• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.92-96
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• 2000

In this experiment, we studied about concentration characteristics of $NO_x$ and generation of ozone in the reactor of corona discharge type by using mixed gas of $NO/N_2$ and $N_2/O_2$. In the case of the initial NO concentration increased, decrease rate of NO concentration was weakened and discharge input power of minimum NO concentration became high. When NO concentration was high, NO decomposition limit was appeared. And NO reduction rate was decreased, when initial NO concentration and discharge input power increased. When discharge input power was 5W, we could know the most proper energy value for treatment of NO. When the concentration of initial NO increased, generation of ozone decreased and in the case of same concentration of NO, according to discharge input power increase, generation of ozone increased.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1122-1137
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• 2021

PM_2.5 concentration in Seoul could be predicted by deep neural network model. In this paper, the contribution of input factors to the model's prediction results is analyzed using the LRP(Layer-wise Relevance Propagation) technique. LRP analysis is performed by dividing the input data by time and PM concentration, respectively. As a result of the analysis by time, the contribution of the measurement factors is high in the forecast for the day, and those of the forecast factors are high in the forecast for the tomorrow and the day after tomorrow. In the case of the PM concentration analysis, the contribution of the weather factors is high in the low-concentration pattern, and that of the air quality factors is high in the high-concentration pattern. In addition, the date and the temperature factors contribute significantly regardless of time and concentration.

• Journal of Environmental Science International
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• v.15 no.7
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• pp.635-642
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• 2006

Present study evaluated the low-temperature destruction of n-hexane and benzene using mesh-type transition-metal platinum(Pt)/stainless steel(SS) catalyst. The parameters tested for the evaluation of catalytic destruction efficiencies of the two volatile organic compounds(VOC) included input concentration, reaction time, reaction temperature, and surface area of catalyst. It was found that the input concentration affected the destruction efficiencies of n-hexane and benzene, but that this input-concentration effect depended upon VOC type. The destruction efficiencies increased as the reaction time increased, but they were similar between two reaction times for benzene(50 and 60 sec), thereby suggesting that high temperatures are not always proper for thermal destruction of VOCs, when considering the destruction efficiency and operation costs of thermal catalytic system together. Similar to the effects of the input concentration on destruction efficiency of VOCs, the reaction temperature influenced the destruction efficiencies of n-hexane and benzene, but this temperature effect depended upon VOC type. As expected, the destruction efficiencies of n-hexane increased as the surface area of catalyst, but for benzene, the increase rate was not significant, thereby suggesting that similar to the effects of the re- action temperature on destruction efficiency of VOCs, high catalyst surface areas are not always proper for economical thermal destruction of VOCs. Depending upon the inlet concentrations and reaction temperatures, almost 100% of both n-hexane and benzene could be destructed, The current results also suggested that when applying the mesh type transition Metal Pt/SS catalyst for the better catalytic pyrolysis of VOC, VOC type should be considered, along with reaction temperature, surface area of catalyst, reaction time and input concentration.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.4
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• pp.41-49
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• 2023

This study examined the effect of input substrate concentration on hydrogen production of microbial electrolysis cells. To compare the performance of MEC according to the input substrate concentration, six laboratory-scale MEC reactors were operated by sequentially increasing the input substrate concentration from 2 g/L of sodium acetate, to 4 g/L, and 6 g/L. The current density, hydrogen production, and SCOD removal rate were analyzed, and energy efficiency and cathodic hydrogen recovery were calculated to compare the performance of MEC. The maximum volumetric current density was obtained at 4 g/L condition (76.3 A/m³) and it decreased to 19.0 A/m³, when the input concentration was increased to 6 g/L, which was a 75% decrease compared to the 4 g/L input condition. Maximum hydrogen production was obtained also at 4 g/L condition (47.3 ± 16.8 mL), but maximum hydrogen yield was obtained at 2 g/L input condition (1.1 L H₂/g COD_in). Energy efficiencies were also highest in 2 g/L condition; the lowest result was observed at 6 g/L condition. Maximum electrical energy efficiency was 76.4%, and the maximum overall energy efficiency was 39.7% at 2 g/L condition. However, when the substrate concentration increased to 6 g/L, the performance was drastically decreased. Cathodic hydrogen recovery also showed a similar tendency with energy efficiency, with the lowest concentration condition showing the best performance. It can be concluded that operating at low input substrate concentration might be better when considering not only hydrogen yield but also energy efficiency.

• Journal of Korean Society for Atmospheric Environment
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• v.5 no.1
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• pp.1-10
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• 1989

The sensitivity analysis is a method to quantify to what extent the output of a model changes with the values of input parameters. This will lead to increase model accuracy through measurement validation. Three line source air quality models, HIWAY 2, PAL, and CALINE 3 were selected for this study. The input parameters analysed included wind speed, wind direction, stability, emission rate, mixing height, receptor distance, initial dispersion coefficient, surface roughness, and averaging time. It turned out that PAL model generally showed higher concentration than other two models, and that between CALINE 3 and HIWAY 2, CALINE 3 showed higher concentration than HIWAY 2 model near the line sources, but beyond a certain downwind distances HIWAY 2 model showed higher concentration. The modesl were very sensitive to wind speed especially in the range of 0 $\sim$ 1 m/s and to wind direction near the parallel wind to streets. In case of emission rate, the output concentration was directly proportional to these input parameters. And the sensitivity of the input parameters such as stability, mixing height, initial dispersion coefficient, surface roughness, and averaging time were not very significant.

