• Journal of Korean Society for Atmospheric Environment
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• v.20 no.6
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• pp.729-738
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• 2004

Seasonal variation of major inorganic ions in the greater Seoul area was estimated using a photochemical box model and a gas/aerosol equilibrium model with emphasis on semi -volatile nitrate. Pollutant emission was determined by season by comparing the predicted concentration with the measurement one obtained for a year from the late 1996. The results showed that particulate nitrate was the highest in summer but about 40% of total nitrate was present in the gas phase. This was due to volatilization at high temperature since ammonia was sufficient to neutralize all nitrate regardless of season. As relative humidity in summer was higher than the deliquescence point, particulate ion concentration with water was two times higher than that in other season. So called ‘NOx disbenefit’ indicating increase in particulate ion concentration with decrease in NOx emission was evident especially in winter.

• Journal of Environmental Impact Assessment
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• v.27 no.2
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• pp.152-169
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• 2018

The purpose of this study was to analyze the effect of adjacentroads on the concentration of negative air ions in urban neighborhood park. The measured factors were negative air ion concentration, positive airion concentration, airtemperature,relative humidity, wind speed, green formation volume factor (GVZ) and distance from highway and general road. The mean negative air ion concentration was $206ea/cm^3$ and the positive air ion concentration was $416ea/cm^3$ in the influence zone of roads. On the other hand, the mean negative air ion was $339ea/cm^3$ and the positive air ion was $229ea/cm^3$ in the unaffected zone of roads, which are inner areas of the park. The difference of the negative air ion concentration according to the influence of the road was statistically significant. The negative air ion concentration model was presented by integrating the correlation analysis with the influence factors, and the explanatory power of the model was increased by adding the influence factor of the road.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1491-1506
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• 2021

To estimate errors in GEMS retrievals for bromine monoxide (BrO) total vertical column densities(VCDs), we perform a sensitivity test using synthetic spectra generated by a radiative transfer model. Hourly synthetic data are produced for 00-07 UTC on the first day of every month in Jul 2013- Jun 2014. Solution errors estimated by the optimal estimation method tend to decrease with increasing air mass factors (AMFs) but increase when AMFs are larger than 5. Interference errors induced by formaldehyde (HCHO) absorption appear to be larger with smaller BrO AMFs. Total BrO retrieval errors estimated by combining solution and interference errors show an average of 26.74±30.18% for all data samples and 60.39±133.78% for those with solar zenith angles higher than 80°. Due to interfering spectral features and measurement errors not considered in thisstudy, errorsin BrO retrievals from actual GEMS measurements may have different magnitudes from our estimates. However, the variability of errors assessed in this study is still expected to appear in the actual BrO retrievals.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.57-65
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• 2021

We propose a novel method to detect abnormal data of specific symptoms using deep learning in air pollution measurement system. Existing methods generally detect abnomal data by classifying data showing unusual patterns different from the existing time series data. However, these approaches have limitations in detecting specific symptoms. In this paper, we use DeepLab V3+ model mainly used for foreground segmentation of images, whose structure has been changed to handle one-dimensional data. Instead of images, the model receives time-series data from multiple sensors and can detect data showing specific symptoms. In addition, we improve model's performance by reducing the complexity of noisy form time series data by using 'piecewise aggregation approximation'. Through the experimental results, it can be confirmed that anomaly data detection can be performed successfully.

• Journal of the Korean earth science society
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• v.23 no.7
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• pp.618-618
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• 2002

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2007.05a
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• pp.247-248
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• 2007

• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.331-331
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• 1998

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2009.06a
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• pp.345-346
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• 2009

• Journal of the Korean hospital association
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• v.26 no.3 s.242
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• pp.16-25
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• 1997

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.1 s.11
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• pp.53-63
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• 1998

The purpose of this study is to investigate the current status of automatic measuring systems for air pollution emissions in Seoul and to suggest an improvement method using GIS and GPS. In Korea, there have been very few critical researches and managements for mobile and area sources regarding moving subjects such as automobiles. In order to control or to make a plan for reducing air pollutions, air pollution emission data based on tim and location, emission inventory systems and emission models should be implemented. Using digital maps and MS Visual Basic, we developed a visualized interface for air pollution emission data from automatic emission measurement systems in Seoul.