GFAS biomass burning emissions

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Overview

NOTE: The GFAS biomass burning emissions inventory will be available for simulations with GEOS-Chem 12 via the HEMCO emissions component. While the standard GEOS-Chem simulation uses GFED4 biomass burning emissions, you may select GFAS instead of GFED4 if your research requires it.

From the GFAS website:

The Global Fire Assimilation System (GFAS) assimilates fire radiative power (FRP) observations from satellite-based sensors to produce daily estimates of biomass burning emissions. It has been extended to include information about injection heights derived from fire observations and meteorological information from the operational weather forecasts of ECMWF.

FRP observations currently assimilated in GFAS are the NASA Terra MODIS and Aqua MODIS active fire products (http://modis-fire.umd.edu/pages/ActiveFire.php).

GFAS data includes: Fire Radiative Power (FRP), dry matter burnt and biomass burning emissions.

Data are available globally on a regular lat-lon grid with horizontal resolution of 0.1 degrees from 2003 to present.

Implementation in GEOS-Chem

To use the GFAS emissions in GEOS-Chem, the following lines must be added to HEMCO_Config.rc

#==============================================================================
# --- GFAS biomass burning ---
#==============================================================================
(((GFAS
0 GFAS_CO    $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc cofire        2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s CO   75    5 3
0 GFAS_NO    $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc noxfire       2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s NO   75    5 3
0 GFAS_BCPI  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc bcfire        2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s BCPI 70/75 5 3
0 GFAS_BCPO  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc bcfire        2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s BCPO 71/75 5 3
0 GFAS_OCPI  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc ocfire        2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s OCPI 72/75 5 3
0 GFAS_OCPO  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc ocfire        2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s OCPO 73/75 5 3
0 GFAS_CO2   $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc co2fire       2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s CO2  75    5 3
0 GFAS_CH4   $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc ch4fire       2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s CH4  75    5 3
0 GFAS_SO2   $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc so2fire       2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s SO2  75    5 3
0 GFAS_NH3   $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc nh3fire       2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s NH3  75    5 3
0 GFAS_ACET  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c3h6ofire     2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s ACET 75    5 3
0 GFAS_ALD2  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c2h4ofire     2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s ALD2 75    5 3
0 GFAS_ALK4  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc hialkanesfire 2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s ALK4 75    5 3
0 GFAS_PRPE1 $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc hialkenesfire 2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s PRPE 75    5 3
0 GFAS_PRPE2 $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c3h6fire      2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s PRPE 75    5 3
0 GFAS_C2H6  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c2h6fire      2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s C2H6 75    5 3
0 GFAS_C3H8  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c3h8fire      2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s C3H8 75    5 3
0 GFAS_CH2O  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc ch2ofire      2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s CH2O 75    5 3
0 GFAS_C2H4  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c2h4fire      2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s C2H4 75    5 3
0 GFAS_ISOP  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c5h8fire      2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s ISOP 75    5 3
0 GFAS_DMS   $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c2h6sfire     2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s DMS  75    5 3
0 GFAS_TOLU  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c7h8fire      2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s TOLU 75    5 3
0 GFAS_BENZ  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c6h6fire      2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s BENZ 75    5 3
0 GFAS_XYLE  $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc c8h10fire     2014-2016/1-12/1-31/0 C xyL=1:scal300 kg/m2/s XYLE 75    5 3
)))GFAS

#==============================================================================
# --- GFAS scale factors ---
#==============================================================================
300 GFAS_EMITL $ROOT/GFAS/v2017-03/$YYYY/GFAS_$YYYY$MM.nc mami 2014-2016/1-12/1-31/0 C xy m 1

Citation

Please acknowledge the use of this data set according to the terms of the Copernicus CAMS License agreement:

Contains modified Copernicus Atmosphere Monitoring Service Information 2018

References

  1. Di Giuseppe, F., S. Rémy, F. Pappenberger, and F. Wetterhall, Combining fire radiative power observations with the fire weather index improves the estimation of fire emissions, Atmos. Chem. Phys., 18, 5359-5370, https://doi.org/10.5194/acp-18-5359-2018, 2018.
  2. Rémy, S., A. Veira, R. Paugam, M. Sofiev, J.W. Kaiser, F. Marenco, S.P. Burton, A. Benedetti, R.J. Engelen, R. Ferrare, J.W. Hair, Two global data sets of daily fire emission injection heights since 2003, Atmos. Chem. Phys., 17, 2921-2942, https://doi.org/10.5194/acp-17-2921-2017, 2017.
  3. Andela, N. (VUA), J.W. Kaiser (ECMWF, KCL), A. Heil (FZ Jülich), T.T. van Leeuwen (VUA), G.R. van der Werf (VUA), M.J. Wooster (KCL), S. Remy (ECMWF) and M.G. Schultz (FZ Jülich), Assessment of the Global Fire Assimilation System (GFASv1).
  4. Kaiser, J. W., A. Heil, M.O. Andreae, A. Benedetti, N.,Chubarova, L. Jones, J.-J. Morcrette, M. Razinger, M.G. Schultz, M. Suttie, and G.R. van der Werf, Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527-554.(2012)
  5. Xu, W., M.J. Wooster, G. Roberts, P. Freeborn, New GOES imager algorithms for cloud and active fire detection and fire radiative power assessment across North, South and Central America, Remote Sensing of Environment, 114, 1876-1895, 2010.
  6. Heil, A., J.W. Kaiser, G.R. van der Werf, M.J. Wooster, M.G. Schultz, H.D. van der Gon, Assessment of the Real-Time Fire Emissions (GFASv0) by MACC, ECMWF Tech. Memo No. 628, 2010.
  7. Di Giuseppe, F., S. Remy, F. Pappenberger, F. Wetterhall, Improving GFAS and CAMS biomass burning estimations by means of the Global ECMWF Fire Forecast system (GEFF), ECMWF Tech. Memo No. 790, 2016.