• Title/Summary/Keyword: 미세먼지 분포도

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Chemical Composition Characteristics of Fine Particulate Matter at Atmospheric Boundary Layer of Background Area in Fall, 2012 (배경지역 대기경계층 미세먼지의 화학조성 특성: 2012년 가을 측정)

  • Ko, Hee-Jung;Lee, Yoon-Sang;Kim, Won-Hyung;Song, Jung-Min;Kang, Chang-Hee
    • Journal of the Korean Chemical Society
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    • v.58 no.3
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    • pp.267-276
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    • 2014
  • The collection of $PM_{10}$ and $PM_{2.5}$ fine particulate matter samples was made at the 1100 m site of Mt. Halla of Jeju Island, located at the atmospheric boundary layer (ABL) of background area, during the fall of 2012. Their ionic and elemental species were analyzed, in order to investigate the chemical compositions and size distribution characteristics. In $PM_{2.5}$ fine particles ($d_p$ < $2.5{\mu}m$), the concentrations of the secondary formed nss-$SO{_4}^{2-}$, $NH_4{^+}$ and $NO_3{^-}$ species were 4.84, 1.98, and $1.27{\mu}g/m^3$, respectively, showing 58.2% of the total $PM_{2.5}$ mass. On the other hand, their concentrations in $PM_{10-2.5}$ coarse particles (2.5 < $d_p$ < $10{\mu}m$) were 0.63, 0.21 and $1.10{\mu}g/m^3$, respectively, occupying 22.8% of the total $PM_{10-2.5}$ mass. The comparative study of size distribution has resulted that $NH_4{^+}$, nss-$SO{_4}^{2-}$, $K^+$ and $CH_3COO^-$ are mostly existed in fine particles, and $NO_3{^-}$ is distributed in both fine and coarse particles, but $Na^+$, $Cl^-$, $Mg^{2+}$ and nss-$Ca^{2+}$ are rich in coarse particle mode.

Emission Characteristics of Particulate Matter and Heavy Metals from Coal Fire Power Plants (석탄화력발전소에서 배출되는 입자상물질 및 중금속 배출 특성)

  • 장하나;유종익;이성준;김기헌;석정희;서용칠;석광설;홍지형
    • Proceedings of the Korea Air Pollution Research Association Conference
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    • 2003.11a
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    • pp.89-90
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    • 2003
  • 석탄화력발전소에서는 다양한 유해물질이 발생한다 먼지, 미세먼지, 유해중금속, 황산화물(SOx), 질산화물(NOx) 등이 그것인데, 이중 황산화물과 질산화물등은 기존 방지장치로 비교적 제어가 용이하다. 반면에, 미세먼지와 유해중금속은 대기중으로 상당량이 배출되어 인체에 심각한 피해를 끼치고 있다. 우리나라 대기환경보전법에서는 대기오염물질을 가스상 물질과 입자상 물질로 구분하고 있다. 이중 입자상물질은 그 입도의 분포가 수십 나노미터에서 수십 마이크론까지 광범위하고 입도에 따른 환경위해성도 다르다. (중략)

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Filtration Characteristics of Paticulate Matter at Bag Filters Coated with PTFE Membrane During Off-Line Pulsing (PTFE membrane이 코팅된 여과백의 off-line 탈진시 미세먼지 집진 특성)

