• Particle and aerosol research
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• v.18 no.1
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• pp.9-21
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• 2022

In this study, a novel antiviral coating method for the air filtration system of subway station was investigated. Using dry aerosol coating process, we developed a high-performance antiviral air filter with spark discharger and carbon brush type ionizer. Silver nanoparticles were produced by a spark discharge generation system with ion injection system and were used as antiviral agents coated onto a medium grade air filter. The pressure drop, filtration efficiency, and antiviral ability of the filter against aerosolized MS2 virus particles as a surrogate of SARS-CoV-2 virus were tested with dust contamination. Dust contamination caused the increase of the filtration efficiency and pressure drop, while the antiviral agents (in this study, silver nanoparticles) coating did not have any significant effect on the filtration efficiency and pressure drop. Using these properties, we suggested a novel method to maximize the antiviral performance of the antiviral air filter that was contaminated by dust particles. Moreover theoretical analysis of antiviral ability with dust contamination and re-coated antiviral agents was carried out using a mathematical model to calculate the time-dependent antiviral effect of the filter under actual conditions of subway station. Our model can be used to apply on antiviral air filtration system of subway station for prevention of pandemic diffusion, and predict the life cycle of an antiviral filter.

• Tuberculosis and Respiratory Diseases
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• v.60 no.6
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• pp.663-672
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• 2006

Background: $PM_{10}$(Particulate matter with a diameter ($<10{\mu}m$), which is characterized by different environmental conditions, is a complex mixture of organic and inorganic compounds. The Asian dust event caused by meteorological phenomena can also produce unique particulate matter in affected areas. This study investigated the cytokine produced by A549 epithelial cells exposed to particles collected during both the Asian dust pfenomenon and ambient air particles in a non-dusty period. Method: Air samples were collected using a high volume air sampler(Sibata Model HV500F) with an air flow at $500{\ell}/min$ for at least 6 hours. The cytokine messenger RNA(mRNA) was measured using a reverse transcriptase polymerase chain reaction(RT-PCR). The A549 cells were exposed to 10 to $500{\mu}g/m{\ell}$ of a suspension containing $PM_{10}$ for 24 hours. Each was compared with those in the non-exposed control cells. Result: The mRNA levels of interleukin(IL)-$1{\alpha}$, $IL-I{\beta}$, IL-8, and the granulocyte macrophage colony stimulating factor(GM-CSF) increased after veing exposed to $PM_{10}$ in the ambient air particles, compared with those in the non-exposed control cells. The increase in $IL-1{\alpha}$ and IL-8 were dose dependent at a $PM_{10}$ concentration between $100{\mu}g/m{\ell}$ and $500{\mu}g/m{\ell}$. The mRNA level of IL-8 in the A549 epithelial cells was higher during the in the Asian dust period($500{\mu}g/m{\ell}$) than during the non dust period. Conclusion: A549 cells exposed to the $PM_{10}$ collected during the Asian dust period produce more proinflammatory cytokine than during non-dusty period. This cytokine enhances the local inflammatory response in the airways and can also contribute to the systemic component of this inflammatory process.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.597-605
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• 2014

The continuous observations for atmospheric aerosols were conducted during 3 years (2009 to 2011) by using Gwangju Institute of Science and Technology (GIST) multi-wavelength Raman lidar at Gwangju, Korea ($35.10^{\circ}N$, $126.53^{\circ}E$). The aerosol depolarization ratios calculated from lidar data were used to identify the Asian dust layer. The optical properties of Asian dust layer were different according to its vertical distribution. In order to investigate the difference between the optical properties of each individual dust layers, the transport pathway and the transport altitude of Asian dust were analyzed by Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We consider that the variation of optical properties were influenced not only their transport pathway but also their transport height when it passed over anthropogenic pollution source regions in China. The lower particle depolarization ratio values of $0.12{\pm}0.01$, higher lidar ratio of $67{\pm}9sr$ and $68{\pm}9sr$ at 355 nm and 532 nm, respectively, and higher ${\AA}ngstr\ddot{o}m$ exponent of $1.05{\pm}0.57$ which are considered as the optical properties of pollution were found. In contrast with this, the higher particle depolarization ratio values of $0.21{\pm}0.09$, lower lidar ratio of $48{\pm}5sr$ and $46{\pm}4sr$ at 355 nm and 532 nm, respectively, and lower ${\AA}ngstr\ddot{o}m$ exponent of $0.57{\pm}0.24$ which are considered as the optical properties of dust were found. We found that the degree of mixing of anthropogenic pollutant aerosols in mixed Asian dust govern the variation of optical properties of Asian dust and it depends on their altitude when it passed over the polluted regions over China.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.2
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• pp.68-81
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• 2023

