Asian Journal of Atmospheric Environment

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

DOI QR Code

Modeling of Emissions from Open Biomass Burning in Asia Using the BlueSky Framework

  • Choi, Ki-Chul (Department of Advanced Technology Fusion, Konkuk University) ;
  • Woo, Jung-Hun (Department of Advanced Technology Fusion, Konkuk University) ;
  • Kim, Hyeon Kook (Department of Advanced Technology Fusion, Konkuk University) ;
  • Choi, Jieun (Department of Environmental Engineering, Konkuk University) ;
  • Eum, Jeong-Hee (Department of Landscape Architecture, Keimyung University) ;
  • Baek, Bok H. (Institute for the Environment, The University of North Carolina)
  • Received : 2011.08.30
  • Accepted : 2013.01.10
  • Published : 2013.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Open biomass burning (excluding biofuels) is an important contributor to air pollution in the Asian region. Estimation of emissions from fires, however, has been problematic, primarily because of uncertainty in the size and location of sources and in their temporal and spatial variability. Hence, more comprehensive tools to estimate wildfire emissions and that can characterize their temporal and spatial variability are needed. Furthermore, an emission processing system that can generate speciated, gridded, and temporally allocated emissions is needed to support air-quality modeling studies over Asia. For these reasons, a biomass-burning emissions modeling system based on satellite imagery was developed to better account for the spatial and temporal distributions of emissions. The BlueSky Framework, which was developed by the USDA Forest Service and US EPA, was used to develop the Asian biomass-burning emissions modeling system. The sub-models used for this study were the Fuel Characteristic Classification System (FCCS), CONSUME, and the Emissions Production Model (EPM). Our domain covers not only Asia but also Siberia and part of central Asia to assess the large boreal fires in the region. The MODIS fire products and vegetation map were used in this study. Using the developed modeling system, biomass-burning emissions were estimated during April and July 2008, and the results were compared with previous studies. Our results show good to fair agreement with those of GFEDv3 for most regions, ranging from 9.7 % in East Asia to 52% in Siberia. The SMOKE modeling system was combined with this system to generate three-dimensional model-ready emissions employing the fire-plume rise algorithm. This study suggests a practicable and maintainable methodology for supporting Asian air-quality modeling studies and to help understand the impact of air-pollutant emissions on Asian air quality.

