• Membrane and Water Treatment
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• v.13 no.5
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• pp.219-225
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• 2022

5th Assessment Report of the Intergovernmental Panel on Climate Change Weather (AR5) predicts that recent severe hydrological events will affect the quality of water and increase water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed, and solar radiation) were compiled into a representative concentration curve (RC), defined using 8.5. AR5 and future use are calculated based on land use. Semi-distributed emission model Calculate emissions for each target period. Meteorological factors affecting water quality (precipitation, temperature, and flow) were input into a multiple linear regression (MLR) model and an artificial neural network (ANN) to analyze the data. Extensive experimental studies of flow properties have been carried out. In addition, an Acoustic Doppler Velocity (ADV) device was used to monitor the flow of a large open channel connection in a wastewater treatment plant in Ho Chi Minh City. Observations were made along different streams at different locations and at different depths. Analysis of measurement data shows average speed profile, aspect ratio, vertical position Measure, and ratio the vertical to bottom distance for maximum speed and water depth. This result indicates that the transport effect of the compound was considered when preparing the hazard analysis.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.219.1-219.1
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• 2011

These studies carried out to know the effect of ammonium on the current generation in the microbial fuel cells (MFCs). MFCs used in the study were enriched with anaerobic digestion sludge and operated for 3 years using artificial wastewater (AWW). When the current was stably generated, ammonium ion with $27.0{\pm}0.0$, $51.5{\pm}0.0$, $103.5{\pm}0.0mg/L$ with acetate fed into the anode compartment. The current values under condition included ammonium were changed from its initial $6.30{\pm}0.06$ to $6.28{\pm}0.36$, $5.95{\pm}0.61$, $5.64{\pm}0.38mA$, respectively. The current value was slightly decreased to $5.64{\pm}0.38mA$ compared to $6.30{\pm}0.06mA$ generated from MFC without ammonium ion in the AWW. But After 3days operating under ammonium concentration with $103.5{\pm}0.0mg/L$, the current was unstably generated when artificial wastewater without ammonium was fed again. MFC enriched with AWW without ammonium ion was inhibited by high concentration of ammonium. At this time, the ammonium was removed 5.27~16.41 mg per day under all conditions.

• 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 Animal Environmental Science
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• v.16 no.2
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• pp.143-152
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• 2010

Conditions for artificial culture of Lemna Paucicostata and its nutritional values were examined in this study. Lemna P. was cultured using artificial wastewater and a bioreactor (total volume $2,630\;cm^3$, working volume $2,240\;cm^3$) was operated at conditions of 6,250 lux and $28^{\circ}C$. Water flow affected the growth of Lemna P.: growth rate was very high (more than $1.1\;d^{-1}$) at a condition of no-water movement, but it was very low (less than $0.15\;d^{-1}$) when water moved slowly. The growth of Lemna P. was higher in $16h\;d^{-1}$ light cycle than in Sand $24h\;d^{-1}$, and it was also severely affected by the initial $NH_4$-N levels of wastewater. The growth rate of Lemna P. was high in lower $NH_4$-N level, indicating that the growth rate is in inverse proportion to $NH_4$-N concentration in wastewater. However, the contents of crude protein (CP) of Lemna P. were proportional to the initial $NH_4$-N concentration. The CP contents of Lemna P. cultured at 2, 10, 50 and 100 $NH_4$-N mg $L^{-1}$ was 18, 24, 37, 43%, respectively, showing the Lemna P. cultured at 50 and $100\;mg\;L^{-1}$ had similar protein contents to linseed (CP 35%), cottonseed (CP 38%) and soybean (CP 45%). Fat, protein, fiber, NDF and ADF contents of Lemna P. harvested at conditions of $16h\;d^{-1}$ light cycle and less than $2\;mg\;L^{-1}$ of $NH_4$-N level was 2.8, 18, 27, 20, 41 and 65.7%, respectively. Since the growth rate of Lemna P. was very high (more than $1.1\;d^{-1}$) at those conditions, it was convinced that mass production of valuable protein and fiber sources are feasible. In particular, since the Lemna P. has unsaturated fatty acids found mainly in animal fat as well as beneficial fatty acids to health such as C18:ln9c, C18:2n6c, C20:5n3 and C22:2, the Lemna P. biomass would be a highly valuable alternative feed source to grains.

