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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Smoke plume height measurement of prescribed burns in the south-eastern United States

Yongqiang Liu A B , Scott L. Goodrick A , Gary L. Achtemeier A , Ken Forbus A and David Combs A
+ Author Affiliations
- Author Affiliations

A USDA Forest Service, Center for Forest Disturbance Science, 320 Green Street, Athens, GA 30602, USA.

B Corresponding author. Email: yliu@fs.fed.us

International Journal of Wildland Fire 22(2) 130-147 https://doi.org/10.1071/WF11072
Submitted: 19 May 2011  Accepted: 16 July 2012   Published: 24 September 2012

Abstract

Smoke plume height is important for modelling smoke transport and resulting effects on air quality. This study presents analyses of ceilometer measurements of smoke plume heights for twenty prescribed burns in the south-eastern United States. Measurements were conducted from mid-winter to early summer between 2009 and 2011. Approximately half of the burns were on tracts of land over 400 ha (1000 acres) in area. Average smoke plume height was ~1 km. Plume height trended upward from winter to summer. These results could be used as an empirical guideline for fire managers to estimate smoke plume height in the south-eastern US when modelling and measurement are not available. The average could be used as a first-order approximation, and a second-order approximation could be obtained by using the average for spring and autumn seasons, and decreasing or increasing by 0.2 km the average for winter or summer. The concentrations of particulate matter with an aerodynamic diameter less than 2.5 or 10 μm (PM2.5 and PM10) within smoke plumes calculated from ceilometer backscatter are ~80 and 90 μg m–3, and trend downward from winter to summer. Large smoke concentrations are found in the lower portion of smoke plumes for many burns. Smoke plume height shows fast and uniform fluctuations at minute scales for almost all burns and slow and irregular fluctuations at scales from tens of minutes to hours for some burns.

Additional keywords: ceilometer measurement, particulate matter concentration.


References

Achtemeier GL (1998) Predicting dispersion and deposition of ash from burning cane. Sugar Cane 1, 17–22.

Achtemeier LG (2009) On the formation and persistence of super fog in woodland smoke. Meteorological Applications 16, 215–225.
On the formation and persistence of super fog in woodland smoke.Crossref | GoogleScholarGoogle Scholar |

Achtemeier GL, Goodrick SA, Liu YQ, Garcia-Menendez F, Hu Y, Odman MT (2011) Modeling smoke from wildland fires: plume-rise and smoke dispersion from Southern United States prescribed burns. Atmosphere 2, 358–388.
Modeling smoke from wildland fires: plume-rise and smoke dispersion from Southern United States prescribed burns.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXhtFyhtL7P&md5=4995b5bdea57a13ee836f218f0a23e2fCAS |

Amiridis V, Giannakaki E, Balis DS, Gerasopoulos E, Pytharoulis I, Zanis P, Kazadzis S, Melas D, Zerefos C (2010) Smoke injection heights from agricultural burning in Eastern Europe as seen by CALIPSO. Atmospheric Chemistry and Physics 10, 11 567–11 576.
Smoke injection heights from agricultural burning in Eastern Europe as seen by CALIPSO.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXmvFemsLg%3D&md5=ed318e157fa6ca413630171c2d1a86b9CAS |

Anderson HE (1982) Aids to determining fuel models for estimating fire behavior. USDA Forest Service, Intermountain Forest and Range Experimental Station, General Technical Report INT-GTR-122. (Ogden, UT)

Andreae MO, Rosenfeld D, Artaxo P, Costa AA, Frank GP, Longo KM, Silva-Dias MAF (2004) Smoking rain clouds over the Amazon. Science 303, 1337–1342.
Smoking rain clouds over the Amazon.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXhsFyrtL4%3D&md5=f3098670e1ee3ac64129b30854030fbdCAS |

Banta RM, Olivier LD, Holloway ET, Kropeli RA, Bartram BW, Cupp RE, Post MJ (1992) Smoke-column observations from two forest fires using Doppler LiDAR and Doppler radar. Journal of Applied Meteorology 31, 1328–1349.
Smoke-column observations from two forest fires using Doppler LiDAR and Doppler radar.Crossref | GoogleScholarGoogle Scholar |

Briggs GA (1975) Plume rise predictions. In ‘Lectures on Air Pollution and Environmental Impact Analysis’. (Ed. DA Haugen) pp. 59–111. (American Meteorological Society: Boston, MA)

Byun DW, Ching J (1999) Science algorithms of the EPA Model-3 community multiscale air quality (CMAQ) modeling system. US Environmental Protection Agency, National Exposure Research Laboratory, EPA/600/R-99/030. (Research Triangle Park, NC)

Byun D, Schere KL (2006) Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system. Applied Mechanics Reviews 59, 51–77.
Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system.Crossref | GoogleScholarGoogle Scholar |

