Articles | Volume 24, issue 18
https://doi.org/10.5194/acp-24-10543-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-10543-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Sep 2024
Research article |
| 23 Sep 2024
| 23 Sep 2024
Light-absorbing black carbon and brown carbon components of smoke aerosol from DSCOVR EPIC measurements over North America and central Africa
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore, Baltimore County, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Alexei Lyapustin
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Gregory L. Schuster
NASA Langley Research Center, Hampton, VA, USA
Sujung Go
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore, Baltimore County, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Yujie Wang
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore, Baltimore County, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Sergey Korkin
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore, Baltimore County, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Ralph Kahn
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Laboratory for Atmospheric and Space Physics, University of Colorado Boulder, Boulder, CO, USA
Jeffrey S. Reid
US Naval Research Laboratory, Monterey, CA, USA
Edward J. Hyer
US Naval Research Laboratory, Monterey, CA, USA
Thomas F. Eck
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore, Baltimore County, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Mian Chin
NASA Goddard Space Flight Center, Greenbelt, MD, USA
David J. Diner
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Olga Kalashnikova
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Oleg Dubovik
Laboratoire d'Optique Atmosphérique, Université de Lille-1, CNRS, Villeneuve-d'Ascq, France
Jhoon Kim
Department of Atmospheric Sciences, Yonsei University, Seoul, Republic of Korea
Hans Moosmüller
Laboratory for Aerosol Science, Spectroscopy, and Optics, Desert Research Institute, Reno, NV, USA
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Cited
12 citations as recorded by crossref.
- Climatology and variability of smoke aerosols from MAIAC EPIC observations over North America (2016–2024) M. Choi et al. https://doi.org/10.3389/frsen.2025.1654779
- Multi-Satellite Assessment of Factors Controlling Biomass Burning Aerosol Formation over the South China Sea L. Liang et al. https://doi.org/10.3390/rs18101462
- Aerosol and cloud retrieval algorithm of TANSO-3/GOSAT-GW: theoretical basis and validations during the 2024 ASIA-AQ campaign using the TROPOMI observations as a testbed H. Lim et al. https://doi.org/10.1186/s40645-026-00820-z
- Black carbon in major global source areas from 2000 to 2023: Spatiotemporal variation, vertical distribution, and extreme case analysis Y. Zhang et al. https://doi.org/10.1016/j.envpol.2025.125929
- Simultaneous retrieval of aerosol optical depth, spectral absorption and layer height from DSCOVR EPIC using MAIAC algorithm A. Lyapustin et al. https://doi.org/10.3389/frsen.2025.1677438
- Brown carbon unveiled: Molecular complexity, observational frontiers, and climate forcing T. Yang et al. https://doi.org/10.1016/j.fmre.2026.01.010
- Retrieval of black carbon aerosol surface concentration using integrated MODIS and AERONET data X. Jiang et al. https://doi.org/10.5194/amt-18-4559-2025
- Absorbing Aerosol Effects on Hyperspectral Surface and Underwater UV Irradiances from OMI Measurements and Radiative Transfer Computations A. Vasilkov et al. https://doi.org/10.3390/rs17030562
- Dense Optical Flow Retrieval of Wildfire Smoke Plume Motion from Spaceborne and Airborne Imagery I. Yanovsky et al. https://doi.org/10.3390/rs18121868
- MAIAC-based climatology of atmospheric iron-oxide dust species from DSCOVR EPIC observations S. Go et al. https://doi.org/10.3389/frsen.2025.1676851
- Collaborative Neural Networks Significantly Improve Global Aerosol Retrievals From Multiangle Polarimeters G. Fu et al. https://doi.org/10.1109/TGRS.2026.3685881
- Decoding clues on dominant combustion phase and aerosol chemical regimes via key tracers of fire plumes E. Dovrou et al. https://doi.org/10.1038/s44407-025-00032-7
12 citations as recorded by crossref.
- Climatology and variability of smoke aerosols from MAIAC EPIC observations over North America (2016–2024) M. Choi et al. https://doi.org/10.3389/frsen.2025.1654779
- Multi-Satellite Assessment of Factors Controlling Biomass Burning Aerosol Formation over the South China Sea L. Liang et al. https://doi.org/10.3390/rs18101462
- Aerosol and cloud retrieval algorithm of TANSO-3/GOSAT-GW: theoretical basis and validations during the 2024 ASIA-AQ campaign using the TROPOMI observations as a testbed H. Lim et al. https://doi.org/10.1186/s40645-026-00820-z
- Black carbon in major global source areas from 2000 to 2023: Spatiotemporal variation, vertical distribution, and extreme case analysis Y. Zhang et al. https://doi.org/10.1016/j.envpol.2025.125929
- Simultaneous retrieval of aerosol optical depth, spectral absorption and layer height from DSCOVR EPIC using MAIAC algorithm A. Lyapustin et al. https://doi.org/10.3389/frsen.2025.1677438
- Brown carbon unveiled: Molecular complexity, observational frontiers, and climate forcing T. Yang et al. https://doi.org/10.1016/j.fmre.2026.01.010
- Retrieval of black carbon aerosol surface concentration using integrated MODIS and AERONET data X. Jiang et al. https://doi.org/10.5194/amt-18-4559-2025
- Absorbing Aerosol Effects on Hyperspectral Surface and Underwater UV Irradiances from OMI Measurements and Radiative Transfer Computations A. Vasilkov et al. https://doi.org/10.3390/rs17030562
- Dense Optical Flow Retrieval of Wildfire Smoke Plume Motion from Spaceborne and Airborne Imagery I. Yanovsky et al. https://doi.org/10.3390/rs18121868
- MAIAC-based climatology of atmospheric iron-oxide dust species from DSCOVR EPIC observations S. Go et al. https://doi.org/10.3389/frsen.2025.1676851
- Collaborative Neural Networks Significantly Improve Global Aerosol Retrievals From Multiangle Polarimeters G. Fu et al. https://doi.org/10.1109/TGRS.2026.3685881
- Decoding clues on dominant combustion phase and aerosol chemical regimes via key tracers of fire plumes E. Dovrou et al. https://doi.org/10.1038/s44407-025-00032-7
Saved (final revised paper)
Latest update: 21 Jul 2026
Short summary
This paper introduces a retrieval algorithm to estimate two key absorbing components in smoke (black carbon and brown carbon) using DSCOVR EPIC measurements. Our analysis reveals distinct smoke properties, including spectral absorption, layer height, and black carbon and brown carbon, over North America and central Africa. The retrieved smoke properties offer valuable observational constraints for modeling radiative forcing and informing health-related studies.
This paper introduces a retrieval algorithm to estimate two key absorbing components in smoke...
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