DOI QR코드

DOI QR Code

Estimation of Biogenic Emissions over South Korea and Its Evaluation Using Air Quality Simulations

남한지역 자연 배출량 산정 및 대기질 모사를 이용한 평가

  • Kim, Soon-Tae (Institute for Multi-dimensional Air Quality Studies, University of Houston) ;
  • Moon, Nan-Kyoung (Korea Environment Institute) ;
  • Cho, Kyu-Tak (Korea Institute of Environmental Science and technology) ;
  • Byun, Dae-Won W. (Institute for Multi-dimensional Air Quality Studies, University of Houston) ;
  • Song, Eun-Young (Institute for Multi-dimensional Air Quality Studies, University of Houston)
  • 김순태 (휴스턴대학교 대기질연구소) ;
  • 문난경 (한국환경정책평가연구원) ;
  • 조규탁 (한국환경기술진흥원) ;
  • 변대원 (휴스턴대학교 대기질연구소) ;
  • 송은영 (휴스턴대학교 대기질연구소)
  • Published : 2008.08.31

Abstract

BEIS2 (Biogenic Emissions Inventory System version 2) and BEIS3.12 (BEIS version 3.12) were used to estimate hourly biogenic emissions over South Korea using a set of vegetation and meteorological data simulated with the MM5 (Mesoscale Model version 5). Two biogenic emission models utilized different emission factors and showed different responses to solar radiations, resulting in about $10{\sim}20%$ difference in the nationwide isoprene emission estimates. Among the 11-vegetation classes, it was found that mixed forest and deciduous forest are the most important vegetation classes producing isoprene emissions over South Korea comprising ${\sim}90%$ of the total. The simulated isoprene concentrations over Seoul metropolitan area show that diurnal and daily variations match relatively well with the PAMS (Photochemical Air Monitoring Station) measurements during the period of June 3${\sim}$June 10, 2004. Compared to BEIS2, BEIS3.12 yielded ${\sim}35%$ higher isoprene concentrations during daytime and presented better matches to the high peaks observed over the Seoul area. This study showed that the importance of vegetation data and emission factors to estimate biogenic emissions. Thus, it is expected to improve domestic vegetation categories and emission factors in order to better represent biogenic emissions over South Korea.

