Monitoring and Analyzing Carbon Monoxide Emissions

Wildfires can result in tremendous economic loss across the United States. The largest fire year on record occurred in 2018 with approximately $3 billion in suppression costs. AIRS data are used widely to monitor and analyze major natural and/or human-caused fires. The AIRS project often provides near-real-time observations of carbon monoxide (CO) emitted from wildfires, such as occurred in the massive complex of fires that occurred in California in 2018. AIRS CO data are also used to improve the understanding of the dispersion of this trace gas and improve the Global Fire Emissions Database.


Environmental Chemistry, Nara, Hideki, Hiroshi Tanimoto, Yukihiro Nojiri, Hitoshi Mukai, Jiye Zeng, Yasunori Tohjima, and Toshinobu Machida, CO emissions from biomass burning in South-east Asia in the 2006 El Niño year: shipboard and AIRS satellite observations, Environmental Chemistry 8, no. 2 (2011): 213-223.

Thakur J, Thever P, Gharai B, Sesha Sai M, Pamaraju V. 2019. Enhancement of carbon monoxide concentration in atmosphere due to large scale forest fire of Uttarakhand, PeerJ 7:e6507,

Assessing Wildfire Danger

Wildfire danger assessment is essential for operational allocation of fire management resources, and in addition to emissions detection, AIRS data have been used to assess wildfire danger across the continental United States (CONUS). Traditional studies focus on meteorological forecasts and fire danger index models (e.g., National Fire Danger Rating System – NFDRS) for predicting fire danger. However meteorological forecasts lose accuracy beyond ~10 days, as such there is no quantifiable method for predicting fire danger beyond this period. AIRS Vapor Pressure Deficit (VPD) observations along with GRACE-assimilated Surface Soil Moisture (SSM) have been used to produce burned area forecasts in nine Geographic Area Coordination Centers (GAACs) across the CONUS. GACCs are geographic boundaries in the CONUS defined by the National Interagency Fire Council (NIFC).

AIRS VPD observations, along with MODIS Enhanced Vegetation Index (EVI) and GRACE-assimilated SSM, have been used to develop spatially gridded probabilistic predictions of fire danger, defined as the expected area burned as a deviation from “normal”. The results show the model predicts spatial patterns of fire danger with 52% overall accuracy over the 2004-2014 record, and up to 75% overall accuracy during the fire season.


Farahmand, A.; Stavros, E.N.; Reager, J.T.; Behrangi, A.; Randerson, J.; Quayle, B. Satellite Hydrology Observations as Operational Indicators of Forecasted Fire Danger across the Contiguous United States, Natural Hazards and Earth System Sciences Discussions 2019, 1–16, doi:10.5194/nhess-2019-129.