An evaluation of empirical and statistically based smoke plume injection height parametrisations used within air quality models
Joseph L. Wilkins
A B C G , George Pouliot A , Thomas Pierce A , Amber Soja D E , Hyundeok Choi D E , Emily Gargulinski D , Robert Gilliam A , Jeffrey Vukovich F and Matthew S. Landis A
+ Author Affiliations
- Author Affiliations
A Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27709, USA.
B School of Environmental and Forest Sciences, University of Washington, Seattle, WA 98195, USA.
C Interdisciplinary Studies Department, Howard University, Washington, DC 20059, USA.
D National Institute of Aerospace, Hampton, VA 23666, USA.
E NASA Langley Research Center, Hampton, VA 23666, USA.
F Office of Air and Radiation, US Environmental Protection Agency, Research Triangle Park, NC 27709, USA.
G Corresponding author. Email: joseph.wilkins@howard.edu
International Journal of Wildland Fire 31(2) 193-211 https://doi.org/10.1071/WF20140
Submitted: 2 September 2020 Accepted: 9 March 2021 Published: 31 January 2022
Journal Compilation © IAWF 2022 Open Access CC BY-NC-ND
Abstract
Air quality models are used to assess the impact of smoke from wildland fires, both prescribed and natural, on ambient air quality and human health. However, the accuracy of these models is limited by uncertainties in the parametrisation of smoke plume injection height (PIH) and its vertical distribution. We compared PIH estimates from the plume rise method (Briggs) in the Community Multiscale Air Quality (CMAQ) modelling system with observations from the 2013 California Rim Fire and 2017 prescribed burns in Kansas. We also examined PIHs estimated using alternative plume rise algorithms, model grid resolutions and temporal burn profiles. For the Rim Fire, the Briggs method performed as well or better than the alternatives evaluated (mean bias of less than ±5–20% and root mean square error lower than 1000 m compared with the alternatives). PIH estimates for the Kansas prescribed burns improved when the burn window was reduced from the standard default of 12 h to 3 h. This analysis suggests that meteorological inputs, temporal allocation and heat release are the primary drivers for accurately modelling PIH.
Keywords: air quality model, CALIOP, ceilometer, MicroPulse scanning lidar, plume rise, prescribed burns, remote sensing, wildfire.
References
Achtemeier GL, Goodrick SA, Liu YQ, Garcia-Menendez F, Hu YT, Odman MT (2011) Modeling smoke plume-rise and dispersion from southern United States prescribed burns with daysmoke. Atmosphere 2, 358–388.| Modeling smoke plume-rise and dispersion from southern United States prescribed burns with daysmoke.Crossref | GoogleScholarGoogle Scholar |
Al-Saadi J, Soja AJ, Pierce RB, Szykman J, Wiedinmyer C, Emmons L, Kondragunta S, Zhang X, Kittaka C, Schaack T, Bowman K (2008) Intercomparison of near-real-time biomass burning emissions estimates constrained by satellite fire data. Journal of Applied Remote Sensing 2, 021504.
| Intercomparison of near-real-time biomass burning emissions estimates constrained by satellite fire data.Crossref | GoogleScholarGoogle Scholar |
Andreae MO, Merlet P (2001) Emission of trace gases and aerosols from biomass burning. Global Biogeochemical Cycles 15, 955–966.
| Emission of trace gases and aerosols from biomass burning.Crossref | GoogleScholarGoogle Scholar |
Baker K, Woody M, Valin L, Szykman J, Yates E, Iraci L, Choi H, Soja A, Koplitz S, Zhou L (2018) Photochemical model evaluation of 2013 California wildfire air quality impacts using surface, aircraft, and satellite data. The Science of the Total Environment 637–638, 1137–1149.
| Photochemical model evaluation of 2013 California wildfire air quality impacts using surface, aircraft, and satellite data.Crossref | GoogleScholarGoogle Scholar | 29801207PubMed |
Baker K, Koplitz S, Foley KM, Hawkins A (2019) Characterizing grassland fire activity in the Flint Hills region and air quality using satellite and routine surface monitor data. The Science of the Total Environment 659, 1555–1566.
| Characterizing grassland fire activity in the Flint Hills region and air quality using satellite and routine surface monitor data.Crossref | GoogleScholarGoogle Scholar | 31096365PubMed |
Baldassarre G, Pozzoli L, Schmidt CC, Unal A, Kindap T, Menzel WP, Whitburn S, Coheur PF, Kavgaci A, Kaiser JW (2015) Using SEVIRI fire observations to drive smoke plumes in the CMAQ air quality model: a case study over Antalya in 2008. Atmospheric Chemistry and Physics 15, 8539–8558.
| Using SEVIRI fire observations to drive smoke plumes in the CMAQ air quality model: a case study over Antalya in 2008.Crossref | GoogleScholarGoogle Scholar |
Briggs GA (1975) Plume rise predictions. In ‘Lectures on air pollution and environmental impact analyses’. (Ed. Haugen, D.) pp. 59–111 (American Meteorological Society: Boston, MA, USA).
