Estimation of black carbon emissions from Siberian fires using satellite observations of absorption and extinction optical depths
Black carbon (BC) emissions from open biomass burning (BB) are known to have a considerable impact on the radiative budget of the atmosphere at both global and regional scales; however, these emissions are poorly constrained in models by atmospheric observations, especially in remote regions. Here,...
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ftdoajarticles:oai:doaj.org/article:8b2f9c5133dc49c0b43da44800b2eece 2023-05-15T13:07:00+02:00 Estimation of black carbon emissions from Siberian fires using satellite observations of absorption and extinction optical depths I. B. Konovalov D. A. Lvova M. Beekmann H. Jethva E. F. Mikhailov J.-D. Paris B. D. Belan V. S. Kozlov P. Ciais M. O. Andreae 2018-10-01T00:00:00Z https://doi.org/10.5194/acp-18-14889-2018 https://doaj.org/article/8b2f9c5133dc49c0b43da44800b2eece EN eng Copernicus Publications https://www.atmos-chem-phys.net/18/14889/2018/acp-18-14889-2018.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 doi:10.5194/acp-18-14889-2018 1680-7316 1680-7324 https://doaj.org/article/8b2f9c5133dc49c0b43da44800b2eece Atmospheric Chemistry and Physics, Vol 18, Pp 14889-14924 (2018) Physics QC1-999 Chemistry QD1-999 article 2018 ftdoajarticles https://doi.org/10.5194/acp-18-14889-2018 2022-12-31T02:13:03Z Black carbon (BC) emissions from open biomass burning (BB) are known to have a considerable impact on the radiative budget of the atmosphere at both global and regional scales; however, these emissions are poorly constrained in models by atmospheric observations, especially in remote regions. Here, we investigate the feasibility of constraining BC emissions from BB using satellite observations of the aerosol absorption optical depth (AAOD) and the aerosol extinction optical depth (AOD) retrieved from OMI (Ozone Monitoring Instrument) and MODIS (Moderate Resolution Imaging Spectroradiometer) measurements, respectively. We consider the case of Siberian BB BC emissions, which have the strong potential to impact the Arctic climate system. Using aerosol remote sensing data collected at Siberian sites of the AErosol RObotic NETwork (AERONET) along with the results of the fourth Fire Lab at Missoula Experiment (FLAME-4), we establish an empirical parameterization relating the ratio of the elemental carbon (EC) and organic carbon (OC) contents in BB aerosol to the ratio of AAOD and AOD at the wavelengths of the satellite observations. Applying this parameterization to the BC and OC column amounts simulated using the CHIMERE chemistry transport model, we optimize the parameters of the BB emission model based on MODIS measurements of the fire radiative power (FRP); we then obtain top-down optimized estimates of the total monthly BB BC amounts emitted from intense Siberian fires that occurred from May to September 2012. The top-down estimates are compared to the corresponding values obtained using the Global Fire Emissions Database (GFED4) and the Fire Emission Inventory–northern Eurasia (FEI-NE). Our simulations using the optimized BB aerosol emissions are verified against AAOD and AOD data that were withheld from the estimation procedure. The simulations are further evaluated against in situ EC and OC measurements at the Zotino Tall Tower Observatory (ZOTTO) and also against aircraft aerosol measurement data collected in ... Article in Journal/Newspaper Aerosol Robotic Network Arctic black carbon Directory of Open Access Journals: DOAJ Articles Arctic Atmospheric Chemistry and Physics 18 20 14889 14924 |
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English |
topic |
Physics QC1-999 Chemistry QD1-999 |
spellingShingle |
Physics QC1-999 Chemistry QD1-999 I. B. Konovalov D. A. Lvova M. Beekmann H. Jethva E. F. Mikhailov J.-D. Paris B. D. Belan V. S. Kozlov P. Ciais M. O. Andreae Estimation of black carbon emissions from Siberian fires using satellite observations of absorption and extinction optical depths |
topic_facet |
Physics QC1-999 Chemistry QD1-999 |
description |
