• Journal of Korean Society on Water Environment
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• v.21 no.1
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• pp.29-33
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• 2005

In order to recycle the waste material and to develop the thickening unit of waste activated sludge from wastewater treatment facilities, the filtration bio-reactor equipped with a shadow mask filter module was employed for this work from which the operating properties and parameters were drawn. The sludge thickening and filtration unit is made of cylindrical acryl tank(12cm i.d. ${\times}$ 58cm height: working volume of 6L), where the flat-sheet type of shadow mask filter module(pore size: 220~250um, opening area: 34.8~39.6%) was installed and the effluent was withdrawn from the effluent port at the lowest point of the reactor, and the filtration was performed only by the hydraulic pressure. For evaluating the operating performance of this reactor, some parameters such as the solid-liquid separation of different biomass concentrations, the water quality of filtrate, the aeration cleaning time and the cleaning effect were investigated. Depending on the MLSS concentrations, the different time to withdraw 3L of filtrate was required in which the longer filtration time was necessary for the higher MLSS concentrations caused by the thicker formation of cake layer: 40 minutes for 5,000 mg/L, 70 minutes for 10,000 mg/L and 100 minutes for 15,000 mg/L, where the concentrations of SS were 8.9, 6.7 and 6.5 mg/L, respectively. Under the same operating conditions (the intensity of aeration cleaning: 80 L/min, MLSS: 10,000 mg/L), the proper aeration cleaning time was revealed 30 seconds, and the stable formation of cake layer was in the range of 10 to 15 minutes. Therefore, the shadow mask considered as a waste material can be of use as a filter material for the sludge thickening system.

• Journal of the Korean Chemical Society
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• v.66 no.3
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• pp.202-208
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• 2022

In this study, we tried to obtain the optimal conditions to reduce odors generated from pig wastewater using magnesia (MgO) through in-situ test after producing a reactor for removing odors. For this purpose, the filling amount of magnesia, the injection amount of pig wastewater, the aeration method, the aeration amount and the aeration time were considered. The field experiment was conducted at Cheongwoon Livestock Farm, which has a pig wastewater reservoir. As the amount of magnesia added to the weight of wastewater (500 kg) increases, the amount of ammonia (NH₃) and hydrogen sulfide (H₂S) generated tended to gradually decrease. As a result of the test, ammonia and hydrogen sulfide in the pig wastewater decreased up to 65% and 77%, respectively, for 2 days aeration after 0.8% of magnesia was added to the reaction tank. The initial pH of the pig wastewater in the reactor was 8.2, and the pH was found to be 9.2 when magnesia was added up to 0.8%. In the light of this trend, it can be known that magnesia gradually increases the pH in the pig wastewater and makes it weakly alkaline. As the pH increases, part of the ammonia gas present in the pig wastewater vaporizes into the air and the remaining part is removed by precipitation after chemical bonding with dissolved magnesium ions and phosphate ions. In order to remove the odor of pig wastewater and turn it into compost, most of the existing livestock farms go through a six-month aeration process using microorganisms. In contrast, the current study proved the effect of removing odors from pig wastewater within 2 days through chemical reactions that do not affect microbial activity.

• 한국생물공학회:학술대회논문집
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• 2000.04a
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• pp.125-128
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• 2000

A recycling reactor system operated under sequential anoxic and oxic conditions for the swine wastewater has been developed, in which piggery slurry is fermentatively and aerobically treated and then part of the effluent recycled to the pigsty. This system significantly removes offensive smells (at both pigsty and treatment plant), BOD and other loads, and appears to be costeffective for the small-scale farms. The most dominant heterotrophs were Alcaligenes faecalis, Brevundimonas diminuta and Streptococcus sp. in order while lactic acid bacteria were dominantly observed in the anoxic tank. We propose a novel monitoring system for a recycling piggery slurry treatment system through neural networks. Here we tried to model treatment process for each tank(influent, fermentation, aeration, first sedimentation and fourth sedimentation tanks) in the system based on population densities of heterotrophic and lactic acid bacteria. Principle component analysis(PCA) was first applied to identify a relation between input(microbial densities and parameters for the treatment such as population densities of heterotrophic and lactic acid bacteria, suspended solids (SS), COD, $NH_3-N$, ortho-P, and total-P) and output, and then multilayer neural networks were employed to model the treatment process for each tank. PCA filtration of input data as microbial densities was found to facilitate the modeling procedure for the system monitoring even with a relatively lower number of input. Neural networks independently trained for each treatment tank and their subsequent combinatorial data analysis allowed a successful prediction of the treatment system for at least two days.

