Preprints
https://doi.org/10.5194/egusphere-2022-450
https://doi.org/10.5194/egusphere-2022-450
 
10 Jun 2022
10 Jun 2022
Status: this preprint is open for discussion.

Sixteen years of MOPITT satellite data strongly constrain Amazon CO fire emissions

Stijn Naus1,2, Lucas G. Domingues3,4, Maarten Krol1,5, Ingrid T. Luijkx1, Luciana V. Gatti4,6, John B. Miller7, Emanuel Gloor8, Sourish Basu9,10, Caio Correia4,6, Gerbrand Koren11, Helen M. Worden12, Johannes Flemming13, Gabrielle Pétron7,14, and Wouter Peters1,15 Stijn Naus et al.
  • 1Meteorology and Air Quality, Wageningen University and Research, The Netherlands
  • 2SRON Netherlands Institute for Space Research, Utrecht, The Netherlands
  • 3National Isotope Centre, GNS Science, New Zealand
  • 4Nuclear and Energy Research Institute, São Paulo, Brazil
  • 5Institute for Marine and Atmospheric Research, Utrecht University, The Netherlands
  • 6National Institute for Space Research (INPE), São José dos Campos, Brazil
  • 7Global Monitoring Laboratory, National Oceanographic and Atmospheric Administration, Boulder, CO, USA
  • 8School of Geography, University of Leeds, Leeds, UK
  • 9Earth System Science Interdisciplinary Center, University of Maryland, MD, USA
  • 10NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 11Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands
  • 12Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO, USA
  • 13European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
  • 14Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
  • 15Centre for Isotope Research, University of Groningen, The Netherlands

Abstract. Despite consensus on the overall downward trend in Amazon forest loss in the previous decade, estimates of yearly carbon emissions from deforestation still vary widely. Estimated carbon emissions are currently often based on data from local logging activity reports, changes in remotely sensed biomass as well as remote detection of fire hotspots, and burned area. Here, we use sixteen years of satellite-derived carbon monoxide (CO) columns to constrain fire CO emissions from the Amazon basin between 2003 and 2018. Through data assimilation, we produce 3-daily maps of fire CO emissions over the Amazon that we verified to be consistent with a long-term monitoring program of aircraft CO profiles over five sites in the Amazon. Our new product independently confirms a long-term decrease of 54 % in deforestation-related CO emissions over the study period. Interannual variability is large, with known anomalously dry years showing a more than fourfold increase in basin-wide fire emissions. At the level of individual Brazilian states, we find that both soil moisture anomalies and human ignitions determine fire activity, suggesting that future carbon release from fires depends on drought intensity as much as on continued forest protection. Our study shows that the atmospheric composition perspective on deforestation is a valuable additional monitoring instrument that complements existing bottom-up and remote sensing methods for land-use change. Extension of such a perspective to an operational framework is timely considering the observed increased fire intensity in the Amazon basin in 2019–2021.

Stijn Naus et al.

Status: open (until 27 Jul 2022)

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Stijn Naus et al.

Data sets

Optimized CO fire emissions Stijn Naus, Lucas G. Domingues, Maarten Krol, Ingrid T. Luijkx, Luciana V. Gatti, John B. Miller, Emanuel Gloor, Sourish Basu, Caio Correia, Gerbrand Koren, Helen M. Worden, Johannes Flemming, Gabrielle Pétron, and Wouter Peters https://doi.org/10.6084/m9.figshare.14294492

Stijn Naus et al.

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Short summary
We assimilate MOPITT CO satellite data in the TM5-4DVAR inverse modeling framework to estimate Amazon fire CO emissions for 2003–2018. We show that fire emissions have decreased over the analysis period, coincident with a decrease in deforestation rates. However, interannual variations in fire emissions are large, and correlate strongly with soil moisture. Our results reveal an important role of robust, top-down fire CO emissions in quantifying and attributing Amazon fire intensity.