• Journal of Korean Society for Atmospheric Environment
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• v.16 no.3
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• pp.211-223
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• 2000

The atmospheric dispersion of a pollutant emitted from a hypothetical source located in the middle of the Yochon Industrial Estate was simulated by using the Regional Atmospheric Modeling System (RAMS). Four horizontally nested grids were employed: the coarsest one covered the southern part of the Korean Peninsula including Mt. Chiri and the finest one covered the Yochon Industrial Estate and the surrounding area. Wind fields were initially assumed horizontally homogeneous with a wind speed of 4m/s, the average for the Yosu area, and were developed without both external forces and diurnal changes in order to investigate the terrain-induced phenomena. Wind directions that could emphasize the terrain effects on the pollutant transport and that could carry pollutants to a highly-popluated area were selected for the dispersion study. A pollutant was released for 24hours from a grid-base volume source after a 24-h blank run for developing the wind field. The dispersion study showed that the pollutant from the present source location did not directly affect the Yosu City, but showed high concentrations at locations behind the hills 5 to 6 km away from the source according to wind directions. When the wind speed was low, close to calm condition, the pollutant was detected at upstream locations 6 to 7 km from the source. In comparison with the results from the RAMS simulation, the Industrial Source Complex Short-Term Model(ISCST3) predicted a narrow dispersion that was sensitive to the wind direction. When the wind velocity was affected by the local environment, the ISCST3 calculation using that data also gave a lop-sided result, which was different from the distribution of the pollutant reproduced by RAMS.

• Journal of Korean Society for Atmospheric Environment
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• v.8 no.3
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• pp.169-178
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• 1992

Dispersion of pollutant in a mountainous area is simulated in a wind tunnel. In the northwest side of the terrain model, the sea level is assumed. Wind from the sea initially confronts hills along the shoreline, a line of large buildings next, and finally a valley between high mountains in the south and in the east. In the northwest wind conditions, severe flow separation occurs in the lee side of hills, even beyond the building area. Pollutant from the buildings is trapped in this region and its concentration is the highest. In the west wind conditions, pollutant from the buildings flows along the hills aslant the main wind direction in this case. Since large valley is located in the downstream, pollutant tends to disperse along the valley.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.2
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• pp.137-145
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• 1997

To predict the effects of air pollutant in the coastal region, we have developed the air pollutant model, the reaction model and the deposition of NO, $NO_2, and O_3$. And the numerical model of air pollutant concentration employed the nested technique to calculate with the higher resolution for the area. The nested technique used two grid systems, one for the large scale calculating region with the coarse mesh grid (CMG) and the other for the small scale region with the fine grid (FMG). In other to prove the validity of the simulation model the calculations were conducted for the present situation. The results of them reasonably agree with the observed data and proved the validity of the model.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 1996.04a
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• pp.34-34
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• 1996

• Journal of Korean Society for Atmospheric Environment
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• v.11 no.E
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• pp.45-54
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• 1995

Indoor air quality models are useful to predict indoor air pollutant concentrations as a function of several indoor factors. Indoor air quality model was developed to evaluate the pollutant removal efficiency of variable-air-volume/bypass filtration system (VAV/BPFS) compared with the conventional variable-air-volume (VAV) system. This model provides relative pollutant removal effectiveness of VAV/BPFS by concentration ratio between the conventional VAV system and VAV/BPFS. The predictions agree closely, from 5 to 10 percent, with the measured values for each energy load. As a results, we recommend the VAV/BPFS is a promising alternative to conventional VAV system because it is capable of reducing indoor air pollutant concentration and maintaining good indoor air quality.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.6
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• pp.813-826
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• 1999

To understand the present status of air pollutant emission data for the greater Seoul area, existing air pollutant emission data were analyzed and compared. For the criteria pollutants, estimation methods of emissions from point, line, and area sources adopted in the previous studies were analyzed and their results were compared. Two sets of VOC emission estimation were also compared and analyzed. There exists a large discrepancy among previous emission data due to the differences in the scope of emission sources and the estimation method including emission factors employed in each estimation. Applications of previous air pollutant emission studies for air quality modeling and related problems were discussed.

