Singh, T; Biswal, A; Mor, S; Ravindra, K; Singh, V; Mor, S (2020). A high-resolution emission inventory of air pollutants from primary crop residue burning over Northern India based on VIIRS thermal anomalies. ENVIRONMENTAL POLLUTION, 266, 115132.

Emissions from the crop residue burning adversely affect the regional and global air quality including public health. In this study, a district-wise comprehensive emission inventory of key pollutants (PM2.5, PM10, CO, CO2, SO2, NOx, N2O, NH3, CH4, NMVOC, EC, OC, PAH) emitted during primary crop residue burning was developed using activity data for the major agrarian states of north India for the agricultural year 2017-18. The emissions were scaled to the spatial resolution of 1 km grid to study the spatial distribution of crop residue burning activities using VIIRS Thermal anomalies datasets. An estimated 20.3 Mt and 9.6 Mt of crop residue were burned in Punjab and Haryana, resulting in an emission of 137.2 Gg and 56.9 Gg of PM2.5 and 163.7 Gg and 72.1 of PM10 Gg for respective states. The emissions of EC, OC, and PAHs were 8.6 Gg, 45.7 Gg, and 0.08 Gg in Punjab, whereas in Haryana emissions were 3.7 Gg, 17.7 Gg, and 0.03 Gg, respectively. The results show that rice and wheat crops were major contributor to residue burnt at the field (>90%) leading to the high load of atmospheric emissions in the IGP region. Further, CO2 equivalent greenhouse gas emissions were 34.8 Tg and 17.3 Tg for Punjab and Haryana, respectively. Around 30000 and 8500 active fires were detected by VIIRS over the agricultural area of Punjab and Haryana during the studied year. The GIS-based bottom-up approach using gridded emission inventory shows pollutant distribution dominates over the south-western part of Punjab and northwestern region of Haryana. The proximity of these regions to Delhi and transboundary movement of emissions towards Indo-Gangetic plains causes high air pollution episodes. The high-resolution inventory of various pollutants will be useful for regional air quality models to better predict and manage the hotspot of air pollution. (C) 2020 Elsevier Ltd. All rights reserved.