• Journal of Korean Society for Atmospheric Environment
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• v.31 no.3
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• pp.209-222
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• 2015

Fine and coarse PM had been collected by LVCI (low volume cascade impactor) and HVAS (high volume air sampler) during January 1989 to April 2012 at Kyung Hee University, Global Campus located on the boarder of Yongin and Suwon. The database of PM mass concentration was constructed and then intensively and extensively investigated to understand monthly, seasonal, and annual patterns of each PM behavior. Especially the study separated all the PM data into the 5 Period Zones, which were classified on the basis of social, political, and environmental issues that might be influencing local ambient air quality during the monitoring period. The overall $PM_{10}$ level had been continuously decreased until 2005 and after then was staggering due to rapidly increasing $PM_{2.5}$ level in $PM_{10}$. The annual average of $PM_{2.5}$ concentration varied from $34.3{\mu}g/m^3$ to $59.0{\mu}g/m^3$, which were much higher than the 2015 ambient air quality standard. The $PM_{2.5}$ level was strongly associated with haze events, while both $PM_{10}$ and $PM_{2.5}$ levels were associated with Yellow storm events. Daily concentrations of $PM_{2.5}$ were ranged $13.1{\sim}212.9{\mu}g/m^3$ in haze days and $33.6{\sim}124.6{\mu}g/m^3$ in Asian dust days. The study also intensively investigated annual and seasonal patterns of $PM_{2.5}/PM_{10}$ ratios.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.E
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• pp.19-27
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• 2000

Particle Induced X-ray Emission (PIXE) and Elemental Analysis Syztem (EAS) were applied to the investiga-tion of the Characteristics and sources of wintertime atmospheric aerosols in Seoul. Atmospheric aerosols were collected by both fine and coarse fractions using a two-stage filter pack sampler from Kon-Kuk university during the winter season of 1999. PIXE was applied to the analysis of the middle and heavy elements with atomic numbers greater than 14(Si) and EAS was applied to the measurement of the light elements such as H, C and N. The fact that 64.2% of mass of fine particles in Seoul consists of the light elements (N, C , and H) suggests that the measurement of light elements is extremely important. The average mass concentration is Seoul was 38.6$\mu\textrm{g}$m(sup)-3. Elements such as Ca, Fe, Mg, and Ti appeared to have very low Fine/Coarse ratios(0.1∼0.4), whereas che-mical components related to anthropogenic sources such as Br, V, Pb, and Zn were observed to accumulate in the fine fraction. In the Asian Dust Storm(ADS) event, the concentation of soil components increased dramatically. Reconstruction of the fine mass concentrations estimated by a newly revised simple model was fairly in good agreement with the measured ones. Source identification was attempted using the enrichment factor and Pearsons coefficient of correlation. The typical elements derived from each source could be classified by this method.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.3
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• pp.329-341
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• 2005

The purpose of this study is to study the $PM_{2.5}$ source characteristics affecting the Seoul area using a chemical mass balance (CMB) receptor model. This study was also to evaluate the $PM_{2.5}$ source profiles, which were directly measured and developed. Asian Dust Storm usually occurred in the spring, and very high $PM_{2.5}$ concentrations were observed in the fall among the sampling periods. So the ambient data collected in the spring and fall were evaluated. The CMB model results as well as the $PM_{2.5}$ source profiles were validated using the diagnostic categories, such as: source contribution estimate, t-statistic, R-square, Chi-square, and percent of total mass explained. In the spring months, the magnitude of $PM_{2.5}$ mass contributors was in the following order: Chinese aerosol $(31.7\%)>$ secondary aerosols ($22.3\%$: ammonium sulfate $13.4\%$ and ammonium nitrate $8.9\%)>$ vehicles ($16.1\%$: gasoline vehicle $1.4\%$ and diesel vehicles $14.7\%)>$biomass burning $(15.5\%)>$ geological material $(10.5\%)$. In the fall months, the general trend of the $PM_{2.5}$ mass contributors was the following: biomass burning $(31.1\%)>$ vehicles ($26.9\%$: gasoline vehicle $5.1\%$ and diesel vehicles $21.8\%)>$ secondary aerosols ($23.0\%$: ammonium sulfate $9.1\%$ and ammonium nitrate $13.9\%)>$ Chinese aerosol $(10.7\%)$. The results show that the $PM_{2.5}$ mass in the Seoul area was mainly affected by the Chinese area.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.449-458
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• 2012

Using the MODerate resolution Imaging Spectro-radiometer (MODIS) retrieved aerosol optical thickness (AOT) along with ground measurements of PM2.5 mass concentration, we assessed local air quality over Dukjuk and Jeju island and estimated possibility of satellite derived PM2.5 during nine intensive observation periods in 15 October 2005 - 24 October 2007. Averaged PM2.5 mass concentrations showed relatively variable as $25.61{\pm}22.92{\mu}g/m^3$ at Dukjuk and $17.33{\pm}10.79{\mu}g/m^3$ at Jeju. The maximum values of $188.89{\mu}g/m^3$ (Dukjuk) and $50.46{\mu}g/m^3$ (Jeju) were recorded during Asian dust storm day. Similarly, the maximum values of MODIS AOT were found as 3.73 (Gosan) and 1.14 (Jeju). Averaged MODIS AOTs at Dukjuk ($0.79{\pm}0.81$) were larger than that at Jeju ($0.42{\pm}0.24$). An empirical relationship between MODIS AOT and PM2.5 mass was obtained and results show that there was a good correlation between satellite and ground based values with a linear correlation coefficient of 0.85 at Dukjuk. The result clearly demonstrates that satellite derived AOT is a good surrogate for monitoring PM air quality over study area. However, meteorological and other ancillary datasets are necessary to further apply satellite data for air quality research.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.366-375
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• 1998

Optical characteristics of the yellow sand and their influences on the ocean color remote sensing has been studied using ocean color sensor SeaWiFS measurements. Two cases of April 18 and April 25, 1998, representing yellow sand and background aerosol, are selected for emphasizing the impact of high aerosol concentration on the ocean color remote sensing. It was shown that NASA's standard atmospheric correction algorithm treats yellow sand area as either too high radiance or cloud area, in which ocean color information is not generated. Optical thickness of yellow sand arrived over the East Asian sea waters in April 18 indicates that there are two groups loaded with relatively homogeneous yellow sand, i.e.: heavy yellow sand area with optical thickness peak around 0.8 and mild area with about 0.4, which are consistent with ground observations. The movement of the yellow sand area obtained from surface weather maps and backward trajectory analysis manifest the notion that the weak yellow sand area was originated from the outer region of the dust storm. It is also noted that high optical thickness associated with the yellow sand is significantly different from what we may observe from background aerosol, which is about 0.2. These characteristics allow us to determine the yellow sand area with an aid of atmospheric correction parameter. Results indicate that the yellow sand area can be determined by applying the features revealed in scattergrams of atmospheric correction parameter and optical thickness.