Keywords

References

  1. 김조천, 김기준, 홍지형, 선우영, 임수길 (2004a) 여름철 참나무속의 이소프렌 배출속도 비교에 관한 연구, 한국대기환경학회지, 20(1), 111-118
  2. 김조천, 홍지형, 강창희, 선우영, 김기준, 임준호(2004b) 침엽수로부터 발생되는 방향성 테르펜의 배출속도 비교 연구, 한국대기환경학회지, 20(2), 175-183
  3. 김태우, 이종범(1996) 수도권 지역의 자연배출량 산출, 한국대기환경학회, 학술대회논문집, 95-98
  4. 문윤섭, 구윤서 (2006) 수도권지역에서 수치 토지피복지도 작성을 통한 대기환경부문 활용사례 연구-MM5내 기온 및 바람장의 민감도 분석과 식생분포에 기인한 VOC 배출량 및 $CO_2$ 플럭스의 실시간 산정을 중심으로, 한국대기환경학회지, 22(5), 661-678
  5. 손윤석, 김조천, 김기준, 임용재, 선우영, 홍지형 (2006) 갈참나무로부터 발생되는 이소프렌의 배출속도 비교 연구, 한국대기환경학회지, 22(6), 791-798
  6. 조규탁, 김조천, 홍지형(2006) BEIS와 CORINAIR 산출방법에 의한 자연식생 VOC 배출량 산출 비교 연구, 한국대기환경학회지, 22(2), 167-177
  7. Benjey, W., M. Houyoux, and J. Susick (2001) Implementation of the SMOKE emissions data processor and SMOKE Tool input data processor in Models-3, U.S. EPA
  8. Byun, D.W. and J.K.S. Ching (1999) Science algorithms of the EPA Models3 Community Multiscale Air Quality (CMAQ) Modeling System, EPA600/R99/030, U.S. EPA
  9. Byun, D.W. and K.L. Schere (2006) Review of the governing equations, computational algorithms, and other components of the models-3 community multiscale air quality (CMAQ) modeling system, Applied Mechanics Reviews, 59(2), 51-77 https://doi.org/10.1115/1.2128636
  10. Byun, D.W., S. Kim, B. Czader, D. Nowak, S. Stetson, and M. Estes (2005) Estimation of biogenic emissions with satellite-derived land use and land cover data for the air quality modeling of houston-galveston ozone nonattainment area, J. of Environmental Management, 75, 285-301 https://doi.org/10.1016/j.jenvman.2004.10.009
  11. Coats, C.J. Jr. (1996) High performance algorithms in the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System, Ninth Joint Conference on Applications of Air Pollution Meteorology with the A & WMA, January 28-February 2, 1996, Atlanta, GA
  12. Fehsenfeld, F., J. Calvert, R. Fall, P. Goldan, A. Guenther, N. Hewitt, B. Lamb, S. Liu, M. Trainer, H. Westberg, and P. Zimmerman (1992) Emissions of volatile organic compounds from vegetation and the implication for atmospheric chemistry, Global Biogeochemical Cycles 6(4), 389-430 https://doi.org/10.1029/92GB02125
  13. Geron, C., A. Guenther, and T. Pierce (1994) An improved model for estimating emissions of volatile organic compounds from forests in the eastern United States, Journal of Geophysical Research, 99, 12773-12792 https://doi.org/10.1029/94JD00246
  14. Gery, M.W., G.Z. Whitten, J.P. Killus, and M.C. Dodge (1989) A photochemical kinetics mechanism for urban and regional scale computer modeling, J. Geophysical Research, 94, 12925 https://doi.org/10.1029/JD094iD10p12925
  15. Grell, G.A., J. Dudhia, and D. Stauffer (1994) A Description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5); NCAR Technical Note NCAR /TN-398+STR; National Center for Atmospheric Research: Boulder, CO
  16. Guenther, A., C. Geron, T. Pierce, B. Lamb, P. Harley, and R. Fall (2000) Natural emissions of non-methane volatile organic compounds, carbon monoxide, and oxides of nitrogen from North America, Atmospheric Environment, 34(12), 2205-2230 https://doi.org/10.1016/S1352-2310(99)00465-3
  17. Guenther, A., C. Nicholas Hewitt, D. Erickson, R. Fall, C. Geron, T. Graedel, P. Harley, L. Klinger, M. Lerdau, W.A. Mckay, T. Pierce, B. Scholes, R. Steinbrecher, R. Tallamraju, J. Taylor, and P. Zimmerman (1995) A global model of natural volatile organic compounds, Journal of Geophysical Research, 100, 8873-8892 https://doi.org/10.1029/94JD02950
  18. Hanna, S. and J. Wilkinson (2004) Analytical Estimation of Uncertainties in Biogenic Emissions Calculated by BEIS3 due to Uncertainties in Model Inputs and Parameters, 13th International Emission Inventory Conference, Clearwater, FL, June 8-10, 2004
  19. Moon, N.-K., S. Kim, D.W. Byun, and Y. Joe (2006) Air Quality Modeling System: I-Development of Emissions Preparation System with the CAPSS, Project final report, Korea Environment Institute, Seoul, Korea
  20. Morris, R.E., B. Koo, A. Guenther, G. Yarwood, D. McNally, T.W. Tesche, G. Tonnesen, J. Boylan, and P. Brewer (2006) Model sensitivity evaluation for organic carbon using two multi-pollutant air quality models that simulate regional haze in the southeastern United States, Atmospheric Environment, 40(26), 4960-4972 https://doi.org/10.1016/j.atmosenv.2005.09.088
  21. Pierce, T.E. (2001) Reconsideration of the Emission Factors assumed in BEIS3 for Three USGS Vegetation Categories: Shrubland, Coniferous Forest, and Deciduous Forest. (Available from http://www.epa.gov/CAIR/pdfs/BEIS_documentation.pdf)
  22. Pierce, T.E., C. Geron, L. Bender, R. Dennis, G. Tonnesen, and A. Guenther (1998) Influence of increased isoprene emissions on regional ozone modeling, J. Geophys. Res., 103, 25622-25629
  23. Tsigaridis, K. and M. Kanakidou (2007) Secondary organic aerosol importance in the future atmosphere, Atmospheric Environment, 41(22), 4682-4692 https://doi.org/10.1016/j.atmosenv.2007.03.045
  24. Vizuete, W., V. Junquer, E. McDonald-Buller, G. McGaughey, G. Yarwood, and D. Allen (2002) Effects of temperature and land use on predictions of biogenic emissions in Eastern Texas, USA, Atmospheric Environment, 36, 3321-3337 https://doi.org/10.1016/S1352-2310(02)00272-8
  25. Wiedinmyer, C., A. Guenther, M. Estes, I.W. Strange, G. Yarwood, and D. Allen (2001) A land use database and examples of biogenic isoprene emission estimates for the state of Texas, USA, Atmospheric Environment, 35, 6465-6477 https://doi.org/10.1016/S1352-2310(01)00429-0
  26. Yarwood, G., G. Wilson, S. Shepard, and A. Guenther (2002) User's Guide to the Global Biosphere Emissions and Interactions System (GloBEIS) Version 3; ENVIRON International Corporation; Novato, CA

Cited by

  1. A Study on the Occurrence Characteristics of Tropical Night Day and Extreme Heat Day in the Metropolitan City, Korea vol.23, pp.5, 2014, https://doi.org/10.5322/JESI.2014.5.873
  2. A Study on the Estimation of BVOCs Emission in Jeju Island (2): Emission Characteristic and Situation vol.24, pp.2, 2015, https://doi.org/10.5322/JESI.2015.24.2.207
  3. Simulation of Air Quality Over South Korea Using the WRF-Chem Model: Impacts of Chemical Initial and Lateral Boundary Conditions vol.25, pp.4, 2015, https://doi.org/10.14191/Atmos.2015.25.4.639