• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.04b
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• pp.121-125
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• 2000

An ozone condenser by a selective adsorption on the silica gel surface is constructed. Ozone density is evaluated by three methods; ultraviolet absorption, thermal decomposition and Q-mass analyzing methods. Thermal decomposition method is found to be available to the density evaluation from dilute to highly condensed ozone. The highest ozone density condensed by the adsorption method is evaluated to be 97 mol%.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.10a
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• pp.45-49
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• 2000

An ozone condenser by a selective adsorption on the silica gel surface is constructed. Ozone density is evaluated by three methods; ultraviolet absorption, thermal decomposition and Q-mass analyzing methods. Thermal decomposition method is found to be available to the density evaluation from dilute to highly condensed ozone. The highest ozone density condensed by the adsorption method is evaluated to be 97 mol%.

• Transactions on Electrical and Electronic Materials
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• v.2 no.2
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• pp.42-45
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• 2001

An ozone condensation system is evaluated from the viewpoint of an ozone supplier for Bi-superconductor thin film growth. An ozone condenser by a selective adsorption on the silica gel surface is constructed. Ozone density is evaluated by three methods; ultraviolet absorption, thermal decomposition and Q-mass analyzing methods. Thermal decomposition method is found to be available to the density evaluation from dilute to highly condensed ozone. The highest ozone density condensed by the adsorption method is evaluated to be 97 mol%.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.135-147
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• 2017

We, for the first time, estimated daily and monthly surface nitrogen dioxide ($NO_2$) volume mixing ratio (VMR) using three regression models with $NO_2$ tropospheric vertical column density (OMIT-rop $NO_2$ VCD) data obtained from Ozone Monitoring Instrument (OMI) in Seoul in South Korea at OMI overpass time (13:45 local time). First linear regression model (M1) is a linear regression equation between OMI-Trop $NO_2$ VCD and in situ $NO_2$ VMR, whereas second linear regression model (M2) incorporates boundary layer height (BLH), temperature, and pressure obtained from Atmospheric Infrared Sounder (AIRS) and OMI-Trop $NO_2$ VCD. Last models (M3M & M3D) are a multiple linear regression equations which include OMI-Trop $NO_2$ VCD, BLH and various meteorological data. In this study, we determined three types of regression models for the training period between 2009 and 2011, and the performance of those regression models was evaluated via comparison with the surface $NO_2$ VMR data obtained from in situ measurements (in situ $NO_2$ VMR) in 2012. The monthly mean surface $NO_2$ VMRs estimated by M3M showed good agreements with those of in situ measurements(avg. R = 0.77). In terms of the daily (13:45LT) $NO_2$ estimation, the highest correlations were found between the daily surface $NO_2$ VMRs estimated by M3D and in-situ $NO_2$ VMRs (avg. R = 0.55). The estimated surface $NO_2$ VMRs by three modelstend to be underestimated. We also discussed the performance of these empirical modelsfor surface $NO_2$ VMR estimation with respect to otherstatistical data such asroot mean square error (RMSE), mean bias, mean absolute error (MAE), and percent difference. This present study shows a possibility of estimating surface $NO_2$ VMR using the satellite measurement.