Cohn SA, Angevine WM (2000) Boundary-layer height and entrainment zone thickness measured by LiDARs and wind-profiling radars. Journal of Applied Meteorology 39, 1233–1247.
Boundary-layer height and entrainment zone thickness measured by LiDARs and wind-profiling radars.Crossref | GoogleScholarGoogle Scholar |

Colarco PR, Schoeberl MR, Doddrodge BG, Marufu LT, Torres O, Welton EJ (2004) Transport of smoke from Canadian forest fires to the surface near Washington, DC. Journal of Geophysical Research 109, D06203
Transport of smoke from Canadian forest fires to the surface near Washington, DC.Crossref | GoogleScholarGoogle Scholar |

Davis KJ, Gamage N, Hagelberg CR, Kiemle C, Lenschow DH, Sullivan PP (2000) An objective method for deriving atmospheric structure from airborne LiDAR observations. Journal of Atmospheric and Oceanic Technology 17, 1455–1468.
An objective method for deriving atmospheric structure from airborne LiDAR observations.Crossref | GoogleScholarGoogle Scholar |

Diner DJ, Nelson DL, Chen Y, Kahn RA, Logan J, Leung F, Val Martin M (2008) Quantitative studies of wildfire smoke injection heights with the Terra Multi-angle Imaging Spectroradiometer. Proceedings of SPIE 7089, 708908
Quantitative studies of wildfire smoke injection heights with the Terra Multi-angle Imaging Spectroradiometer.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 | 1:CAS:528:DC%2BD2sXhtVWntbfO&md5=265b7f3ff7b69ae86fa0003f4fd8f936CAS |

Freitas SR, Longo KM, Trentmann J, Latham D (2010) Technical Note: Sensitivity of 1-D smoke plume rise models to the inclusion of environmental wind drag. Atmospheric Chemistry and Physics 10, 585–594.
Technical Note: Sensitivity of 1-D smoke plume rise models to the inclusion of environmental wind drag.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXjsFGjsb4%3D&md5=37095d61733e5245443e05ce53d33b4eCAS |

Grell G, Freitas SR, Stuefer M, Fastet J (2011) Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts. Atmospheric Chemistry and Physics 11, 5289–5303.
Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXht1WjtrzE&md5=f742f8b6324e90caf913a7786ac2e6ddCAS |

Guldberg PH (1975) A comparison study of plume rise formulas applied to tall stack data. Journal of Applied Meteorology 14, 1402–1405.
A comparison study of plume rise formulas applied to tall stack data.Crossref | GoogleScholarGoogle Scholar |

Hardy C, Ferguson SA, Speers-Hayes P, Doughty CB, Teasdale DR (1993) Assessment of PUFF: a dispersion model for smoke management. USDA Forest Service, Pacific Northwest Region, Final Report. (Seattle, WA)

Harrison H, Hardy C (2002) Plume rise from gigawatt fires: observations and models. Available at http://www.atmos.washington.edu/~harrison/reports/plume3.pdf [Verified 25 August 2012]

Houyoux M, Vukovich J, Seppanen C, Brandmeyer JE (2002) SMOKE User Manual. MCNC Environmental Modeling Center. (Research Triangle Park, NC)

Jones TA, Christopher SA (2008) Variability of Georgia and Florida air quality as a function of radar derived aerosol coverage and height. In ‘15th Joint Conference on the Applications of Air Pollution Meteorology’, 20–24 January 2008, New Orleans, LA. Paper J1.3. (American Meteorological Society: Boston, MA)

Kahn RA, Li WH, Moroney C, Diner DJ, Martonchik JV, Fishbein E (2007) Aerosol source plume physical characteristics from space-based multiangle imaging. Journal of Geophysical Research 112, D11205
Aerosol source plume physical characteristics from space-based multiangle 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 |

Kaufman YJ, Koren I (2006) Smoke and pollution aerosol effect on cloud cover. Science 313, 655–658.
Smoke and pollution aerosol effect on cloud cover.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28Xnsl2hsb0%3D&md5=972c6e25807efde560647dc2e9667299CAS |

Kaufman YJ, Koren I, Remer LA, Rosenfeld D, Rudich Y (2005) The effect of smoke, dust, and pollution aerosol on shallow cloud development over the Atlantic Ocean. Proceedings of the National Academy of Sciences of the United States of America 102, 11 207–11 212.
The effect of smoke, dust, and pollution aerosol on shallow cloud development over the Atlantic Ocean.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXoslKisbY%3D&md5=0db042ac004b06f46f18384d141d662dCAS |

