25 Apr 2022
25 Apr 2022
Status: a revised version of this preprint was accepted for the journal ACP.

Derivation and validation of top-down African biomass burning CO emissions and fuel consumption measures derived using geostationary FRP data and Sentinal-5P TROPOMI CO retrievals

Hannah Mai Nguyen1,2, Jiangping He1,3, and Martin J. Wooster1,2,3 Hannah Mai Nguyen et al.
  • 1Department of Geography, King’s College London, London, WC2R 2ND, UK
  • 2Leverhulme Centre for Wildfires, Environment and Society, UK
  • 3National Centre for Earth Observation (NCEO), UK

Abstract. We present the first top-down CO fire emissions inventory for Africa based on the direct relation between geostationary satellite-based Fire Radiative Power (FRP) measures and satellite observations of Total Column Carbon Monoxide (TCCO). This work extends significantly the previous Fire Radiative Energy Emissions (FREM) approach that derived Total Particulate Matter (TPM) emission coefficients from FRP measures and Aerosol Optical Depth (AOD) observations. The use of satellite-based CO observations to derive CO emission coefficients, CeCO, addresses key uncertainties in the use of AOD measures to estimate fire-generated CO emissions including; the requirement for a smoke mass extinction coefficient in the AOD to TPM conversion; and the large variation in TPM emission factors – which are used to convert TPM emissions to CO emissions. We use the FREM-derived CO emission coefficients to produce a Pan-African CO fire emission inventory spanning 16 years. Regional CO emissions are in close agreement with the most recent version of GFED(v4.1s), despite the two inventories using completely different satellite datasets and methodologies to derive CO emissions. Dry Matter Consumed (DMC) and DMC per unit area values are generated from our CO emission inventory – the latter using the 20 m resolution Sentinal-2 FireCCISFD burnt area (BA) product for 2019. We carry out an evaluation of our FREM-based CO emissions by using them as input in the WRF-CMAQ chemical transport model and comparing simulated TCCO fields to independent Sentinal-5P TROPOMI TCCO observations. The results of this validation show FREM CO emissions to generally be in good agreement with these independent measures – particularly in the case of individual fire-generated CO plumes where modelled in-plume CO was within 5 % of satellite observations with a coefficient of determination of 0.80. Modelled and observed CO, averaged over the full model domain, are within 4 % of each other, though localised regions show an overestimation of modelled CO by up to 50 %. However, when compared to other evaluations of current state-of-the-art fire emissions inventories, the FREM CO emission inventory derived in this work shows some of the best agreement with independent measures. Updates to the previously published FREM TPM emissions coefficients are also provided in the Appendix of this article, along with a satellite and ground-based validation of this FREM TPM emissions inventory. The methodology and resulting CO fire inventory described in this work will form the basis of an upcoming operational LSASAF CO fire emissions product for Africa.

Hannah Mai Nguyen et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on acp-2022-193', Patrick Freeborn, 10 Jun 2022
    • AC1: 'Reply on CC1', Hannah Nguyen, 01 Aug 2022
  • RC1: 'Comment on acp-2022-193', Anonymous Referee #1, 14 Jun 2022
    • AC2: 'Reply on RC1', Hannah Nguyen, 01 Aug 2022
  • RC2: 'Comment on acp-2022-193', Anonymous Referee #2, 04 Jul 2022
    • AC3: 'Reply on RC2', Hannah Nguyen, 01 Aug 2022

Hannah Mai Nguyen et al.

Hannah Mai Nguyen et al.


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Short summary
This work presents novel methodological advances in the estimation of open biomass burning emissions via a fully ‘top-down’ approach that exploits satellite-derived observations of Fire Radiative Power and carbon monoxide. We produce a 16 year record of fire-generated CO emissions and Dry Matter Consumed per unit area for Africa and validate these emissions estimates through their use in an atmospheric model whose simulation output is then compared to independent satellite observations of CO.