• Microbiology and Biotechnology Letters
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• v.17 no.6
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• pp.629-633
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• 1989

In the continuous reactor, the hydrogen production rate and residual glucose concentration were increased with increase of input glucose concentration, dilution rate, and recycle rate. The maximum production rate was 91 mL/Lㆍh at dilution rate 0.4/h, input glucose concentration 5.4g/L, and recycle rate 70/h in this experimental range.

• KSBB Journal
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• v.8 no.3
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• pp.243-255
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• 1993

In this study, it was observed that hydrogen Productivity varied with stirrer speed, bead radius, input glucose concentration and dilution rate in a continuous stirred tank reactor in which immobilized R. rubrum KS-301 was used as a hydrogen-producing bacterium The mass transfer resistance due to cell immobilization was also studied. In order to estimate an effectiveness factor, Des of glucose was first obtained, which was subsequently represented by the correlation equation between Dos and Xb, As a result external mass transfer resistance could be neglected for stirrer speeds greater than 400rpn With bead radius increasing, the hydrogen productivity and internal effectiveness factor decreased. With input 91ucose concentration increasing, the hydrogen productivity and interval and external effectiveness factor increased. Although an Internal effectiveness factor was not affected, hydrogen productivity Increased with dilution rate increasing. An overall effectiveness factor remained nearly constant for the dilution rates investigate4 but increased with input 91ucose concentration increasing.

• Journal of Environmental Science International
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• v.20 no.4
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• pp.501-509
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• 2011

Unlike many laboratory-scale studies on absorption of organic compounds (VOCs), limited pilot-scale studies have been reported. Accordingly, the present study was carried out to examine operation parameters for the effective control of a hydrophilic VOC (methyl ethyl ketone, MEK) by applying a circular pilot-scale packed-absorption system (inside diameter 37 cm ${\times}$ height 167 cm). The absorption efficiencies of MEK were investigated for three major operation parameters: input concentration, water flow rate, and ratio of gas flow-rate to washing water amount (water-to-gas ratio). The experimental set-up comprised of the flow control system, generation system, recirculation system, packed-absorption system, and outlet system. For three MEK input concentrations (300, 350, and 750 ppm), absorption efficiencies approached near 95% and then, decreased gradually as the operation time increased, thereby suggesting a non-steady state condition. Under these conditions, higher absorption efficiencies were shown for lower input concentration conditions, which were consistent with those of laboratory-scale studies. However, a steady state condition occurred for two input concentration conditions (100 and 200 ppm), and the difference in absorption efficiencies between these two conditions were insignificant. As supported by an established gas-liquid absorption theory, a higher water flow rate exhibited a greater absorption efficiency. Moreover, as same with the laboratory-scale studies, the absorption efficiencies increased as water-to-gas ratios increased. Meanwhile, regardless of water flow rates or water-to-gas ratios, as the operation time of the absorption became longer, the pH of water increased, but the elevation extent was not substantial (maximum pH difference, 1.1).

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.1
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• pp.62-69
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• 2021

This study aimed to verify the suitability of an air quality regulating service for wetland ecosystem service evaluation by investigating the effect of reducing particulate matter (PM) on vegetation in wetlands. We installed tunnel-type experimental plots at Yonghwasil Pond in the National Institute of Ecology and set up the input and output of PM by applying the natural vegetation of the relevant wetlands. We took measurements by replicating four different conditions four times each. The air quality regulating service in each experimental plot was measured based on PM10 concentration; further, the difference between the input and the output concentration of PM passing through the Phragmites australis community tunnel was measured using a light scattering method. For the Phragmites australis community in the outdoor conditions and bare land, the PM concentration was measured with the same specifications as tunnel-type experimental plots without setting up the input and output. For the tunnel-type experimental plots, PM10 concentration was significantly lower in the output than in the input. Furthermore, in the outdoor conditions, a comparison between the Phragmites australis community and bare land showed that the concentration was relatively low in the former than in the latter. This confirmed the PM reducing effect due to the blockage and absorption of PM depending on the growth of Phragmites australis. Based on the results of this study, we assessed the air quality regulating service in wetlands as an evaluation indicator.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1414-1424
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• 2021

In this paper, the importance of input factors of a DNN (Deep Neural Network) PM_2.5 forecasting model using LRP(Layer-wise Relevance Propagation) is analyzed, and forecasting performance is improved. Input factor importance analysis is performed by dividing the learning data into time and PM_2.5 concentration. As a result, in the low concentration patterns, the importance of weather factors such as temperature, atmospheric pressure, and solar radiation is high, and in the high concentration patterns, the importance of air quality factors such as PM_2.5, CO, and NO₂ is high. As a result of analysis by time, the importance of the measurement factors is high in the case of the forecast for the day, and the importance of the forecast factors increases in the forecast for tomorrow and the day after tomorrow. In addition, date, temperature, humidity, and atmospheric pressure all show high importance regardless of time and concentration. Based on the importance of these factors, the LRP_DNN prediction model is developed. As a result, the ACC(accuracy) and POD(probability of detection) are improved by up to 5%, and the FAR(false alarm rate) is improved by up to 9% compared to the previous DNN model.