• Journal of Environmental Science International
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• v.22 no.1
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• pp.7-15
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• 2013

Aerosol characterization study for individual particle in Busan metropolitan industrial complex was carried out from December 2010 to August 2011. SEM(scanning electron microscope)-EDX(energy dispersive x-ray) analysis was used for the analysis of 600 single particles during the sampling periods to identify non-metallic aerosol particle sources. Average $PM_{10}$ concentration was 65.5 ${\mu}g/m^3$ in summer, 104.1 ${\mu}g/m^3$ in winter during the sample periods. And Average $PM_{2.5}$ concentration was 24.5 ${\mu}g/m^3$ in summer, 64.5 ${\mu}g/m^3$ in winter individually. Particle density, enrichment factor, correlation analysis, principle component analysis were performed based on chemical composition data. Particle density distribution was measured to 2~4 $g/cm^3$, and the density of $PM_{2.5}$ was measured above 3 $g/cm^3$. In general, the elements Si, Ca, Fe and Al concentrations were higher in all samples of individual particles. The non-ferrous elements Zn, Br, Pb, Cu concentrations were higher in summer than in winter. The concentrations were not changed with the seasons because of non-ferrous industry emission pattern.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.1
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• pp.39-51
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• 2012

Aerosol slurry samples were collected in 60-min interval using Korean Semi-continuous Elements in Aerosol Sampler (KSEAS) between May 19 and June 6, 2010 at an urban site of Gwangju. The $PM_{2.5}$ samples were collected with a flow rate of 16.7 L/min and particles are grown by condensation of water vapor in a condenser maintained at ${\sim}5^{\circ}C$ after saturation by direct injection of steam. The resulting droplets are collected in a liquid slurry with a airdroplet separator. Concentrations of 16 elements (Al, Fe, Mn, Ca, K, Cu, Zn, Pb, Cd, Cr, Ti, V, Ni, Co, As, Se) in the collected slurry samples were determined off-line by ICP-MS. KSEAS sample analysis encompassed the sampling periods for which 24-hr average elemental species concentrations were calculated for comparison with those derived from 24-hr integrated filter samples. Relationship between elemental species measured by two methods indicated high correlation coefficients (r), mostly greater than r of 0.80. However, we note that concentrations of Al, K, Ca, Mn, and Fe, which are often associated with crustal elemental particles, in the KSEAS samples, were substantially lower (1.4~11 times) than those found in the typical filter-based samples. This discrepancy is probably due to difficulties in transferring insoluble dust particles to the collection vials in the KSEAS. Temporal profiles of elemental concentrations indicate that some transient events in their concentrations are observed over the sampling periods. For the elemental species studied, atmospheric concentrations during the transient events increased by factors of 4 in Mn~80 in Zn, compared to their background levels. Principle component analyses were applied to the hourly KSEAS data sets to identify sources affecting the concentrations of the metal constituents observed. In this study, we conclude that hourly measurements for particle-bound elemental constituents were extremely useful for revealing the short-term variability in their concentrations and developing insights into their sources.

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.693-710
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• 2013

This study investigates the distribution of suspended particulates during the Asian dust period in Busan, Korea in the spring of 2009. Weather map and automatic weather system (AWS) data were used to analyze the synoptic weather conditions during the period. Particulate matter 10, laser particle counter data, satellite images and a backward trajectories model were used to analyze the aerosol particles distribution and their origins. In Case 1 (20 February 2009), when the $PM_{10}$ concentration increased, the aerosol volume distribution of small ($0.3-1.0{\mu}m$) particles decreased, while the concentration of large ($1.0-10.0{\mu}m$) particles increased. When the $PM_{10}$ concentration decreased, the aerosol volume distribution was observed to decrease as well. The prevailing winds changed from weak northerly winds to strong southwesterly winds when the concentration of the large particles increased. The correlation coefficient between the $PM_{10}$ concentration and aerosol volume distribution of large particles showed a high positive value of over 0.9. The results from the trajectory model show that the Asian dust originated in the Gobi desert and the Nei Mongol plateau. In Case 2 (25 April 2009), when the $PM_{10}$ concentration increased, the aerosol volume concentration of small ($0.3-0.5{\mu}m$) particles decreased, but the concentration of large ($0.5-10.0{\mu}m$) particles increased. The opposite was observed when the $PM_{10}$ concentration decreased. The prevailing winds changed from northeasterly winds to southwesterly and northeasterly winds. The correlation coefficient between the $PM_{10}$ concentration and aerosol volume distribution of large particles ($1.0-10.0{\mu}m$) showed a high positive value of about 0.9. The results from the trajectory model show that the Asian dust originated in Manchuria and the eastern coast of China.