This study aims to establish a scenario based on the spacing and arrangement of the roadside trees to reduce heat waves and fine dust in cities that occurred during the urbanization process and to quantitatively analyze the degree of reduction. The ENVI-met 5.0.2v model, a micro-climate simulation program, was used to analyze the degree of improvement in the thermal environment and fine dust according to the roadside tree scenario. As a result of temperature analysis according to street tree spacing, the narrower the distance between roadside trees, the lower the temperature during the day as the number of planted trees increased, and a similar pattern was shown regardless of the distance between roadside trees in the morning and evening. In the case of fine dust emitted from the road, the concentration of fine dust increased slightly due to the increase in roadside trees, but the concentration of sidewalks where people walk increased slightly or there was no difference because of blocking fine dust on trees. The temperature according to the arrangement of street trees tended to decrease as the number of planted trees increased as the arrangement increased. However, not only the amount of trees but also the crown projected area was judged to have a significant impact on the temperature reduction because the temperature reduction was greater in the scenario of planting the same amount of trees and widening the interval of arrangement. In terms of the arrangement, the fine dust concentration showed a difference from the results according to the interval, suggesting that the fine dust concentration may change depending on the relationship between the main wind direction and the tree planting direction. By quantitatively analyzing the degree of thermal environment and fine dust improvement caused by roadside trees, this study is expected to promote policies and projects to improve the roadside environment efficiently, such as a basic plan for roadside trees and a project for wind corridor forests.

• Journal of Preventive Medicine and Public Health
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• v.16 no.1
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• pp.67-77
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• 1983

To investigate the an air pollution by particulate matter and its dispersion, a cement plant produceing portland cement 600,000 ton/year and its vicinity were surveyed from Obtober, 1980 to April, 1983. The survey was mainly focused on main stack emmission rate of the cement plant and particle size distribution in the dust, dustfall and total suspended particulate concentration in the area by month and distance from the stack. The results of the study were as follows; 1. The main stack emission rate was surveyed before and after the spray tower was additionally installed to the original E.P bag filter. Before the spray tower installed, the main stack emission rate was higher ($0.64g/Nm^3$) than the emission standard of Korean Environmental Preservation Law's ($0.59g/Nm^3$, amended to $0.4g/Nm^3$ on April 1983), but after the spray tower was installed, its main stack emission rate was markedly decreased to the standard ($0.43g/Nm^3$). 2. $2{\sim}3{\mu}m$ of the particle size was the largest portion (20.8%) of the dust particulate from the main stack and 50% of the frequency distribution was $1.5{\mu}m$ of the size. Most particle size was below $10{\mu}m$. 3. The spray tower reduced the dustfall to $37.81{\sim}9.76\;ton/km^2/month$ while dustfall appeared at $45.29-15.45ton/km^2/month$, in the vicinity of plant before spray tower installed 4. Mean concentrations of total suspended particulate for 24 hours of the various stations were determined in $20.6-200.0{\mu}g/m^3$, 3 stations of tham were higher than the value of Harry and William's arthmetic average standard $130{\mu}g/m^3$. 5. Linear regression between dustfall [X] and total suspended particulate[Y] concentration was an equation, Y=4.024X+11.479.[r=0.91] 6. During the whole seasons in the opposite area 100m apart from the omission source the prevailing wind direction was with estimated more than $30ton/km^2/month$, and the concentration of total suspended particulate for 24 hours averaging time was more than $140{\mu}g/m^3$ in the same area and direction. 7. Assuming the wind direction were constant through the day dustfalls for a day were estimated at $13.40ton/km^2/day,\;10.79ton/km^2/day$ and $4.55ton/km^2/day$ at various distances of 100m, 500m and 1,500m from the emission source respectively. 8. In the simutalion of dustfall and suspended dust by area, Gaussian dispersion model modified by size distribution of particulate matter was not applicated since the emission of dust were from multi sources other them stack. From the above results, it could be applied that the dispersion of dust from the cement plant is estimated and regulated for the purpose of environmental protection.

