• Journal of Korean Society for Atmospheric Environment
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• v.18 no.5
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• pp.345-353
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• 2002

A study of polydispersed aerosol dynamics by Electrostatic Precipitator (ESP) was carried out. The log-normal particle size distribution was assumed and moment method was considered. In order to apply moment method in Deutsch-Anderson equation, Cunningham slip correction factor and Cochet's charge equation were simplified for certain range of particle size. The three parameters, which explain the particle size distribution, such as total number concentration, geometric mean diameter, and geometric standard deviation were considered to derive the analytic solution. The obtained solution was compared with available numerical results (Bai et al., 1995). The comparison of the numerical and analytic results showed a good agreement.

• Asian Journal of Atmospheric Environment
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• v.6 no.4
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• pp.304-313
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• 2012

In this study, the ${\AA}$ngstrom exponent for polydispersed aerosol during dynamic processes was investigated. Log-normal aerosol size distribution was assumed, and a sensitivity analysis of the ${\AA}$ngstrom exponent with regards the coagulation and condensation process was performed. The ${\AA}$ngstrom exponent is expected to decrease because of the particle growth due to coagulation and condensation. However, it is difficult to quantify the degree of change. In order to understand quantitatively the change in the ${\AA}$ngstrom exponent during coagulation and condensation, different real and imaginary parts of the refractive index were considered. The results show that the ${\AA}$ngstrom exponent is sensitive to changes in size distribution and refractive index. The total number concentration decreases and the geometric mean diameter of aerosols increase during coagulation. On the while, the geometric standard deviation approaches monodispersed size distribution during the condensation process, and this change in size distribution affects the ${\AA}$ngstrom exponent. The degree of change in the ${\AA}$ngstrom exponent depends on the refractive index and initial size distribution, and the size parameter changes with the ${\AA}$ngstrom exponent for a given refractive index or chemical composition; this indicates that the size distribution plays an important role in determining the ${\AA}$ngstrom exponent as well as the chemical composition. Subsequently, this study shows how the ${\AA}$ngstrom exponent changes quantitatively during the aerosol dynamics processes for a log-normal aerosol size distribution for different refractive indices; the results showed good agreement with the results for simple analytic size distribution solutions.

• Journal of Preventive Medicine and Public Health
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• v.19 no.1 s.19
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• pp.130-136
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• 1986

The particle size of suspended particulates was measured by a Anderson air sampler from Mar. 1982 to Feb. 1984 in a part of Seoul. It was concluded as follows : 1) The arithmetic concentration of suspended particulates was $147.8{\mu}g/m^3$ in Spring, 136.9 in Summer, 131.9 in Autumn and 158.1 in Winter respectively. 2) The cumulative distribution of suspended particulates size in logarithmic diagram showed similar to normal log distribution. 3) The atmospheric particulate matters showed a bimodal size distribution on the base of unit particle concentrations, which divided at approximately $2{\mu}m$ in the diameter. 4) While the fine particulates less than $2.1{\mu}m\;was\;35.4{\sim}45.0%$, the coarse particulates was $55.0{\sim}64.5%$. 5) The higher the concentration of suspended particulates, the more increased the ratio of fine particulates. The higher the concentration of suspended particulates, the lower median size of suspended particulate as well. 6) The respirable dust particulates less than $4.7{\mu}m\;was\;52.2{\sim}62.9%$ in seasonal average through the 2 year samples. With the above result, air pollution concerned with public health could be evaluated and the control measures also are suggested.

• Journal of Environmental Science International
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• v.19 no.3
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• pp.331-342
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• 2010

Aerosol physical properties have been measured at Pusan National University by using the 16-channel LPC(Laser Particle Counter), and particle characteristics have been examined for the period from Aug. 4 2007 to Dec. 30, 2008. Annual total average, seasonal average, and other averages of the meteorologically classified four categories such as Asian dust, precipitation, foggy, and clear days are respectively described here. Both annually and seasonally averaged number concentration show three peaks at the particle diameter of 0.3, 1.3, and $4{\mu}m$, respectively. However, the first peak for summer season tends to be shifted toward smaller size than other seasons, implying the strong fine particle generation. Meteorological condition shows strong contrast in aerosol concentrations. In Asian dust case, relatively lower number concentrations of fine particles (i.e., smaller than $0.5{\mu}m$) were predominant, while higher concentrations of coarse particles were found particularly for the size bigger than $0.5{\mu}m$. In precipitation day, number concentrations were decreased by approximately 30% due to the removal process of precipitation. Foggy day shows significantly higher concentrations for fine particles, implying the importance of the aerosol condensation process of micro-fine-particle growing to fine-particle. Finally the regressed particle size distribution function was fitted optimally with two log-normal distribution, and discussed the similarities and differences among four categorized cases of the Asian dust, precipitation, foggy, and clear days.

