• Asian Journal of Atmospheric Environment
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• v.5 no.1
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• pp.8-20
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• 2011

Atmospheric visibility is one of the indicators used to evaluate the status of air quality. Based on a conceptual definition of visibility as the maximum distance at which the outline of the selected target can be recognized, an image analysis technique is introduced here and an algorithm is developed for visibility monitoring. Although there are various measurement techniques, ranging from bulk and precise instruments to naked eye observation techniques, each has their own limitations. In this study, a series of image analysis techniques were introduced and examined for in-situ application. An imaging system was built up using a digital camera and was installed on the study sites in Incheon and Seoul separately. Visual range was also monitored by using a dual technology visibility sensor in Incheon and transmissometer in Seoul simultaneously. The Sobel mask filter was applied to detect the edge lines of objects by extracting the high frequency from the digital image. The root mean square (RMS) index of variation among the pixels in the image was substantially correlated with the visual ranges in Incheon and Seoul with correlations of $R^2$=0.88 and $R^2$=0.71, respectively. The regression line equations between the visual range and the RMS index in Incheon and Seoul were VR=$2.36e^{0.46{\times}(RMS)}$ and VR=$3.18e^{0.15{\times}(RMS)}$, respectively. It was also confirmed that the fine particles ($PM_{2.5}$) have more impacts to the impairment of visibility than coarse particles.

• Journal of Korean Society for Atmospheric Environment
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• v.5 no.2
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• pp.55-71
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• 1989

This study was carried out to determine the ozone concentration to behaviour and the factors to be influenced the variation of its concentration in the ambient air in Seoul. Measurements of ozone concentrations were made at 10 monitoring station to take care of SIHE (Seoul Institute of Health & Environment) during December 1987 to November 1988, also measured the hourly average concentration of sulfur dioxide, total suspended particulate, nitrogen oxide $(NO & NO_2)$, carbon monoxide, hydro carbon $(n-CH_4 & THC)$ and meteorological factors, that is, temperature, humidity, wind velocity wind direction and ultraviolet intensity etc, for the same period at same place. The basis of the data obtained were analyzed statistically along with the various data. The results were as follows; 1. The annually arithmetic mean concentration of ozone for the 10 sites during one years was 10.0 ppb and ranged from 3.1 $\pm$ 4.5ppb at the Kuro industrial complex to 17.2 $\pm$ 18.7 ppb at the Ssangmun site. 2. The frequency of hours on which oxidant concentrations exceeded the present short term standard of ozone (100 ppb) were 78 times. 3. The diurnal patterns of hourly ozone concentrations in Seoul area was a typical bi-modal variation which have 4 to 5 a.m. peak and 3. to 4 p.m peak. 4. The time ozone of highest ozone concentration in a whole day and hight was 1 to 5 p.m and 90.9 percent of appearence rate. 5. The diurnal patterns of hourly ozone concentrations in Seoul were on the whole the order of daytime from 5.8ppb to 28.7 ppb evening from 1.7 to 18.7 ppb night time from 1.9 to 9.3 ppb daybreak from 1.4ppb according to measuring sites, and the highest that observed at the Ssangmun area while the lowest was the Kuro industrial complex monitor sites. 6. The weekly variation of ozone concentration was the higher level ozone concentration in the day of the week occured sunday-monday and weekend but the decrease were observed from wednesday to thursday.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.132-137
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• 2017

Drone is currently used for wide application areas in our real life. Also it performs more important functions. We propose a method of drone operation system for the prevention of industrial disaster. In normal operation of drone system the drone monitors the industrial sites according to the planned flight path with acquiring the monitored images and send the image information to the server. The server analyzes and compares the images to DB information by calculating the similarity based on the threshold. Then the system decides whether the industrial sites has problems or not. If the abnormal condition is occurred, the drone change the flight path to abnormal flight path and keep monitoring the industrial sites with measuring the air status by sensors and sends all information to server system on the ground. If the emergency case is occurred, drone approaches the closest position of accident points and acquiring the all information and send them to server and 119 center.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.137-147
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• 2012

Land surface temperature in ecohydrology is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. And there are an insufficient number of soil temperature monitoring stations. In this study, a grid-based land surface temperature prediction model is proposed. Target sites are Andong and Namgang dam region. The proposed model is run in the following way. At first, geo-referenced site specific air temperatures are estimated using a kriging technique from data collected from 60 point weather stations. Then surface soil temperature is computed from the estimated geo-referenced site-specific air temperature and normalized difference vegetation index. After the model is calibrated with data collected from observed remote-sensed soil temperature, a soil temperature map is prepared based on the predictions of the model for each geo-referenced site. The daily and monthly simulated soil temperature shows that the proposed model is useful for reproducing observed soil temperature. Soil temperatures at 30 and 50 cm of soil depth are also well simulated.

