Quantifying uncertainties in U.S. wildland fire emissions across space and time scales

Smoke from wildland fire is a growing concern as air quality regulations tighten and public acceptance declines. Wildland fire emissions inventories are not only important for understanding smoke impacts on air quality but also in quantifying sources of greenhouse gas emissions. Wildland fire emissions can be calculated using a number of models and methods. We show an overview of results from the Smoke and Emissions Model Intercomparison Project (SEMIP) describing uncertainties in calculations of U.S. wildland fire emissions across space and time scales from single fires to annual national totals. Differences in emissions calculated from different models and systems and satallite algorithms and ground based systems are shown. The relative importance of uncertainties in fire size and available fuel data, consumption modeling techniques, and emissions factors are compared and quantified and can be applied to various use cases that include air quality impact modeling and greenhouse gas accounting. The results of this work show where additional information and updated models can most improve wildland fire emission inventories.