• Journal of Korean Society of Water and Wastewater
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• v.30 no.4
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• pp.427-440
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• 2016

Various kinds of processes are used in the Public Sewage Treatment Works(PSTWs) in order to achieve water quality criteria and TMDL in the watershed. The performance of the existing processes at PSTWs depends on influent characteristics, effluent quality target, amount of sludge production, power cost and other factors. In present, the Selection Guideline for the Available Treatment Process of PSTWs is used for a process decision in the country. But there are some problems regarding redundancy of assessment factors and complexity of assessment procedure in the guideline. In this study, we did a test application of AHP for process selection of PSTWs, which propose is to simplify assessment factors such as pollutant removal amount, sludge generation, electricity consumption, stability of operation, convenience of maintenance, easiness of existing process application, installation cost, and operating cost concerning of environmental factors, technical factors and economical factors. According to the study, the PSTWs selection procedure guideline can be improved using application of AHP method.

• Membrane and Water Treatment
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• v.9 no.5
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• pp.363-371
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• 2018

In this work, it was investigated the usability of artificial bee colony (ABC) and genetic algorithm (GA) in modeling adsorption of Co(II) onto drinking water treatment sludge (DWTS). DWTS, obtained as inevitable byproduct at the end of drinking water treatment stages, was used as an adsorbent without any physical or chemical pre-treatment in the adsorption experiments. Firstly, DWTS was characterized employing various analytical procedures such as elemental, FT-IR, SEM-EDS, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS's Co(II) removal potential was modelled via ABC and GA methods considering the effects of certain experimental parameters (initial pH, contact time, initial Co(II) concentration, DWTS dosage) called as the input parameters. The accuracy of ABC and GA method was determined and these methods were applied to four different functions: quadratic, exponential, linear and power. Some statistical indices (sum square error, root mean square error, mean absolute error, average relative error, and determination coefficient) were used to evaluate the performance of these models. The ABC and GA method with quadratic forms obtained better prediction. As a result, it was shown ABC and GA can be used optimization of the regression function coefficients in modeling adsorption experiments.

• Journal of Korean Society on Water Environment
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• v.22 no.3
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• pp.540-545
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• 2006

The anaerobic digester supernatant (ADS) with high $NH_4-N$ concentration often results in a $NH_4-N$ overloading to the mainstream process of municipal wastewater treatment plant (MWTP). The nitrogen removal from the ADS is therefore important in order to achieve a stable mainstream process performance as well as to prevent $NH_4-N$ overloading due to ADS. Recently because of several advantages compared to the full nitrification, many works have shown interests in controlling the build-up of $NO_2-N$ in nitritation processes. The application of nitritation could save the aeration power compared to the full nitrification processes. In addition, the denitrification of $NO_2-N$ could reduce organic carbon requirements compared to the $NO_3-N$ denitrification. The purpose of this research was to find out the characteristics of the ADS nitritation and $NO_2-N$ accumulating factors from the laboratory reactor study. As a result based on the long-term laboratory experiment, it can be concluded that the degree of nitritation was closely related with the availability of alkalinity, free ammonia (FA), solid retention time (SRT) and solid concentration in the nitritation reactor.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.535-545
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• 2020

This study aims to conserve and monitor energy use in public sewage treatment plants by utilizing data from the SCADA system and by controlling the aeration rate required for maintaining effluent water quality. Power consumption in the sewage treatment process was predicted using the equipment's uptime, efficiency, and inherent power consumption. The predicted energy consumption was calibrated by measured data. Additionally, energy efficiency indicators were proposed based on statistical data for energy use, capacity, and effluent quality. In one case study, a sewage treatment plant operated via the SBR process used ~30% of energy consumed in maintaining the bioreactors and treated water tanks (included decanting pump and cleaning systems). Energy consumption analysis with the K-ECO Tool-kit was conducted for unit processing. The results showed that about 58.7% of total energy consumed was used in the preliminary and biological treatment rotating equipment such as the blower and pump. In addition, the energy consumption rate was higher to the order of 19.2% in the phosphorus removal process, 16.0% during sludge treatment, and 6.1% during disinfection and discharge. In terms of equipment energy usage, feeding and decanting pumps accounted for 40% of total energy consumed following 27% for blowers. By controlling the aeration rate based on the proposed feedback control system, the DO concentration was reduced by 56% compared pre-controls and the aeration amount decreased by 28%. The overall power consumption of the plant was reduced by 6% via aeration control.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.378-384
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• 2019

In the food wastewater treatment facilities, the water quality improvement effect and the greenhouse gas emission amount followed by the change in electricity usage through a change of the aeration tank ventilation system were evaluated. also, the amount of greenhouse gas emission followed by the change in electricity usage through the change of the sludge dewatering, storage, transporting method was also evaluated. The total GHG emission from food wastewater treatment facility improvement were divided into direct emissions from the treatment processes and indirect ones from electricity usage. The water quality improvement effect of wastewater treatment plant was found to be 63.3% for BOD removal rate, 42.0% for COD removal rate, 71.0% for SS removal rate and 39.6% for T-N removal rate. and according to the results of calculating output by applying both direct emissions of greenhouse gas (Scope 1) and the indirect emission (Scope 2) of greenhouse gas followed by changes in power consumption. It was estimated that there was a total of 276.0tCO2eq./yr(7.5%) greenhouse gas reduction effect from 3,668.8tCO2eq./yr before improvement to 3,392.8tCO2eq./yr after improvement. In this result is not due to the effects of water quality improvement of emission source, but because the reduction in electricity use has reduced the amount of greenhouse gas emissions.