Charland AM, Clements CB (2013) Kinematic structure of a wildland fire plume observed by Doppler lidar. Journal of Geophysical Research, D, Atmospheres 118, 3200–3212.
| Kinematic structure of a wildland fire plume observed by Doppler lidar.Crossref | GoogleScholarGoogle Scholar |
Clements CB, Oliphant AJ (2014) The California State University mobile atmospheric profiling system: a facility for research and education in boundary layer meteorology. Bulletin of the American Meteorological Society 95, 1713–1724.
| The California State University mobile atmospheric profiling system: a facility for research and education in boundary layer meteorology.Crossref | GoogleScholarGoogle Scholar |
Clements CB, Potter BE, Zhong S (2006) In situ measurements of water vapor, heat and CO2 fluxes within a prescribed grass fire. International Journal of Wildland Fire 15, 299–306.
| In situ measurements of water vapor, heat and CO2 fluxes within a prescribed grass fire.Crossref | GoogleScholarGoogle Scholar |
Clements CB, Zhong S, Goodrick S, Li J, Bian X, Potter BE, Heilman WE, Charney JJ, Perna R, Jang M, Lee D, Patel M, Street S, Aumann G (2007) Observing the dynamics of wildland grass fires: FireFlux – a field validation experiment. Bulletin of the American Meteorological Society 88, 1369–1382.
| Observing the dynamics of wildland grass fires: FireFlux – a field validation experiment.Crossref | GoogleScholarGoogle Scholar |
Clements CB, Lareau NP, Seto D, Contezac J, Davis B, Teske C, Zajkowski TJ, Hudak AT, Bright BC, Dickinson MB, Butler BW, Jimenez D, Hiers JK (2016) Fire weather conditions and fire–atmosphere interactions observed during low-intensity prescribed fires – RxCADRE 2012. International Journal of Wildland Fire 25, 90–101.
| Fire weather conditions and fire–atmosphere interactions observed during low-intensity prescribed fires – RxCADRE 2012.Crossref | GoogleScholarGoogle Scholar |
Clements CB, Lareau NP, Kingsmill DE, Bowers CL, Camacho CP, Bagley R, Davis B (2018) The Rapid Deployments to Wildfires Experiment (RaDFIRE): observations from the fire zone. Bulletin of the American Meteorological Society 99, 2539–2559.
| The Rapid Deployments to Wildfires Experiment (RaDFIRE): observations from the fire zone.Crossref | GoogleScholarGoogle Scholar |
Colarco PR, Schoeberl MR, Doddridge BG, Marufu LT, Torres O, Welton EJ (2004) Transport of smoke from Canadian forest fires to the surface near Washington, DC: injection height, entrainment, and optical properties. Journal of Geophysical Research 109, D06203.
| Transport of smoke from Canadian forest fires to the surface near Washington, DC: injection height, entrainment, and optical properties.Crossref | GoogleScholarGoogle Scholar |
Fann N, Alman B, Broome RA, Morgan GG, Johnston FH, Pouliot G, Rappold AG (2018) The health impacts and economic value of wildland fire episodes in the US: 2008–2012. The Science of the Total Environment 610–611, 802–809.
| The health impacts and economic value of wildland fire episodes in the US: 2008–2012.Crossref | GoogleScholarGoogle Scholar | 28826118PubMed |
Freitas SR, Longo KM, Andreae MO (2006) Impact of including the plume rise of vegetation fires in numerical simulations of associated atmospheric pollutants. Geophysical Research Letters 33, L17808.
| Impact of including the plume rise of vegetation fires in numerical simulations of associated atmospheric pollutants.Crossref | GoogleScholarGoogle Scholar |
Freitas SR, Longo KM, Chatfield R, Latham D, Silva Dias MAF, Andreae MO, Prins E, Santos JC, Gielow R, Carvalho Jr JA (2007) Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models. Atmospheric Chemistry and Physics 7, 3385–3398.
| Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models.Crossref | GoogleScholarGoogle Scholar |
Gelaro R, McCarty W, Suárez MJ, et al. (2017) The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Journal of Climate 30, 5419–5454.
| The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2).Crossref | GoogleScholarGoogle Scholar | 32020988PubMed |
Giglio L, Descloitres J, Justice CO, Kaufman YJ (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment 87, 273–282.
| An enhanced contextual fire detection algorithm for MODIS.Crossref | GoogleScholarGoogle Scholar |
Giglio L, Van der Werf G, Randerson J, Collatz G, Kasibhatla P (2006) Global estimation of burned area using MODIS active fire observations. Atmospheric Chemistry and Physics 6, 957–974.
| Global estimation of burned area using MODIS active fire observations.Crossref | GoogleScholarGoogle Scholar |
Giglio L, Randerson JT, van der Werf GR, Kasibhatla PS, Collatz GJ, Morton DC, DeFries RS (2010) Assessing variability and long-term trends in burned area by merging multiple satellite fire products. Biogeosciences 7, 1171–1186.
| Assessing variability and long-term trends in burned area by merging multiple satellite fire products.Crossref | GoogleScholarGoogle Scholar |
Goodrick SL, Achtemeier GL, Larkin NK, Liu Y, Strand TM (2013) Modelling smoke transport from wildland fires: a review International Journal of Wildland Fire 22, 83–94.
| Modelling smoke transport from wildland fires: a reviewCrossref | GoogleScholarGoogle Scholar |
Gordon M, Makar PA, Staebler RM, Zhang J, Akingunola A, Gong W, Li S-M (2018) A comparison of plume rise algorithms to stack plume measurements in the Athabasca oil sands. Atmospheric Chemistry and Physics 18, 14695–14714.
| A comparison of plume rise algorithms to stack plume measurements in the Athabasca oil sands.Crossref | GoogleScholarGoogle Scholar |
Hyer EJ, Allen DJ, Kasischke ES (2007) Examining injection properties of boreal forest fires using surface and satellite measurements of CO transport. Journal of Geophysical Research 112, D18307.
| Examining injection properties of boreal forest fires using surface and satellite measurements of CO transport.Crossref | GoogleScholarGoogle Scholar |
Ichoku C, Ellison L (2014) Global top–down smoke-aerosol emissions estimation using satellite fire radiative power measurements. Atmospheric Chemistry and Physics 14, 6643–6667.
| Global top–down smoke-aerosol emissions estimation using satellite fire radiative power measurements.Crossref | GoogleScholarGoogle Scholar |
Ichoku C, Kahn R, Chin M (2012) Satellite contributions to the quantitative characterization of biomass burning for climate modelling. Atmospheric Research 111, 1–28.
| Satellite contributions to the quantitative characterization of biomass burning for climate modelling.Crossref | GoogleScholarGoogle Scholar |
Johnston FH, Henderson SB, Chen Y, Randerson JT, Marlier M, Defries RS, Kinney P, Bowman DM, Brauer M (2012) Estimated global mortality attributable to smoke from landscape fires. Environmental Health Perspectives 120, 695–701.
| Estimated global mortality attributable to smoke from landscape fires.Crossref | GoogleScholarGoogle Scholar | 22456494PubMed |
Kahn RA, Li WH, Moroney C, Diner DJ, Martonchik JV, Fishbein E (2007) Aerosol source plume physical characteristics from space-based multi angle imaging. Journal of Geophysical Research, D, Atmospheres 112, D11205.
| Aerosol source plume physical characteristics from space-based multi angle imaging.Crossref | GoogleScholarGoogle Scholar |
Kahn RA, Chen Y, Nelson DL, Leung FY, Li Q, Diner DJ, Logan JA (2008) Wildfire smoke injection heights: Two perspectives from space. Geophysical Research Letters 35, L04809.
| Wildfire smoke injection heights: Two perspectives from space.Crossref | GoogleScholarGoogle Scholar |
Kochanski AK, Mallia DV, Fearon MG, Mandel J, Souri AH, Brown T (2019) Modeling wildfire smoke feedback mechanisms using a coupled fire–atmosphere model with a radiatively active aerosol scheme. Journal of Geophysical Research, D, Atmospheres 124, 9099–9116.
| Modeling wildfire smoke feedback mechanisms using a coupled fire–atmosphere model with a radiatively active aerosol scheme.Crossref | GoogleScholarGoogle Scholar |
Kovalev VS, Newton J, Wold C, Hao WM (2005) Simple algorithm to determine the near-edge smoke boundaries with scanning lidar Applied Optics 44, 1761–1768.
