Wildland fire emission factors in North America: synthesis of existing data, measurement needs and management applications
Open accessAbstract
Field and laboratory emission factors (EFs) of wildland fire emissions for 276 known air pollutants sampled across Canada and the US were compiled. An online database, the Smoke Emissions Repository Application (SERA), was created to enable analysis and summaries of existing EFs to be used in smoke management and emissions inventories. We evaluated how EFs of select pollutants (CO, CO2, CH4, NOx, total particulate matter (PM), PM2.5 and SO2) are influenced by combustion phase, burn type and fuel type. Of the 12 533 records in the database, over a third (n = 5637) are represented by 23 air pollutants, most designated as US Environmental Protection Agency criteria air pollutants, greenhouse gases, hazardous air pollutants or known air toxins. Among all pollutants in the database, including the most common pollutants PM, CO, CO2 and CH4, records are unevenly distributed with a bias towards flaming combustion, prescribed burning and laboratory measurements. Across all EFs, records are most common for south-eastern and western conifer forests and western shrubland types. Based on identified data gaps, we offer recommendations for future studies, including targeting underrepresented air pollutants, smouldering combustion phases and improved source characterisation of wildland fire emissions.
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Prichard et al. (2020) found a fire average for North American conifer forests of EFCO2 1629.54 ± 63.43, EFCO 104.01 ± 34.93, and EFCH4 5.05 ± 2.41.
“Additionally, our calculated emission factors also agree well with recently compiled emission factors for North American conifer forests, where Prichard et al. (2020) found a fire average for EF CO 2 of 1629.54 ± 63.43, EF CO of 104.01 ± 34.93, and EF CH 4 of 5.05 ± 2.41.”
From Ground solar absorption observations of total column CO, CO <sub>2</sub> , CH <sub>4</sub> , and aerosol optical depth from California's Sequoia Lightning Complex Fire: emission factors and modified combustion efficiency at regional scales (2023) · cites this paper as Prichard et al., 2020
Table 5 (shown in the Sample calculations section; page unavailable) gives exactly these fire-average means and standard deviations for CO₂, CO and CH₄. The table labels the figures as applying to western US conifer forests (western pine and mixed conifer), not North American conifer forests as a whole. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe authors' calculated emission factors agree well with recently compiled emission factors for North American conifer forests.
“Additionally, our calculated emission factors also agree well with recently compiled emission factors for North American conifer forests, where Prichard et al. (2020) found a fire average for EF CO 2 of 1629.54 ± 63.43, EF CO of 104.01 ± 34.93, and EF CH 4 of 5.05 ± 2.41.”
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Research works printed but not linked: 29
- Akagi SK, Yokelson RJ, Wiedinmyer C, Alvarado MJ, Reid JS, Karl T, Crounse JD, Wennberg PO (2011) Emission factors for open and domestic biomass burning for use in atmospheric models. Atmospheric Chemistry and Physics 11, 4039-4072. doi:10.5194/ACP-11-4039-2011 · DOI · Paper page
- Albini FA, Reinhardt ED (1997) Improved calibration of a large fuel burnout model. International Journal of Wildland Fire 7, 21-28. doi:10.1071/WF9970021 · DOI
- Andreae MO, Merlet P (2001) Emissions of trace gases and aerosols from biomass burning. Global Biogeochemical Cycles 15, 955-966. doi:10. 1029/2000GB001382 · DOI
- Aurell J, Gullett BK (2013) Emission factors from aerial and ground measurements of field and laboratory forest burns in the southeastern U.S.: PM 2.5 , black and brown carbon, VOC, and PCDD/PCDF. Environ- mental Science & Technology 47, 8443-8452. doi:10.1021/ES402101K · DOI
- Aurell J, Gullett BK, Tabor D (2015) Emissions from southeastern U.S. grasslands and pine savannas: comparison of aerial and ground field measurements with laboratory burns. Atmospheric Environment 111, 170-178. doi:10.1016/J.ATMOSENV.2015.03.001 · DOI
