• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.04a
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• pp.93-94
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• 2008

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2006.04a
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• pp.283-284
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• 2006

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.10a
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• pp.359-360
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• 2008

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2009.10a
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• pp.489-490
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• 2009

• Asian Journal of Atmospheric Environment
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• v.12 no.3
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• pp.244-254
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• 2018

Ulaanbaatar, the capital of Mongolia, is subject to high levels of atmospheric pollution during winter, which severely threatens the health of the population. By analyzing surface meteorological data, ground-based LIDAR data, and radiosonde data collected from 2008 to 2016, we studied seasonal variations in particulate matter (PM) concentration, visibility, relative humidity, temperature inversion layer thickness, and temperature inversion intensity. PM concentrations started to exceed the 24-h average standard ($50{\mu}g/m^3$) in mid-October and peaked from December to January. Visibility showed a significant negative correlation with PM concentration. Relative humidity was within the range of 60-80% when there were high PM concentrations. Both temperature inversion layer thickness and intensity reached maxima in January and showed similar seasonal variations with respect to PM concentration. The monthly average temperature inversion intensity showed a strong positive correlation with the monthly average $PM_{2.5}$ concentration. Furthermore, the temperature inversion layer thickness exceeded 500 m in midwinter and overlaid the weak mixed layer during daytime. Radiative cooling enhanced by the basin-like terrain led to a stable urban atmosphere, which strengthened particulate air pollution.

• Atmosphere
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• v.29 no.4
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• pp.439-450
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• 2019

Present weather plays an important role not only for atmospheric sciences but also for public welfare and road safety. While the widely used state-of-the-art visibility and present weather sensor yields present weather, a single type of measurement is far from perfect to replace long history of human-eye based observation. Truly automatic present weather observation enables us to increase spatial resolution by an order of magnitude with existing facilities in Korea. 8 years of human-eyed present weather records in 19 sites over Korea are compared with visibility sensors and auxiliary measurements, such as humidity of AWS. As clear condition agrees with high probability, next best categories follow fog, rain, snow, mist, haze and drizzle in comparison with human-eyed observation. Fog, mist and haze are often confused due to nature of machine sensing visibility. Such ambiguous weather conditions are improved with empirically induced criteria in combination with visibility and humidity. Differences between instrument manufacturers are also found indicating nonstandard present weather decision. Analysis shows manufacturer dependent present weather differences are induced by manufacturer's own algorithms, not by visibility measurement. Accuracies of present weather for haze, mist, and fog are all improved by 61.5%, 44.9%, and 26.9% respectively. The result shows that automatic present weather sensing is feasible for operational purpose with minimal human interactions if appropriate algorithm is applied. Further study is ongoing for impact of different sensing types between manufacturers for both visibility and present weather data.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.6
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• pp.863-875
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• 2006

Intensive visibility monitoring was conducted to investigate physical and chemical characteristics of visibility impairment by airborne pollen. Light attenuation coefficients were optically measured by a transmissometer, a nephelometer, and an aethalometer. Elemental, ionic, and carbonaceous species were chemically analyzed on the filters collected by $PM_{2.5}$ and $PM_{10}$ samplers. Aerosol size distribution was analyzed using a cascade impactor during airborne pollen period. Airborne pollen count was calculated using a scanning electron microscope. Airborne pollen was emitted into the atmosphere in springtime and funker degraded visibility through its scattering and absorbing the light. Average light extinction coefficient was measured to be $211{\pm}36Mm^{-1}$ when airborne pollen was not observed. But it increased to $459{\pm}267Mm^{-1}$ during the airborne pollen period due to increase of average $PM_{2.5}$ and $PM_{10}$ mass concentration and relative humidity and airborne pollen count concentration for $PM_{10}$, which were measured to be $46.5{\pm}29.1{\mu}g\;m^{-3},\;97.0{\pm}41.7{\mu}g\;m^{-3},\;54.1{\pm}11.6%$, and $68.2{\pm}89.7m^{-3}$, respectively. Average light extinction efficiencies for $PM_{2.5}$ and $PM_{10}$ were calculated to be $5.9{\pm}0.9$ and $4.5{\pm}0.8m^2 g^{-1}$ during the airborne pollen period. Light extinction efficiency for $PM_{10}$ increased further than that for $PM_{2.5}$. The average light extinction budget by airborne pollen was estimated to be about 24% out of the average measured light extinction coefficient during the airborne pollen period.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.707-723
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• 2020

