Verification of reproducibility of biomass burning aerosol distribution by regional modeling

Makiko Nakata; Souichiro Hioki; Sonoyo Mukai

doi:10.1117/12.2679086

19 October 2023 Verification of reproducibility of biomass burning aerosol distribution by regional modeling

Makiko Nakata, Souichiro Hioki, Sonoyo Mukai

Proceedings Volume 12730, Remote Sensing of Clouds and the Atmosphere XXVIII; 127300O (2023) https://doi.org/10.1117/12.2679086
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Conference Poster

Abstract

Open burning of biomass occurs in many parts of the world and is a major environmental problem. This is because biomass combustion is a major source of greenhouse gases, reactive trace gases, and particulate matter emissions into the atmosphere. Emissions from combustion of biomass have the potential to impact local, regional, and global air quality issues and climate change. Satellite information on fire activity and vegetation productivity has been combined to create a data set of gas and aerosol emissions from fires. We used these emission data to obtain aerosol distributions of open burning origin by using a regional chemical transport model simulation. This study targets severe biomass burning aerosols in Sumatra Island in September 2019. We simulated the meteorological fields required for offline calculations of chemical transport models with the SCALE (Scalable Computing for Advanced Library and Environment) regional model. Simulation results were validated with biomass burning aerosol distributions derived from JAXA/GCOM-C/Second Generation Global Imager (SGLI) and aerosol optical thickness from the NASA/AErosol RObotic NETwork (AERONET). The biomass burning aerosol distribution was found to be well reproduced, but there was an underestimation in aerosol volume.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Makiko Nakata, Souichiro Hioki, and Sonoyo Mukai "Verification of reproducibility of biomass burning aerosol distribution by regional modeling", Proc. SPIE 12730, Remote Sensing of Clouds and the Atmosphere XXVIII, 127300O (19 October 2023); https://doi.org/10.1117/12.2679086

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