• Journal of Korean Society of Water and Wastewater
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• v.24 no.3
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• pp.267-276
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• 2010

Many plants have been improved to adapt the target of the biological treatment processes changed from organics to nutrients since the water quality criteria of effluent was reinforced and included T-N and T-P for the municipal wastewater treatment plant. To meet the criteria of T-N and T-P, the conventional biological reactor such as aeration tank in activated sludge system is changed to the BNR (biological nutrient removal) processes, which are typically divided into three units as anaerobic, anoxic and oxic tank. Therefore, the solid separation process should be redesigned to fit the BNR processes in case of the application of the DAF (dissolved air flotation) process as an alternatives because the solid-liquid separation characteristics of microbial flocs produced in the BNR processes are also different from that of activated sludge system as well. The results of this study revealed that the microbial floc of the anaerobic tank was the hardest to be separated among the three steps of the unit tanks for the BNR processes. On the contrary, the oxic tank was best for the removal efficiency of nutrients as well as suspended solid. In addition, the removal efficiency of nutrients was much improved under the chemical coagulation treatment though coagulation was not indispensable with a respect to the solid separation. On the other hand, in spited that the separation time for the microbial floc from the BNR processes were similar to the typical particles like clay flocs, over $2.32{\times}10^3$ ppm of air volume concentration was required to keep back the break-up of the bubble-floc agglomerates.

• Biotechnology and Bioprocess Engineering:BBE
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• v.5 no.5
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• pp.355-361
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• 2000

A recycling reactor system operated under sequential anoxic and oxic conditions for the treatment of swine wastewater has been developed, in which piggery slurry is fermentatively and aerobically treated and then part of the effluent is recycled to the pigsty. This system significantly removes offensive smells (at both the pigsty and the treatment plant), BOD and others, and may be cost effective for small-scale farms. The most dominant heterotrophic were, in order, Alcaligenes faecalis, Brevundimonas diminuta and Streptococcus sp., while lactic acid bacteria were dominantly observed in the anoxic tank. We propose a novel monitoring system for a recycling piggery slurry treatment system through the use of neural networks. In this study, we tried to model the treatment process for each tank in the system (influent, fermentation, aeration, first sedimentation and fourth sedimentation tanks) based upon the population densities of the heterotrophic and lactic acid bacteria. Principal component analysis(PCA) was first applied to identify a relationship between input and output. The input would be microbial densities and the treatment parameters, such as population densities of heterotrophic and lactic acid bacteria, suspended solids(SS), COD, NH$_4$(sup)+-N, ortho-phosphorus (o-P), and total-phosphorus (T-P). then multi-layer neural networks were employed to model the treatment process for each tank. PCA filtration of the input data as microbial densities was found to facilitate the modeling procedure for the system monitoring even with a relatively lower number of imput. Neural network independently trained for each treatment tank and their subsequent combined data analysis allowed a successful prediction of the treatment system for at least two days.

• Journal of the Korea Organic Resources Recycling Association
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• v.22 no.4
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• pp.62-71
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• 2014

Three types of diffuser systems were manufactured and applied to investigate the effect of liquid fertilization of pig manure slurry by application of aeration processes. In the first type reactor, commonly used diffuser system, which diffuse air upward by diffusing aerator fixed at the bottom of the reactor is installed. In case of the second type, air diffuser is installed 10 cm above of the bottom of a reactor. In the third type reactor, the venturi-type air diffuser is installed at circulation pipe, which return pig slurry in the reactor(mixing-in-pipe process). The pig manure slurry separated to solid/liquid was flowed into the experimental reactor, and left as it for one week to precipitate solids. The concentration of organic matter, T-N, T-P and BOD in the raw pig manure slurry flowed into the reactor of bottom-fixed type aeration process were 1.82%, 4,400 mg/L, 360 mg/L and 13,542 mg/L, respectively. After aeration the concentration of organic matters, T-N, T-P and BOD in the slurry were 2.01%, 4,400 mg/L, 420 mg/L and 16,824 mg/L, respectively. The concentration of organic matter, T-N, T-P and BOD in the mixing-in-pipe type changed from 1.58%, 3,700 mg/L, 260 mg/L and 15,735 mg/L to 1.96%, 4,000 mg/L, 340 mg/L, and 18,098 mg/L, respectively. Changes of the concentration of organic matter, T-N, T-P and BOD of the pig manure slurry collected from the middle layers of two aeration reactors; bottom aeration process and the mixing-in-pipe process, were 10.4%, 0%, 16.7% and 24.2% and 24.0%, 8.1%, 30.8% and 15.0%, respectively. The thickness of foam layer generated on the surface of pig manure slurry in aeration tank was thinner in mixing-in-pipe reactor than bottom-fixed type aeration reactor.

