FINN - Fire INventory from NCAR

Fire INventory from NCAR (FINN): A daily fire emissions product for atmospheric chemistry models

Open biomass burning makes up an important part of the total global emissions of greenhouse gases, reactive trace gases, and particulate matter. Although episodic in nature and highly variable, open biomass burning emissions can contribute to local, regional, and global air quality problems and climate forcings. The Fire INventory from NCAR (FINN) model provides high resolution, global emission estimates from open burning; these emissions have been developed specifically to provide input needed for modeling atmospheric chemistry and air quality in a consistent framework at scales from local to global. The inventory framework produces daily emission estimates at a horizontal resolution of ~1 km2.  The product differs from other inventories because it provides a unique combination of high temporal and spatial resolution, global coverage, and estimates for a large number of chemical species.

FINN emission estimates are based on the framework described by Wiedinmyer et al. [2006; 2011]. FINN uses satellite observations of active fires and land cover, together with emission factors and estimated fuel loadings to provide daily, highly-resolved (1 km) open burning emissions estimates for use in regional and global chemical transport models.Smoke from western wildfires  Daily fire emissions for 01 January 2002 through 31 July 2013 have been estimated using the first version of the FINN model framework and are available for download and use at A processor to include FINNv1 emission estimates and apply a plume rise to the emissions within the WRF-chem online chemical and transport model is also available for download at FINN fire emissions are calculated in real time and are processed as inputs to the WACCM real time forecasts (available via

In recent years, FINN emissions have been used in many various modeling studies that simulate the chemical and climate impacts from fires. By using FINN emissions within the WRF-Chem model, Jiang et al. (2012) explored the impacts of fire plumes on ozone chemistry during a wildfire event in Idaho and Montana during August 2007. WRF-chem simulated the immediate addition fire emissions combined with the changes in photolysis rates, boundary layer height, and biogenic emissions. The results highlighted the importance of including the radiative impacts of fire plumes. val Martin et al. (2013) used FINN emissions in conjunction with satellite observations to explore the importance of fire smoke or air quality and regional climate in Colorado. This work is being continued in an effort led by Gabi Pfister to investigate the health impacts of the fire smoke and degraded air quality from the 2012 fires in Colorado.

More recent efforts associated with the FINN model include the development of version 2.0 of the model and a global emissions inventory from open burning of waste and trash.


Jiang, X., C. Wiedinmyer, A.G. Carlton.  Aerosols from fires: an examination of the effects on ozone photochemistry in the Western United States. Environmental Science & Technology, 46(21), 442-460, doi:10.1021/es301541k .

Val Martin, M., Heald, C. L., Ford, B., Prenni, A. J., and Wiedinmyer, C.: A decadal satellite analysis of the origins and impacts of smoke in Colorado, Atmos. Chem. Phys., 13, 7429-7439, doi:10.5194/acp-13-7429-2013, 2013.

Wiedinmyer, C., S. K. Akagi, R. J. Yokelson, L. K. Emmons, J. A. Al-Saadi, J. J. Orlando, and A. J. Soja. "The Fire Inventory from Ncar (Finn): A High Resolution Global Model to Estimate the Emissions from Open Burning." Geoscientific Model Development 4, no. 3 (2011): 625-41. (
Wiedinmyer, Christine, Brad Quayle, Chris Geron, Angle Belote, Don McKenzie, Xiaoyang Zhang, Susan O'Neill, and Kristina Klos Wynne. "Estimating Emissions from Fires in North America for Air Quality Modeling." Atmospheric Environment 40, no. 19 (2006): 3419-32.

Click to download FINN data and utilities and view FINN daily plots.




ACOM | Atmospheric Chemistry Observations & Modeling