• Particle and aerosol research
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• v.14 no.2
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• pp.25-33
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• 2018

In this study, the concentration of fine indoor dust and the size distribution of fine indoor dust were analyzed by measuring the dust generated during the cleaning process of an indoor office. We measured $PM_{10}$, $PM_{2.5}$, and $PM_{1.0}$ and analyzed the size distributions of dust larger than $0.3{\mu}m$ in diameter during cleaning. The results showed that the concentration of $PM_{10}$ increased rapidly during cleaning, however $PM_{1.0}$ did not increase. Before cleaning with a broom, the fine dust concentration was about $50{\mu}g/m^3$, but increased to about $400{\mu}g/m^3$ as cleaning progressed. In the case of indoor cleaning with a vacuum cleaner, the concentration of $PM_{10}$ increased during the cleaning process and the increase of $PM_{2.5}$ was relatively small. $PM_{1.0}$ did not increase as in the case of cleaning the broom.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2019.10a
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• pp.71-71
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• 2019

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2019.10a
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• pp.72-72
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• 2019

• Particle and aerosol research
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• v.13 no.2
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• pp.97-104
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• 2017

In order to characterize atmospheric aerosols in Chungcheong area, black carbon concentration, which is known to be closely related to global warming, was measured and compared with $PM_{10}$, $PM_{2.5}$ concentrations and various meteorological parameters such as wind velocity and wind direction. Multi Angle Absorption Photometer (MAAP), a filter-based equipment, was used for the black carbon measurement, and the $PM_{10}$, $PM_{2.5}$ concentrations, wind velocity and wind direction were provided by the local monitoring stations. Black carbon concentration was monitored to be high in spring and winter but low in fall. $PM_{10}$ concentration was observed to be high when westerly wind was strong.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.919-932
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• 2019

Fine particulate matter (PM2.5) is not only affected by anthropogenic emissions, but also intensifies, migrates, decreases by hydrometeorological factors. Therefore, it is essential to understand relationships between the hydrometeorological factors and PM2.5 concentration. In Korea, PM2.5 concentration is measured at the ground observatories and estimated data are given to locations where observatories are not present. In this way, the data is not suitable to represent an area, hence it is impossible to know accurate concentration at such locations. In addition, it is hard to trace migration, intensification, reduction of PM2.5. In this study, we analyzed the relationships between hydrometeorological factors, acquired from Global Land Data Assimilation System (GLDAS), and PM2.5 by means of Bayesian Model Averaging (BMA). By BMA, we also selected factors that have meaningful relationship with the variation of PM2.5 concentration. 4 PM2.5 concentration models for different seasons were developed using those selected factors, with Aerosol Optical Depth (AOD) from MODerate resolution Imaging Spectroradiometer (MODIS). Finally, we mapped the result of the model, to show spatial distribution of PM2.5. The model correlated well with the observed PM2.5 concentration (R ~0.7; IOA ~0.78; RMSE ~7.66 ㎍/㎥). When the models were compared with the observed PM2.5 concentrations at different locations, the correlation coefficients differed (R: 0.32-0.82), although there were similarities in data distribution. The developed concentration map using the models showed its capability in representing temporal, spatial variation of PM2.5 concentration. The result of this study is expected to be able to facilitate researches that aim to analyze sources and movements of PM2.5, if the study area is extended to East Asia.

• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.36-58
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• 2022

In this study, the weather conditions corresponding to the increase in the environmental concentration of fine dust (PM₁₀) and ultrafine dust (PM_2.5) from 2001 to 2019 in Jeju and Seogwipo cities were analyzed. The increase in the levels of PM₁₀ and PM_2.5 was observed in the order: spring > winter > autumn > summer. In both cities, PM₁₀ and PM_2.5 levels increased more frequently during the day in spring and summer and at night in autumn and winter, with PM_2.5 showing a greater increase in concentration than PM₁₀. The air temperature and wind speed corresponding with increased levels of PM₁₀ were higher than their respective seasonal averages in spring and winter, but lower in summer and autumn. Relative humidity was lower than the seasonal average during all seasons. The air temperature variation corresponding with increased levels of PM_2.5 showed the same seasonal trend as that observed for PM₁₀. The relative humidity was higher than the respective seasonal averages in spring and summer, and lower in winter. The wind speed was lower than the seasonal average in both the cities. When the PM₁₀ and PM_2.5 levels increased, the wind direction was from the north and the west during the day and varied according to the season at night. The rate of the increase in the PM₁₀ concentration was the highest in both cities at the wind speed of 1.6 - 3.4 ms^-1 during the day and night except during night in the summer. The highest concentration of PM_2.5 was observed with the wind speed range of 1.6 - 3.4 ms^-1 in Jeju, and 0.3 - 1.6 ms^-1 in Seogwipo. The results of this study applied to urban and landscape planning will aid in the formulation of strategies to reduce the adverse effects of fine particular matter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.140-145
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• 2022

