Browsing by Author "Kumari Aditi"

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Contrasting nature of aerosols over South Asian cities and its surrounding environment
(Elsevier Ltd, 2024) Akanksha Pandey; Kumari Aditi; Harshita Baranwal; Asfa Siddiqui; Tirthankar Banerjee
Cross-country assessment of aerosol loading was made over several South Asian megacities using multiple high-resolution remote-sensing database to assess how aerosols vary within the city and its suburbs. Parameters sensitive to aerosol optical and microphysical properties were processed over city-core and its surrounding, separated by a buffer. Cities across the Indo-Gangetic Plain (IGP; AOD:0.52–0.72) along with Mumbai (0.47) and Bangalore (0.46) denote comparatively high aerosol loading against non-IGP cities. City-core specific AOD was invariably high compared to surrounding, however with varying gradient having robust geographical signature. Exceptions to this general trend were in Kathmandu (ΔAOD: 0.07) and Dhaka (ΔAOD: 0.01) while strong positive AOD gradient was noted in Bangalore (+0.11), Colombo (+0.08) and in Mumbai (+0.07). While all mainland cities exhibited robust intraannual variability, distinction between city-core and its surrounding AOD exhibited varying seasonality. City-specific geometric coefficient of variation indicated insignificant association with mean AOD as opposed to European and American cities. Both pixel-based and city-specific analysis revealed a strong increasing trend in AOD with highest magnitude in Varanasi and Bangalore. Aerosol sub-types based on aerosols’ sensitivity to UV-absorption and particle size denotes higher relative abundance of carbonaceous smoke aerosols within city-core, without having significant distinction for mineral dusts and urban aerosols. © 2024 Elsevier Ltd
Forest fire emission estimates over South Asia using Suomi-NPP VIIRS-based thermal anomalies and emission inventory
(Elsevier Ltd, 2025) Kumari Aditi; Akanksha Pandey; Tirthankar Banerjee
Emission estimates of carbon-containing greenhouse gases (CO2, CH4) and aerosols (PM2.5) were made from forest fire across South Asia using Visible Infrared Imaging Radiometer Suite (VIIRS) based thermal anomalies and fire products. VIIRS 375 m I-band active fire product was selectively retrieved for the years 2012–2021 over forest cover across South Asia. Annual incidence of fire events across South Asia was 0.17 (±0.05) million (M) with robust spatio-temporal variation. Fire occurrences were mainly concentrated over the forest across Hindu Kush Himalayan region (HKH; 56%), Deccan Plateau (DP) and Central Highlands (CH; 34%). Monthly mean fire incidences emphasize February to May as a typical forest fire season, accounting 90% of annual fire counts. The highest fire pixel density (>1.5 km −2 yr−1) was noted over the tropical dry/moist deciduous and tropical semi-evergreen forests. Strong diurnal nature of fire radiative power (FRP) was evident with >85% of FRP linked to daytime retrieval. VIIRS based Fire Emission Inventory (VFEI, Version 0) was followed to constitute regional emissions of PM2.5 and green house gases from forest fire. Forest fire accounted a yearly emission of 91.58 (±14.76) and 0.25 (±0.04) Tg yr−1 CO2 and CH4 respectively, with 25.14 (±3.94) Tg of cumulative carbon release per year, i.e., roughly 1.3% of global fire-related carbon emission. Fire associated PM2.5 emission rate was 0.60 (±0.10) Tg yr−1, 95% of which emitted during peak fire season as was the case for carbon-containing gases. Forest fire across HKH (75%) and DP + CH (20%) predominately contribute to the regional carbon emission, while also accounting 68% (HKH) and 27% (DP + CH) of fire associated PM2.5 emission budget. With >70% of forest fires within South Asia being typically anthropogenic, forest fire appears to be a major sector of greenhouse gas and aerosols emissions, and necessitate planning and strict legalities to reduce emission load. © 2024 Elsevier Ltd
Retrieval uncertainty and consistency of Suomi-NPP VIIRS Deep Blue and Dark Target aerosol products under diverse aerosol loading scenarios over South Asia
(Elsevier Ltd, 2023) Kumari Aditi; Abhishek Singh; Tirthankar Banerjee
