal depending on raw water quality. Water treatment plant from intake station to gauging well flows for about 10 hours in Y Water Supply Office. It is limited to control of THMs formation because of excessive reaction time between chlorine and THMs precursors in the intake station. Therefore, as multi-points prechlorination from intake station to gauging well, THMs formation was decreased in the water treatment, and it was willing to prevent overdosage of chlorine. The concentration of THMs was 0.021 mg/L in the summer, 0.015 mg/L in the winter, respectively. Also, THMs formation showed that 0.013 mg/L in the water of gauging well after prechlorination, 0.014 mg/L in the flocculation/sedimentation/filtration, 0.016 mg/L in the water after postchlorination, respectively. THMFP(Trihalomethane Formation Potential) removed 42.7% and 50% through the flocculation/sedimentation and filtration, respectively, and it is similar TOC removal efficiency. In this study, multi-points prechlorination from intake station to gauging well decreases in contact time and concencrations of NOM and chlorine. Also, it decreases in THMs and amount of chlorine uesd. In the result of multi-points prechlorination in the summer, the concentration of THMs was 0.013mg/L in the treated water. In view of these facts, THMs formation can be decreased approximately 50%.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1283-1293
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• 2022

The purpose of this study is to predict residual chlorine in order to maintain stable residual chlorine concentration in sedimentation basin by using artificial intelligence algorithms in water treatment process employing pre-chlorination. Available water quantity and quality data are collected and analyzed statistically to apply into mathematical multiple regression and artificial intelligence models including multi-layer perceptron neural network, random forest, long short term memory (LSTM) algorithms. Water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage data are used as the input parameters to develop prediction models. As results, it is presented that the random forest algorithm shows the most moderate prediction result among four cases, which are long short term memory, multi-layer perceptron, multiple regression including random forest. Especially, it is result that the multiple regression model can not represent the residual chlorine with the input parameters which varies independently with seasonal change, numerical scale and dimension difference between quantity and quality. For this reason, random forest model is more appropriate for predict water qualities than other algorithms, which is classified into decision tree type algorithm. Also, it is expected that real time prediction by artificial intelligence models can play role of the stable operation of residual chlorine in water treatment plant including pre-chlorination process.