In an advanced modern society, among air pollutants caused by urban industrialization and public transportation, fine dust flows into indoors from the outdoors. The fine dust meter used indoors provides limited information and measures the pollution level differently, so there is a problem that users cannot monitor and monitor the data they want. To solve this problem, in this paper, indoor air quality data fine dust and ultra-fine dust (PM1.0, PM2.5, PM10), VOC (Volatile Organic Compounds) and PIR (Passive Infrared Sensor) are used to measure fine dust. and a monitoring system were designed and implemented. We propose a fine dust meter and monitoring system that is installed in a designated area to measure fine dust in real time, collects, stores, and visualizes data through App Engine of Google Cloud Platform and provides it to users.

• Journal of Platform Technology
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• v.9 no.4
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• pp.79-89
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• 2021

In this paper, the fine dust (PM10) and ultrafine dust (PM2.5) measurement platforms are designed to be mobile and fixed using oneM2M, the international standard for IoT. The fine dust measurement platform is composed and designed with a fine dust measurement device, agent, oneM2M platform, oneM2M IPE, and monitoring system. The main difference between mobile and fixed is that the mobile uses the MQTT protocol for interconnection between devices and services without blind spots based on LTE connection, and the fixed uses the LoRaWAN protocol with low power and wide communication range. Not only fine dust, but also temperature, humidity, atmospheric pressure, volatile organic compounds (VOC), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and noise data related to daily life were collected. The collected sensor values were managed using the common API provided by oneM2M through the agent and oneM2M IPE, and it was designed into four resource types: AE and container. Six functions of operability, flexibility, convenience, safety, reusability, and scalability were analyzed through the fine dust measurement platform design.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.16-23
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• 2019

Fine particulate matter known as PM 2.5 refers to the atmospheric particulate matter that has a diameter less than 2.5 micrometer identified as dangerous element for human health and its concentration can provide us a clear picture about air dust concentration. Humans stay indoor almost 90% of their life time and also there is no official indoor dust concentration data, so our study is focused on measuring the indoor air quality. Indoor dust data monitoring is very important in hospital environments beside that other places can also be considered for monitoring like classrooms, cements factories, computer server rooms, petrochemical storage etc. In this paper, visible light communication system is proposed by Manchester encoding technique for electromagnetic interference (EMI)-free indoor dust monitoring. Important indoor environment information like dust concentration is transferred by visible light channel in wide range. An average voltage-tracking technique is utilized for robust light detection to eliminate ambient light and low-frequency noise. The incoming light is recognized by a photo diode and are simultaneously processed by a receiver micro-controller. We can monitor indoor air quality in real-time and can take necessary action according to the result.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.6
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• pp.520-529
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• 2015

The ambient $PM_{2.5}$ samples were collected by $PM_{2.5}$ sampler from September 2010 to December 2012 at Daegu University, Gyeongsan. A total of 260 samples were collected and 27 species were analyzed by inductively coupled plasma, ion chromatography, and thermal optical reflectance methods. Factor analysis identified four sources such as biomass burning source/secondary aerosol source, soil source, industry source, and incinerator source/mobile source. Also, backward trajectories were calculated using HYSPLIT 4 (Hybrid single-particle lagrangian integrated trajectory) model and PSCF (Potential source contribution function) model was applied to identify the possible source locations of carbonaceous species and water soluble ions species. PSCF results showed that the possible source locations of most chemical constituents measured in Gyeongsan were the industrial areas in the eastern coast of China, northeast regions of China, the Gobi Desert, and east sea of Korea.