• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.2021-2030
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• 2017

In this paper, the unipolar corona-needle charger was developed and its capabilities were both numerically and experimentally investigated. The experimental corona discharges and particle losses in the charger were obtained at different corona voltage, aerosol flow rate and particle diameter for positive and negative coronas. Inside the charger, the electric field and charge distribution and the transport behavior of the charged particle were predicted by a numerical simulation. The experimental results yielded the highest ion number concentrations of about $1.087{\times}10^{15}ions/m^3$ for a positive corona voltage of about 3.2 kV, and $1.247{\times}10^{16}ions/m^3$ for a negative corona voltage of about 2.9 kV, and the highest $N_it$ product for positive and negative coronas was found to about $7.53{\times}10^{13}$ and $8.65{\times}10^{14}ions/m^3$ s was occurred at the positive and negative corona voltages of about 3.2 and 2.9 kV, respectively, and the flow rate of 0.3 L/min. The highest diffusion loss was found to occur at particles with diameter of 30 nm to be about 62.50 and 19.33 % for the aerosol flow rate of 0.3 and 1.5 L/min, respectively, and the highest electrostatic loss was found to occur at particles with diameters of 75 and 50 nm to be about 86.29 and 72.92 % for positive and negative corona voltages of about 2.9 and 2.5 kV, respectively. The numerical results for the electric field distribution and the charged particles migration inside the charger were used to guide the description of the electric field and the behavior of charged particle trajectories to improve the design and refinement of a unipolar corona-needle charger that otherwise could not be seen from the experimental data.

• Particle and aerosol research
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• v.8 no.1
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• pp.17-28
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• 2012

Air pollution levels of gases and aerosol particles inside the Jeongneung and Hongjimun tunnels of the Naebu express way in Seoul were investigated through on-road measurement using a mobile emission laboratory (MEL) on February 8, 2011. The concentrations of $NO_x$, $CO_2$, number concentration of particles ranging 21-560 nm, and surface area of particles deposited on a human lung almost linearly increased with increasing distance from the tunnel entrance, and decreased rapidly before the tunnel exit. This trend was observed regardless of tunnel length and driving directions, which thought to be caused by semi-transverse ventilation facilities of the tunnels. The concentration increments per 1-m distance for $NO_x$, $CO_2$, deposited particle surface area, and number of particles ranging 21-560 nm were 0.61~0.80 ppb, 0.16~0.21 ppm, $0.20{\sim}0.29{\mu}m^2/cm^3$, and 117~192 particles/$cm^3$, respectively. Average pollution levels inside the two tunnels for $CO_2$, deposited particle surface area, and number of particles >5.6 nm ranged 681~748 ppm, $246{\sim}381{\mu}m^2/cm^3$, and $2.4{\sim}6.7{\times}10^5$ particles/$cm^3$, respectively. In case of $NO_x$, the maximum concentration exceeded 1 ppm. These pollution levels inside the tunnels are much higher than those at urban background sites. This result can be utilized as basic data to evaluate the effectiveness of present ventilation system for reducing the pollution level caused by vehicles inside the tunnels.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.1
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• pp.119-129
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• 2005

The ambient TSP data measured at Seoul, Incheon. Taean, Daegu, Busan in Korea were used to explain the chemical composition and general features of Asian Dust (AD) observed in Korea. 9 episodes out of 19 were sampled from 2000 through May 2002, and measurements were conducted covering ionic and metal components with mass concentration. The results showed that daily averaged mass concentration (TSP) during the AD episodes was 458 $\mu\textrm{g}$/㎥, and ionic and metal concentrations were 27.93 $\mu\textrm{g}$/㎥ and 71.7 $\mu\textrm{g}$/㎥, respectively, accounting for 6.1 % and 15.5% of the total aerosol mass. TSP concentrations during episodes were varied from 120 to 1742 $\mu\textrm{g}$/㎥ according to the impact of Asian Dusts and had a tendency of showing higher values at sites in the west side of Korea, which can be explained by the effect of diffusion and deposition. In this study, ionic components like Ca (NO$_3$)$_2$, CaSO$_4$, NaNO$_3$, Na$_2$SO$_4$ were prominent types in secondary aerosol during AD periods and also indicated that V, Co as well as soil elements such as Ca, Fe, Mg, Mn, K correlated well with Al, while Cu, Cd, Pb, Zn didn't agree well with it. In addition, enrichment factors (EFs) for each metal component were obtained to provide simple information about source contribution of Asian Dust, and the results were compared with those from other AD studies. In this study, the results showed that aerosol properties in Korea during the Asian Dust were considerably different from those of general atmospheric condition and specially varied from case to case rather than site to site, which implies that there are certain variations in the soil of source region, pathways of air mass, and meteorological condition. For the enhanced study, those factors should be combined with the features of Asian Dust resolved from this study.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.45-59
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• 2009

