Highlights Normalized Burn Ratio Thermal (NBRT) is used to estimate the high vegetation burning ratios over Uttarakhand. Maximum fires are observed during April to June months over the forest area due to high temperature. The results demonstrate the potential of Earth satellite data in emissions characterization and in AQ management.

    Abstract Confirmed rise in average surface temperature and consequent prolonged dry days in tropical Himalayan foothills (tarai region) favors frequent wildfire event which make susceptible to the local forest vegetation and ecology. Recent improvement in spatio-temporal resolution of space-borne sensors provides an opportunity to routinely map these wildfires and estimate the consequence. Utilizing both active and passive space-borne multi-sensors, this study presents the active fire counts, columnar and vertical distribution of aerosol during 2013–2018 over Uttarakhand region of India. Our analysis shows maxima in active fire counts during April to late June months while minima in monsoon over the region. Particularly owing to the high temperature, low moisture, drying up of natural spring and availability of fuel materials in summer and scare precipitation in winter. Some limited spatio-temporal scale fire episodes are also marked in winter. The AOD values with maximum of 3.2 (0.5 mean) observed during the April 2016, while for the successive next two months, AOD of 2.0 and 1.2 are found over the fire burning regions. The Normalized Burn Ratio Thermal (NBRT) index are also found to be much higher for April and May 2016 with respect to 2015 and 2017. The comparative analysis of NBRT shows a positive difference towards the western side of Uttarakhand. Vertical feature mask and aerosol subtype profile details about the polluted dust and elevated smoke aerosols from surface to 10 km range during the intense fire events smoke were elevated and trapped within 3 to 10 km. The results demonstrate the potential of earth’s observing satellites for characterization of emissions and in air quality management.


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