Development of a Receptor Methodology for Quantitative Assessment of Ambient PM-10 Sources in Suwon Area

수원지역 대기 중 PM-10 오염원의 정량평가를 위한 수용방법론의 개발

  • 김관수 (경희대학교 환경·응용화학부 대기오염연구실 및 산학협력기술연구원) ;
  • 황인조 (경희대학교 환경·응용화학부 대기오염연구실 및 산학협력기술연구원) ;
  • 김동술 (경희대학교 환경·응용화학부 대기오염연구실 및 산학협력기술연구원)
  • Published : 2001.02.01

Abstract

A total of 328 ambient PM-10 samples was collected by a PM-10 high volume air sampler during the periods of February 1997 to February 1999 from Kyung Hee University at Suwon Campus. The samples were analyzed for their bulk chemical compositions(Cu, Fe, Pb, Zn, Al, $Na^{+}$, $NH_{4}^{+}$, $K^{+}$, $Ca^{2+]$, $Mg^{2+}$, $Cl^{-}$, $NO_{3}^{-}$, and $SO_{4}^{2-}$ by both an atomic absorption spectrophotometer and an ion chromatograph. The purpose of this study was t develop a receptor methodology for quantitative assessment of PM-10 sources. The data obtained from this study were ex-tensively examined using the target transformation factor analysis(TTFA) and the chemical mass balance (CMB). When TTFA was initially applied seasonal basis. five sources(such as automobile-related, sulfate-related, incine-ration, soil and combustion-related) were identified both during winter and fall. Since the total number and the type of sources were resolved by TTFA for the four seasons, CMB was employed to cross-check the results of TTEA. The total of six source categories identified by TTEA was intensively investigated on the basis of source profiles acquired from various source libraries established both in Korea and abroad. The results of this study showed the applicability of two popular receptor models as a new methdology for quantitative assessment PM-10 sources in Korea. Seasonally segmented data sets with the combined application of TTFA and CMB yielded a physically reasonable source apportionment result and provided a mean to increase the number of potential sources. Furthermore, this study suggested the possibility of the CMB application to ambi-ent data from Korea after identifying potential sources through traditional factor analysis.

Keywords

References

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