Journal of Korean Society for Atmospheric Environment (한국대기환경학회지)

Korean Society for Atmospheric Environment (한국대기환경학회)
권호 표지
DOI QR코드

DOI QR Code

Development and Validation Test of Effective Wet Scavenging Contribution Regression Models Using Long-term Air Monitoring and Weather Database

장기간 대기오염 및 기상자료를 이용한 유효강수세정 기여율 회귀모델의 개발 및 유효성 검사

  • Lim, Deukyong (Department of Environmental Science and Engineering, College of Engineering, Kyung Hee University) ;
  • Lee, Tae-Jung (Department of Environmental Science and Engineering, College of Engineering, Kyung Hee University) ;
  • Kim, Dong-Sool (Department of Environmental Science and Engineering, College of Engineering, Kyung Hee University)
  • 임득용 (경희대학교 환경학 및 환경공학과) ;
  • 이태정 (경희대학교 환경학 및 환경공학과) ;
  • 김동술 (경희대학교 환경학 및 환경공학과)
  • Received : 2013.03.04
  • Accepted : 2013.04.29
  • Published : 2013.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

This study used long-term air and weather data from 2000 to 2009 as raw data sets to develop regression models in order to estimate precipitation scavenging contributions of ambient $PM_{10}$ and $NO_2$ in Korea. The data were initially analyzed to calculate scavenging ratio (SR), defined as the removal efficiency for $PM_{10}$ and $NO_2$ by actual precipitation. Next, the effective scavenging contributions (ESC) with considering precipitation probability density were calculated for each sector of precipitation range. Finally, the empirical regression equations for the two air pollutants were separately developed, and then the equations were applied to test the model validity with the raw data sets of 2010 and 2011, which were not involved in the modeling process. The results showed that the predicted $PM_{10}$ ESC by the model was 23.8% and the observed $PM_{10}$ ESCs were 23.6% in 2010 and 24.0% in 2011, respectively. As for $NO_2$, the predicted ESC by the model was 16.3% and the observed ESCs were 16.4% in 2010 and 16.6% in 2011, respectively. Thus the developed regression models fitted quite well the actual scavenging contribution for both ambient $PM_{10}$ and $NO_2$. The models can then be used as a good tool to quantitatively apportion the natural and anthropogenic sink contribution in Korea. However, to apply the models for far future, the precipitation probability density function (PPDF) as a weather variable in the model equations must be renewed periodically to increase prediction accuracy and reliability. Further, in order to apply the models in a specific local area, it is recommended that the long-term oriented local PPDF should be inserted in the models.