• Journal of Life Science
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• v.23 no.10
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• pp.1273-1279
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• 2013

Aromatic hydrocarbons, such as phenol, have been detected frequently in wastewater, soil, and groundwater because of the extensive use of oil products. Bacterial strains (56 isolates) that degraded phenol were isolated from soil and industrial wastewater contaminated with hydrocarbons. GN13, which showed the best cell growth and phenol degradation, was selected for further analysis. The GN13 isolate was identified as Neisseria sp. based on the results of morphological, physiological, and biochemical taxonomic analyses and designated as Neisseria sp. GN13. The optimum temperature and pH for phenol removal of Neisseria sp. GN13 was $32^{\circ}C$ and 7.0, respectively. The highest cell growth occurred after cultivation for 30 hours in a jar fermentor using optimized medium containing 1,000 mg/l of phenol as the sole carbon source. Phenol was not detected after 27 hours of cultivation. Based on the analysis of catechol dioxygenase, it seemed that catechol was degraded through the meta- and ortho-cleavage pathway. Analysis of the biodegradation of phenol by Neisseria sp. GN13 in artificial wastewater containing phenol showed that the removal rate of phenol was 97% during incubation of 30 hours. The removal rate of total organic carbon (TOC) by Neisseria sp. GN13 and activated sludge was 83% and 78%, respectively. The COD removal rate by Neisseria sp. GN13 from petrochemical wastewater was about 1.3 times higher than that of a control containing only activated sludge.

• Korean Journal of Environmental Agriculture
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• v.17 no.3
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• pp.200-204
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• 1998

Physical and chemical properties of artificial soil produced by firing process were analyzed and compared with normal dry field soil and soil quality standards. Material used for production was water and wastewater treatment sludge, chabizite, and lime. The mixed material was thermally treated in the firing kiln at about $300^{\circ}C$ and $1,000^{\circ}C$, respectively, as per designed process. General properties of the artificial soil were classified as sand by unified soil classification method and similar to the dry-field soil, and even soil conditioning effect were expected when it is mixed properly with normal soil. The artificial soil is high in pH and permeability compared to the dry-field soil. Heavy metal concentrations of the artificial soil met the soil quality standards for the farmland. Overall, the artificial soil was thought to be an appropriate soil which can be returned safely to the nature without significant adverse effect. The cost for the artificial soil production process needs to be lowered for practical application as a sludge treatment, therefore, commercializing of the artificial soil is under review.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.1
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• pp.94-103
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• 2006

The pollution in closing water can be caused by not only artificial factor like sewage but also natural factor like elution from sediment. In this study we analyzed Sediment Oxygen Demand (SOD) for verification of sediment purification effect and sediment elution experiment as well as general items like COD, TN, TP, SS to complement and assess the effect of sediment and water quality. The experiment result showed that the release rate of OSD system were 4 times and 3 times as large as control for P and Fe respectively. SOD for operated OSD system and control were $12.18gO_2{\cdot}m^{-2}{\cdot}d^{-1}$ and $47.95gO_2{\cdot}m^{-2}{\cdot}d^{-1}$. From water qualities analyzed by COD, TN, TP, SS, chlorophyll-a, the removal efficiency increase of TN, TP, chlorophyll-a and COD were about 10~20%, 40~50% and 10% respectively. In conclusion, OSD can contribute to improvement of both the waterbody and the sediment environment effectively.

• Journal of Korean Society of Water and Wastewater
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• v.18 no.4
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• pp.437-444
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• 2004

To control algal bloom in reservoirs in Korea, artificial circulation systems have been applied. Diffuser block aeration systems have been increasingly used in Korean reservoirs especially for shallow ones. However, there has been no sound theoretical background for the design and operation of the system. Also there has not been sufficient post-installation studies to validate the effectiveness of the system. As a result, it has been repeatedly reported that the success of the system is not certain. Proper consideration on thermal stratification regimes of reservoirs and flow dynamics induced by bubble plumes are essential elements in design processes of the aeration system. This paper discusses the current methods in the design of diffuser type aeration system and suggests a new design method based on fluid mechanical theory. Example calculations were discussed using observed data of the Yeoncho Dam and it seems that the results represent the current situation successfully.

• Journal of Korean Society of Water and Wastewater
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• v.14 no.3
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• pp.281-290
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• 2000

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. ANFIS, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an application of network-based fuzzy inference system(ANFIS) for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water which supplied in Kwangju city. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supply, (b) the mean temperature, and (c) the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.46% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.5
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• pp.619-630
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• 2009

The study area investigated in this research is Hwaseong city, Gyeonggi-Do where small scale development is currently in progress. For the last three years, we carried out the environmental and ecological assessment by using data from The Ministry of Environment and Han River Basin Environmental Office. Most of development works in Hwaseong city, Gyeonggi-Do are small scale developments which are related with factory and distribution complex based on individual laws and regulations. However, environmental and ecological assessment is not being sufficiently reflected beforehand. Especially, because the development takes place mainly in the outskirts of the city, the fine forest is continuously being damaged. We analyzed changes in green zone caused by the developments. As a result, the percentage of original green zone was decreasing while the percentage of artificial green zone was increasing. We should maintain the percentage of the original green zone in order to conserve natural environment. In the past three years, the damage of the DGN (Degree of Green Naturality, 7) area that has high conservative value was little, but, there was serious damage in the area of DGN 6. In order to conserve natural environment, political and institutional investigation should be seriously carried out for mitigation of environmental and ecological damages.