• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.33 no.6
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• pp.24-31
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• 2004

국내의 경우, 2004년 5월부터 시행예정인 다중이용시설 등의 실내공기질관리법에 따라서, 학교 등의 일부 건축물을 제외하고 신축공동주택 및 대부분의 거주용 공간에 대한 실내공기질관리법이 제정되었다. 이러한, 건축물 내에는 다양한 오염원(sources)과 휘발성유기화합물(VOCs), 포름알데히드(HCHO), 라돈(Radon), 석면(Asbestos), 일산화탄소(CO), 이산화탄소($CO_2$), 이산화질소(NO$_2$), 오존(O$_3$), 미세 먼지(PM10), 부유세균 등 유해오염물질(contaminants)이 존재하고 있다. 또한, 실내공기오염은 각 오염원에서의 유해오염물질 방산정도(emission rate)가 실내외 환경조건, 적용 건축자재의 종류 및 공법 , 환기설비의 특성 및 유형 등에 따라 큰 차이를 보이고 있으므로, 이에 대한 정확한 측정방법의 정립과 그에 따른 적절한 실태조사의 실시가 필요하다. (중략)

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.11-12
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• 2022

이 연구는 대기오염과 미세먼지의 각 성분이 질환에 미치는 영향에 대한 데이터만 존재한다면 어떠한 질환이든 위험도 예측 결과를 알 수 있는 것에 의미가 있다. 또한 기존의 대기정보에 따른 정보를 예상하는데 필요한 데이터 종류와 수가 많았으며 계산의 복잡성이 높았고 정보의 제공 범위가 넓었다. 하지만 이 연구는 과거 대기 데이터와 딥러닝을 통해서 낮은 비용으로 더욱 자세하게 유해질환 위험도를 예측하는 시스템을 구축하였다. 이 연구에서 구축한 시스템은 예측 결과 88.9%의 정확도를 보였다. 이 시스템은 입력되는 데이터의 정보에 따라 세분화된 지역의 대기환경 정보 또한 파악 가능하며 그 과정이 매우 간편하고 유용하다. 이 시스템은 공기질 예측을 위해 유용하게 사용될 수 있을 것이라고 사료된다.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.1
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• pp.59-77
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• 2008

The purpose of this study is to investigate the impact of traffic-related air pollution on the urban population in the Metropolitan Seoul area. In particular, this study analyzes urban population exposure to traffic-related particulate materials(PM). For the purpose, this study examines the relationships between traffic flows and PM concentration levels during the last fifteen years. Traffic volumes have been decreased significantly in recent year in Seoul, however, PM levels have been declined less compare to traffic volumes. It may be related with the rapid growth in the population and vehicle numbers in Gyenggi, the outskirt of Seoul, where several New Towns have been developed in the middle of 1990's. The spatial pattern of commuting has changed, and thus and travel distances and traffic volumes have increased along the main roads connecting CBDs in Seoul and New Towns consisting of large residential apartment complexes. These changes in traffic flows and travel behaviors cause increasing exposure to traffic-related air pollution for urban population over the Metropolitan Seoul area. GIS techniques are applied to analyze the spatial patterns of traffic flows, population distributions, PM distributions, and passenger flows comprehensively. This study also analyzes real time base traffic flow data and passenger flow data obtained from T-card transaction database applying data mining techniques. This study also attempts to develop a space-time model for assessing journey-time exposure to traffic related air pollutants based on travel passenger frequency distribution function. The results of this study can be used for the implications for sustainable transport systems, public health and transportation policy by reducing urban air pollution and road traffics in the Metropolitan Seoul area.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.05b
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• pp.191-192
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• 2003

본 연구는 서울을 중심으로 한 수도권지역에서 해륙풍과 주풍 및 계절풍을 고려하여 대기오염 측정소가 있는 지점을 중심으로 강화도 석모리, 인천 용현동, 서울 불광동, 정동, 전농동, 방이동지점과 양평 국수리지점을 측정장소로 선정하여 미세먼지 분야의 측정자료를 해석한 것으로 1차 측정은 2002년 8월 5일 ∼8월 22일, 2차 측정은 2002년 10월 10일 ∼ 10월 18일까지 실시 되었으며, 3차 측정은 2003년 1월 10일∼l월 24일까지 겨울 집중 측정이 실시되었으며, 측정결과를 해석중에 있다. 또, 4차 측정은 2003년6월에 실시될 예정이다. (중략)

• Journal of odor and indoor environment
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• v.17 no.4
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• pp.303-314
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• 2018

The urban railway system is a convenient public transportation system, as it carries many people without increasing traffic congestion. However, air quality in urban railway environments is worse than ambient air quality due to the internal location of the source of air pollutants and the isolated space. In this paper, characteristics of particulate matter (PM) pollution in urban railway environments are described from the perspective of diurnal variation, chemical composition and source apportionment of PM. PM concentrations in concourse, platform, passenger cabin, and tunnel are summarized through an analysis of 34 journal articles published in Korea and overseas. This information will be helpful in developing effective policies to reduce PM pollution in urban railway environments.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.495-505
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• 2006