• Journal of Environmental Health Sciences
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• v.30 no.5 s.81
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• pp.417-426
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• 2004

We investigate changing characteristics and concentration distribution of ambient air quality using data from which obtained local ambient air monitoring network and local meterological measuring sites in Gwangju area from January to December in 2003. Sulfur dioxide ($SO_2$) showed that increase from 8 AM and decrease in 6 PM but, it was not drastically changed concentration. it also 0.010 ppm in 1995 from at this time it's decrease step by step and than some constant in year 2001 to 2003. Nitrogen dioxide ($NO_2$) concentration was showed highest peak in 10 AM and increase again at 6 PM. And also it showed peak concentration (0.026 ppm) in 2001 and decreased from after that times. Ozone was showed peak concentration in 1 PM and Nitrogen dioxide was ditto in 10 AM from this data, we can conclude that this two article ws showed chemical reaction by 3 to 5 hours. There was no case of Ozone alarm in Gwangju area since 1995, but it showed highest ozone concentration (over 0.070 ppm) in May and June of the year and 2 to 4 PM of the day and sometimes it showed increase at the dawn. Ozone product optimum condition was that air temperature is over $25^{\circ}C$, no rain and increase solar radiation (over $20MJ/m^2$) and no wind or below 2.0 m/s wind speed.

• Journal of Environmental Science International
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• v.1 no.2
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• pp.33-48
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• 1992

Since November 1990, the observations of methane (CH4) level have been carried out at Tae-ahn Peninsula (TAP) in Korea. Analysis on atmospheric data obtained in the period from November 1990 to August 1992 is carried out and the results are included in this study. We 임ole that CIL does not have a clear seasonal cycle with a minor maximum in August- september and with a minimum in June-July. The variations in monthly average level are much larger with 1765.01∼ 1857.21 pub (amplitude 92.20 ppb). The occurrence of a minimum in June-July is due to the inflow of the North Pacific air, an increase of OH radical and due to a decrease in CH4 emission from rice paddy. A maximum in August and September appears to result from an increase in organic materials in agriculture (rice paddy) and forests, inputs of local sources due to weak airflows, stagnation of the warm and moist air and from a decrease in OH radical.'rho present analysis indicates that according to CH4 data from Mongolia and from several sites in North Pacific TAP is influenced as much as 31 pub in average from the inputs of Chinese omission. When the atmospheric CH4 of TAP is compared with data observed at Korea National University of Education (KNU), the values of KNU are higher (127 ppb) than those of TAP. It is clear that air samples taken at KNU are influenced strongly by local sources in central Korea than those at TAP. According to analysis of trajectories and airflows, we find that there are 4 types in classification. Firstly, when an air flow is originated mainly in China values of CH4 gas are in medium ranges. Secondly, when an airflow is from both local (Korea) and China we find higher values. Thirdly, with an airflow from both local (Korea) and Japan origins medium values are recorded. Fourths)r, when an airflow of maritime origin arrives low values of atmospheric CH4 are observed at TAP.

• Journal of Environmental Science International
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• v.24 no.12
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• pp.1559-1567
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• 2015

This study investigated the association between $PM_{2.5}$ concentrations obtained with portable real-time monitors and those obtained with gravimetric methods in national urban air-quality monitoring sites in Seoul, South Korea. We used the SidePak AM510 Personal Aerosol Monitor (TSI Inc., 500 Cardigan Road Shoreview, MN) and DustTrak DRX 8533 (TSI Inc., 500 Cardigan Road Shoreview, MN) as portable real-time monitors for measuring $PM_{2.5}$ concentrations and compared these values with those measured with the PMS-103 or SEQ 47/50 models operated by Federal Reference Method (FRM) or the European Committee for Standardization(ECS), respectively, in national urban air-quality monitoring sites in Seoul. Measurements were conducted every other day in the winter and spring seasons of 2014. The estimated daily mean concentrations of $PM_{2.5}$ ranged between 13.4 and $161.9{\mu}g/m^3$ using AM 510 and between 22.0 and $156.0{\mu}g/m^3$ using DustTrak. The Spearman correlation coefficient for $PM_{2.5}$ concentrations between AM 510 and gravimetric results was 0.99, and the correlation between DustTrak and gravimetric results was 0.87. The correction factor suggested was 0.42 and 0.29 for AM 510 and DustTrak, respectively. We found that $PM_{2.5}$ concentrations measured with real-time monitors could overestimate true $PM_{2.5}$ concentrations and therefore the application of a correction factor (0.43) is strongly suggested for quantification when Real-time monitors were operated of $PM_{2.5}$ levels at urban atmospheric environment of South Korea.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1711-1720
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• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.57-81
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• 2019

Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.103-111
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• 2022

Fine dust can cause serious problems to human health, and fugitive dust generated at construction sites is one of the main sources of fine dust in Korea. However, monitoring of the amount of fugitive dust generated at the ready-mixed concrete plant site is not performed, and only passive monitoring methods are partially applied in the field. Since it is impossible to control fugitive dust after it is exposed to the air, it is very important to suppress the occurrence or to remove it immediately at the stage of occurrence. Therefore, after identifying the characteristics through real-time monitoring in the fugitive dust generation stage, systematic management is required for suppressing or removing scattering dust in the field. In this study, the scattering dust generation characteristics were analyzed by measuring the particle mass concentration(PMC) of Fugitive dust generated at the aggregate unloading site of the ready-mixed concrete plant in real-time.