@Article{PereiraSRFFCKW:2016:AsFiEm,
               author = "Pereira, Gabriel and Siqueira, Ricardo and Ros{\'a}rio, Nilton E. 
                         and Freitas, Karla Maria Longo de and Freitas, Saulo Ribeiro de 
                         and Cardozo, Francielle S. and Kaiser, Johannes W. and Wooster, 
                         Martin J.",
          affiliation = "{Universidade Federal de S{\~a}o Jo{\~a}o del Rei (UFSJ)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidade Federal de S{\~a}o Paulo (UNIFESP)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Universidade Federal de S{\~a}o 
                         Jo{\~a}o del Rei (UFSJ)} and {Max Planck Institute for Chemistry 
                         (MPIC)} and {King’s College London (KCL)}",
                title = "Assessment of fire emission inventories during the South American 
                         Biomass Burning Analysis (SAMBBA) experiment",
              journal = "Atmospheric Chemistry and Physics",
                 year = "2016",
               volume = "16",
               number = "11",
                pages = "6961--6975",
             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 September31 
                         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 0.750.92, with 
                         typically 2030 % 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.",
                  doi = "10.5194/acp-16-6961-2016",
                  url = "http://dx.doi.org/10.5194/acp-16-6961-2016",
                 issn = "1680-7324",
                label = "lattes: 9873289111461387 5 PereiraSRLFCKW:2016:AsFiEm",
             language = "en",
           targetfile = "pereira_asessment.pdf",
        urlaccessdate = "28 abr. 2024"
}