In this study, a decision tree type of quality control (QC) method was developed to improve the temporal-spatial representation and accuracy of the visibility data being operated by the Korea Meteorological Administration (KMA). The quality of the developed QC method was evaluated through the application to the 3 years (2016.03-2019.02) of 290 stations visibility data. For qualitative and quantitative verification of the developed QC method, visibility and naked-eye data provided by the KMA and QC method of the Norwegian Meteorological Institute (NMI) were used. Firstly, if the sum of missing and abnormal data exceeds 10% of the total data, the corresponding point was removed. In the 2nd step, a temporal continuity test was performed under the assumption that the visibility changes continuously in time. In this process, the threshold was dynamically set considering the different temporal variability depending on the visibility. In the 3rd step, the spatial continuity test was performed under the assumption of spatial continuity for visibility. Finally, the 10-minute visibility data was calculated using weighted average method, considering that the accuracy of the visibility meter was inversely proportional to the visibility. As results, about 10% of the data were removed in the first step due to the large temporal-spatial variability of visibility. In addition, because the spatial variability was significant, especially around the fog area, the 3rd step was not applied. Through the quantitative verification results, it suggested that the QC method developed in this study can be used as a QC tool for visibility data.

• Asian Journal of Atmospheric Environment
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• v.4 no.3
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• pp.115-140
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• 2010

Great concerns about atmospheric aerosols are attributed to their multiple roles to atmospheric processes. For example, atmospheric aerosols influence global climate, directly by scattering or absorbing solar radiations and indirectly by serving as cloud condensation nuclei. They also have a significant impact on human health and visibility. Many of these effects depend on the size and composition of atmospheric aerosols, and thus detailed information on the physicochemical properties and the distribution of airborne particles is critical to accurately predict their impact on the Earth's climate as well as human health. A single particle analysis technique, named low-Z particle electron probe X-ray microanalysis (low-Z particle EPMA) that can determine the concentration of low-Z elements such as carbon, nitrogen and oxygen in a microscopic volume has been developed. The capability of quantitative analysis of low-Z elements in individual particle allows the characterization of especially important atmospheric particles such as sulfates, nitrates, ammonium, and carbonaceous particles. Furthermore, the diversity and the complicated heterogeneity of atmospheric particles in chemical compositions can be investigated in detail. In this review, the development and methodology of low-Z particle EPMA for the analysis of atmospheric aerosols are introduced. Also, its typical applications for the characterization of various atmospheric particles, i.e., on the chemical compositions, morphologies, the size segregated distributions, and the origins of Asian dust, urban aerosols, indoor aerosols in underground subway station, and Arctic aerosols, are illustrated.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.369-370
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• 2000

동북아시아에서 화석연료의 연소로부터 배출되는 인위적 대기오염물질의 증가는 심각한 문제로 대두되고 있다. 우리 나라의 경우는 도시화, 인구 밀집과 자동차의 증가로 인한 대기오염물질 배출은 대도시에서 공기질 저하를 야기하고 있다. 특히, 서울 지역은 가시도(Visibility), 오존 등의 심각한 공기오염문제를 경험하고 있다. 이러한 대기오염은 국지적 기상변화에 따라 발생하는 도시형 스모그나 안개과 밀접한 관계가 있는 것으로 추정되며, 발생시 에어로졸의 특성변화가 예상되고 있으나, 스모그나 안개 발생시 에어로졸의 특성이나 고도 분포에 대한 연구는 미흡한 실정에 있다. (중략)