Wildland Fire Sensor Challenge Solver sensor system measurements and EPA reference method measurements (PM2.5, carbon monoxide, carbon dioxide, ozone) from Phase I EPA research chamber (Chapel Hill, NC) and Phase II U.S. Forest Service (Missoula, MT) combustion chamber testing. This dataset is associated with the following publication: Landis, M., R. Long, J.D. Krug, M. Colon, R. Vanderpool, A. Habel, and S. Urbanski. The U.S. EPA Wildland Fire Sensor Challenge: Performance and Evaluation of Solver Submitted Multi-Pollutant Sensor Systems. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 247: NA, (2021).

High time resolution (10 s) chamber study burn emission measurements and commercial laboratory fuel analysis reports. This dataset is associated with the following publication: Urbanski, S., R. Long, H. Halliday, A. Habel, E. Lincoln, and M. Landis. Fuel layer specific pollutant emission factors for fire prone forest ecosystems of the western U.S. and Canada. Atmospheric Environment: X. Elsevier B.V., Amsterdam, NETHERLANDS, 0000, (2022).

Reference and sensor data from grassland prescribed burn experiments in 2017 and chamber burn experiments in 2018 used in the paper "Summary of Evaluation of Commercially Available Air Sensor Performance in Biomass Burning Plumes" by Whitehill et al. This dataset is associated with the following publication: Whitehill, A., R. Long, S. Urbanski, M. Colon, A. Habel, and M. Landis. Evaluation of carpool and aeroqual air sensors in biomass burning plumes. ATMOSPHERE. MDPI, Basel, SWITZERLAND, 13(6): 877, (2022).

Emissions from a stand replacement prescribed burn were sampled using an unmanned aircraft system (UAS, or “drone”) in Fishlake National Forest, Utah, U.S.A. Sixteen flights over three days in June 2019 provided emission factors for a broad range of compounds including carbon monoxide (CO), carbon dioxide (CO2), nitric oxide (NO), nitrogen oxide (NO2), particulate matter < 2.5 microns in diameter (PM2.5), volatile organic compounds (VOCs) including carbonyls, black carbon, and elemental/organic carbon. To our knowledge, this is the first UAS-based emission sampling for a fire of this magnitude, including both slash pile and crown fires resulting in wildfire-like conditions. The burns consisted of drip torch ignitions as well as ground-mobile and aerial helicopter ignitions of large stands comprising over 1,000 ha, allowing for comparison of same-species emission factors burned under different conditions. The use of a UAS for emission sampling minimizes risk to personnel and equipment, allowing flexibility in sampling location and ensuring capture of representative, fresh smoke constituents. PM2.5 emission factors varied 5-fold and, like most pollutants, varied inversely with combustion efficiency resulting in lower emission factors from the slash piles than the crown fires. This dataset is associated with the following publication: Aurell, J., B. Gullett, A. Holder, F. Kiros, B. Mitchell, A. Watts, and R. Ottmar. Wildland Fire Emission Sampling at Fishlake National Forest, Utah Using an Unmanned Aircraft System. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 247: 118193, (2021).

Emissions from a stand replacement prescribed burn were sampled using an unmanned aircraft system (UAS, or “drone”) in Fishlake National Forest, Utah, U.S.A. Sixteen flights over three days in June 2019 provided emission factors for a broad range of compounds including carbon monoxide (CO), carbon dioxide (CO2), nitric oxide (NO), nitrogen oxide (NO2), particulate matter < 2.5 microns in diameter (PM2.5), volatile organic compounds (VOCs) including carbonyls, black carbon, and elemental/organic carbon. To our knowledge, this is the first UAS-based emission sampling for a fire of this magnitude, including both slash pile and crown fires resulting in wildfire-like conditions. The burns consisted of drip torch ignitions as well as ground-mobile and aerial helicopter ignitions of large stands comprising over 1,000 ha, allowing for comparison of same-species emission factors burned under different conditions. The use of a UAS for emission sampling minimizes risk to personnel and equipment, allowing flexibility in sampling location and ensuring capture of representative, fresh smoke constituents. PM2.5 emission factors varied 5-fold and, like most pollutants, varied inversely with combustion efficiency resulting in lower emission factors from the slash piles than the crown fires. This dataset is associated with the following publication: Aurell, J., B. Gullett, A. Holder, F. Kiros, B. Mitchell, A. Watts, and R. Ottmar. Wildland Fire Emission Sampling at Fishlake National Forest, Utah Using an Unmanned Aircraft System. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 247: 118193, (2021).

Reference and sensor data from grassland prescribed burn experiments in 2017 and chamber burn experiments in 2018 used in the paper "Summary of Evaluation of Commercially Available Air Sensor Performance in Biomass Burning Plumes" by Whitehill et al.

Reference and sensor data from grassland prescribed burn experiments in 2017 and chamber burn experiments in 2018 used in the paper "Summary of Evaluation of Commercially Available Air Sensor Performance in Biomass Burning Plumes" by Whitehill et al.

This data set contains annual modeled estimates of wildland fire emissions at 0.01 degree (~1-km) spatial resolution from the Wildland Fire Emissions Information System (WFEIS v0.5) for the conterminous U.S. (CONUS) and Alaska for 2001 through 2013. WFEIS is a web-based tool that provides resources to quantify emissions from past fires and output results as spatial data files (French et al., 2014). The data set includes emissions estimates of carbon (C), carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), other non-methane hydrocarbons (NMHC), and particulate matter (PM) as well as estimates of above-ground biomass, total fuel availability, and consumption estimates.

This dataset contains the underlying data for the evaluation of a 5 year CMAQ simulation with and without fires. The pollutant evaluated in the journal article is PM2.5. Daily Average concentrations of PM2.5 from two 5 year CMAQ simulations are included. Area burned on a daily basis is also included. Finally model and observed paired CSV files of PM2.5 are included for the 5 year simulation from the IMPROVE and CSN networks. Datasets are in several formats including netCDF (tar and zipped), csv (tar and zipped), and Excel. This dataset is associated with the following publication: Wilkins, J., G. Pouliot, K. Foley, W. Appel, and T. Pierce. The impact of US wildland fires on ozone and particulate matter: a comparison of measurements and CMAQ model predictions from 2008 to 2012. International Journal of Wildland Fire. CSIRO Publishing, Collingwood Victoria, AUSTRALIA, 27(10): 684-698, (2018).

This data set contains annual modeled estimates of wildland fire emissions at 0.01 degree (~1-km) spatial resolution from the Wildland Fire Emissions Information System (WFEIS v0.5) for the conterminous U.S. (CONUS) and Alaska for 2001 through 2013. WFEIS is a web-based tool that provides resources to quantify emissions from past fires and output results as spatial data files (French et al., 2014). The data set includes emissions estimates of carbon (C), carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), other non-methane hydrocarbons (NMHC), and particulate matter (PM) as well as estimates of above-ground biomass, total fuel availability, and consumption estimates.