| Simple algorithm to determine the near-edge smoke boundaries with scanning lidarCrossref | GoogleScholarGoogle Scholar |
Labonne M, Bréon F-M, Chevallier F (2007) Injection height of biomass burning aerosols as seen from a spaceborne lidar. Geophysical Research Letters 34, L11806.
| Injection height of biomass burning aerosols as seen from a spaceborne lidar.Crossref | GoogleScholarGoogle Scholar |
Lareau NP, Clements CB (2016) Environmental controls on pyrocumulus and pyrocumulonimbus initiation and development. Atmospheric Chemistry and Physics 16, 4005–4022.
| Environmental controls on pyrocumulus and pyrocumulonimbus initiation and development.Crossref | GoogleScholarGoogle Scholar |
Larkin NK, O’Neill SM, Solomon R, Raffuse S, Strand T, Sullivan DC, Ferguson SA (2009) The BlueSky smoke modeling framework. International Journal of Wildland Fire 18, 906–920.
| The BlueSky smoke modeling framework.Crossref | GoogleScholarGoogle Scholar |
Lelieveld J, Evans JS, Fnais M, Giannadaki D, Pozzer A (2015) The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature 525, 367–371.
| The contribution of outdoor air pollution sources to premature mortality on a global scale.Crossref | GoogleScholarGoogle Scholar | 26381985PubMed |
Leung F-YT, Logan JA, Park R, Hyer E, Kasischke E, Streets D, Yurganov L (2007) Impacts of enhanced biomass burning in the boreal forests in 1998 on tropospheric chemistry and the sensitivity of model results to the injection height of emissions. Journal of Geophysical Research 112, D10313.
| Impacts of enhanced biomass burning in the boreal forests in 1998 on tropospheric chemistry and the sensitivity of model results to the injection height of emissions.Crossref | GoogleScholarGoogle Scholar |
Liu Y-Q, Goodrick S, Achtemeier G, Forbus K, Combs D (2013) Smoke plume height measurement of prescribed burns in the southeastern United States. International Journal of Wildland Fire 22, 130–147.
| Smoke plume height measurement of prescribed burns in the southeastern United States.Crossref | GoogleScholarGoogle Scholar |
Liu Y, Kochanski A, Baker KR, Mell W, Linn R, Paugam R, Mandel J, Fournier A, Jenkins MA, Goodrick S, Achtemeier G, Zhao F, Ottmar R, French NHF, Larkin N, Brown T, Hudak A, Dickinson M, Potter B, Clements C, Urbanski S, Prichard S, Watts A, McNamara D (2019) Fire behaviour and smoke modelling: model improvement and measurement needs for next-generation smoke research and forecasting systems. International Journal Wildland Fire 28, 570–588.
| Fire behaviour and smoke modelling: model improvement and measurement needs for next-generation smoke research and forecasting systems.Crossref | GoogleScholarGoogle Scholar |
Mallia DV, Kochanski AK, Urbanski SP, Lin JC (2018) Optimizing smoke and plume rise modeling approaches at local scales. Atmosphere 9, 166.
| Optimizing smoke and plume rise modeling approaches at local scales.Crossref | GoogleScholarGoogle Scholar |
Marsha A, Larkin NK (2019) A statistical model for predicting PM2.5 for the western United States Journal of the Air & Waste Management Association 69, 1215–1229.
| A statistical model for predicting PM2.5 for the western United StatesCrossref | GoogleScholarGoogle Scholar |
McCarthy N, McGowan H, Guyot A, Dowdy A (2018) MOBILE X-POL RADAR: A new tool for investigating pyroconvection and associated wildfire meteorology. Bulletin of the American Meteorological Society 99, 1177–1195.
| MOBILE X-POL RADAR: A new tool for investigating pyroconvection and associated wildfire meteorology.Crossref | GoogleScholarGoogle Scholar |
McKendry IG, van der Kampa D, Strawbridge KB, Christen A, Crawford B (2009) Simultaneous observations of boundary layer aerosol layers with CL31 ceilometer and 1064/532 nm lidar. Atmospheric Environment 43, 5847–5852.
| Simultaneous observations of boundary layer aerosol layers with CL31 ceilometer and 1064/532 nm lidar.Crossref | GoogleScholarGoogle Scholar |
McKendry IG, Gallagher J, Campuzano P, Bertram A, Strawbridge K, Leaitch R, Macdonald AM (2010) Ground-based remote sensing of an elevated forest fire aerosol layer. Atmospheric Chemistry and Physics 10, 11-921–11-930.
