Assessment of fire emission inventories during the South American Biomass Burning Analysis (SAMBBA) experiment

Copernicus GmbH - Tập 16 Số 11 - Trang 6961-6975
Gabriel Pereira1, Ricardo Almeida de Siqueira2, Nilton E. Rosário3, K. Longo2,4, Saulo R. Freitas2,4, Francielle S. Cardozo1, Johannes W. Kaiser5, Martin J. Wooster6,7
1Department of Geoscience, Federal University of Sao Joao del-Rei (UFSJ), Sao Joao del-Rei, Brazil
2Center for Weather Forecast and Climate Studies, National Institute for Space Research (INPE), Cachoeira Paulista, Brazil
3Environmental Sciences Department, São Paulo Federal University (UNIFESP), Diadema, São Paulo, Brazil
4now at: Global Modeling and Assimilation Office, NASA Goddard Space Flight Center and USRA/GESTAR, Greenbelt, MD, USA
5Max Planck Institute for Chemistry (MPIC), Mainz, Germany
6Department of Geography, King's College London (KCL), London, UK
7NERC National Centre for Earth Observation (NCEO), Leicester, UK

Tóm tắt

Abstract. Fires associated with land use and land cover changes release large amounts of aerosols and trace gases into the atmosphere. Although several inventories of biomass burning emissions cover Brazil, there are still considerable uncertainties and differences among them. While most fire emission inventories utilize the parameters of burned area, vegetation fuel load, emission factors, and other parameters to estimate the biomass burned and its associated emissions, several more recent inventories apply an alternative method based on fire radiative power (FRP) observations to estimate the amount of biomass burned and the corresponding emissions of trace gases and aerosols. The Brazilian Biomass Burning Emission Model (3BEM) and the Fire Inventory from NCAR (FINN) are examples of the first, while the Brazilian Biomass Burning Emission Model with FRP assimilation (3BEM_FRP) and the Global Fire Assimilation System (GFAS) are examples of the latter. These four biomass burning emission inventories were used during the South American Biomass Burning Analysis (SAMBBA) field campaign. This paper analyzes and inter-compared them, focusing on eight regions in Brazil and the time period of 1 September–31 October 2012. Aerosol optical thickness (AOT550 nm) derived from measurements made by the Moderate Resolution Imaging Spectroradiometer (MODIS) operating on board the Terra and Aqua satellites is also applied to assess the inventories' consistency. The daily area-averaged pyrogenic carbon monoxide (CO) emission estimates exhibit significant linear correlations (r, p  >  0.05 level, Student t test) between 3BEM and FINN and between 3BEM_ FRP and GFAS, with values of 0.86 and 0.85, respectively. These results indicate that emission estimates in this region derived via similar methods tend to agree with one other. However, they differ more from the estimates derived via the alternative approach. The evaluation of MODIS AOT550 nm indicates that model simulation driven by 3BEM and FINN typically underestimate the smoke particle loading in the eastern region of Amazon forest, while 3BEM_FRP estimations to the area tend to overestimate fire emissions. The daily regional CO emission fluxes from 3BEM and FINN have linear correlation coefficients of 0.75–0.92, with typically 20–30 % higher emission fluxes in FINN. The daily regional CO emission fluxes from 3BEM_FRP and GFAS show linear correlation coefficients between 0.82 and 0.90, with a particularly strong correlation near the arc of deforestation in the Amazon rainforest. In this region, GFAS has a tendency to present higher CO emissions than 3BEM_FRP, while 3BEM_FRP yields more emissions in the area of soybean expansion east of the Amazon forest. Atmospheric aerosol optical thickness is simulated by using the emission inventories with two operational atmospheric chemistry transport models: the IFS from Monitoring Atmospheric Composition and Climate (MACC) and the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modelling System (CCATT-BRAMS). Evaluation against MODIS observations shows a good representation of the general patterns of the AOT550 nm time series. However, the aerosol emissions from fires with particularly high biomass consumption still lead to an underestimation of the atmospheric aerosol load in both models.

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