• Particle and aerosol research
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• v.7 no.3
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• pp.99-108
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• 2011

To establish area specific control strategies for the reduction of the ozone concentration, the Ozone Isopleth Plotting Package for Research(OZIPR) model has been widely used. However, the model results tend to changed by various input parameters such as the background concentration, emission amount of NOx and volatile organic compounds (VOCs), and meteorological condition. Thus, sensitivity analysis should be required to ensure the reliability of the result. The OZIPR modeling results for five local government districts in the Seoul Metropolitan Area (SMA) in June 2000 were used for the sensitivity analysis. The sensitivity analysis result showed that the modeling result of the SMA being VOC-limited region be still valid for a wide range of input parameters' variation. The estimated ozone concentrations were positively related with the initial VOCs concentrations while were negatively related with the initial NOx concentrations. But, the degree of the variations at each local district was different suggesting area specific characteristics being also important. Among the five local governments, Suwon was chosen to identify other variance through the period from April to September in 2000. The monthly modeling results show different ozone values, but still showing the characteristics of VOCs-limited region. Limitations due to not considering long range transport and transfer from neighbor area, limitation of input data, error between observed data and estimated data are all discussed.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.413-421
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• 2016

In this study, correlations between Moderate Resolution Imaging Spectroradiometer (MODIS) derived Aerosol Optical Depth (AOD) values and surface-level $PM_{2.5}$ concentrations at Gosan, Korea have been investigated. For this purpose, data from various instruments, such as satellite, sunphotometer, Optical Particle Counter (OPC), and Micro Pulse Lidar (MPL) on 14-24 October 2009 were used. Direct comparison between sunphotometer measured AOD and surface-level $PM_{2.5}$ concentrations showed a $R^2=0.48$. Since the AERONET L2.0 data has significant number of observations with high AOD values paired to low surface-level $PM_{2.5}$ values, which were believed to be the effect of thin cloud or Asian dust. Correlations between MODIS AOD and $PM_{2.5}$ concentration were increased by screening thin clouds and Asian dust cases by use of aerosol profile data on Micro-Pulse Lidar Network (MPLNet) as $R^2$ > 0.60. Our study clearly demonstrates that satellite derived AOD is a good surrogate for monitoring atmospheric PM concentration.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.19-36
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• 2024

The global seasonal forecasting system version 6 (GloSea6) operated by the Korea Meteorological Administration for 1- and 3-month prediction products does not include complex atmospheric chemistry-aerosol physical processes (UKCA). In this study, low-resolution GloSea6 and GloSea6 coupled with UKCA (GloSea6-UKCA) were installed in a CentOS-based Linux cluster system, and preliminary prediction results for the spring of 2000 were examined. Low-resolution versions of GloSea6 and GloSea6-UKCA are highly needed to examine the effects of atmospheric chemistry-aerosol owing to the huge computational demand of the current high resolution GloSea6. The spatial distributions of the surface temperature and daily precipitation for April 2000 (obtained from the two model runs for the next 75 days, starting from March 1, 2000, 00Z) were compared with the ERA5 reanalysis data. The GloSea6-UKCA results were more similar to the ERA5 reanalysis data than the GloSea6 results. The surface air temperature and daily precipitation prediction results of GloSea6-UKCA for spring, particularly over East Asia, were improved by the inclusion of UKCA. Furthermore, compared with GloSea6, GloSea6-UKCA simulated improved temporal variations in the temperature and precipitation intensity during the model integration period that were more similar to the reanalysis data. This indicates that the coupling of atmospheric chemistry-aerosol processes in GloSea6 is crucial for improving the spring predictions over East Asia.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.93-101
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• 2020

For the first time in Korea, aerosol type was separated as PD (Pure dust), DDM (Dust Dominant Mixed), PDM (Pollution Dominant Mixed), NA (Non-Absorbing), WA (Weakly Absorbing), MA (Moderately Absorbing), and SA (Strongly Absorbing) using depolarization ratio and single-scattering albedo based on AERONET sunphotometer data. Then, seasonal and annual occurrence frequency and AOD variation are analyzed. The proportion of pollution aerosols (NA, WA, MA, SA combined) was 58.9, 46.2, 59.5, and 67.1% at Anmyeon, Gosan, Gwangju, Seoul, respectively, with Seoul being the highest and the lowest at Gosan. Annual rate changestended to increase NA and decrease PD and DDM. The AOD by type showed the highest NA at all sites. In addition, the ratio of NA and AOD continued to increase.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

• Particle and aerosol research
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• v.8 no.3
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• pp.111-120
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• 2012

In Daegu, a road cleaning system was constructed in the central part of the city and has been operated from April, 2011. We evaluated the effect of the system on the concentration of $PM_{10}$ at a roadside monitoring site. The ambient $PM_{10}$ concentration data were logged every 1 min for a period of 20 weeks from May to October, 2011, by means of light scattering method, and then every 5 min data were used in the statistical analysis. The measured data were verified by comparing them with beta-ray data obtained at the same site. Correlation coefficient between the two groups was highly significant (r=0.79), though the absolute levels of light scattering data appeared to be approximately 2.8 times higher than the beta-ray data. Diurnal, daily, weekly, and monthly variations of $PM_{10}$ data did not show any evidence of decreasing effect owing to the clean road system. A comparison of roadside $PM_{10}$ data with non-roadside data also revealed very similar pattern, implying the variation of the $PM_{10}$ concentrations is mainly affected by the traffic conditions near the monitoring site. However, if the operating conditions of the clean road system can be improved, i.e. increasing the frequency and duration of water cleaning, the road cleaning effect may improve the air quality indirectly by means of removing the resuspended particles from the road.