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http://dx.doi.org/10.5572/KOSAE.2013.29.1.74

Identification of PM10 Chemical Characteristics and Sources and Estimation of their Contributions in a Seoul Metropolitan Subway Station  

Park, Seul-Ba-Sen-Na (Department of Environmental Science and Engineering, Kyung Hee University)
Lee, Tae-Jung (Department of Environmental Science and Engineering, Kyung Hee University)
Ko, Hyun-Ki (Department of Environmental Science and Engineering, Kyung Hee University)
Bae, Sung-Joon (R&D Center, Seoul Metro)
Kim, Shin-Do (Department of Environmental Engineering, University of Seoul)
Park, Duckshin (Eco-transport Research Division, Korea Railroad Research Institute)
Sohn, Jong-Ryeul (Department of Environmental Health, College of Health Sciences, Korea University)
Kim, Dong-Sool (Department of Environmental Science and Engineering, Kyung Hee University)
Publication Information
Journal of Korean Society for Atmospheric Environment / v.29, no.1, 2013 , pp. 74-85 More about this Journal
Abstract
Since the underground transportation system is a closed environment, indoor air quality problems may seriously affect many passengers' health. The purpose of this study was to understand $PM_{10}$ characteristics in the underground air environment and further to quantitatively estimate $PM_{10}$ source contributions in a Seoul Metropolitan subway station. The $PM_{10}$ was intensively collected on various filters with $PM_{10}$ aerosol samplers to obtain sufficient samples for its chemical analysis. Sampling was carried out in the M station on the Line-4 from April 21 to 28, July 13 to 21, and October 11 to 19 in the year of 2010 and January 11 to 17 in the year of 2011. The aerosol filter samples were then analyzed for metals, water soluble ions, and carbon components. The 29 chemical species (OC1, OC2, OC3, OC4, CC, PC, EC, Ag, Al, Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Si, Ti, V, Zn, $Cl^-$, $NO_3{^-}$, $SO_4{^{2-}}$, $Na^+$, $NH_4{^+}$, $K^+$, $Mg^{2+}$, $Ca^{2+}$) were analyzed by using ICP-AES, IC, and TOR after proper pretreatments of each sample filter. Based on the chemical information, positive matrix factorization (PMF) model was applied to identify the $PM_{10}$ sources and then six sources such as biomass burning, outdoor, vehicle, soil and road dust, secondary aerosol, ferrous, and brakewear related source were classified. The contributions rate of their sources in tunnel are 4.0%, 5.8%, 1.6%, 17.9%, 13.8% and 56.9% in order.
Keywords
$PM_{10}$; PMF model; Subway station; Source contribution; Indoor air quality;
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Times Cited By KSCI : 4  (Citation Analysis)
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