This research presents the effect of Asian dust on the derived sea surface temperature (SST) from measurements of the Advanced Very High Resolution Radiometer (AVHRR) instrument flown onboard NOAA polar orbiting satellites. To analyze the effect, A VHRR infrared brightness temperature (TB) is estimated from simulated radiance calculated from radiative transfer model on various atmospheric conditions. Vertical profiles of temperature, pressure, and humidity from radiosonde observation are used to build up the East Asian atmospheric conditions in spring. Aerosol optical thickness (AOT) and size distribution are derived from skyradiation measurements to be used as inputs to the radiative transfer model. The simulation results show that single channel TB at window region is depressed under the Asian dust condition. The magnitude of depression is about 2K at nadir under moderate aerosol loading, but the magnitude reaches up to 4K at slant path. The dual channel difference (DCD) in spilt window region is also reduced under the Asian dust condition, but the reduction of DCD is much smaller than that shown in single channel TB simulation. Owing to the depression of TB, SST has cold bias. In addition, the effect of AOT on SST is amplified at large satellite zenith angle (SZA), resulting in high variance in derived SSTs. The SST depression due to the presence of Asian dust can be expressed as a linear function of AOT and SZA. On the basis of this relationship, the effect of Asian dust on the SST retrieval from the conventional daytime multi-channel SST algorithm can be derived as a function of AOT and SZA.

• Particle and aerosol research
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• v.14 no.4
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• pp.135-144
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• 2018

Based on a two-year measurement data, major sources for the ambient carbonaceous aerosols at the Anmyeon Global Atmosphere Watch (GAW) station were identified by using the Positive Matrix Factorization (PMF) model. The particulate matter less than or equal to $2.5{\mu}m$ in aerodynamic diameter (PM2.5) aerosols were sampled between June 2015 to May 2017 and carbonaceous species including ~80 organic compounds were analyzed. When the number of factors was 5 or 6, the performance evaluation parameters showed the best results, With 6 factor case, the characteristics of transported factors were clearer. The 6 factors were identified with various analyses including chemical characteristics and air parcel movement analysis. The 6 factors with their relative contributions were (1) anthropogenic Secondary Organic Aerosols (SOA) (10.3%), (2) biogenic sources (24.8%), (3) local biomass burning (26.4%), (4) transported biomass burning (7.3%), (5) combustion related sources (12.0%), and (6) transported sources (19.2%). The air parcel movement analysis result and seasonal variation of the contribution of these factors also supported the identification of these factors. Thus, the Anmyeon Island GAW station has been affected by both regional and local sources for the carbonaceous aerosols.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.1
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• pp.17-31
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• 2004

The subway play an important part in serious traffic problems. However, because subway system is a closed environment, many serious air pollution problems occurred in subway stations and injured passenger's health. Therefor, it is a necessary to identify sources and to estimate pollutant sources in order to protect passenger's health and to keep clean subway environment. The purpose of this study was to analyze a air quality in the subway stations and to apply a new receptor methodology for quantitatively estimate of PM10 sources. In this study, the size distributions of particulate matters has been measured by using Aerosizer LD (U.S.A., API, Inc.). It's real time measurement capability of time-of-flight technique offers a significant advantage of user convenience and air pollution management. Also, the mass concentrations of PM 10 has been measured by using mini-vol portable sampler (U.S.A., Airmetrics Co.). The sampling performed in Seoul subway stations during the period of February 2000 and April 2000. The number distribution data used in this study consisted of 26 raw data sets in the Jongno-sam-ga station. Correlation Analysis can be used in subway stations for source separation and identification. Then, number contribution from each source is determined by the particle number balance (PNB). The mass concentration data used in this study consisted of 31 raw data in the 8 different stations. The mass contributions of PM10 sources in the concourse by using PMF/CMB model.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.1
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• pp.51-63
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• 1997

