• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.49-60
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• 2019

Recently the concentration of fine dust and ultra fine dust becomes so bad, which seriously threatens the health and even the life of people. So, government started to investigate several ways to reduce the amount of fine dust and ultra fine dust. From a few years ago it has been known that ships anchored at port emit a lot of pollution and seriously affect air quality of neighboring cities. To reduce the pollution emitted by ship AMP (Alternative Maritime Power Supply) has been proposed, which uses the electricity instead of bunker C oil or diesel. Many developed countries already installed AMP to improve air quality in port area. Korea is in the stage of planning to install AMP at port. However, there are many complicated problems to be handled before AMP installation. Due to huge initial cost and long period of construction ship owner and habour operating company are reluctant to AMP installation. And there are serious technological difficulties in constructing AMP in existing harbour. Lack of AMP core technology and operational difficulties of AMP are also big challenges to be conquered. In this study SWOT/AHP method is used to find strategic and efficient ways to handle above complicated challenges and then to vitalize the AMP installation.

• Fire Science and Engineering
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• v.31 no.5
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• pp.44-52
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• 2017

This paper is based on a study of the response characteristics of photoelectric type smoke detector chambers according to dust color. Due to an amendment to the Fire Safety Codes to automatic fire alarm systems and visual alarm device, the installation of indoor smoke detectors has become mandatory, but in Korea there is still insufficient research on the non-operation or false alarms that could arise in indoor environments by indoor dust and other environmental conditions etc. In light of this, for this study, research was conducted on the indoor adaptability of smoke detector under various colors of fiber dust that were judged to occur most frequently in among the common indoor dust, photoelectric smoke detector with the lattice-type smoke detection chamber that the smoke detector which is most popular in the country was used, and four colors of fiber dust (brown, white, gray and black) were used the test dusts for carrying out dust and sensitivity testing. Also, the voltage of the photocell part of the smoke chamber was measured, and the scattering phenomenon in the chamber was observed. The result of the testing showed that all four dust types were suitable for dust and sensitivity testing under conditions of pollution A. Yet, there were occasions, at pollution B or C, where the brown, white and gray dust would cause fail alarm during operation testing. And black dust was confirmed to cause non-operation during operation testing. In the case of brown and white dust, the voltage measurement result of the photocell part of the smoke chamber confirmed that the voltage increases as the pollution level increases, and in the case of gray and black dust, the voltage decreases.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.14-26
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• 2022

Recently, according to the severity of air pollution, interest in air pollution is increasing. The IoT based fine dust monitoring system proposed in this paper allows the measurement and monitoring of fine dust, volatile organic compounds, carbon dioxide, etc., which are the biggest causes affecting the human body among air environmental pollution. The proposed system consisted of a device that measures atmospheric environment information, a server system for storing and analyzing measured information, an integrated monitoring management system for administrators and smart phone applications for users to enable visualization analysis of atmospheric environment information in real time. In addition, the effectiveness of the proposed fine dust monitoring system based on the Internet of Things was verified by using the response speed of the system, the transmission speed of the sensor data, and the measurement error of the sensor. The fine dust monitoring system based on the Internet of Things proposed in this paper is expected to increase user convenience and efficiency of the system by visualizing the air pollution condition after measuring the air environment information with portable fine dust measuring device.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.10a
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• pp.345-348
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• 2008

In this paper, we investigated a dust pollution and spot survey of electrical installation in vulnerable area. From the survey results, we know that the dust was easily accumulated in cabinet panel because the cabinet panel cover was opened and the management of installation was not good. Although the dust pollution was not difference, the possibility of accident become increased by dust in salt area. Thus, it is necessary to variation of cabinet panel shape to prevention of electrical disaster in dust occurrence and another protection devices.

• Journal of Environmental Science International
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• v.22 no.9
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• pp.1187-1197
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• 2013

The result of a small electrostatic precipitator which is in order to decrease indoor air pollution for optimal efficiency was shown as follows. Although the closer distance between the discharge electrode and dust collecting electrode shows the better throughput efficiency by forming strong electrostatic Field, it does not have profound impact in case of optimal dust collecting area. G.P(gas passage) which is the distance from dust collecting electrode to dust collecting electrode is a crucial factor to decide dust collecting efficiency. The narrower distance of G.P shows the better throughput efficiency whereas it decreases when the distance is too narrow since sparks ensue by increasing the capacity of electrostatic charging system 5 mm regards as optimal efficiency in this experiment. Although the higher voltage shows the higher dust collecting efficiency overall, the experiment was not able to keep performing since the sparks which decrease dust collecting efficiency ensue over 40 kV. The efficient and safe voltage state is considered 3.6 kV in this experiment. The most crucial factor for dust collecting efficiency of an electrostatic precipitator which is in order to decrease indoor air pollution is applied voltage. In addition, optimal raw gas flow rate(2.4 m/sec) is more important factor than the excessive increase of dust collecting area.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.439-441
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• 2007