Black carbon (BC) emissions from open biomass burning (BB) are known to have a considerable impact on the radiative budget of the atmosphere at both global and regional scales; however, these emissions are poorly constrained in models by atmospheric observations, especially in remote regions. Here, we investigate the feasibility of constraining BC emissions from BB using satellite observations of the aerosol absorption optical depth (AAOD) and the aerosol extinction optical depth (AOD) retrieved from OMI (Ozone Monitoring Instrument) and MODIS (Moderate Resolution Imaging Spectroradiometer) measurements, respectively. We consider the case of Siberian BB BC emissions, which have the strong potential to impact the Arctic climate system. Using aerosol remote sensing data collected at Siberian sites of the AErosol RObotic NETwork (AERONET) along with the results of the fourth Fire Lab at Missoula Experiment (FLAME-4), we establish an empirical parameterization relating the ratio of the elemental carbon (EC) and organic carbon (OC) contents in BB aerosol to the ratio of AAOD and AOD at the wavelengths of the satellite observations. Applying this parameterization to the BC and OC column amounts simulated using the CHIMERE chemistry transport model, we optimize the parameters of the BB emission model based on MODIS measurements of the fire radiative power (FRP); we then obtain top-down optimized estimates of the total monthly BB BC amounts emitted from intense Siberian fires that occurred from May to September 2012. The top-down estimates are compared to the corresponding values obtained using the Global Fire Emissions Database (GFED4) and the Fire Emission Inventory–northern Eurasia (FEI-NE). Our simulations using the optimized BB aerosol emissions are verified against AAOD and AOD data that were withheld from the estimation procedure. The simulations are further evaluated against in situ EC and OC measurements at the Zotino Tall Tower Observatory (ZOTTO) and also against aircraft aerosol measurement data collected in ... |
format |
Article in Journal/Newspaper |
author |
I. B. Konovalov D. A. Lvova M. Beekmann H. Jethva E. F. Mikhailov J.-D. Paris B. D. Belan V. S. Kozlov P. Ciais M. O. Andreae |
author_facet |
I. B. Konovalov D. A. Lvova M. Beekmann H. Jethva E. F. Mikhailov J.-D. Paris B. D. Belan V. S. Kozlov P. Ciais M. O. Andreae |
author_sort |
I. B. Konovalov |
title |
Estimation of black carbon emissions from Siberian fires using satellite observations of absorption and extinction optical depths |
title_short |
Estimation of black carbon emissions from Siberian fires using satellite observations of absorption and extinction optical depths |
title_full |
Estimation of black carbon emissions from Siberian fires using satellite observations of absorption and extinction optical depths |
title_fullStr |
Estimation of black carbon emissions from Siberian fires using satellite observations of absorption and extinction optical depths |
title_full_unstemmed |
Estimation of black carbon emissions from Siberian fires using satellite observations of absorption and extinction optical depths |
title_sort |
estimation of black carbon emissions from siberian fires using satellite observations of absorption and extinction optical depths |
publisher |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/acp-18-14889-2018 https://doaj.org/article/8b2f9c5133dc49c0b43da44800b2eece |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Aerosol Robotic Network Arctic black carbon |
genre_facet |
Aerosol Robotic Network Arctic black carbon |
op_source |
Atmospheric Chemistry and Physics, Vol 18, Pp 14889-14924 (2018) |
op_relation |
https://www.atmos-chem-phys.net/18/14889/2018/acp-18-14889-2018.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 doi:10.5194/acp-18-14889-2018 1680-7316 1680-7324 https://doaj.org/article/8b2f9c5133dc49c0b43da44800b2eece |
op_doi |
https://doi.org/10.5194/acp-18-14889-2018 |
container_title |
Atmospheric Chemistry and Physics |
container_volume |
18 |
container_issue |
20 |
container_start_page |
14889 |
op_container_end_page |
14924 |
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1766030535973404672 |