Keywords

References

  1. Chate, D.M., P.S.P. Rao, M.S. Naik, G.A. Momin, P.D. Safai, and K. Ali (2003) Scavenging of aerosols and their chemical species by rain, Atmospheric Environment, 37, 2477-2484. https://doi.org/10.1016/S1352-2310(03)00162-6
  2. Choi, Y.J., W.S. Kim, and K.J. Ko (2010) Co-effect analysis of air quality management measures in Seoul, Seoul Development Institute.
  3. Engelmann, R.J. (1970) Scavenging prediction using ratios of concentrations in air and precipitation, Journal of Applied Meteorology, 10, 493-497.
  4. González, C.M. and B.H. Aristizábal (2012) Acid rain and particulate matter dynamics in a mid-sized Andean city: The effect of rain intensity on ion scavenging, Atmospheric Environment, 60, 164-171. https://doi.org/10.1016/j.atmosenv.2012.05.054
  5. Granat, L., M. Norman, C. Leck, U.C. Kulshrestha, and H. Rodhe (2002) Wet scavenging of sulfur compounds and other constituents during the Indian Ocean Experiment (INDOEX), Journal of Geophysical Research, 107 D19, 8025. https://doi.org/10.1029/2001JD000499
  6. Hicks, B.B. (2005) A climatology of wet deposition scavenging ratios for the United States, Atmospheric Environment, 39, 1585-1596.
  7. Kim, H.S., J.B. Huh, P.K. Hopke, T.M. Holsen, and S.M. Yi (2007) Characteristics of the major chemical constituents of PM2.5 and smog events in Seoul, Korea in 2003 and 2004, Atmospheric Environment, 41, 6762-6770. https://doi.org/10.1016/j.atmosenv.2007.04.060
  8. Kim, Y.G., S.Y. Lee, Y.K. Lim, and S.K. Song (2007) Design and assessment of an ozone potential forecasting model using multi-regression equations in Ulsan Metropolitan area, J. KOSAE, 23(1), 14-28. https://doi.org/10.5572/KOSAE.2007.23.1.014
  9. KMA (2012) Weather Dictionary. Available from URL:http://www.kma.go.kr/index.jsp.
  10. Koester, C.J. and R.A. Hites (1992) Wet and dry deposition of chlorinated dioxins and furan, Environmental Science and Technology, 26, 1375-1382. https://doi.org/10.1021/es00031a015
  11. Lee, H.S. and B.W. Kang (2001) Chemical characteristics of principal PM2.5 species in Chongju, South Korea, Atmospheric Environment, 35, 739-746. https://doi.org/10.1016/S1352-2310(00)00267-3
  12. Lim, D.Y., J.S. Heo, and D.S. Kim (2002) Washout removal efficiencies of major air pollutants by precipitation, J. KOSAE, 18(E2), 97-106.
  13. Lim, D.Y., T.J. Lee, and D.S. Kim (2012) Quantitative estimation of precipitation scavenging and wind dispersion contributions for PM10 and NO2 using longterm air and weather monitoring database during 2000-2009 in Korea, J. KOSAE, 28(3), 325-347. https://doi.org/10.5572/KOSAE.2012.28.3.325
  14. MOE(2012) Annual Report of Ambient Air Quality in Korea, 2011.
  15. NOAA (2012) Weather Terminology. Available from URL:http://www.noaa.gov/.
  16. Ruijgrok, W., H. Visser, and F.G. Romer (1992) The scavenging and wet deposition of acidifying components in Arnhem: 1984-1990. In: Schwartz, S.E. and Slinn, W.G.N. (Eds.), Precipitation Scavenging and Air-Surface Exchange. Hemisphere Publishing Corp, Washington, DC, 471-482.
  17. Shin, M.K., C.D. Lee, H.S. Ha, C.S. Choe and Y.H. Kim (2007) The influence of meteorological factors on PM10 Concentration in Incheon, J. KOSAE, 23(3), 322-331. https://doi.org/10.5572/KOSAE.2007.23.3.322
  18. Yang, F., L. Huang, W. Zhang, K. He, Y. Ma, J.R. Brook, J. Tan, Q. Zhao, and Y. Cheng (2011) Carbonaceous species in PM2.5 at a pair of rural/urban sites in Beijing, 2005-2008, Atmospheric Chemistry and Physics, 11, 7893-7903. https://doi.org/10.5194/acp-11-7893-2011
  19. Yang, L., X. Zhou, Z. Wang, Y. Zhou, S. Cheong, P. Xu, X. Gao, W, Nie, X. Wang, and W. Wang (2012) Airborne fine particulate pollution in Jinan, China:concentrations, chemical compositions and influence on visibility impairment, Atmospheric Environment, 55, 506-514. https://doi.org/10.1016/j.atmosenv.2012.02.029

Cited by

  1. PM10 and PM2.5 Characterization based on Mass Concentration Long-term (1989 ~ 2012) Database in Yongin-Suwon Area vol.31, pp.3, 2015, https://doi.org/10.5572/KOSAE.2015.31.3.209
  2. and Meteorological Data in Pohang, a Steel-Industrial City vol.32, pp.3, 2016, https://doi.org/10.5572/KOSAE.2016.32.3.329