• Korean Journal of Environmental Agriculture
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• v.19 no.2
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• pp.177-182
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• 2000

Removal rate of swine wastewater containing organic matter was 99 percent in case of high loading rate. The studies of swine wastewater treatment aim to development of process using soil microorganism. Microorganism was devoted to improve the treatment efficiency of the process. Biochemical oxygen demand (BOD) concentration of treated swine wastewater was under 150 mg/L in anaerobic reactor. Also, value of km and Y were $0.73\;hr^{-1}$ and 0.433 g/VSS/g BODrm/d at microorganism of post aeration tank in anaerobic reactor.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1400-1404
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• 2010

In this study the flow duration curves and load duration curves for Nakdong river basin are analyzed. The TANK model is used as s hydrologic simulation model whose parameters are estimated from 8-days intervals flow data measured by Nakdong River Water Environment Laboratory. also in this study a Minimum Variance Unbiased Estimator(MVUE) is confirmed that it provides satisfactory load estimate. The Seven-Parameter Log Linear Model for estimating Total Organic Carbon(TOC) and Biochemical Oxygen Demand(BOD) loads in Nakdong river using a MVUE.

• Journal of Korean Society on Water Environment
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• v.39 no.4
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• pp.269-287
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• 2023

The genus-level biotic index of benthic macroinvertebrates (Benthic Macroinvertebrates Genus Index, BMGI) was developed and applicated based on the data collected from 13,347 sampling units of 814 sites from 2010 to 2021 in Korea. Tolerant values of 274 indicator taxa were established by analyzing the relationship between the relative frequency and abundance of indicator taxa and the water quality index considering biochemical oxygen demand (BOD₅), total suspended solids (TSS), and total phosphorus (T-P). BMGI showed a slightly higher correlation with water quality than the species-level biotic index (Benthic Macroinvertebrates Index, BMI) that was developed and applied in Korea. Although the BMGI does not contain species-level information, the reason why BMGI shows higher applicability than BMI seems to be due to the increase in the number of indicator taxa and the decrease in the misidentification of immature aquatic insects. The coefficient of determination in multiple regression with BOD₅, TSS, and TP for BMGI was 0.62 in the long-term averaged data of 814 sites, and the standardized coefficient of BOD₅ was -0.46, TSS was -0.17 and T-P was -0.21, respectively. As a result of the evaluation by BMGI, of the 814 sites, 38% were in good, 25% in fair, and 37% in poor condition.

• Proceedings of the Korean Society of Dyers and Finishers Conference
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• 2008.10a
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• pp.115-116
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• 2008

The textile wastewater discharged from printing and dyeing processes is characterized by high chemical oxygen demand(COD), low biochemical oxygen demand(BOD), and heavy color. The release of dyes into the environment constitutes only small proportion of water pollution, but dyes are visible in small quantities due to their brilliance. In this study, We are investigated to optimization of Ozone Oxidation process for Decolorization.

• KSBB Journal
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• v.22 no.3
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• pp.129-133
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• 2007

This study represents that a removal efficiency of organic matters in wastewater is activated by a sludge process using new mixed microbial population. In case of mixed microorganisms, removal rates of suspended solid (SS), biochemical oxygen demand (BOD) and chemical oxygen demand (COD) were over 90 percent under experimental condition, and removal efficiency of organic matters, sludge density index (SDI) and capillary suction time (CST) in mixed population were higher than that in not-mixed microorganism, while total kjeldahl nitrogen (TKN) and total phosphorus (T-P) which indicate a degree of eutrophication were removed easily in both case. From these results, we may propose that an application of the mixed microbial population is useful to treat domestic wastewater including a great deal of organic matters.

