@Article{FerradaZhWaLyWaFrCa:2022:InVIFi,
               author = "Ferrada, Gonzalo A. and Zhou, Meng and Wang, Jun and Lyapustin, 
                         Alexei and Wang, Yujie and Freitas, Saulo Ribeiro de and 
                         Carmichael, Gregory R.",
          affiliation = "{The University of Iowa} and {The University of Iowa} and {The 
                         University of Iowa} and {NASA Goddard Space Flight Center} and 
                         {University of Maryland Baltimore County} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)} and {The University of Iowa}",
                title = "Introducing the VIIRS-based Fire Emission Inventory version 0 
                         (VFEIv0)",
              journal = "Geoscientific Model Development",
                 year = "2022",
               volume = "15",
               number = "21",
                pages = "8085--8109",
                month = "Nov.",
             abstract = "A new open biomass burning inventory is presented that relies on 
                         the fire radiative power data from the Visible Infrared Imaging 
                         Radiometer Suite (VIIRS) on board the Suomi NPP satellite. This 
                         VIIRS-based Fire Emission Inventory (VFEI) provides emission data 
                         from early 2012 to 2019 for more than 40 species of gases and 
                         aerosols at spatial resolutions of around 500 m. We found that 
                         VFEI produces similar results when compared to other major 
                         inventories in many regions of the world. Additionally, we 
                         conducted regional simulations using VFEI with the Weather 
                         Research and Forecasting (WRF) model with chemistry (WRF-Chem) for 
                         Southern Africa (September 2016) and North America (July-August 
                         2019). We compared aerosol optical depth (AOD) from the model 
                         against two observational datasets: the MODIS Multi-Angle 
                         Implementation of Atmospheric Correction (MAIAC) product and 
                         AErosol RObotic NETwork (AERONET) stations. Results showed good 
                         agreement between both simulations and the datasets, with mean AOD 
                         biases of around +0.03 for Southern Africa and -0.01 for North 
                         America. Both simulations were not only able to reproduce the AOD 
                         magnitudes accurately, but also the inter-diurnal variations of 
                         smoke concentration. In addition, we made use of the airborne data 
                         from the ObseRvations of Aerosols above CLouds and their 
                         intEractionS (ORACLES; Southern Africa) and the Fire Influence on 
                         Regional to Global Environments Experiment and Air Quality 
                         (FIREX-AQ; North America) campaigns to evaluate the simulations. 
                         In Southern Africa, results showed correlations higher than 0.77 
                         when comparing carbon monoxide and black carbon. In North America, 
                         correlations were lower and biases higher. However, this is 
                         because the model was not able to reproduce the timing, shape, and 
                         location of individual plumes over complex terrain (Rocky 
                         Mountains) during the FIREX-AQ campaign period.",
                  doi = "10.5194/gmd-15-8085-2022",
                  url = "http://dx.doi.org/10.5194/gmd-15-8085-2022",
                 issn = "1991-959X",
             language = "en",
           targetfile = "gmd-15-8085-2022.pdf",
        urlaccessdate = "06 jun. 2024"
}