Spatiotemporal Variation of Burnt Area Detected from High-Resolution Sentinel-2 Observation during the Post-Monsoon Fire Seasons of 2022—2024 in Punjab, India

Underestimation of PM2.5 emissions from the agricultural sector persists as a major difficulty for air quality studies, partly because of underutilization of high-resolution observation platform for constructing a global emissions inventory. Coarse-resolution products used for such purpose often miss fine-scale burnt areas created by stubble burning practices, which are primary sources of agricultural PM2.5 emissions. For this study, we used the high-resolution Sentinel-2 observations to examine the spatiotemporal variability of burnt areas in Punjab, a major hotspot of agricultural burning in India, during the post-monsoon fire season (October–December) in 2022–2024. The results highlight the Sentinel-2 capability of detecting more than 34,000 km2 of burnt areas (approx. 68% of Punjab’s total area) as opposed to the less than 7,000 km2 (approx. 12% of Punjab’s total area) detected by MODIS. The study also reveals, in unprecedented detail, multi-annual spatial and temporal shifting of burning events from northern to central and southern Punjab. This detection discrepancy has led to marked disparities in estimated monthly emissions, with approximately 427.5 million tons of PM2.5 emitted in October 2022 compared to 8.7 million tons found by EDGAR v.8.1, underscoring higher resolution observation systems intended to support construction of a global PM2.5 emissions inventory.