Bar, Somnath; Ranjan Parida, Bikash; Chandra Pandey, Arvind; Kumar, Navneet: Pixel-Based Long-Term (2001–2020) Estimations of Forest Fire Emissions over the Himalaya. In: Remote Sensing. 2022, vol. 14, iss. 21, 1--20.
Online-Ausgabe in bonndoc: https://hdl.handle.net/20.500.11811/10791
@article{handle:20.500.11811/10791,
author = {{Somnath Bar} and {Bikash Ranjan Parida} and {Arvind Chandra Pandey} and {Navneet Kumar}},
title = {Pixel-Based Long-Term (2001–2020) Estimations of Forest Fire Emissions over the Himalaya},
publisher = {MDPI},
year = 2022,
month = oct,

journal = {Remote Sensing},
volume = 2022, vol. 14,
number = iss. 21,
pages = 1--20,
note = {Forest/wildfires have been one of the most notable severe catastrophes in recent decades across the globe, and their intensity is expected to rise with global warming. Forest fire contributes significantly to particulate and gaseous pollution in the atmosphere. This study has estimated the pixel-based emissions (CO, CO2, CH4, NOx, SO2, NH3, PM2.5, PM10, OC, and BC) from forest fires over the Himalaya (including India, Nepal, and Bhutan). The MODIS-based burned area (MCD64A1), Land Use Land Cover (LULC; MCD12A1), NDVI (MOD13A2), percentage tree cover (MOD44A6), gridded biomass, and species-wise emissions factors were used to estimate the monthly emissions from forest fires over the last two decades (2001–2020). A bottom-up approach was adopted to retrieve the emissions. A substantial inter-annual variation of forest burn area was found over the western, central (Nepal), and eastern Himalaya (including Bhutan). The eastern Himalaya exhibited the highest average annual CO2 emission, i.e., 20.37 Tg, followed by Nepal, 15.52 Tg, and the western Himalaya, 4.92 Tg. Spatially, the higher CO2 (0.01–0.02 Tg year−1/km2) and CO (0.007–0.002 Tg year−1/km2) emissions were detected along the south-eastern parts of the eastern Himalaya, southern regions of Nepal, and south-eastern parts of the western Himalaya. The trend of forest fire emissions in 2001–2010 was significantly positive, while in the next decade (2011–2020) a negative trend was recorded. The estimated pixel-based emission and Global Fire Emission Dataset (GFEDv4.1s) data demonstrated a promising association with a correlation coefficient (r) between 0.80 and 0.93. An inventory of forest fire emissions over long-term periods can be helpful for policymakers. In addition, it helps to set guidelines for air quality and atmospheric transport modelling and to better understand atmospheric pollution over the Himalayan and associated regions.},
url = {https://hdl.handle.net/20.500.11811/10791}
}

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