Estimation of Biomass Burning Emissions in South and Southeast Asia Based on FY-4A Satellite Observations
In recent years, frequent open biomass burning (OBB) activities such as agricultural residue burning and forest fires have led to severe air pollution and carbon emissions across South and Southeast Asia (SSEA). We selected this area as our study area and divided it into two sub-regions based on cli...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/16/5/582 |
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| Summary: | In recent years, frequent open biomass burning (OBB) activities such as agricultural residue burning and forest fires have led to severe air pollution and carbon emissions across South and Southeast Asia (SSEA). We selected this area as our study area and divided it into two sub-regions based on climate characteristics and geographical location: the South Asian Subcontinent (SEAS), which includes India, Laos, Thailand, Cambodia, etc., and Equatorial Asia (EQAS), which includes Indonesia, Malaysia, etc. However, existing methods—primarily emission inventories relying on burned area, fuel load, and emission factors—often lack accuracy and temporal resolution for capturing fire dynamics. Therefore, in this study, we employed high-resolution fire point data from China’s Feng Yun-4A (FY-4A) geostationary satellite and the Fire Radiative Power (FRP) method to construct a daily OBB emission inventory at a 5 km resolution in this region for 2020–2022. The results show that the average annual emissions of carbon (C), carbon dioxide (CO<sub>2</sub>), carbon monoxide (CO), methane (CH<sub>4</sub>), non-methane organic gases (NMOGs), hydrogen (H<sub>2</sub>), nitrogen oxide (NO<sub>X</sub>), sulfur dioxide (SO<sub>2</sub>), fine particulate matter (PM<sub>2.5</sub>), total particulate matter (TPM), total particulate carbon (TPC), organic carbon (OC), black carbon (BC), ammonia (NH<sub>3</sub>), nitric oxide (NO), nitrogen dioxide (NO<sub>2</sub>), non-methane hydrocarbons (NMHCs), and particulate matter ≤ 10 μm (PM<sub>10</sub>) are 178.39, 598.10, 33.11, 1.44, 4.77, 0.81, 1.02, 0.28, 3.47, 5.58, 2.29, 2.34, 0.24, 0.58, 0.43, 0.99, 1.87, and 3.84 Tg/a, respectively. Taking C emission as an example, 90% of SSEA’s emissions come from SEAS, especially concentrated in Laos and western Thailand. Due to the La Niña climate anomaly in 2021, emissions surged, while EQAS showed continuous annual growth at 16.7%. Forest and woodland fires were the dominant sources, accounting for over 85% of total emissions. Compared with datasets such as the Global Fire Emissions Database (GFED) and the Global Fire Assimilation System (GFAS), FY-4A showed stronger sensitivity and regional adaptability, especially in SEAS. This work provides a robust dataset for carbon source identification, air quality modeling, and regional pollution control strategies. |
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| ISSN: | 2073-4433 |