Tianjia Liu , Loretta Mickley, Sukhwinder Singh, Meha Jain, Ruth DeFries, Miriam Marlier

In north India, agricultural burning adversely affects local and regional air quality during the post-monsoon season (October to November), when the prevailing meteorology is favorable for smog and haze formation. Quantifying the contribution of smoke to air pollution in this region, however, is challenging. While the Moderate Resolution Imaging Spectroradiometer (MODIS), aboard NASA’s Terra and Aqua satellites, provides a nearly 20-year record of global fire activity, the sensor cannot adequately capture small, short-lasting agricultural fires due to its moderate spatial resolution (500 m to 1 km) and limited overpasses (twice daily for each satellite), as well as the hazy conditions that typically obscure the north India land surface at this time of year. Moreover, current global fire emissions inventories based on MODIS observations can differ by up to an order of magnitude in this region. Here we incorporate household survey data to bridge gaps in MODIS observations and improve estimates of fire emissions over the states of Punjab, Haryana, Uttar Pradesh, and Bihar during the 2003-2018 post-monsoon burning seasons. We develop a novel method that adjusts MODIS Fire Radiative Power (FRP) for: (1) small fires detected by the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375-m spatial resolution, (2) cloud/haze gaps in satellite observations, (3) partial-field burning practices, and (4) the diurnal cycle of fire activity. Adjusting FRP for the fire diurnal cycle yields the largest boost to emissions due to the short lifetime of the fires (~1/2 hour) and the brief windows of satellite detection. Using adjusted FRP, we estimate on average 10.8 ± 2.7 Tg dry matter (DM) burned each year, yielding emissions of 68 ± 17 Gg organic carbon (OC), 5.8 ± 1.5 Gg black carbon (BC), 821 ± 206 Gg CO, and 15.4 ± 3.9 Tg CO2. On average, our OC+BC emissions are ~250% higher than estimates from five widely used global fire emissions inventories. Our estimate for Punjab, which contributes two-thirds of emissions in the region, is consistent with our bottom-up validation, which uses burn rates from the household survey and government crop production statistics in 2016 and 2017. We spatially disaggregate the state-level emissions to construct a gridded inventory at daily, 0.25° x 0.25° resolution over north India from 2003-2018. The inventory, SAGE-IGP (Survey Constraints on FRP-based Agricultural Fire Emissions in the Indo-Gangetic Plain), improves modeling assessments of air quality impacts from agricultural burning, thus supporting effective policy development.