Estimating emissions from forest fires in Thailand using MODIS active fire product and country specific data
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Author list: Junpen A., Garivait S., Bonnet S.
Publisher: Springer
Publication year: 2013
Journal: Asia-Pacific Journal of Atmospheric Sciences (1976-7633)
Volume number: 49
Issue number: 3
Start page: 389
End page: 400
Number of pages: 12
ISSN: 1976-7633
eISSN: 1976-7951
Languages: English-Great Britain (EN-GB)
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Abstract
Studies on air pollution and climate change have shown that forest fires constitute one of the major sources of atmospheric trace gases and particulate matter, especially during the dry season. However, these emissions remain difficult to quantify due to uncertainty on the extent of burned areas and deficient knowledge on the forest fire behaviours in each country. This study aims to estimate emissions from forest fires in Thailand by using the combination of the Moderate Resolution Imaging Spectroradiometer (MODIS) for active fire products and country-specific data based on prescribed burning experiments. The results indicate that 27817 fire hotspots (FHS) associated with forest fires were detected by the MODIS during 2005-2009. These FHS mainly occurred in the northern, western, and upper north-eastern parts of Thailand. Each year, the most significant fires were observed during January-May, with a peak in March. The majority of forest FHS were detected in the afternoon. According to the prescribed burning experiments, the average area of forest burned per fire event was found to fall within the range 1.09 to 12.47 ha, depending upon the terrain slope and weather conditions. The total burned area was computed at 159309 ha corresponding to the surface biomass fuel of 541515 tons dry matter. The forest fire emissions were computed at 855593 tons of CO2, 56318 tons of CO, 3682 tons of CH4, 108 tons of N2O, 4928 tons of PM2.5, 4603 tons of PM10, 357 tons of BC and 2816 tons of OC. ฉ 2013 Korean Meteorological Society and Springer Science+Business Media Dordrecht.
Keywords
air pollution, fire characteristics, fire hotspots, Remote Sensing
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