  • Kim, Joung-Hun;Moon, Il-Shik;Hwang, Min-Young;Kim, Ryang-Gyoon;Ko, Daekwun
    • Journal of Korean Society of Environmental Engineers
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    • v.39 no.7
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    • pp.391-402
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    • 2017
  • Particulate matter becomes an important issue in the environmental society recently so that it is necessary to evaluate that the commercial application of baghouse systems for effective control of fine particulates is viable. A laboratory-scale baghouse experimental apparatus with filter bags made of PTFE felt or PTFE felt coated with PTFE membrane is used to investigate the filtration performances of fine particulates. Experiments by changing filtration velocity, inlet dust concentration, and average dust particle size show that the dust collection efficiency becomes higher at lower filtration velocity, higher inlet dust concentration and larger average dust particle size. The total pressure drop through the filter media and dust layer becomes higher at higher filtration velocity and higher inlet dust concentration. The dust collection efficiency is higher and the pressure drop is lower at a baghouse with filter bags coated with PTFE membrane than that without membrane coating. From the result that the dust collection efficiency of $PM_{2.5}$ in a reasonable filtration velocity range during off-line pulsing at a baghouse with PTFE felt bag filters coated with PTFE membrane is as high as 99.99%, it is confirmed that the use of baghouse is an effective measure to control the fine particulates.

A Study on the Prediction of Residual Probability of Fine Dust in Complex Urban Area (복잡한 도심에서의 유입된 미세먼지 잔류 가능성 예보 연구)

  • Park, Sung Ju;Seo, You Jin;Kim, Dong Wook;Choi, Hyun Jeong
    • Journal of the Korean earth science society
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    • v.41 no.2
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    • pp.111-128
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    • 2020
  • This study presents a possibility of intensification of fine dust mass concentration due to the complex urban structure using data mining technique and clustering analysis. The data mining technique showed no significant correlation between fine dust concentration and regional-use public urban data over Seoul. However, clustering analysis based on nationwide-use public data showed that building heights (floors) have a strong correlation particularly with PM10. The modeling analyses using the single canopy model and the micro-atmospheric modeling program (ENVI-Met. 4) conducted that the controlled atmospheric convection in urban area leaded to the congested flow pattern depending on the building along the distribution and height. The complex structure of urban building controls convective activity resulted in stagnation condition and fine dust increase near the surface. Consequently, the residual effect through the changes in the thermal environment caused by the shape and structure of the urban buildings must be considered in the fine dust distribution. It is notable that the atmospheric congestion may be misidentified as an important implications for providing information about the residual probability of fine dust mass concentration in the complex urban area.

Spatial Information Application Case for Appropriate Location Assessment of PM10 Observation Network in Seoul City (서울시 미세먼지 관측망 위치 적정성 평가를 위한 공간정보 활용방안)

  • Jeong, Jong-Chul
    • Journal of Cadastre & Land InformatiX
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    • v.47 no.2
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    • pp.175-184
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    • 2017
  • Recently, PM10 is becoming a main issue in Korea because it causes a variety of diseases, such as respiratory and ophthalmologic diseases. This research studied to spatial information application cases for evaluating the feasibility of the location for PM10 observation stations utilizing Geogrphic Information System(GIS) spatial analysis. The spatial Information application cases for optimal location assessment were investigated to properly manage PM10 observation stations which are closely related with public spatial data and health care. There are 31 PM10 observation stations in Seoul city and the observed PM10 data at these stations were utilized to understand the overall assessment of PM10 stations to properly manage using interpolation methods. The estimated PM10 using Inverse Distance Weighted(IDW) and Kriging techniques and the map of PM10 concentrations of monitoring stations in Seoul city were compared with public spatial data such as precipitation, floating population, elementary school location. On the basis of yearly, seasonal and daily PM10 concentrations were used to evaluate the feasibility analysis and the location of current PM10 monitoring stations. The estimated PM10 concentrations were compared with floating population and calculated 2015 PM10 distribution data using zonal statistical methods. The national spatial data could be used to analyze the PM10 pollution distribution and additional determination of PM10 monitoring sites. It is further suggested that the spatial evaluation of national spatial data can be used to determine new location of PM10 monitoring stations.

Estimating Fine Particulate Matter Concentration using GLDAS Hydrometeorological Data (GLDAS 수문기상인자를 이용한 초미세먼지 농도 추정)

  • Lee, Seulchan;Jeong, Jaehwan;Park, Jongmin;Jeon, Hyunho;Choi, Minha
    • 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.