Biomass burning emissions

This page describes the options for biomass burning emissions in GEOS-Chem.

GFED4

The GFED4 biomass burning emission inventory is now the current default biomass burning dataset for GEOS-Chem (introduced in v10-01, June 2015). The current GFED4 archive contains data from 1997 through 2016.

GFED4 has since superseded the obsolete GFED3 and GFED2 inventories.

--Bob Yantosca (talk) 19:18, 2 January 2019 (UTC)

FINNv1

The FINNv1 biomass burning emission inventory has been added to GEOS-Chem v10-01 via the HEMCO emissions component. This inventory may be used to replace GFED4 for research purposes.

--Melissa Sulprizio 10:21, 18 February 2015 (EST)

QFED

The QFED biomass burning emission inventory has been added to GEOS-Chem v10-01 via the HEMCO emissions component. This inventory may be used to replace GFED4 for research purposes.

--Melissa Sulprizio (talk) 18:27, 14 September 2016 (UTC)

GFAS

The GFAS biomass burning emission inventory was added in GEOS-Chem 12.2.0 via the HEMCO emissions component. This inventory may be used to replace GFED4 for research purposes.

--Melissa Sulprizio (talk) 12:19, 4 October 2018 (UTC)

FIRECAM tool

I developed the FIRECAM tool for end-users to quickly compare fire emissions estimates from five global inventories (GFEDv4s, GFASv1.2, FINNv1.5, QFEDv2.5r1, and FEERv1.0-G1.2) for a given study region. Currently, FIRECAM supports six species: CO2, CO, CH4, OC, BC, and PM2.5. FIRECAM compares the five inventories at an aggregated 0.5deg x 0.5deg spatial resolution for the 2003-2018 time period. Please see the FIRECAM website and our paper for more information. The paper describes the methodological differences among these inventories and metrics we developed to diagnose spatial biases and uncertainties. We recommend end-users to use multiple inventories in model runs, if possible. As we show in our paper, the choice of emissions inventory can significantly impact model results. If this is not feasible, please take the time to see how much emissions estimates vary in your study region using the FIRECAM tool.

--Tianjia Liu (talk) 15:30, 21 August 2019 (EDT)

References

1. Duncan, B.N., et al., Interannual and Seasonal Variability of Biomass Burning Emissions Constrained by Satellite Observations, J. Geophys. Res., 108(D2), 4040, doi:10.1029/2002JD002378, 2003. PDF
2. Hyer, E., FLAMBE Biomass Burning emissions for ARCTAS, 2008. PDF
3. Lobert, J. M., W. C. Keene, J. A. Logan, and R. Yevich, Global chlorine emissions from biomass burning: the reactive chlorine emissions inventory, J. Geophys. Res., 8, 2999-3014, 2008.
4. Mu, M., J.T. Randerson, G.R. van der Werf, L. Giglio, P. Kasibhatla, D. Morton, G.J. Collatz, R.S. DeFries, E.J. Hyer, E.M. Prins, D.W.T. Griffith, D. Wunch, G.C. Toon, V. Sherlock, and P.O. Wennberg, Daily and 3-hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide, Journal of Geophysical Research-Atmospheres, 116, D24303, doi:10.1029/2011JD016245, 2011.
5. Nassar, R., J. A. Logan, I. A. Megretskaia, L. T. Murray, L. Zhang, and D. B. A. Jones, Analysis of tropical tropospheric ozone, carbon monoxide and water vapor during the 2006 El Niño using TES observations and the GEOS-Chem model, J. Geophys. Res., 114, D17304, doi:10.1029/2009JD011760, 2009. PDF
6. Liu, T., L.J. Mickley, R.S. DeFries, M.E. Marlier, M.F. Khan, M.T. Latif, and A. Karambelas, Diagnosing spatial uncertainties and relative biases in global fire emissions inventories: Indonesia as regional case study, Remote Sens. Environ., 237, 111557. Article
7. van der Werf, G. R., J. T. Randerson, L. Giglio, T. T. van Leeuwen, Y. Chen, B. M. Rogers, M. Mu, M. J. E. van Marle, D. C. Morton, G. J. Collatz, R. J. Yokelson, and P. S. Kasibhatla, Global fire emissions estimates during 1997–2016, Earth Sys. Sci. Data, 9, 697-720, 2017. Article
8. Wiedinmyer, C., S.K. Akagi, R.J. Yokelson, L.K. Emmons, J.J. Orlando, and A.J. Soja, The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, 2011. Article
9. 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. Article
10. Darmenov, A.S. and A. da Silva, The Quick Fire Emissions Dataset (QFED) - Documentation of versions 2.1, 2.2, and 2.4, NASA Technical Report Series on Global Modeling and Data Assimilation, Volume 32, 2013. Article
11. Ichoku, C. and L. Ellison, Global top-down smoke-aerosol emissions estimation using satellite fire radiative power measurements, Atmos. Chem. Phys., 14, 6643–6667, 2014. Article

--Melissa Payer 15:10, 21 February 2012 (EST)