• Membrane Journal
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• v.16 no.3
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• pp.182-187
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• 2006

The purpose of this study was to investigate effect of coagulation on filtration performance of membrane in submerged MBR system and influence of continuous aeration to reduce fouling of membrane surface on coagulated floc. For this purpose, aeration tank sludge of MBR system was compared with jar-test sludge. The experimental results were analysed in terms of floc size and SRF (Specific resistance of Filtration). The more alum was added, the more content of floc below $10{\mu}m$ reduced and SRF decreased. But compared with jar-test results, it was found that effect of coagulation on MBR floc was reduced. Operation time of membrane in alum added MBR was longer than that in control MBR. But operation time was not proportional to alum dose. It was thought that the result was reason that floc below $10{\mu}m$ was not reduced sufficiently by shear force of continuous aeration. Moreover it was founded that if alum is added more than proper dose, it brings filtration resistance to increase.

• Journal of Sensor Science and Technology
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• v.9 no.2
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• pp.127-133
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• 2000

We propose a novel monitoring system for a recycling piggery slurry treatment system through neural networks. Here we tried to model treatment process for each tank(influent, fermentation, aeration, first sedimentation and fourth sedimentation tanks) in the system based on population densities of heterotrophic and lactic acid bacteria. Principle component analysis(PCA) was first applied to identify a relation between input(microbial densities and parameters for the treatment) and output, and then multilayer neural networks were employed to model the treatment process for each tank. PCA filtration of input data as microbial densities was found to facilitate the modeling procedure for the system monitoring even with a relatively lower number of input. Neural networks independently trained for each treatment tank and their subsequent combinatorial data analysis allowed a successful prediction of the treatment system for at least two days.

• Journal of Climate Change Research
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• v.7 no.2
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• pp.103-110
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• 2016

In this study, we researched the characteristics of $CH_4$ and $N_2O$ emission of the wastewater treatment (WWT) process in the dairy industry. For flux measurements at the air-water interface, a floating dynamic flow-through chamber was used above the water surface. $CH_4$ and $N_2O$ concentration from the WWT process was measured by NDIR (Non-Dispersive Infrared) Analyser. In the study, $CH_4$ and $N_2O$ fluxes results showed a distinct difference for each WWT process. 60% of the GHG emissions which was the highest percentage were from the equalization tank. Reactor tank was second with 27% of the total emissions from the WWT. Aeration tank was third with 12% of the total emissions. The tendency was that the more the wastewater was treated, the less GHGs were emitted. $CH_4$ and $N_2O$ showed the same tendency. This indicates that the concentrations and properties of wastewater could affect the tendency.

• Journal of Animal Environmental Science
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• v.8 no.1
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• pp.9-16
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• 2002

This study was conducted to develope the new solid separating system which can be efficiently and economically removed the solid parts in high pollutants concentration of pig slurry. The pollutants concentration, BOD$_{5}$ , COD and SS of the slurry used in this study was 15,990($\pm$2,389)mg/l, 20,004($\pm$5,512)mg/l and 26,486($\pm$5,935)mg/l, respectively. After removal of solid part in slurry, the pollutants concentration, BOD$_{5}$, COD and SS was change into 5,617($\pm$690)mg/l, 5,553($\pm$633)mg/land 1,456($\pm$341)mg/l, respectively in the Fixed biological membrane tank. The reduction of the pollutants concentration of suspend liquid through membrane will be allowed to greatly improve the water purification by an Activated sludge method. This separating system consisted of a temporary storage, a circulating tank and a Fixed Biological membrane tank. A temporary storage which has a draining system of screw type and an aeration device played a tremendous role in draining the solid by filled an aeration of 0.3 l/min. A Fixed Biological membrane tank of which a styrofoam filled in a 2/3 volume as a Biological media was fixed by a stainless steel net (pore size : 0.5mm) to separate the liquid layer of influx in them. The separating system efficiency factors were the speed of screw motor, cycle number of slurries in a circulating tank and moisture contents of solid effluent through the screw path. Although the pollutants concentration was very variable in temporary storage, the final concentration of $BOD_5$ and SS, except COD of the suspended liquid in a Fixed biological membrane were not different regardless of cycle number of a circulating tank. Moisture contents of effluent from temporary storage was 73% under the speed 1 ppm of screw motor and 62% under the 1/4rpm of it.