Integrating the Global Forest Fire Emissions Prediction System version 1.0 to GEOS-Chem

Wildfire smoke is an increasingly important driver of regional air-quality degradation, with well-established impacts on public health and visibility. Although emission controls have reduced many anthropogenic air pollutants over recent decades, wildfire activity has intensified in many regions, increasing the contribution of fine particulate matter (PM_2.5; aerodynamic diameter < 2.5 μm) to surface pollution episodes. A key limitation in simulating wildfire smoke in chemical transport models is uncertainty in biomass-burning emissions, as inventories can have different mythologies and assumptions, such as fire occurrence, intensity, burn area, fuel characterization, and emission factors. These discrepancies can translate into substantial variability in modeled PM_2.5 and related co-emitted species, complicating both forecasting and attribution of smoke impacts. Here, we implement and evaluate the Global Forest Fire Emissions Prediction System (GFFEPS), a wildfire emissions framework developed by Environment and Climate Change Canada (ECCC), within the GEOS-Chem chemical transport model. We perform simulations for Canada, the United States, and Europe in 2019, and for Australia in 2019–2020, to quantify the sensitivity of simulated smoke to fire emissions and to assess model skill against observations. GFFEPS-driven simulations are compared with those using widely applied global biomass-burning inventories (the Global Fire Emissions Database (GFED), the Global Fire Assimilation System (GFAS), and the Quick Fire Emissions Dataset (QFED2)) and evaluated using ground-based PM_2.5 monitoring data across each region. Inventory choice strongly influences both the magnitude and timing of simulated PM_2.5 enhancements, with clear regional dependence and the largest inter-inventory spread during extreme fire events. Over North America, GFFEPS shows the best overall performance among the four inventories based on the mean error metric. Over Australia, GFFEPS generally underestimates PM_2.5 concentrations but remains a strong performer, ranking second behind GFAS using the same evaluation metric. Over Europe, GFFEPS ranks third, following GFAS and GFED, and is closely comparable to QFED2. These results highlight the need to better constrain fire detection and fuel consumption estimates, and demonstrate the value of GFFEPS within GEOS-Chem for diagnosing key drivers of inter-inventory differences and improving confidence in regional wildfire smoke simulations.