• Atmosphere
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• v.25 no.4
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• pp.659-667
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• 2015

In this study, sensitivity of inflow wind speed and turbulent Schmidt number to pollutant dispersion in an urban street canyon is investigated, by comparing CFD-simulated results to wind-tunnel results. For this, we changed systematically inflow wind speed at the street-canyon height ($1.5{\sim}10.0m\;s^{-1}$ with the increment of $0.5m\;s^{-1}$) and turbulent Schmidt number (0.2~1.3 with interval of 0.1). Also, we performed numerical experiments under the conditions that turbulent Schmidt numbers selected with the magnitude of mean kinetic energy at each grid point were assigned in the street canyon. With the increase of the inflow wind speed, the model underestimated (overestimated) pollutant concentration in the upwind (downwind) side of the street canyon because of the increase of pollutant advection. This implies that, for more realistic reproduction of pollutant dispersion in urban street canyons, large (small) turbulent Schmidt number should be assigned for week (strong) inflow condition. In the cases of selectively assigned turbulent Schmidt number, mean bias remarkably decreased (maximum 60%) compared to the cases of constant turbulent Schmidt number assigned. At week (strong) inflow wind speed, root mean square error decreases as the area where turbulent Schmidt number is selectively assigned becomes large (small).

• Journal of Environmental Science International
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• v.3 no.1
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• pp.31-38
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• 1994

The diffusion of the pollutants released into atmosphere is dependent on its chemical reaction, topography and micrometeorological characteristics. The purpose of the study is to investigate how much micrometeorological characteristics such as stability, wind speed and mixing height affect the diffusion of the air pollutants. For this purpose, this paper let 1) the basic theory be K-theory, 2) eddy diffusivity and wind speed be dependent on mixing height and stability, and 3) Grout method be used for numeric calculation. The result was 1) the more unstable condition, the higher mixing height and the higher wind speed we, the lower pollutants concentration appears, 2) the most intensive effect on the distribution of the pollutant concentration is the atmospheric stability.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.3
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• pp.297-310
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• 2007

Recent evidence has demonstrated that the pollutant recirculation can play an important role in leading to high ozone $(O_3)$ concentrations. In this study, the MM5-CAMx air quality modeling system was applied to simulate the pollutant recirculation and identify the transport of pollution during the high $O_3$ event (the maximum $O_3$ of 195 ppb) observed in the Greater Seoul Area (GSA) on $1{\sim}4$ June in 2004. The results showed a weak northeasterly synoptic wind during the night and early morning moved the air parcels containing the locally emitted urban pollution to the coast, which contributed to enhance $O_3$ formation in the southwest part of the GSA. As the sea breeze developed and started to penetrate inland in the late afternoon, the rapid build-up of $O_3$ concentration was found in the southwest coastal area due to the recirculation of the polluted air loaded with high level $O_3$. The simulated backward trajectories and observations at coastal sites confirmed the recirculation of pollutant with the late sea breeze is the dominant factor affecting the occurrence of high $O_3$ concentrations in the southwestern GSA.

• Atmosphere
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• v.34 no.3
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• pp.283-304
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• 2024

This study analyzed the variability and correlation between ground-level air pollutant concentrations and the atmospheric mixing layer height using data from four types of air pollutants (PM_2.5, PM₁₀, NO₂, and O₃) collected at AirKorea monitoring stations nationwide over a five-year period (2018~2022), and aerosol backscatter data observed by the Vaisala CL31 to derive atmospheric mixing layer heights. The five-year trends and variability of ground-level air pollutant concentrations under seasonal and hourly conditions were examined, as well as the seasonal distribution and diurnal variation of the atmospheric mixing layer height. Five correlation coefficient methodologies were applied to analyze the correlations between ground-level air pollutants and atmospheric mixing layer height under various seasonal and hourly conditions, confirming the dilution effect of the atmospheric mixing layer height. The results showed that PM_2.5, PM₁₀, and NO₂ generally had negative correlations with the atmospheric mixing layer height, while O₃ showed a strong positive correlation up to an altitude of 1,200~1,500 meters, and a negative correlation beyond that altitude. It was also shown that a single high concentration event (e.g., PM₁₀) can alter the overall correlation. The correlation can also vary depending on the characteristics of the correlation coefficient methodology, highlighting the importance of applying the appropriate methodology for each case during the analysis process.