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Related Experiment Videos

CO2 emissions from the 2010 Russian wildfires using GOSAT data.

Meng Guo1, Jing Li2, Jiawei Xu1

  • 1School of Geographical Sciences, Northeast Normal University, Changchun 130024, Jilin Province, China.

Environmental Pollution (Barking, Essex : 1987)
|April 14, 2017
PubMed
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Wildfires in western Russia in 2010 emitted an estimated 255.76 Tg CO2. This study introduces a novel remote sensing method to assess biomass burning impacts on the carbon cycle and global warming.

Area of Science:

  • Atmospheric Science
  • Remote Sensing
  • Environmental Science

Background:

  • Intense heat waves and atmospheric blocking caused widespread wildfires in western Russia during summer 2010.
  • Wildfires significantly impact atmospheric composition and the global carbon cycle.

Purpose of the Study:

  • To evaluate carbon dioxide (CO2) emissions from the 2010 western Russia wildfires using satellite data.
  • To propose and validate a new remote sensing methodology for assessing wildfire-related CO2 emissions.
  • To enhance understanding of biomass burning effects on regional/continental carbon cycles and global warming.

Main Methods:

  • Utilized Greenhouse gases Observing SATellite (GOSAT) data, including Cloud and Aerosol Imager (CAI) and Fourier-Transform Spectrometer (FTS) Thermal InfraRed (TIR) sensors.
Keywords:
Biomass burning model (BBM)CO(2) emissionsGOSAT dataWildfire

Related Experiment Videos

  • Employed GOSAT CAI for smoke plume identification and FTS TIR for plume height estimation (approx. 800 hPa).
  • Calculated CO2 emissions using GOSAT data and compared results with the Biomass Burning Model (BBM).

    • Main Results:

    • GOSAT CAI effectively identified smoke plumes from the 2010 wildfires.
    • GOSAT FTS TIR enabled estimation of plume heights at approximately 1.58 km (800 hPa).
    • Estimated CO2 emissions from GOSAT data were 255.76 Tg, closely aligning with BBM estimates (261.82–302.48 Tg).

    Conclusions:

    • GOSAT data provides a viable method for estimating CO2 emissions from large-scale wildfires.
    • The proposed remote sensing approach can improve the accuracy of greenhouse gas emission models.
    • This research contributes to a better understanding of wildfire impacts on the atmospheric carbon cycle and global warming.