• Atmosphere
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• v.32 no.2
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• pp.119-133
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• 2022

From 2015 to 2021, high-concentration fine dust episodes with a daily average PM_2.5 concentration of 50 ㎍ m^-3 or higher were selected and classified into 3 types [long range transport (LRT), mixed (MIX) and Local emission and stagnant (LES)] using synoptic chart and backward trajectory analysis. And relationships between the fine particle data (PM_2.5 and PM₁₀ concentration and PM_2.5/PM₁₀ ratio) and meteorological data (PBLH, Ta, WS, U-wind, and Rainfall) were analyzed using hourly observation for the classification episodes on the Korean Peninsula and the Seoul metropolitan area (SMA). In LRT, relatively large particles such as dust are usually included, and in LES, fine particle is abundant. In the Korean peninsula, the rainfall was relatively increased centered on the middle and western coasts in MIX and LES. In the SMA, wind speed was rather strong in LRT and weak in LES. In LRT, rainfall was centered in Seoul, and in MIX and LES, rainfall appeared around Seoul. However, when the dust cases were excluded, the difference between the LRT and other types of air quality was decreased, but the meteorological variables (Ta, RH, Pa, PBLH, etc.) were further strengthened. In the case of the Korean Peninsula, it is difficult to find a clear relationship because regional influences (topographical elevation, cities and coasts, etc.) are complexly included in a rather wide area. In the SMA, it is analyzed that the effects of urbanization such as the urban heat island centered on Seoul coincide with the sea and land winds, resulting in a combination of high concentrations and meteorological phenomena.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.6
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• pp.412-420
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• 2014

Water quality variations were investigated at 4 locations of Jungrang river (upper, middle and lower basins) during a period of 3 rainfall events. During the rainfall, concentrations of $COD_{Mn}$, SS and $BOD_5$ significantly increased, while the concentration of T-N decreased and that of T-P remained relatively constant. This pattern became more apparent as the level of accumulative precipitation and rainfall intensity increased. Simple regression analysis showed that the accumulative precipitation was positively correlated with all water quality pollutants except for T-N. With increasing accumulative precipitation, the concentration of T-N decreased, while the others increased. $R^2$ of simple regressions of hourly average rainfall intensity and water quality pollutants, showed wider range of variation ranged from 0.483 to 0.992, which indicated a strong correlation. The stronger the hourly average rainfall intensity, the more T-N and T-P in the upper basin, more $COD_{Mn}$ in the middle and lower basins, more SS with gradual increase from upper to lower areas, and more $BOD_5$ with gradual decrease from upper to lower region. Simple regression showed that water quality pollution in the upper basin was more sensitive to an increase of rainfall discharge than that in the middle and lower areas.

• Journal of Environmental Science International
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• v.23 no.11
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• pp.1889-1907
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• 2014

The characteristics of meteorological conditions related to changes in atmospheric environment on Jeju Island were investigated during recent years (2010-2012). This analysis was performed using the hourly observed data of meteorological variables (air temperature, wind speed and direction) and air pollutants ($O_3$, $PM_{10}$, $SO_2$, $NO_2$, and CO). Out of 5 pollutants, $O_3$ and $PM_{10}$ concentrations have frequently exceeded national environmental standards in the study area during the study period, with relatively higher concentrations than the others. The concentrations of $O_3$ and $PM_{10}$ in 2010 and 2011 were somewhat higher than those in 2012, and their highest concentrations were mostly observed in spring followed by fall. Nighttime $O_3$ concentrations (with relatively high concentration levels) were almost similar to its daytime concentrations, due to less $O_3$ titration by very low NO concentrations in the target area and in part to $O_3$ increase resulting from atmospheric transport processes. The transport effect related to the concentration variations of $O_3$ and $PM_{10}$ was also clarified in correlation between these pollutants and meteorological variables, e.g. the high exceedance frequency of concentration criteria with strong wind speed and the high concentrations with the westerly/northwesterly winds (e.g., transport from the polluted regions of China). The overall results of this study suggest that the changes in atmospheric environment in the study area were likely to be caused by the transport effect (horizontal and vertical) due to the meteorological conditions rather than the contribution of local emission sources.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.13 no.3
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• pp.245-253
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• 2001