Total suspended particulate matters in the ambient air were analyzed for eight chemical elements (Ca, Co, Cu, Fe, Mn, Pb, Si, and Zn) using an x-ray fluorescence spectrometry (XRF) at the Kyung Hee University - Suwon Campus during 1989 to 1994. To use these data as basis for source identification study, membership of each sample was selected to represent one of the well defined sample groups. The data sets consisting of 83 objects and 8 variables were initially separated into two groups, fine (d$_{p}$<3.3 ${\mu}{\textrm}{m}$) and coarse particle groups (d$_{p}$>3.3 ${\mu}{\textrm}{m}$). A hierarchical clustering method was examined to obtain possible member of homogeneous sample classes for each of the two groups by transforming raw data and by applying various distances. A disjoint principal component analysis was then used to define homogeneous sample classes after deleting outliers. Each of five homogeneous sample classes was determined for the fine and the coarse particle group, respectively. The data were properly classified via an application of logarithmic transformation and Euclidean distance concept. After determining homogeneous classes, correlation coefficients among eight chemical variables within all the homogeneous classes for calculated and meteorological variables (temperature. relative humidity, wind speed, wind direction, and precipitation) were examined as well to intensively interpret environmental factors influencing the characteristics of each class for each group. According to our analysis, we found that each class had its own distinct seasonal pattern that was affected most sensitively by wind direction.ion.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.1
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• pp.1-10
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• 1998

Relationships between TSP and PM10 concentrations were evaluated using their respective data sets collected from Taegu and Kyeungsan areas during the period of December 1993 to November 1994. The collection of data was made using the gravimetric and $\beta$-ray absorption ($\beta$-MPM) methods for 7 days of every month from three urban sites in Taegu and one suburban site in Kyeungsan. Correlation coefficients between TSP and PM10 concentrations for these four sampling sites were found in the range of 0.85 $\sim$ 0.96. Correlation analysis was also conducted for $\beta$-PM concentration data that were measured only from the residential and commercial sites. The correlation coefficients between TSP and $\beta$-PM concentrations were 0.9 in the residential site and 0.8 in the commercial site. By contrast, the correlation coefficients between PM10 $\beta$-PM concentrations were almost identical for both the residential and commercial sites with a value of 0.88. The mean ratio for PM10 to TSP concentrations for all sites was appeared to be 0.68. The analysis of seasonal trends in PM10/TSP ratios showed that the contribution of PM10 to TSP concentrations was more significant during winter (0.70 $\sim$ 0.75) than during summer (0.61 $\sim$ 0.68). The results of this study may provide empirical informations on the compatability of aerosol data measured by different sampling methods.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.342-347
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• 2011

Solar energy is attenuated by absorbing gases (ozone, aerosol, water vapour and mixed gas) and cloud in the atmosphere. And these are measured with solar instruments (pyranometer, phyheliometer). However, solar energy is insufficient to represent detailed energy distribution, because the distributions of instruments are limited on spatial. If input data of solar radiation model is accurate, the solar energy reaches at the surface can be calculated accurately. Recently a variety of satellite measurements are available to TERA/AQUA (MODIS), AURA (OMI) and geostationary satellites (GMS-5, GOES-9, MTSAT-1R, MTSAT-2 and COMS). Input data of solar radiation model can be used aerosols and surface albedo of MODIS, total ozone amount of OMI and cloud fraction of meteorological geostationary satellite. The solar energy reaches to the surface is calculated hourly by solar radiation model and those are accumulated monthly and annual. And these results are verified the spatial distribution and validated with ground observations.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.527-544
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• 2018

This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the $3.7{\mu}m$ and $10.8{\mu}m$ channels of the meteorological imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), with sea surface temperature from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Previous algorithms generally employed threshold values including the brightness temperature difference between the near infrared and infrared. The threshold values were previously determined from climatological analysis or model simulation. Although this method using predetermined thresholds is very simple and effective in detecting low cloud, it has difficulty in distinguishing fog from stratus because they share similar characteristics of particle size and altitude. In order to improve this, the unsupervised learning approach, which allows a more effective interpretation from the insufficient information, has been utilized. The unsupervised learning method employed in this paper is the expectation-maximization (EM) algorithm that is widely used in incomplete data problems. It identifies distinguishing features of the data by organizing and optimizing the data. This allows for the application of optimal threshold values for fog detection by considering the characteristics of a specific domain. The algorithm has been evaluated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) vertical profile products, which showed promising results within a local domain with probability of detection (POD) of 0.753 and critical success index (CSI) of 0.477, respectively.