• Journal of Korean Society for Atmospheric Environment
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• v.4 no.2
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• pp.57-66
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• 1988

Sandy dust phenomena was observed from April 19 to 23, 1988 in Seoul and suspended particulate was collected by Andersen air sampler during this period. The samples were analyzed for 16 components $(SO_n^{2-}, NO_3^-, Cl^-, PO_4^{3-}, NH_4^+, F^-, Al, Fe, K, Cu, Mn, Na, Pb, Mg, Ca, Cd)$. The conclusions are as follwes: 1. Total suspended particulate concentation during the period of sandy dust phenomena was 489 $\mug/m^3$ (ordinary times: 140-125 $mug/m^3$) 2. The water - soluble ion component concentration of suspended particulate during the period of sandy dust phenomena was few and the metal concentration of that was more than that of ordinary times. 3. The cumulative frequency distribution of suspended particulates in logarithmic diagram did not show similar to normal log distribution during the period of sandy dust phenomena. 4. $SO_4^{2-}, NO_3^-, Cl^-, and PO_4^{3-}$ was onsided to coarse particle, and $NH_4^+$ and F to fine particle in the size distribution of water - soluble ion components during the period of sandy dust phenomena. 5. Metal concentration was high and Al, Fe, Cu, Mn, Na, Mg, and Ca was onsided to coarse particle, and K, Pb, and Cd to fine particle in the size distribution of metal components. 6. During the period of sandy dust phenomena the quantity of respirable particle (< 1 $\mum$) was about 3 times and that of metal components were about 2 - 11 times than that of ordinary times. 7. The concentrations of $NO_3^-, Cl^-, NH_4^+$ at ordinary times were 1.1 - 4 time than that of the period of sandy dust phenomena.

• Journal of Pharmaceutical Investigation
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• v.12 no.4
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• pp.112-125
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• 1982

Sulfamethoxazole particles were microencapsulated using the gelatin-acacia complex coacervation method. Micromeritic properties and dissolution characteristics of the microcapsules were studied. The particle size distribution followed log-normal form. As the hardening time increased, the particle size and wall thickness increased ($45.3-52.0\;{\mu}m$, $2.02-5.12\;{\mu}m$, respectively). This is considered to be due to the cross-linked wall structure of formalized microcapsules which prevents shrinking of gelatin during the dehydration and drying processes. An increase of hardening time clearly delayed the release rate. The in vitro 50% dissolution time $(t_{50})$ for unencapsulated sulfamethoxazole powder was less than 3 min.; for microcapsules hardened for 30 min, the $t_{50}$ was 20.1 min.; for those hardened for 60 min. the $t_{50}$ was 25.0 min.; for those hardened for 120 min., the $t_{50}$ was 35.8 min. The surface of the unhardened microcapsules was smooth and had no cracking or pore penetration. However, the surface of the hardened microcapsules was folded and invaginated.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.2
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• pp.264-274
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• 1997

A numerical analysis on condensation and coagulation of the metallic species with fly ash particles pre-existing in an incinerator was performed. Waste was simplified as a mixture of methane, chlorine, and small amounts of Pb and Sn. Vapor-phase amounts of Pb- and Sn -compounds were first calculated assuming a thermodynamic equilibrium state. Then theories on vapor-to-particle conversion, vapor condensation onto the fly ash particles, and particle-particle interaction were examined and incorporated into equations of aerosol dynamics and vapor continuity. It was assumed that the particles followed a log-normal size distribution and thus a moment model was developed in order to predict the particle concentration and the particle size distribution simultaneously. Distributions of metallic vapor concentration (or vapor pressure) were also obtained. Temperature drop rate of combustion gas, fly ash concentration and its size were selected as parameters influencing the discharged amount of metallic species. In general, the coagulation between the newly formed metal particles and the fly ash particles was much greater than that between the metal particles themselves or between the fly ash particles themselves. It was also found that the amount of metallic species discharged into the atmosphere was increased due to coagulation. While most of PbO vapors produced from the combustion were eliminated due to combined effect of condensation and coagulation, the highly volatile species, PbCl$_{2}$ and SnCl$_{4}$ vapors tended to discharge into the atmosphere without experiencing either the condensation or the coagulation. For Sn vapors the tendency was between that of PbO vapors and that of PbCl$_{2}$ or SnCl$_{4}$. To restrain the discharged amount of hazardous metallic species, the coagulation should be restrained, the number concentration and the size of pre-existing fly ash particles should be increased, and the temperature drop rate of combustion gas should be kept low.