| Ground-based remote sensing of an elevated forest fire aerosol layer.Crossref | GoogleScholarGoogle Scholar |
McKenzie D, Raymond CL, Kellogg L-KB, Norheim RA, Andreu AG, Bayard AC, Kopper KE, Elman E (2007) Mapping fuels at multiple scales: landscape application of the Fuel Characteristic Classification System. Canadian Journal of Forest Research 37, 2421–2437.
| Mapping fuels at multiple scales: landscape application of the Fuel Characteristic Classification System.Crossref | GoogleScholarGoogle Scholar |
Mims SR, Kahn RA, Moroney CM, Gaitley BJ, Nelson DL, Garay MJ (2010) MISR stereo heights of grassland fire smoke plumes in Australia. IEEE Transactions on Geoscience and Remote Sensing 48, 25–35.
| MISR stereo heights of grassland fire smoke plumes in Australia.Crossref | GoogleScholarGoogle Scholar |
Münkel C, Eresmaa N, Räsänen J, Karppinen A (2007) Retrieval of mixing height and dust concentration with lidar ceilometers. Boundary-Layer Meteorology 124, 117–128.
| Retrieval of mixing height and dust concentration with lidar ceilometers.Crossref | GoogleScholarGoogle Scholar |
Omar AH, Winker DM, Vaughan MA, Hu Y, Trepte CR, Ferrare RA, Lee K-P, Hostetler CA, Kittaka C, Rogers RR, Kuehn RE, Liu Z (2009) The Calipso Automated Aerosol Classification and Lidar Ratio selection algorithm. Journal of Atmospheric and Oceanic Technology 26, 1994–2014.
| The Calipso Automated Aerosol Classification and Lidar Ratio selection algorithm.Crossref | GoogleScholarGoogle Scholar |
Ottmar RD, Sandberg DV, Riccardi CL, Prichard SJ (2007) An overview of the fuel characteristic classification system – quantifying, classifying, and creating fuelbeds for resource planning. Canadian Journal of Forest Research 37, 2383–2393.
| An overview of the fuel characteristic classification system – quantifying, classifying, and creating fuelbeds for resource planning.Crossref | GoogleScholarGoogle Scholar |
Paugam R, Wooster M, Freitas S, Val Martin M (2016) A review of approaches to estimate wildfire plume injection height within large-scale atmospheric chemical transport models. Atmospheric Chemistry and Physics 16, 907–925.
| A review of approaches to estimate wildfire plume injection height within large-scale atmospheric chemical transport models.Crossref | GoogleScholarGoogle Scholar |
Peterson DA, Hyer EJ, Campbell JR, Fromm MD, Hair JW, Butler CF, Fenn MA (2015) The 2013 Rim Fire: Implications for predicting extreme fire spread, pyroconvection, and smoke emissions. Bulletin of the American Meteorological Society 96, 229–247.
| The 2013 Rim Fire: Implications for predicting extreme fire spread, pyroconvection, and smoke emissions.Crossref | GoogleScholarGoogle Scholar |
Peterson DA, Hyer EJ, Campbell JR, Solbrig JE, Fromm MD (2017) A conceptual model for development of intense pyrocumulonimbus in western North America. Monthly Weather Review 145, 2235–2255.
| A conceptual model for development of intense pyrocumulonimbus in western North America.Crossref | GoogleScholarGoogle Scholar |
Peterson DA, Campbell J, Hyer E, Fromm M, Kablick G, Cossuth J, DeLand M (2018) Wildfire-driven thunderstorms cause a volcano-like stratospheric injection of smoke. NPJ Climate and Atmospheric Science 1, 30.
| Wildfire-driven thunderstorms cause a volcano-like stratospheric injection of smoke.Crossref | GoogleScholarGoogle Scholar |
Pierce RB, Al‐Saadi JA, Schaack T, et al. (2003) Regional Air Quality Modeling System (RAQMS) predictions of the tropospheric ozone budget over east Asia. Journal of Geophysical Research 108, 8825.
| Regional Air Quality Modeling System (RAQMS) predictions of the tropospheric ozone budget over east Asia.Crossref | GoogleScholarGoogle Scholar |
Pierce RB, Al‐Saadi J, Kittaka C, et al. (2009) Impacts of background ozone production on Houston and Dallas, Texas, air quality during the Second Texas Air Quality Study field mission. Journal of Geophysical Research - Atmospheres 114, D00F09.