• Industrial Engineering and Management Systems
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• v.2 no.1
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• pp.35-44
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• 2003

Recovery of end-of-life (EOL) products is an environmentally and economically sound way to achieve many of the goals of sustainable development. Many product recovery systems are dependent upon destructive disassembly such as shredding, which undesirably causes a large volume of shredder dust and makes parts reuse impossible. Although non-destructive disassembly has been considered as an alternative for solving the problems, the classification of disassembled items has not been sufficiently investigated. In this paper, we propose a model that mathematically optimizes the disassembly and classification of EOL products. Based on the AND/OR graph that illustrates all possible disassembly sequences of a given product, we identify the physical properties that are considered as constraints in the model. As a result of the solution procedure, the recovery problem can be transformed into a mixed integer linear programming (MILP) model. We show an example that illustrates the concept of our model.

• Journal of Korea Multimedia Society
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• v.25 no.3
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• pp.468-475
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• 2022

Currently, fine dust forecast models are operated by dividing the country into 19 regions. Therefore, it is important to reduce the learning time and the number of models as well as accurate forecast performance to operate lots of forecast models. In this paper, we develop a categorical wide area model that outputs forecast results categorically and integrates the regions with similar regional characteristics. The proposed model improved the convergence rate by 223 times compared to the existing model, which outputs at a single concentration value, and reduced the number of forecast models by a third.

• Korean Chemical Engineering Research
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• v.50 no.1
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• pp.76-82
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• 2012

Biomass and coal are great potential energy sources for gasification process. These solids can be gasified to produce syngas and bio-oil which can be upgraded further to transportation fuel. Two biomass and three coals have been gasified with steam in a thermobalance reactor under atmospheric pressure in order to evaluate their kinetic rate information The effects of gasification temperature ($600{\sim}850^{\circ}C$) and partial pressure of steam (30~90 kPa) on the gasification rate have been investigated. The three different types of gas-solids reaction models have been applied to the experimental data to compare their predictions of reaction behavior. The modified volumetric reaction model predicts the conversion data well, thus that model was used to evaluate kinetic parameters in this study. The gasification reactivity of five solids has been compared. The obtained activation energy of coal and biomass gasification were well in the reasonable range. The expression of apparent reaction rates for steam gasification of five solids have been proposed as basic information for the design of coal gasification processes.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.899-904
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• 2022

As the world becomes an aging society due to a decrease in the birth rate and an increase in life expectancy, a system for health management of the elderly population is needed. Among them, various studies on occupancy and activity types are being conducted for smart home care services for indoor health management. In this paper, we propose a random forest model that classifies activity type as well as occupancy status through indoor temperature and humidity, CO2, fine dust values and UWB radar positioning for smart home care service. The experiment measures indoor environment and occupant positioning data at 2-second intervals using three sensors that measure indoor temperature and humidity, CO2, and fine dust and two UWB radars. The measured data is divided into 80% training set data and 20% test set data after correcting outliers and missing values, and the random forest model is applied to evaluate the list of important variables, accuracy, sensitivity, and specificity.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.53-54
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• 2022

There is an increasing demand for prediction of asbestos concentration which has an fatal effect on human body. While demolishing asbestos, the dust scatters and makes workers be exposed to danger. Up to this date, however, factors that particularly influences have not considered in predicting asbestos concentration. Most of the studies could not quantify the distribution of asbestos. Also, they did not use nominal data on buildings as important factors. Therefore, this study aims to build an asbestos concentration prediction model by quantifying distribution of asbestos and using nominal data of buildings based on Artificial Neural Network (ANN). This model can give significant contribution of improving the safety of workers and be useful for finding effective ways to demolish asbestos in planning.