• Proceedings of the Korean Magnestics Society Conference
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• 2012.11a
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• pp.104-105
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• 2012

The temperature dependence of the effective magnetic anisotropy constant K(T) of ferrite nanoparticles is obtained based on the measurements of SQUID magnetometry. For this end, a very simple but intuitive and direct method for determining the temperature dependence of anisotropy constant K(T) in nanoparticles is introduced in this study. The anisotropy constant at a given temperature is determined by associating the particle size distribution f(r) with the anisotropy energy barrier distribution $f_A(T)$. In order to estimate the particle size distribution f(r), the first quadrant part of the hysteresis loop is fitted to the classical Langevin function weight-averaged with the log?normal distribution, slightly modified from the original Chantrell's distribution function. In order to get an anisotropy energy barrier distribution $f_A(T)$, the temperature dependence of magnetization decay $M_{TD}$ of the sample is measured. For this measurement, the sample is cooled from room temperature to 5 K in a magnetic field of 100 G. Then the applied field is turned off and the remanent magnetization is measured on stepwise increasing the temperature. And the energy barrier distribution $f_A(T)$ is obtained by differentiating the magnetization decay curve at any temperature. It decreases with increasing temperature and finally vanishes when all the particles in the sample are unblocked. As a next step, a relation between r and $T_B$ is determined from the particle size distribution f(r) and the anisotropy energy barrier distribution $f_A(T)$. Under the simple assumption that the superparamagnetic fraction of cumulative area in particle size distribution at a temperature is equal to the fraction of anisotropy energy barrier overcome at that temperature in the anisotropy energy barrier distribution, we can get a relation between r and $T_B$, from which the temperature dependence of the magnetic anisotropy constant was determined, as is represented in the inset of Fig. 1. Substituting the values of r and $T_B$ into the $N{\acute{e}}el$-Arrhenius equation with the attempt time fixed to $10^{-9}s$ and measuring time being 100 s which is suitable for conventional magnetic measurement, the anisotropy constant K(T) is estimated as a function of temperature (Fig. 1). As an example, the resultant effective magnetic anisotropy constant K(T) of manganese ferrite decreases with increasing temperature from $8.5{\times}10^4J/m^3$ at 5 K to $0.35{\times}10^4J/m^3$ at 125 K. The reported value for K in the literatures is $0.25{\times}10^4J/m^3$. The anisotropy constant at low temperature region is far more than one order of magnitude larger than that at 125 K, indicative of the effects of inter?particle interaction, which is more pronounced for smaller particles.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.47 no.4
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• pp.177-186
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• 2015

Until Mandelbrot introduced the concept of fractal geometry and fractal dimension in early 1970s, it has been generally considered that the geometry of nature should be too complex and irregular to describe analytically or mathematically. Here fractal dimension indicates a non-integer number such as 0.5, 1.5, or 2.5 instead of only integers used in the traditional Euclidean geometry, i.e., 0 for point, 1 for line, 2 for area, and 3 for volume. Since his pioneering work on fractal geometry, the geometry of nature has been found fractal. Mandelbrot introduced the concept of fractal geometry. For example, fractal geometry has been found in mountains, coastlines, clouds, lightning, earthquakes, turbulence, trees and plants. Even human organs are found to be fractal. This suggests that the fractal geometry should be the law for Nature rather than the exception. Fractal geometry has a hierarchical structure consisting of the elements having the same shape, but the different sizes from the largest to the smallest. Thus, fractal geometry can be characterized by the similarity and hierarchical structure. A process requires driving energy to proceed. Otherwise, the process would stop. A hierarchical structure is considered ideal to generate such driving force. This explains why natural process or phenomena such as lightning, thunderstorm, earth quakes, and turbulence has fractal geometry. It would not be surprising to find that even the human organs such as the brain, the lung, and the circulatory system have fractal geometry. Until now, a normal frequency distribution (or Gaussian frequency distribution) has been commonly used to describe frequencies of an object. However, a log-normal frequency distribution has been most frequently found in natural phenomena and chemical processes such as corrosion and coagulation. It can be mathematically shown that if an object has a log-normal frequency distribution, it has fractal geometry. In other words, these two go hand in hand. Lastly, applying fractal principles is discussed, focusing on pulp and paper industry. The principles should be applicable to characterizing surface roughness, particle size distributions, and formation. They should be also applicable to wet-end chemistry for ideal mixing, felt and fabric design for papermaking process, dewatering, drying, creping, and post-converting such as laminating, embossing, and printing.

• Korean Journal of Soil Science and Fertilizer
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• v.17 no.4
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• pp.343-348
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• 1984

Variation of soil properties within mapping unit of lava plain soils was statistically summarized. Properties such as particle size distribution, moisture retention, color, pH, and CEC are relatively unaffected by soil management while Na, K, base saturation, and available $P_2O_5$ most affected by management. These soils were correctly classified with regard to order at 66.5, to greatgroup at 56.0, and to series at 43.8%. CV values greater than 90% could be symptomatic of skew distribution. Distributions of sand content and some chemical properties were log-normal.