In order to classify aerosol type, Aerosol Optical Thickness (AOT) and Fine mode Fraction (FF), which is the optical thickness ratio of small particles$(<1{\mu}m)$ to total particles, data from MODIS (MODerate Imaging Spectraradiometer) aerosol products were analyzed over North-East Asia during one year period of 2005. A study area was in the ocean region of $20^{\circ}N\sim50^{\circ}N$ and $110^{\circ}E\simt50^{\circ}E$. Three main atmospheric aerosols such as dust, sea-salt, and pollution can be classified by using the relationship between AOT and FF. Dust aerosol has frequently observed over the study area with relatively high aerosol loading (AOT>0.3) of large particles (FF<0.65) and its contribution to total AOT in spring was up to 24.0%. Pollution aerosol, which is originated from anthropogenic sources as well as a natural process like biomass burning, has observed in the regime of high FF (>0.65) with wide AOT variation. Average pollution AOT was $0.31{\pm}0.05$ and its contribution to total AOT was 79.8% in summer. Characteristic of sea-salt aerosol was identified with low AOT (<0.3), almost below 0.1, and slightly higher FF than dust and lower FF than pollution. Seasonal analysis results show that maximum AOT $(0.33{\pm}0.11)$ with FF $(0.66{\pm}0.21)$ in spring and minimum AOT $(0.19{\pm}0.05)$, FF $(0.60{\pm}0.14)$ in fall were observed in the study area. Spatial characteristic was that AOT increasing trend is observed as closing to the eastern part of China due to transport of aerosols from China by the prevailing westerlies.

• Horticultural Science & Technology
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• v.33 no.5
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• pp.751-762
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• 2015

This study was performed to investigate the stability of soil moisture in controlling air ventilation rate within a horizontal biofilter, and to compare removal efficiency (RE) of indoor air pollutants including fine dust, volatile organic compounds (VOCs), and formaldehyde (HCHO), depending on whether dieffenbachias (Diffenbachia amoena) were planted in the biofilter. The relative humidity, air temperature, and soil moisture contents showed stable values, regardless of the presence of D. amoena, and the plants grew normally in the biofilter. REs for number of fine dust particles (PM10 and PM2.5) within the biofilter filled with only soil were at least 30% and 2%, respectively. REs for number of fine dust particles (PM10 and PM2.5) within the biofilter including the plants were above 40% and 4%, respectively. RE for fine dust (PM10) weight was above 4% and 20%, respectively, in the biofilter containing only soil or soil together with plants. In the case of the biofilter filled with only soil, REs for xylene, ethylbenzene, toluene or total VOC (T-VOC) were each more than 63%; however, REs for benzene and formaldehyde (HCHO) were above 22% and 38%, respectively. In the biofilter with the plants, REs for xylene, ethylbenzene, toluene, and T-VOC were each above 72%, and REs for benzene and HCHO were above 39%. Thus, RE of the biofilter integrated with plants was found to be higher for volatile organic compounds than for fine dust. Hence, the biofilter was very effective for indoor air quality improvement and the effect was higher when integrated with plants.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3740-3747
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• 2009

To protect the citizens' health of Gyeongju and to secure basic data for the assessment of health and environmental risk, distribution characteristics of meteorological elements were investigated and numerical simulation of wind field using RAMS model was carried out. In addition, measurement and analysis of air pollutants, forecasting the behavior air pollutants using ISC-AEROMOD view, and health and environmental risk-influenced zones were defined through managing air polluting materials to prevent health damage and property damage. According to the survey results of air pollution in Gyeongju and surroundings, average annual concentration of air pollutants in Gyeongju was slightly lower than that in Pohang and Ulsan areas, but concentration of particulate matters and nitrogen dioxide at Gyeongju Station Square and Yonggang Crossing were sometimes higher than that in Pohang and Ulsan areas. Results of the modeling of moving and diffusion of air pollutants that affect citizens' health showed that parts of the 1st through 4th industrial complexes together with POSCO were included in particulate matters and sulfur dioxide influenced areas in Pohang Steel Complex area, and that Haedo-dong, Sangdae-dong, Jecheol-dong and Jangheung-dong in Pohangnam-gu represented locally worsened air quality due to a quantity of air pollutant emission from dense steel industries and large scale industrial facilities.

• Journal of the Mineralogical Society of Korea
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• v.23 no.2
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• pp.99-106
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• 2010

To evaluate a potential wash-out effect of rainfalls, a preliminary environmental magnetic test was attempted. Measurement of isothermal remanent magnetization (IRM) and intensive microscopic observations were carried out on the solid particles extracted from the rainfalls collected for the past year (2009) in Daejeon, Korea. Dust particles collected from the rain-free (daily dust) or dustheavy days (during the Asian dust storm event) were also used as a comparison. IRMs were unanimously low for the solid particles extracted from the rainfalls, indicating an efficient wash-out effect of rainfalls as long as the magnetic concentration is concerned. Electron microscopy identified carbonbearing material, (carbon-coated) magnetite, and quartz. It is highly likely that the carbon-containing particles were produced by anthropogenic fossil fuel combustion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.8-14
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• 2020

The human impact of particulate matter are revealed and demand for improved forecast accuracy is increasing. Recently, efforts is made to improve the accuracy of PM10 predictions by using machine learning, but prediction performance is decreasing due to the particulate matter data with a large rate of low concentration occurrence. In this paper, separation prediction model by concentration is proposed to improve the accuracy of PM10 particulate matter forecast. The low and high concentration prediction model was designed using the weather and air pollution factors in Cheonan, and the performance comparison with the prediction models was performed. As a result of experiments with RMSE, MAPE, correlation coefficient, and AQI accuracy, it was confirmed that the predictive performance was improved, and that 20.62% of the AQI high-concentration prediction performance was improved.