Enhanced Estimation of Biomass Burning Emissions for Indonesian Peatland and Non-peatland Fires

Indonesia has experienced frequent fires due to extensive canal drainage for agricultural development since 1970s. Biomass burning emissions (BBE) released from these fires have led to Indonesia being the worlds 3rd largest emitter of greenhouse gases in 2000. Due to severe BBE effects on climate, weather, and human activities, both bottom-up and top-down approaches have been developed to estimate BBE. The bottom-up method estimates BBE based on burned area and fuel loading, in which fuel loading always has considerable uncertainties. By contrast, the top-down approach for estimating BBE, based on smoke trace gases and aerosols, bypasses the need for fuel load estimates. This approach directly links satellite fire radiative power (FRP) to the emission rate of total particulate matter (TPM) of smoke aerosols via a smoke emission coefficient (Ce). However, accurate calculation of Ce and temporal-integrated FRP (i.e., fire radiative energy, FRE) remains challenging due to frequent cloud interferences and low-temperature smoldering fires. As a result, existing estimates of biomass burning emissions differ largely with a factor of 2-8 in Indonesia. This study is, therefore, to develop innovative algorithms to enhance the top-down approach in the quantifications and evaluations of BBE estimation based on multiple new generation satellite data across Indonesia. First, regional Ce values are estimated from FRP and the emission rate of smoke aerosols based on VIIRS active fire and aerosol products. Second, FRE is calculated from the diurnal FRP that is reconstructed by fusing cloud-corrected FRP retrievals from high spatial resolution VIIRS and high temporal resolution Himawari-8 AHI. Third, BBE estimation during a specific period is calculated directly from the AHI-VIIRS based FRE and Ce values. Finally, the BBE estimation is evaluated by comparing it with both MODIS aerosol optical depth and TROPOMI carbon monoxide products. This study provides important insights to understand the accuracy of FRE-based emissions estimations and further helps to improve fire emissions quantification.