| Impacts of background ozone production on Houston and Dallas, Texas, air quality during the Second Texas Air Quality Study field mission.Crossref | GoogleScholarGoogle Scholar |
Pouliot G, Pierce T, Benjey W, O’Neill SM, Ferguson SA (2005) Wildfire emission modeling: integrating BlueSky and SMOKE. In ‘14th Annual International Emission Inventory Conference’, 11–14 April 2005, Las Vegas, NV. (US Environmental Protection Agency: Research Triangle Park, NC) Available at http://www.epa.gov/ttn/chief/conference/ei14/session12/pouliot.pdf [Verified 25 August 2018].
Raffuse S, Wade K, Stone J, Sullivan D, Larkin N, Strand T, Solomon R (2009) Validation of modeled smoke plume injection heights using satellite data. In ‘Eighth Symposium on Fire and Forest Meteorology’, 12–15 October 2009, Kalispell, MT.
Raffuse SM, Craig KJ, Larkin NK, Strand TT, Sullivan DC, Wheeler NJM, Solomon R (2012) An evaluation of modeled plume injection height with satellite-derived observed plume height. Atmosphere 3, 103–123.
| An evaluation of modeled plume injection height with satellite-derived observed plume height.Crossref | GoogleScholarGoogle Scholar |
Rappold AG, Reyes J, Pouliot G, Cascio WE, Diaz-Sanchez D (2017) Community vulnerability to health impacts of wildland fire smoke exposure. Environmental Science & Technology 51, 6674–6682.
| Community vulnerability to health impacts of wildland fire smoke exposure.Crossref | GoogleScholarGoogle Scholar |
Rio C, Hourdin F, Chédin A (2010) Numerical simulation of tropospheric injection of biomass burning products by pyro-thermal plumes. Atmospheric Chemistry and Physics 10, 3463–3478.
| Numerical simulation of tropospheric injection of biomass burning products by pyro-thermal plumes.Crossref | GoogleScholarGoogle Scholar |
Saide PE, Peterson DA, da Silva A, Anderson B, Ziemba LD, Diskin G, Sachse GW, Hair JW, Butler CF, Fenn ME, Jimenez JL, Campuzano-Jost P, Perring AE, Schwarz JP, Markovic MZ, Russell P, Redemann J, Shinozuka Y, Streets DG, Yan F, Dibb JE, Yokelson RJ, Toon OB, Hyer E, Carmichael GR (2015) Revealing important nocturnal and day-to-day variations in fire smoke emissions through a multiplatform inversion. Geophysical Research Letters 42, 3609–3618.
| Revealing important nocturnal and day-to-day variations in fire smoke emissions through a multiplatform inversion.Crossref | GoogleScholarGoogle Scholar |
Shankar U, McKenzie D, Prestemon JP, Baek BH, Omary M, Yang D, Xiu A, Talgo K, Vizuete W (2019) Evaluating wildfire emissions projection methods in comparisons of simulated and observed air quality. Atmospheric Chemistry and Physics 19, 15157–15181.
| Evaluating wildfire emissions projection methods in comparisons of simulated and observed air quality.Crossref | GoogleScholarGoogle Scholar |
Sofiev M, Ermakova T, Vankevich R (2012) Evaluation of the smoke-injection height from wildland fires using remote-sensing data. Atmospheric Chemistry and Physics 12, 1995–2006.
| Evaluation of the smoke-injection height from wildland fires using remote-sensing data.Crossref | GoogleScholarGoogle Scholar |
Sofiev M, Vankevich R, Ermakova T, Hakkarainen J (2013) Global mapping of maximum emission heights and resulting vertical profiles of wildfire emissions. Atmospheric Chemistry and Physics 13, 7039–7052.
| Global mapping of maximum emission heights and resulting vertical profiles of wildfire emissions.Crossref | GoogleScholarGoogle Scholar |
Soja AJ, Al-Saadi JA, Giglio L, Randall D, Kittaka C, Pouliot GA, Kordzi JJ, Raffuse SM, Pace TG, Pierce T, Moore T, Roy B, Pierce B, Szykman JJ (2009) Assessing satellite-based fire data for use in the National Emissions Inventory. Journal of Applied Remote Sensing 3, 031504.