Mixing zone characteristics of the wastewater effluents discharged from Sokcho ocean outfall have been investigated using an outfall mixing zone model which was developed on the basis of Huang et al.'s(1996) analysis method. The model was applied to Sokcho ocean outfall case and was used to simulate the concentration distribution of wastewater effluents using winter season's data, ie. daily effluent flowrate, ocean current and density stratification data which were measure for two months in the outfall area. Hourly concentration distribution of outfall effluent discharges was calculated and they were averaged for the period of 15 days which covers the ambient flow variability of the neap and the spring tidal currents. The results show that near-field dilution was relatively high with the minimum dilution of 130 for the winter season. The mixing zone was extended to the coastal beach area rather than offshore because of major direction of coastal currents. This may cause a deteriorating impact on coastal water quality, especially to the adjacent swimming beach area.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.5
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• pp.513-525
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• 2016

To propose an effective ensemble methods in predicting $PM_{10}$ concentration, six experiments were designed by different ensemble average methods (e.g., non-weighted, single weighted, and cluster weighted methods). The single weighted method was calculated the weighted value using both multiple regression analysis and singular value decomposition and the cluster weighted method was estimated the weighted value based on temperature, relative humidity, and wind component using multiple regression analysis. The effects of ensemble average methods were significantly better in weighted average than non-weight. The results of ensemble experiments using weighted average methods were distinguished according to methods calculating the weighted value. The single weighted average method using multiple regression analysis showed the highest accuracy for hourly $PM_{10}$ concentration, and the cluster weighted average method based on relative humidity showed the highest accuracy for daily mean $PM_{10}$ concentration. However, the result of ensemble spread analysis showed better reliability in the single weighted average method than the cluster weighted average method based on relative humidity. Thus, the single weighted average method was the most effective method in this study case.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.5
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• pp.545-557
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• 2011

The objective of this study was to estimate the trends of each pollutant using the air pollution monitoring networks data from January 2005 to December 2008 in Daegu area. Also, the spatial characteristics of each pollutant were determined using the Pearson correlation coefficients and COD (coefficients of divergence). In this study, the trends of hourly, monthly, seasonal, and total average concentrations of each pollutant for the 10 sites were analyzed. The Ihyeon site showed highest concentration for the $SO_2$, $NO_2$, and PM10}. In the case of $O_3$, the Jisan site showed highest concentration among the other sites. Also, industrial area presented highest concentration for the $SO_2$, CO, and PM10. On the other hand, $NO_2$ showed highest in commercial area. The IDW (inverse distance weighting) method was used to estimate characteristics of spatial distribution. The results provide identify spatial distribution for each pollutant. Also, the Pearson correlation coefficients and COD values provide spatial variability among the monitoring sites. The COD of each pollutant showed very low values for all of the sites pairs. On the other hand, the Pearson correlation coefficients showed high values for all of the sites pairs. Finally, analysis of spatial variability can be used to characterize the spatial uniformity and similarity of concentrations from each pollutant.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.3
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• pp.310-320
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• 2008

Concentration of tropospheric ozone ($O_3$) was investigated for the South Korea. And then the critical ozone levels, expressed as AOT40 (Accumulated exposure over a threshold of 40 ppb) to vegetation have been used in this region within the UNECE (United Nations Economic Commission for Europe) Convention on Long-Range Trans-boundary Air Pollution (CLRTAP). Hourly ozone concentration data from 1996 to 2001 at 26 air monitoring stations was used to estimate the exceedance of the critical levels. It was calculated for daylight hours for each station, and mapped using surface interpolation over the South Korea. The critical levels of ozone have shown the highly exceeded value in the Gyeonggi region, southern coastal region and central inland of the South Korea. It was some different from the typical ozone distribution which represented highly in the western inland and coastal regions. The area exceeding the critical level for crops was founded to be more than 40% of the whole South Korean territory. While that for trees was to be about 17% of the South Korea. The critical ozone critical level was based upon data from experiments on specific species, and thus may not be fully representative for all types of vegetation. Nevertheless, the critical level and its exceedance of the ozone concentration would be one of the useful tools for international agreements on abatement strategies to prevent ecosystem damage.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.1
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• pp.49-60
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• 2000

