A global CO fire emissions assessment and its connection with drought events

Fire is a dominant terrestrial ecosystem disturbance and a major driver of atmospheric composition. Quantifying fire emissions and their variability remains a key challenge, particularly as fire frequency and intensity vary and increase under climate change. Inverse modeling provides a powerful framework to estimate fire emissions by constraining chemistry transport models (CTMs) with satellite observations, while simultaneously delivering three-dimensional information on the transport and distribution of fire-related pollutants.

In this study, we use the global CTM TM5 coupled with a four-dimensional variational data assimilation system (TM5-4DVar) to better constrain fire-related carbon monoxide (CO) emissions using satellite observations. We assimilate CO column super-observations from the Measurements of Pollution In The Troposphere (MOPITT) instrument aboard NASA’s Terra satellite (version 9) and, separately, higher spatiotemporal resolution CO observations from the TROPOspheric Monitoring Instrument (TROPOMI) aboard ESA’s Sentinel-5P. The assimilations are performed globally at 3° × 2° horizontal resolution over multiple years (2019–2024).

The posterior simulations provide insights into both regional fire emissions and the horizontal and vertical transport of CO, enabling assessment of downwind pollution impacts, evaluated against independent ground-based observations. Results show bias reductions with posterior simulated mixing ratios in comparison to prior simulations based on bottom-up emission inventories. We further investigate the influence of regional drought conditions on fire-related CO emissions and examine correlations with key environmental variables, including climate and vegetation indicators. Our results contribute to an improved understanding of interactions among fire emissions, climate, and atmospheric composition, and demonstrate the value of remote sensing data assimilation for reducing uncertainties and advancing fire emission monitoring.