- Chen LWA, Verburg P, Shackelford A, Zhu D, Susfalk R, Chow JC, Watson JG (2010) Moisture effects on carbon and nitrogen emission from burning of wildland biomass. Atmospheric Chemistry and Physics 10, 6617-6625. doi:10.5194/ACP-10-6617-2010 · DOI
- Drury SA, Larkin N, Strand TT, Huang S, Strenfel SJ, Banwell EN, O'Brien TE, Raffuse SM (2014) Intercomparison of fire size, fuels, fuel consump- tion, and smoke emissions estimates in the 2006 Tripod Fire, Washington, USA. Fire Ecology 10, 56-83. doi:10.4996/FIREECOLOGY.1001056 · DOI
- Garcia-Menendez F, Hu Y, Odman MT (2013) Simulating smoke transport from wildland fires with a regional-scale air quality model: sensitivity to uncertain wind fields. Journal of Geophysical Research, D, Atmospheres 118, 6493-6504. doi:10.1002/JGRD.50524 · DOI
- Gilman JB, Lerner BM, Kuster WC, Goldan PD, Warneke C, Veres PR, Roberts JM, de Gouw JA, Burling IR, Yokelson RJ (2015) Biomass burning emissions and potential air quality impacts of volatile organic compounds and other trace gases from fuels common in the US. Atmospheric Chemistry and Physics 15, 13915-13938. doi:10.5194/ ACP-15-13915-2015 · DOI
- Grandesso E, Gullet B, Touati A, Tabor D (2011) Effect of moisture, charge size, and chlorine concentration on PCDD/F emissions from simulated open burning of forest biomass. Environmental Science & Technology 45, 3887-3894. doi:10.1021/ES103686T · DOI
- Hu Y, Fernandez-Anez N, Smith TEL, Rein G (2018) Review of emissions from smouldering peat fires and their contribution to regional haze episodes. International Journal of Wildland Fire 27, 293-312. doi:10. 1071/WF17084 · DOI
- Koss AR, Sekimoto K, Gilman JB, Selimovic V, Coggon MM, Zarzana KJ, Yan B, Lerner BM, Brown SS, Jimenez JL, Krechmer J, Roberts JM, Warneke C, Yokelson RJ, de Gouw J (2018) Non-methane organic gas emissions from biomass burning: identification, quantification, and emission factors from PTR-ToF during the FIREX 2016 laboratory experiment. Atmospheric Chemistry and Physics 18, 3299-3319. doi:10. 5194/ACP-18-3299-2018 · DOI
- Larkin NK, O'Neill SM, Solomon R, Raffuse S, Strand T, Sullivan DC, Krull C, Rorig M, Peterson J, Ferguson SA (2009) The BlueSky smoke modeling framework. International Journal of Wildland Fire 18, 906- 920. doi:10.1071/WF07086 · DOI
- Larkin NK, Raffuse SM, Strand TM (2014) Wildland fire emissions, carbon, and climate: U.S. emissions inventories. Forest Ecology and Management 317, 61-69. doi:10.1016/J.FORECO.2013.09.012 · DOI
- Laursen KK, Hobbs PV, Radke LF (1992) Some trace gas emissions from North American biomass fires with an assessment of regional and global fluxes from biomass burning. Journal of Geophysical Research 97, 20687-20701. doi:10.1029/92JD02168 · DOI
- Lincoln E, Hao W, Weise DR, Johnson TJ (2014) Wildland fire emission factors database. Forest Service Research Data Archive. (Fort Collins, CO) doi:10.2737/RDS-2014-0012 · DOI
- Liu X, Huey LG, Yokelson RJ, Selimovic V, Simpson IJ, Mu ¨ller M, Jimenez JL, Campuzano-Jost P, Beyersdorf AJ, Blake DR, Butter- field Z, Choi Y, Crounse JD, Day DA, Diskin GS, Dubey MK, Fortner E, Hanisco TF, Hu W, King LE, Kleinman L, Meinardi S, Mikoviny T, Onasch TB, Palm BB, Peischl J, Pollack IB, Ryerson TB, Sachse GW, Sedlacek AJ, Shilling JE, Springston S, St Clair JM, Tanner DJ, Teng AP, Wennberg PO, Wisthaler A, Wolfe GA (2017) Airborne measurements of western U.S. wildfire emissions: comparison with prescribed burning and air quality implications. Jour- nal of Geophysical Research. Atmospheres 122, 6108-6129. doi:10. 1002/2016JD026315 MACTEC Federal Programs (2004) Emission reduction techniques for agricultural burning and wildland fire: a guide to the final work products. Prepared for the Fire Emissions Joint Forum, Western Regional Air Partnership (WRAP). (Durham, NC) · DOI · Paper page
- May AA, McMeeking GR, Lee T, Taylor JW, Craven JS, Burling I, Sullivan AP, Akagi S, Collett JL, Jr, Flynn M, Coe H, Urbanski SP, Seinfeld JH, Yokelson RJ, Kreidenweis SM (2014) Aerosol emissions from prescribed fires in the United States: a synthesis of laboratory and aircraft measurements. Journal of Geophysical Research, D, Atmo- spheres 119, 11826-11849. doi:10.1002/2014JD021848 · DOI
- Miller C, O'Neill SM, Rorig M, Alvarado E (2019) Air quality challenges of prescribed fire in complex terrain and the wildland urban interface surrounding Bend, Oregon. Atmosphere 10, 515. doi:10.3390/ ATMOS10090515 · DOI
