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  Constraining CO2 emissions from open biomass burning by satellite observations of co-emitted species: a method and its application to wildfires in Siberia

Konovalov, I. B., Berezin, E. V., Ciais, P., Broquet, G., Beekmann, M., Hadji-Lazaro, J., Clerbaux, C., Andreae, M. O., Kaiser, J. W., & Schulze, E.-.-D. (2014). Constraining CO2 emissions from open biomass burning by satellite observations of co-emitted species: a method and its application to wildfires in Siberia. Atmospheric Chemistry and Physics, 14(19), 10383-10410. doi:10.5194/acp-14-10383-2014.

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資料種別: 学術論文

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 作成者:
Konovalov, I. B.1, 著者
Berezin, E. V.1, 著者
Ciais, P.1, 著者
Broquet, G.1, 著者
Beekmann, M.1, 著者
Hadji-Lazaro, J.1, 著者
Clerbaux, C.1, 著者
Andreae, M. O.2, 著者           
Kaiser, J. W.3, 著者           
Schulze, E. -D.1, 著者
所属:
1external, ou_persistent22              
2Biogeochemistry, Max Planck Institute for Chemistry, Max Planck Society, ou_1826286              
3Atmospheric Chemistry, Max Planck Institute for Chemistry, Max Planck Society, ou_1826285              

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 要旨: A method to constrain carbon dioxide (CO2) emissions from open biomass burning by using satellite observations of co-emitted species and a chemistry-transport model (CTM) is proposed and applied to the case of wildfires in Siberia. CO2 emissions are assessed by means of an emission model assuming a direct relationship between the biomass burning rate (BBR) and the fire radiative power (FRP) derived from MODIS measurements. The key features of the method are (1) estimating the FRP-to-BBR conversion factors (alpha) for different vegetative land cover types by assimilating the satellite observations of co-emitted species into the CTM, (2) optimal combination of the estimates of alpha derived independently from satellite observations of different species (CO and aerosol in this study), and (3) estimation of the diurnal cycle of the fire emissions directly from the FRP measurements. Values of alpha for forest and grassland fires in Siberia and their uncertainties are estimated using the Infrared Atmospheric Sounding Interferometer (IASI) carbon monoxide (CO) retrievals and MODIS aerosol optical depth (AOD) measurements combined with outputs from the CHIMERE mesoscale chemistry-transport model. The constrained CO emissions are validated through comparison of the respective simulations with independent data of ground-based CO measurements at the ZOTTO site. Using our optimal regional-scale estimates of the conversion factors (which are found to be in agreement with earlier published estimates obtained from local measurements of experimental fires), the total CO2 emissions from wildfires in Siberia in 2012 are estimated to be in the range from 280 to 550 Tg C, with the optimal (maximum likelihood) value of 392 Tg C. Sensitivity test cases featuring different assumptions regarding the injection height and diurnal variations of emissions indicate that the derived estimates of the total CO2 emissions in Siberia are robust with respect to the modeling options (the different estimates vary within less than 15% of their magnitude). The CO2 emission estimates obtained for several years are compared with independent estimates provided by the GFED3.1 and GFASv1.0 global emission inventories. It is found that our "top-down" estimates for the total annual biomass burning CO2 emissions in the period from 2007 to 2011 in Siberia are by factors of 2.5 and 1.8 larger than the respective bottom-up estimates; these discrepancies cannot be fully explained by uncertainties in our estimates. There are also considerable differences in the spatial distribution of the different emission estimates; some of those differences have a systematic character and require further analysis.

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 日付: 2014
 出版の状態: 出版
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 識別子(DOI, ISBNなど): ISI: 000344164800001
DOI: 10.5194/acp-14-10383-2014
 学位: -

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出版物 1

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出版物名: Atmospheric Chemistry and Physics
種別: 学術雑誌
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出版社, 出版地: Katlenburg-Lindau, Germany : European Geosciences Union
ページ: - 巻号: 14 (19) 通巻号: - 開始・終了ページ: 10383 - 10410 識別子(ISBN, ISSN, DOIなど): ISSN: 1680-7316
CoNE: https://pure.mpg.de/cone/journals/resource/111030403014016