Keywords

References

  1. Anderson, K.G., Sandberg, V.D., Norheim, A.R. (2004) Fire Emission Production Simulator (FEPS) User's Guide. U.S. Forest Service.
  2. Belward, A.S., Estes, J.E., Kline, K.D. (1999) The IGBPDIS Global 1-km Land-Cover Data Set DISCover: A Project Overview. Photogrammetric Engineering and Remote Sensing 65, 1013-1020.
  3. Burgan, R.E., Klaver, R.W., Klaver, J.M. (1998) Fuel Models and Fire Potential from Satellite and Surface Observations. International Journal of Wildland Fire 8(3), 159-170. https://doi.org/10.1071/WF9980159
  4. Giglio, L., Descloitres, J., Justice, C.O., Kaufman, Y. (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment 87, 273-282. https://doi.org/10.1016/S0034-4257(03)00184-6
  5. Giglio, L., Csiszar, I., Justice, C. O. (2006) Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Journal of Geophysical Research 111, G02016, doi:10.1029/2005JG000142.
  6. Giglio, L., Randerson, J.T., van der Werf, G.R., Kasibhatla, P.S., Collatz, G.J., Morton, D.C., DeFries, R.S. (2010) Assessing variability and long-term trends in burned area by merging multiple satellite fire products. Biogeosciences 7, 1171-1186. https://doi.org/10.5194/bg-7-1171-2010
  7. Hardy, C., Menakis, J.P., Garner, J.L.(1998) FMI/WESTAR emissions inventory and spatial data for the western United States, USDA Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory, Missoula, MT.
  8. Houyoux, M.R., Vukovich, J.M., Brandmeyer, J. (2007) SMOKE User Manual, version 2.3., MCNC Environmental Programs, Research Triangle Park, NC, USA.
  9. Jeong, J.I., Park, R.J., Youn, D. (2008) Effects of Siberian forest fires on air quality in East Asia during May 2003 and its climate implication. Atmospheric Environment 42, 8910-8922. https://doi.org/10.1016/j.atmosenv.2008.08.037
  10. Kuenzli, N., Avol, E., Wu, J., Gauderman, W.J., Rappaport, E., Millstein, J., Bennion, J., McConnell, R., Gilliland, F.D., Berhane, K. (2006) Health effects of the 2003 southern California wildfire on children. American Journal of Respiratory and Critical Care Medicine 174, 1221-1228. https://doi.org/10.1164/rccm.200604-519OC
  11. McKenzie, D., Kopper, K.E., Bayard, A.C. (2004) A rulebased fuzzy classification for landscape modeling of fuel succession. Proceedings of the 2003 Sydney Fire Conference.
  12. Michel, C., Liousse, C., gregoire, J.M., Tansey, K., Carmichael, G.R., Woo J.-H. (2005) Biomass burning emission inventory from burnt area data given by the SPOT-VEGETATION system in the frame of TRACEP and ACE-Asia campaigns. Journal of Geophysical Research 110, D09304, doi:10.1029/2004JD005461.
  13. MOE (Ministry Of Environment) (2009) Development of high-resolution meteorological-atmospheric chemistry modeling system for support urban-scale PM forecast.
  14. Ottmar, R.D., Burns, M.F., Hall, J.N., Hanson, A.D. (1993) CONSUME users guide. USDA Forest Service General Technical Report PNWGTR-304. Pacific Northwest Research Station, Portland, OR.
  15. Pouliot, G., Pierce, T., Benjey, W. (2005) Wildfire Emission Modeling: Integrating BlueSky and SMOKE. 14th International Emission Inventory Conference. "Transforming Emission Inventories Meeting Future Challenges Today".
  16. Pryden, A.D. (2008) Getting started with the BlueSky Framework version 3.0. Sonoma Technology, Inc.
  17. Roy, D.P., Lewis, P.E., Justice, C.O. (2002). Burned area mapping using multi-temporal moderate spatial resolution data-a bi-directional reflectance model-based expectation approach. Remote Sensing of Environment 83, 263-286. https://doi.org/10.1016/S0034-4257(02)00077-9
  18. Roy, D.P., Jin, Y., Lewis, P.E., Justice, C.O. (2005). Prototyping a global algorithm for systematic fire affected area mapping using MODIS time series data. Remote Sensing of Environment 97, 137-162. https://doi.org/10.1016/j.rse.2005.04.007
  19. Roy, D.P., Boschetti, L., Justice, C.O., Ju, J. (2008) The Collection 5 MODIS Burned Area Product - Global Evaluation by Comparison with the MODIS Active Fire Product. Remote Sensing of Environment 112, 3690-3707. https://doi.org/10.1016/j.rse.2008.05.013
  20. Sandberg, D.V., Peterson, J.L. (1984) A source strength model for prescribed fires in coniferous logging slash. In: Proceedings, 21st annual meeting of the Air Pollution Control Association, Pacific Northwest International Section, 1984 November 12-14, Portland, OR. Pittsburgh, PA: Air Pollution Control Association.
  21. Sandberg, D., Ottmar, R., Cushon, G. (2001) Characterizing fuels in the 21st century. International Journal of Wildland Fire 10, 381-387. https://doi.org/10.1071/WF01036
  22. Scepan, J. (1999) Thematic Validation of High-Resolution Global Land-Cover Data Sets. Photogrammetric Engineering and Remote Sensing 65, 1051-1060.
  23. Streets, D.G., Yarber, K.F., Woo, J.-H., Carmichael, G.R. (2003) Biomass burning in Asia: Annual and seasonal estimates and atmospheric emissions. Global Biogeochemical Cycles 17(4), 1099, doi:10.1029/2003GB002040.
  24. Tanimoto, H., Kajii, Y., Hirokawa, J., Akimoto, H., Minko, N.P. (2000) The atmospheric impact of boreal forest fires in far eastern Siberia on the seasonal variation of carbon monoxide: Observations at Rishiri, A northern remote island in Japan. Geophysical Research Letters 27(24), 4073-4076. https://doi.org/10.1029/2000GL011914
  25. van der Werf, G.R., Randerson, J.T., Giglio, L., Collatz, G.J., Kasibhatla, P.S., Arellano, A.F. (2006) Interannual variability in global biomass burning emissions from 1997 to 2004. Atmospheric Chemistry and Physics 6, 3423-3441. https://doi.org/10.5194/acp-6-3423-2006
  26. van der Werf, G.R., Randerson, J.T., Giglio, L., Collatz, G.J., Mu, M., Kasibhatla, P.S., Morton, D.C. (2010) Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009). Atmospheric Chemistry and Physics 10, 11707-11735. https://doi.org/10.5194/acp-10-11707-2010
  27. Woo, J.-H., Streets, D.G., Carmichael, G.R., Tang, Y., Yoo, B., Lee, W., Thongboonchoo, N., Pinnock, S., Kurata, G., Uno, I., Fu, Q., Vay, S., Sachse, G.W., Blake, D.R., Fried, A., Thornton, D.C. (2003) The Contribution of Biomass and Biofuel Emissions to Trace Gas Distributions in Asia during the TRACE-P Experiment. Journal of Geophysical Research 108(D21), 8812, doi:10.1029/2002JD003200.
  28. Woo, J.-H., Choi, K.-C., Kim, H.K., Baek, B.H., Jang, M., Eum, J.-H., Song, C.H., Ma, Y.-I., Sunwoo, Y., Chang, L.-S. and Yoo, S.H. (2012) Development of an anthropogenic emissions processing system for Asia using SMOKE, Atmospheric Environment, 58, 5-13. https://doi.org/10.1016/j.atmosenv.2011.10.042
  29. Yevich, R., Logan, J.A. (2003) An assessment of biofuel use and burning of agricultural waste in the developing world. Global Biogeochemical Cycles 17(4), 1095.

Cited by

  1. Trends in peroxyacetyl nitrate (PAN) in the upper troposphere and lower stratosphere over southern Asia during the summer monsoon season: regional impacts vol.14, pp.23, 2014, https://doi.org/10.5194/acp-14-12725-2014
  2. Light-absorbing impurities in snow of the Indian Western Himalayas: impact on snow albedo, radiative forcing, and enhanced melting pp.1614-7499, 2019, https://doi.org/10.1007/s11356-019-04183-5
  3. Trends in Peroxyacetyl Nitrate (PAN) in the upper troposphere and lower stratosphere over Southern Asia during the summer monsoon season: regional impacts vol.14, pp.13, 2013, https://doi.org/10.5194/acpd-14-19055-2014
  4. Development of an Emissions Processing System for Climate Scenario Inventories to Support Global and Asian Air Quality Modeling Studies vol.11, pp.4, 2013, https://doi.org/10.5572/ajae.2017.11.4.330
  5. Development of the CREATE Inventory in Support of Integrated Climate and Air Quality Modeling for Asia vol.12, pp.19, 2013, https://doi.org/10.3390/su12197930