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Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)
Journal article   Open access   Peer reviewed

Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)

Gonzalo Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo Freitas and Gregory Carmichael
Geoscientific Model Development, Vol.15(21), pp.8085-8109
01/01/2022
DOI: 10.5194/gmd-15-8085-2022
url
https://doi.org/10.5194/gmd-15-8085-2022View
Published (Version of record) Open Access

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.
Air Quality Atmospheric Chemistry Atmospheric Models Clouds Ecosystems Radiometry Aerosol optical depth Aerosol Robotic Network Aerosols Atmospheric correction Biomass Biomass burning Black carbon Carbon monoxide Correlation Datasets Diurnal variations Emission inventories Emissions Fires Gases Hydrocarbons Imaging radiometers Infrared imaging Infrared radiometers MODIS Mountains Optical analysis Optical thickness Plumes Radiation Radiometers Regions Satellites Simulation Weather forecasting

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