| Assessing satellite-based fire data for use in the National Emissions Inventory.Crossref | GoogleScholarGoogle Scholar |
Soja A, Fairlie T, Westberg D, Pouliot G (2012) Biomass burning plume injection height using CALIOP, MODIS and the NASA Langley Trajectory Model. 2012 US EPA International Emission Inventory Conference. Available at https://www3.epa.gov/ttnchie1/conference/ei20/session7/asoja.pdf [Verified 19 March 2021]
Sokolik IN, Soja AJ, DeMott PJ, Winker D (2019) Progress and challenges in quantifying wildfire smoke emissions, their properties, transport, and atmospheric impacts. Journal of Geophysical Research, D, Atmospheres 124, 13005–13025.
| Progress and challenges in quantifying wildfire smoke emissions, their properties, transport, and atmospheric impacts.Crossref | GoogleScholarGoogle Scholar |
Spinhirne JD (1993) Micro pulse lidar. IEEE Transactions on Geoscience and Remote Sensing 31, 48–55.
| Micro pulse lidar.Crossref | GoogleScholarGoogle Scholar |
Spinhirne JD, Rall JAR, Scott VS (1995) Compact eye-safe lidar systems. The Review of Laser Engineering 23, 112–118.
| Compact eye-safe lidar systems.Crossref | GoogleScholarGoogle Scholar |
Sullivan DC, Raffuse SM, Pryden DA, Craig KJ, Reid SB, Wheeler NJM, Chinkin LR, Larkin NK, Solomon R, Strand T (2008) Development and applications of systems for modeling emissions and smoke from fires: The BlueSky Smoke Modeling Framework and SMARTFIRE. Presented at the 17th International Emissions Inventory Conference led by the Environmental Protection Agency, Portland, OR, USA, 5 June 2008.
Thomas JL, Polashenski CM, Soja AJ, Marelle L, Casey KA, Choi HD, Raut J-C, Wiedinmyer C, Emmons LK, Fast JD, Pelon J, Law KS, Flanner MG, Dibb JE (2017) Quantifying black carbon deposition over the Greenland ice sheet from forest fires in Canada. Geophysical Research Letters 44, 7965–7974.
| Quantifying black carbon deposition over the Greenland ice sheet from forest fires in Canada.Crossref | GoogleScholarGoogle Scholar |
Tosca M, Randerson J, Zender C, Nelson D, Diner D, Logan J (2011) Dynamics of fire plumes and smoke clouds associated with peat and deforestation fires in Indonesia. Journal of Geophysical Research, D, Atmospheres 116, D08207.
| Dynamics of fire plumes and smoke clouds associated with peat and deforestation fires in Indonesia.Crossref | GoogleScholarGoogle Scholar |
Tsaknakis G, Papayannis A, Kokkalis P, Amiridis V, Kambezidis HD, Mamouri RE, Georgoussis G, Avdikos G (2011) Inter-comparison of lidar and ceilometer retrievals for aerosol and Planetary Boundary Layer profiling over Athens, Greece. Atmospheric Measurement Techniques 4, 1261–1273.
| Inter-comparison of lidar and ceilometer retrievals for aerosol and Planetary Boundary Layer profiling over Athens, Greece.Crossref | GoogleScholarGoogle Scholar |
US Environmental Protection Agency (US EPA) (2018) 2014 National Emissions Inventory, Version 2 Technical Support Document. Available at https://www.epa.gov/sites/production/files/2018-07/documents/nei2014v2_tsd_05jul2018.pdf [Verified 19 March 2021]
Val Martin M, Logan JA, Kahn RA, Leung FY, Nelson DL, Diner DJ (2010) Smoke injection heights from fires in North America: Analysis of 5 years of satellite observations. Atmospheric Chemistry and Physics 10, 1491–1510.
| Smoke injection heights from fires in North America: Analysis of 5 years of satellite observations.Crossref | GoogleScholarGoogle Scholar |
Val Martin M, Kahn RA, Logan JA, Paugam R, Wooster M, Ichoku C (2012) Space-based observational constraints for 1-D fire smoke plume-rise models. Journal of Geophysical Research, D, Atmospheres 117, D22204.
| Space-based observational constraints for 1-D fire smoke plume-rise models.Crossref | GoogleScholarGoogle Scholar |
Val Martin M, Kahn RA, Tosca MG (2018) A global analysis of wildfire smoke injection heights derived from space-based multi-angle imaging. Remote Sensing 10, 1609.