• Journal of Animal Environmental Science
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• v.7 no.2
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• pp.77-82
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• 2001

This research was carried out to investigate the daily amount and characteristics of wastewater produced from bucket milkers, pipeline, tandem ad herringbone milking system for washing operations after milking included 28 dairy farms. The average amount of wastewater produced from milking system was 9.8l/head/day. The amount of wastewater varied from a low of 8.2 litters/head/day(pipeline milking system) to 13.4 litter/head/day(herringbone milking system). The moisture content, Biochemical Oxygen Demand($BOD_5$), Chemical Oxygen Demand($COD_{Mn}$), Suspended Solids(SS), Total Nitrogen(T-N) and Total Phosphorus(T-P) concentration of wastewater were 99.9%, 394mg/l, 417.3mg/l, 1,201.3mg/l, 3.78mg/l, 0.51mg/l.

• Korean Journal of Ecology and Environment
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• v.48 no.1
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• pp.12-25
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• 2015

The tributaries of Daechung Lake play an important role in controlling eutrophication in the lake, which is used for agricultural purposes and as potable water. However, water quality properties were not extensively studied in the tributaries of Daechung Lake. The objectives of this study are to investigate spatial and temporal properties of water quality and to characterize streams which could threaten water quality of Daechung Lake. For this study, water samples were weekly or monthly collected from February 2014 to October 2014 in 9 streams. Water quality parameters analyzed in this study include biochemical oxygen demand (BOD), chemical oxygen demand (COD), total organic carbon (TOC), total nitrogen and phosphorus (TN and TP), suspended solids (SS), and chlorophyll a. Based on temporal distribution and principal component analysis, BOD, COD, TOC, SS, and TP were controlled by not only river discharge that increased during summer due to heavy rain fall, but also due to anthropogenic input (e.g., bridge construction and/or agricultural activity). Dilution is also one of the factors explaining TN and conductivity, both of which decreased with increased discharge. Generally, concentrations of contaminants (BOD, COD, TOC, TN and TP) in the tributaries were higher than those of Daechung Lake. However, pollution load indicated that only the main channel of Geum River and Sook Stream may largely influence lake waters, attributed mostly to their large volumes. This implies that the main channel and Sook Stream are the major influences on the water quality of Daechung Lake.

• Journal of Animal Environmental Science
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• v.7 no.3
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• pp.169-172
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• 2001

This research was carried out to investigate the quantity of Holstein milking cow manure excreted and their characteristics. The average body weight of the Holstein milking cow during experiment was 550.0kg, and fried intake(DM basis), water consumption, milk yield was 16.7, 85.4, 24.4k7/day/head, repectively. The average manure production of Holstein milking cow was 63.5kg/day/head(feces 42.3, urine 10.2kg). The average moisture content of feces and urine was 83.9%, 96.9%, respectively. Wastewater pollutant concentration of $BOD_5$(Biochemical Oxygen demand). $COD_{Mn}$ (Chemical Oxygen demand), SS(Suspended Solids), T-N(Total Nitrogen) and T-P(Total Phosphorus), excreted from Holstein milking cow was 16,560, 40,329, 78,500, 2,854, 577mg/ l in feces and 4,580, 7,575, 370, 4,164, 7mg/ l in urine, repectively.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.67-78
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• 2019

The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.67-76
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• 2019

The objectives of this study were to analyze trends of water pollutants and to evaluate the achievement of water quality standards by subbasins in the Han River. The trends of 40 water pollutants at 232 water quality measurement points were analyzed. Chemical oxygen demand (COD), Total organic carbon (TOC), Total coliforms (TC), et cetera were found to be worsening trend. For evaluation of achievement, we evaluated water quality arithmetic mean with river environment standards and human health standards at representative points of the subbasin. Biochemical oxygen demand (BOD), TOC, Total phosphorus (T-P), Fecal coliforms (FC), TC exceeded water quality standards, and water quality of human health standards was all satisfied. So, we prioritized pollutants. If pollutants exceed water quality standards or were worse, they were classified first pollutants. Although BOD and T-P are first pollutants because of water quality standards excess, they are continuously improved. Also, it is better to maintain current status because water quality management system of BOD and T-P is well prepared. Meanwhile, TOC, TC, and FC exceed water quality standards. Furthermore, they were worse gradually, but there is a lack of management systems such as water quality standards of the effluence facilities. Therefore, it is necessary to supplement the system. The results of this study can be used as primary data for the establishment of water quality standards and selection of management pollutants.