Retrieval accuracy and stability of two operational aerosol retrieval algorithms, Deep Blue (DB) and Dark Target (DT), applied on Visible Infrared Imaging Radiometer Suite (VIIRS) on-board Suomi National Polar-orbiting Partnership (S-NPP) satellite were evaluated over South Asia. The region is reported to be highly challenging to accurate estimation of satellite-based aerosol optical properties due to variations in surface reflectance, complex aerosol system and regional meteorology. Performance of both algorithms were initially evaluated by comparing their ability to retrieve aerosol signal over the complex geographical region under specific air pollution emission scenario. Thereafter, retrieval accuracy was investigated against 10 AERONET sites across South Asia, selected based on their geography and predominance aerosol types, from year 2012–2021. Geo-spatial analysis indicates DB to efficiently retrieve fine aerosol features over bright arid surfaces, and for smoke/dust dominating events whereas DT was better to identify small fire events under dark vegetated surface. Both algorithms however, indicate unsatisfactory retrieval accuracy against AERONET having 56–59% of valid retrievals with high RMSE (0.30–0.33) and bias. Overall, DB slightly underpredicted AOD with −0.02 mean bias (MB) whereas DT overpredicted AOD (MB: 0.13), with seasonality in their retrieval efficiency against AERONET. Time-series analysis indicates stability in retrieving AOD and match-up number for both algorithms. Retrieval bias of DB and DT AOD against AERONET AOD under diverse aerosol loading, aerosol size, scattering/absorbing aerosol, and surface vegetation coverage scenarios revealed DT to be more influenced by these conditions. Error analysis indicates at low AOD (≤0.2), accuracy of both DB and DT were subject to underlying vegetation coverage. At AOD>0.2, DB performed well in retrieving coarse aerosols whereas DT was superior when fine aerosols dominated. Overall, accuracy of both VIIRS algorithms require further refinement to continue MODIS AOD legacy over South Asia. © 2023 Elsevier Ltd
Three-dimensional nature of summertime aerosols over South Asia
(Elsevier B.V., 2022) Abhishek Singh; Avinash Anchule; Tirthankar Banerjee; Kumari Aditi; Alaa Mhawish
Three-dimensional (temporal-spatial-vertical) climatology of South Asian summertime (MAMJ, 2010–2019) aerosols and aerosol sub-types was explored using multiple high-resolution satellite-based observations and reanalysis dataset. Vertical stratification of aerosol layer and aerosol sub-types was identified using observation from space-borne lidar. Aerosol optical depth (AOD) was particularly high across the Indo-Gangetic Plain (IGP; AOD ± SD: 0.56 ± 0.12) and over eastern coast of India (AOD: 0.6–0.8), with prevalence of heterogeneous aerosol sub-types having strong spatial gradient. Clearly, aerosols over north-western arid part were highly absorbing (Ultra-violet Aerosol Index, UVAI > 0.80) and coarse (Ångström exponent, AE < 0.8), with an indication of desert/−mineral dust aerosols. In contrast, fine and moderate to non-absorbing aerosols (UVAI: 0.20–0.50) dominate from central to lower IGP, including in Bangladesh, with signature of anthropogenic emissions. Prevailing aerosols over twelve South Asian cities were classified into six aerosol sub-types constraining their particle size and UV-absorbing potential. Overall, mineral dust, smoke and urban aerosols were the three major aerosol sub-types that prevail across South Asia during summer. In particular, 58–70 % of retrieval days over Karachi and Multan were dust dominated; 57–64 % days were dust or urban aerosols dominated over Lahore, Delhi, Kanpur and Varanasi, and 56–77 % days were smoke or urban aerosols dominated over Dhaka, Kathmandu, Chennai, Mumbai, Colombo and Nagpur. Prevailing aerosols were vertically stratified as 50–70 % of total AOD was retrieved <2 km from the surface except in few cities where 70–80 % of AOD was retrieved <3 km height. Mineral dust and/or urban aerosols emerged as the most abundant aerosol types near the surface (<1 km) in all the cities except in Chennai, with their abundance remained as a function of emission sources and geographical location. © 2022 Elsevier B.V.