| A global analysis of wildfire smoke injection heights derived from space-based multi-angle imaging.Crossref | GoogleScholarGoogle Scholar |
van der Werf GR, Randerson JT, Giglio L, Collatz GJ, Mu M, Kasibhatla PS, Morton DC, DeFries RS, Jin Y, van Leeuwen TT (2010) Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009). Atmospheric Chemistry and Physics 10, 11707–11735.
| Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009).Crossref | GoogleScholarGoogle Scholar |
van Leeuwen TT, van derWerf GR, Hoffmann AA, Detmers RG, Rücker G, French NHF, Archibald S, Carvalho JA, Cook GD, de Groot WJ, Hély C, Kasischke ES, Kloster S, McCarty JL, Pettinari ML, Savadogo P, Alvarado EC, Boschetti L, Manuri S, Meyer CP, Siegert F, Trollope LA, Trollope WSW (2014) Biomass burning fuel consumption rates: a field measurement database. Biogeosciences 11, 7305–7329.
| Biomass burning fuel consumption rates: a field measurement database.Crossref | GoogleScholarGoogle Scholar |
Walter C, Freitas SR, Kottmeier C, Kraut I, Rieger D, Vogel H, Vogel B (2016) The importance of plume rise on the concentrations and atmospheric impacts of biomass burning aerosol Atmospheric Chemistry and Physics 16, 9201–9219.
| The importance of plume rise on the concentrations and atmospheric impacts of biomass burning aerosolCrossref | GoogleScholarGoogle Scholar |
Welton EJ, Campbell JR (2002) Notes and correspondence: Micropulse lidar signals: uncertainty analysis. Journal of Atmospheric and Oceanic Technology 19, 2089–2094.
| Notes and correspondence: Micropulse lidar signals: uncertainty analysis.Crossref | GoogleScholarGoogle Scholar |
Westphal DL, Toon OB (1991) Simulations of microphysical, radiative, and dynamical processes in continental-scale forest smoke plume. Journal of Geophysical Research 96, 22379–22400.
| Simulations of microphysical, radiative, and dynamical processes in continental-scale forest smoke plume.Crossref | GoogleScholarGoogle Scholar |
Whitehill AR, George I, Long R, Baker KR, Landis M (2019) Volatile organic compound emissions from prescribed burning in Tallgrass Prairie ecosystems. Atmosphere 10, 464.
| Volatile organic compound emissions from prescribed burning in Tallgrass Prairie ecosystems.Crossref | GoogleScholarGoogle Scholar |
Wilkins JL, Pouliot G, Foley K, Appel W, Pierce T (2018) 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 27, 684–698.
| The impact of US wildland fires on ozone and particulate matter: a comparison of measurements and CMAQ model predictions from 2008 to 2012.Crossref | GoogleScholarGoogle Scholar |
Wilkins JL, de Foy B, Thompson AM, Peterson DA, Hyer EJ, Graves C, Fishman J, Morris GA (2020) Evaluation of stratospheric intrusions and biomass burning plumes on the vertical distribution of tropospheric ozone over the Midwestern US. Journal of Geophysical Research: Atmospheres 125, e2020JD032454
| Evaluation of stratospheric intrusions and biomass burning plumes on the vertical distribution of tropospheric ozone over the Midwestern US.Crossref | GoogleScholarGoogle Scholar |
Winker D, Vaughan MA, Omar A, Hu Y, Powell KA, Liu Z, Hunt WH, Young SA (2009) Overview of the CALIPSO mission and CALIOP data processing algorithms. Journal of Atmospheric and Oceanic Technology 26, 2310–2323.
| Overview of the CALIPSO mission and CALIOP data processing algorithms.Crossref | GoogleScholarGoogle Scholar |
Wooster MJ, Roberts G, Perry GLW, Kaufman YJ (2005) Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release. Journal of Geophysical Research, D, Atmospheres 110, D24311.
| Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release.Crossref | GoogleScholarGoogle Scholar |
Wotawa G, Trainer M (2000) The influence of Canadian Forest fires on pollutant concentrations in the United States. Science 288, 324–328.
| The influence of Canadian Forest fires on pollutant concentrations in the United States.Crossref | GoogleScholarGoogle Scholar | 10764643PubMed |
Zhou L, Baker KR, Napelenok SL, Pouliot G, Elleman R, O’Neill SM, Urbanski SP, Wong DC (2018) Modeling crop residue burning experiments to evaluate smoke emissions and plume transport. The Science of the Total Environment 627, 523–533.
| Modeling crop residue burning experiments to evaluate smoke emissions and plume transport.Crossref | GoogleScholarGoogle Scholar | 29426175PubMed |