- Ottmar RD (2014) Wildland fire emissions, carbon, and climate: modeling fuel consumption. Forest Ecology and Management 317, 41-50. doi:10. 1016/J.FORECO.2013.06.010 · DOI
- Prichard SJ, Kennedy MC, Wright CS, Cronan JB, Ottmar RD (2017) Predicting forest floor and woody fuel consumption from prescribed burns in southern and western pine ecosystems of the United States. Forest Ecology and Management 405, 328-338. doi:10.1016/ J.FORECO.2017.09.025 · DOI
- Radke LF, Hegg DA, Hobbs PV, Nance JD, Lyons JH, Laursen KK, Weiss RE, Riggan PJ, Ward DE (1991) Particulate and trace gas emissions from large biomass fires in North America. In 'Global biomass burning: atmospheric, climatic and biospheric implications'. (Ed. JS Levine) pp. 209-224. (MIT Press: Cambridge, MA)
- Robertson KM, Hsieh YP, Bugna GC (2014) Fire environment effects on particulate matter emission factors in southeastern US pine-grasslands. Atmospheric Environment 99, 104-111. doi:10.1016/J.ATMOSENV. 2014.09.058 · DOI
- Sekimoto K, Koss AR, Gilman JB, Selimovic V, Coggon MM, Zarzana KJ, Yuan B, Lerner BM, Brown SS, Warneke C, Yokelson RJ, Roberts JM, de Gouw J (2018) High-and low-temperature pyrolysis profiles describe volatile organic compound emissions from western US wildfire fuels. Atmospheric Chemistry and Physics 18, 9263-9281. doi:10.5194/ ACP-18-9263-2018 · DOI
- Strand TM, Larkin NK, Craig KJ, Raffuse S, Sullivan D, Solomon R, Rorig M, Wheeler N, Pryden D (2012) Analyses of BlueSky Gateway PM 2.5 predictions during the 2007 southern and 2008 northern California fires. Journal of Geophysical Research 117, D17301. doi:10.1029/ 2012JD017627 · DOI
- Urbanski S (2013) Combustion efficiency and emission factors for wildfire- season fires in mixed conifer forests of the northern Rocky Mountains, US. Atmospheric Chemistry and Physics 13, 7241-7262. doi:10.5194/ ACP-13-7241-2013 · DOI
- Urbanski S (2014) Wildland fire emissions, carbon, and climate: emission factors. Forest Ecology and Management 317, 51-60. doi:10.1016/ J.FORECO.2013.05.045 · DOI
- Yokelson RJ, Griffith DWT, Ward DE (1996) Open path Fourier transform infrared studies of large-scale laboratory biomass fires. Journal of Geophysical Research 101, 21067-21080. doi:10.1029/96JD01800 · DOI
- Yokelson RJ, Burling IR, Gilman JB, Warneke C, Stockwell CE, de Gouw J, Akagi SK, Urbanski SP, Veres P, Roberts JM, Kuster WC, Reardon J, Griffith DWT, Johnson TJ, Hosseini S, Miller JW, Cocker DR, III, Jung H, Weise DR (2013) Coupling field and laboratory measurements to estimate the emission factors of identified and identified trace gases for prescribed fires. Atmospheric Chemistry and Physics 13, 89-116. doi:10.5194/ACP-13-89-2013 · DOI
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Frausto-Vicencio, I., Heerah, S., Meyer, A. G., Parker, H. A., Dubey, M., & Hopkins, F. M. (2023) · Atmospheric Chemistry and Physics · doi:10.5194/acp-23-4521-2023 · Cited by 10 · see citing works
- Authors
- Prichard, S. J., O’Neill, S. M., Eagle, P., Andreu, A. G., Drye, B., Dubowy, J., Urbanski, S., & Strand, T. M.
- Affiliations
- University of Washington (US)
- US Forest Service (US)
- Scion (NZ)
- Corresponding author
- Prichard, Susan J.
- Venue
- International Journal of Wildland Fire
- Publisher
- CSIRO Publishing
- Published
- 2020-01-07
- Volume
- 29
- Issue
- 2
- Pages
- 132-147
- ISSN
- 1049-8001 (ISSN-L)
- 1448-5516
- OpenAlex
- W2997797297
- Cited by
- 136
- References
- 0
- Citations by year
- 2026: 20 · 2025: 24 · 2024: 25 · 2023: 32 · 2022: 20 · 2021: 12 · 2020: 3
- FWCI
- 6.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Wildland Fire (publishedVersion, cc-by-nc-nd)
- Funders
- U.S. Forest Service
- Strategic Environmental Research and Development Program
- Pacific Northwest Research Station
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric chemistry and aerosols
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Toxic Organic Pollutants Impact
- Keywords
- wildfire emissions, emission factors, smoke management, emission inventory, combustion phase, fuel type, particulate matter, carbon monoxide, methane, nitrogen oxides, sulfur dioxide, greenhouse gases, hazardous air pollutants, prescribed burning, coniferous forest, shrubland, data gaps, source characterization
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