The seoul metropolitan subway has installed 8 lines and about 500 stations to transport 5 million passengers everyday. The underground air pollution level in the subway stations is very severe status, which is very harmful to the commutators and its personals. Although subway roles as such a massive and huge transportation system, the subway doesn't adapt yet any real-time air monitoring system. They have only some hand-held type detector equipments for monitoring air pollution. Therefore subway passengers are exposed to the harmful air pollution environment. The most harmful environmental parameters among the air pollution are known as the dust and sound noise dB level in the subway station. Because the dust is consisted of very small particles, we can't see them easily in dark condition on the platform, but it is very harmful. The monitoring system for air pollution is developed using embedded system attached with 6 different environmental sensors. This system monitors air pollution of dust sound noise, gas, temperature, humidity, inflammable gas, toxic gas in the subway ?station. The sensor unit of the ARM-CPU board and sensor transmits real time environmental data to the main server using Zigbee wireless communication module and TCP/IP network. The main control server receives and displays the real-time environmental data, and it send alarms to the personals when high level value.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.328-337
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• 2021

Air pollution, which is a class 1 carcinogen, such as asbestos and benzene, is the cause of various diseases. The spread of ultra-air pollution is one of the important causes of the spread of the corona virus. This paper analyzes and predicts fine dust and ultra-air pollution from 2015 to 2019 based on weather data such as average temperature, precipitation, and average wind speed in Seoul and atmospheric environment data such as SO2, NO2, and O3. Linear regression, SVM, and ensemble models among machine learning models were compared and analyzed to predict fine dust by grasping and analyzing the status of air pollution and ultra-air pollution by season and month. In addition, important features(attributes) that affect the generation of fine dust and ultra-air pollution are identified. The highest ultra-air pollution was found in March, and the lowest ultra-air pollution was observed from August to September. In the case of meteorological data, the data that has the most influence on ultra-air pollution is average temperature, and in the case of meteorological data and atmospheric environment data, NO2 has the greatest effect on ultra-air pollution generation.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.15-20
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• 2023

This study aims to enhance the accuracy of fine dust predictions by analyzing various factors within the local environment, in addition to atmospheric conditions. In the atmospheric environment, meteorological and air pollution data were utilized, and additional factors contributing to fine dust generation within the region, such as traffic volume and electricity transaction data, were sequentially incorporated for analysis. XGBoost, Random Forest, and ANN (Artificial Neural Network) were employed for the analysis. As variables were added, all algorithms demonstrated improved performance. Particularly noteworthy was the Artificial Neural Network, which, when using atmospheric conditions as a variable, resulted in an MAE of 6.25. Upon the addition of traffic volume, the MAE decreased to 5.49, and further inclusion of power transaction data led to a notable improvement, resulting in an MAE of 4.61. This research provides valuable insights for proactive measures against air pollution by predicting future fine dust levels.

• Journal of Environmental Health Sciences
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• v.35 no.4
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• pp.249-258
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• 2009

The objectives of this study were to compare the relative risk of all-cause mortality and cause-specific mortality associated with Asian dust events, and especially to investigate the effects on the susceptible population such as the elderly and children, which were based on the data in Seoul from 2000 to 2006. Both of the study periods with/without Asian dust days, respiratory-cause mortality was the highest, followed by cardiovascular-cause mortality and all-cause mortality in sequence among mortality related to air pollution for all-aged group. As to susceptible group, the relative risk of mortality is the highest for +65 yrs group among all-cause mortality. According to comparison of mortality with/without Asian dust days, the relative risk of all-cause mortality is larger in the model with Asian dust days than the one in the model without Asian dust days among all age group (except for under 15 yrs group) and all air pollutants. The relative risk of cause-specific mortality (except for ozone in under 15 yrs group in case of respiratory-cause mortality, and ozone in all age group and over 65 yrs group in case of cardiovascular-cause mortality) per IQR increase of each pollutant is larger in the model without Asian dust days.

• Atmosphere
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• v.20 no.4
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• pp.483-494
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• 2010

The vertical profiles of the extinction coefficient, the backscatter coefficient, and the lidar ratio (i.e., extinction-to-backscattering ratio) for Asian dust and pollution aerosols are determined from Raman (inelastic) and elastic backscatter signals. The values of lidar ratios during two polluted days is found between 52 and 82 sr (July 22, 2009) and 40~60 sr (July 31, 2009) at 52 nm, with relatively low value of particle depolarization ratio (<5%) and high value of sun photometer-derived Angstrom exponent (> 1.2). However, lidar ratios between 25 and 40 sr are found during two Asian dust periods (October 20, 2009 and March 15, 2010), with 10~20% of particle depolarization ratio and the relatively low value of sun photometer-derived Angstrom exponent (< 0.39). The lidar ratio, particle depolarization ratio and color ratio are useful optical parameter to distinguish non-spherical coarse dust and spherical fine pollution aerosols. The comparison of aerosol extinction profiles determined from inelastic-backscatter signals by the Raman method and from elastic-backscatter signals by using the Fernald method with constant value of lidar ratio (50 sr) have shown that reliable aerosol extinction coefficients cannot be determined from elastic-backscatter signals alone, because the lidar ratio varies with aerosol types. A combined Raman and elastic backscatter lidar system can provide reliable information about the aerosol extinction profile and the aerosol lidar ratio.