The concentration of atmospheric mercury(Hg0 and relevent environmental parameters that include both meteorological and criteria pollutant data were dtermined at hourly intervals during two field campaigns covering the periods of September 1997 and May/June 1998. The mean concentrations of Hg for the two study periods were computed as 3.94 and 3.43ngm-3, respectively. Through a separation of these data into both daytime and nighttime periods, we further analyzed diurnal variation patterns for Hg between two different seasons. Using our Hg data sets, we were able to recognize two contrasting diurnal variation patterns of Hg between two diffeerent seasons that can be characterized as: (1) the occurrences of peak Hg concentration during daytime(fall0 and (2) slight reductions in daytime Hg concentration relative to nighttiime Hg data(summer). To study the systematic differences in diurnal patterns between two different seasons, we analyzed Hg data in terms of different statistical approaches such as correlation(and linear regression0 and factor analysis. Results of these analyses consistently indicated that different mechanisms were responsible for controlling the daytime distribution patterns of Hg. The variation of boundary layer conditions betwen day/night periods may have been important in introducing the relative reduction in daytime Hg levels during summer. However, when the relationship between Hg and concurrently determined O3 is concerned, these differences are unlikely to be an effective sink mechanism within the ranges of ozone concentrations determined concurrently during this study, regardless of season. To further provide the general account for short-term variations in Hg distribution data, we should be able to describe the various factors underlying its sink mechanism.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.1
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• pp.82-99
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• 2016

This study was carried out to understand the regional contribution of Particulate Matter (PM) emissions from East Asia ($82^{\circ}{\sim}149^{\circ}E$, $18^{\circ}{\sim}53^{\circ}N$) to Seoul during high concentration period in February 2014. The Community Multi-scale Air Quality (CMAQ) version 5.0.2 with Decoupled Direct Method (DDM) was used to analyze levels of contributions over Seoul. In order to validate model performance of the CMAQ, predicted PM and its chemical species concentrations were compared to observations in China and Seoul. Model predictions could depict the daily and hourly variations of observed PM. The calculated PM concentrations, however, had a tendency of underestimation. The discrepancies are due to uncertainties of meteorological data, emission inventories and CMAQ model itself. The high PM concentration in Seoul was induced by stationary anticyclone over the West Coast of Korea during 24 to 27 February. The DDM in CMAQ was used to analyze the contributions of emissions from East Asia on Seoul during this PM episode. $PM_{10}$ concentration in Seoul is contributed by 39.77%~53.19% from China industrial and urban region, 15.37%~37.10% from South Korea, and 9.03%~18.05% North Korea. These indicate that $PM_{10}$ concentrations in Seoul during the episode period are dominated by long-range transport from China region as well as domestic sources. It was also found that the largest contribution region in China were Shandong peninsula during the PM event period.

• Asian Journal of Atmospheric Environment
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• v.5 no.1
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• pp.29-40
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• 2011

In this study, the effects of an urban thermal environment on air quality were investigated using hourly surface weather observation data and air quality data over six summers from 2000 to 2005 in two cities on the Korean Peninsula. One, the city of Daegu, is representative of basin topography and the other, the city of Busan, represents a coastal area. It is known that the characteristics of an urban thermal environment are represented as an "urban heat island". Here, we focus on the nighttime urban thermal environment, which is called a "tropical night", during the summer. On tropical nights in Busan, the temperature and cloud cover levels were higher than on non-tropical nights. Wind speed did not appear to make a difference even on a tropical night. However, the frequency of southwestern winds from the sea was higher during tropical nights. The prevailing southwest winds in all areas meant an inflow of air from the sea. So at most of the air quality stations, the ozone concentration during tropical nights was lower than during non-tropical nights. In Daegu, the tropical nights had higher temperatures and cloud covers. Despite these higher temperatures, the ozone concentration during the tropical nights was lower than that on non-tropical nights at most of the air quality stations. This feature was caused by low irradiance, which in turn caused an increased cloud cover. Wind speed was stronger during the tropical nights and dispersed the air pollutants. These meteorological characteristics of the tropical nights reduced ozone concentrations in the Daegu Basin.