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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-210
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-210
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model description paper 08 Oct 2019

Submitted as: model description paper | 08 Oct 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

APIFLAME v2.0 trace gas and aerosol emissions from biomass burning: application to Portugal during the summer of 2016 and evaluation against satellite observations of CO (IASI) and AOD (MODIS)

Solène Turquety1, Laurent Menut1, Guillaume Siour2, Sylvain Mailler1,3, Juliette Hadji-Lazaro4, Maya George4, Cathy Clerbaux4,5, Daniel Hurtmans5, and Pierre-François Coheur5 Solène Turquety et al.
  • 1LMD/IPSL, Laboratoire de Météorologie Dynamique, Sorbonne Université, Ecole Polytechnique, IPSL Research University,Ecole Normale Supérieure, CNRS, 75252 Paris, France
  • 2Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA), UMR7583, CNRS, Université Paris-Est-Créteil,Université de Paris, Institut Pierre Simon Laplace, Créteil, France
  • 3Ecole des Ponts ParisTech, Université Paris-Est, 77455 Champs-sur-Marne, France
  • 4LATMOS/IPSL, Sorbonne Université, UVSQ, CNRS, Paris, France
  • 5Université libre de Bruxelles (ULB), Service de Chimie Quantique et Photophysique, Atmospheric Spectroscopy, Brussels, Belgium

Abstract. Biomass burning emissions are a major source of trace gases and aerosols. Wildfires being highly variable in time and space, calculating emissions requires a numerical tool able to estimate fluxes at the kilometer scale and with an hourly time-step. Here, the APIFLAME model version 2.0 is presented. It is structured to be modular in terms of input databases and processing methods. The main evolution compared to the version v1.0 is the possibility to merge burned area and fire radiative power (FRP) satellite observations to modulate the temporal variations of fire emissions and to integrate small fires that may not be detected in the burned area product. Accounting for possible missed detection due to small fires results in an increase ranging from ∼ 5 % in Africa and Australia to ∼ 30 % in North America, on average over the 2013–2017 time period based on the Moderate-Resolution Imaging Spectroradiometer (MODIS) collection 6 fire products.

An illustration for the case of south-western Europe during the summer of 2016, marked by large wildfires in Portugal, is presented. Emissions calculated using different possible configurations of APIFLAME show a dispersion of 75% on average over the domain during the largest wildfires (8–14/08/2016), which can be considered as an estimate of uncertainty on emissions (excluding the uncertainty on emission factors). Corresponding enhancements of aerosols and carbon monoxide (CO) simulated with the regional chemistry transport model CHIMERE are consistent with observations (good timing for the beginning and end of the events, ± 1 day for the timing of the peak values) but tend to be overestimated compared to observations at surface stations. On the contrary, vertically integrated concentrations tend to be underestimated compared to satellite observations of total column CO by the Infrared Atmospheric Sounding Interferometer (IASI) instrument and aerosol optical depth (AOD) by MODIS, which allow regional scale evaluation. This underestimate is lower close to the fire region (5 % to 40 % for AOD depending on the configuration, and 8–18 % for total CO) but rapidly increases downwind. For all comparisons, better agreement is achieved when emissions are injected higher into the free troposphere using a vertical profile as estimated from observations of aerosol plume height by the MISR satellite instrument (injection up to 4 km). The overestimate compared to surface sites and underestimate compared to satellite observations point to uncertainties not only on emissions (total mass and daily variability) but also on their injection profile and on the modelling of the transport of these dense plumes.

Solène Turquety et al.
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Solène Turquety et al.
Data sets

APIFLAMEv2 global burned area from MODIS satellite observations 2014-2017 S. Turquety https://doi.org/10.14768/20190913002.1

APIFLAMEv2 biomass burning emissions in Europe during the Summer 2016 S. Turquety https://doi.org/10.14768/20190913003.1

Model code and software

APIFLAMEv2 biomass burning emissions model S. Turquety https://doi.org/10.14768/20190913001.1

Solène Turquety et al.
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Short summary
Biomass burning emissions are a major source of trace gases and aerosols that needs to be accounted for for air quality assessment and forecasting. The APIFLAME model presented in this publication allows the calculation of these emissions based on satellite observations at hourly time-step and kilometric scale. An illustration for the simulation of the pollution plume associated with the large wildfires that burned in Portugal in August 2016 is presented.
Biomass burning emissions are a major source of trace gases and aerosols that needs to be...
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