Kiefer MT, Heilman WE, Zhong S, Charney JJ, Bian X, Shadbolt RP, Hom JL, Clark KL, Skowronski N, Gallagher M, Patterson M (2011) Development of a fine scale smoke dispersion modeling system: part II – case study of a prescribed burn in the New Jersey Pine Barrens. In ‘Ninth Symposium on Fire and Forest Meteorology’, 18–21 October 2011, Palm Springs, CA. (Eds BE Potter, TJ Brown) (American Meteorological Society) Available at http://ams.confex.com/ams/9FIRE/webprogram/9FIRE.html [Verified 25 August 2012]

Koren I, Kaufman YJ, Remer LA, Martins JV (2004) Measurement of the effect of Amazon smoke on inhibition of cloud formation. Science 303, 1342–1345.
Measurement of the effect of Amazon smoke on inhibition of cloud formation.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXhsFyrtL8%3D&md5=d9a851f51ddb88abed85afb710597a2eCAS |

Kovalev VA, Petkov A, Cyle W, Urbanski S, Hao WM (2009) Determination of smoke plume and layer heights using scanning LiDAR data. Applied Optics 48, 5287–5294.
Determination of smoke plume and layer heights using scanning LiDAR data.Crossref | GoogleScholarGoogle Scholar |

Labonne M, Breon FM, 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 |

Larkin NK, O’Neill S, Solomon R, Raffuse S, Strand T, Sullivan DC, Krull C, Rorig M, Peterson J, Ferguson S (2009) The BlueSky smoke modeling framework. International Journal of Wildland Fire 18, 906–920.
The BlueSky smoke modeling framework.Crossref | GoogleScholarGoogle Scholar |

Latham D (1994) PLUMP: a one-dimensional plume predictor and cloud model for fire and smoke managers. USDA Forest Service, Intermountain Research Station, General Technical Report INT-GTR-314. (Missoula, MT)

Lavrov A, Utkin A, Vilar R, Fernandes A (2003) Application of LiDAR in ultraviolet, visible and infrared ranges for early forest fire detection. Applied Physics B, Lasers and Optics 76, 87–95.
Application of LiDAR in ultraviolet, visible and infrared ranges for early forest fire detection.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXht1Gks7k%3D&md5=0fa31a910791bfda71fdb46258dddcdbCAS |

Lavrov A, Utkin AB, Vilar R, Fernandes A (2006) Evaluation of smoke dispersion from forest fire plumes using LiDAR experiments and modelling. International Journal of Thermal Sciences 45, 848–859.
Evaluation of smoke dispersion from forest fire plumes using LiDAR experiments and modelling.Crossref | GoogleScholarGoogle Scholar |

Liu YQ (2005) Land breeze and thermals: a scale threshold to distinguish their effects. Advances in Atmospheric. Science 22, 889–902.
Land breeze and thermals: a scale threshold to distinguish their effects.Crossref | GoogleScholarGoogle Scholar |

Liu YQ, Goodrick SL, Achtemeier GL, Jackson WA, Qu J, Wang W (2009) Smoke incursions into urban areas: simulation of a Georgia prescribed burn. International Journal of Wildland Fire 18, 336–348.
Smoke incursions into urban areas: simulation of a Georgia prescribed burn.Crossref | GoogleScholarGoogle Scholar |

Liu YQ, Achtemeier GL, Goodrick GL, Jackson WA (2010) Important parameters for smoke plume rise simulation with Daysmoke. Atmospheric Pollution Research 1, 250–259.
Important parameters for smoke plume rise simulation with Daysmoke.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhtlelsL%2FM&md5=4fc7b69f5ea22d29d3e9e841d0c8ec87CAS |

Mandel J, Beezley JD, Kochanski AK (2011) Coupled atmosphere-wildland fire modeling with WRF 3.3 and SFIRE 2011. Geoscientific Model Development 4, 591–610.
Coupled atmosphere-wildland fire modeling with WRF 3.3 and SFIRE 2011.Crossref | GoogleScholarGoogle Scholar |

Martucci G, Matthey R, Mitev V, Richner H (2010) Frequency of boundary-layer top fluctuations in convective and stable conditions using laser remote sensing. Boundary-Layer Meteorology 135, 313–331.
Frequency of boundary-layer top fluctuations in convective and stable conditions using laser remote sensing.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 | 1:CAS:528:DC%2BC3MXmvFemtrg%3D&md5=264d7c40c995edce10307bc84da1cc1dCAS |

Melnikov VM, Zrnic DS, Rabin RM, Zhang P (2008) Radar polarimetric signatures of fire plumes in oklahoma. Geophysical Research Letters 35, L14815
Radar polarimetric signatures of fire plumes in oklahoma.Crossref | GoogleScholarGoogle Scholar |

Menut L, Flamant C, Pelon J, Flamant PH (1999) Urban boundary-layer height determination from LiDAR measurements over the Paris area. Applied Optics 38, 945–954.
Urban boundary-layer height determination from LiDAR measurements over the Paris area.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD1c7ks1ajug%3D%3D&md5=61d37424aa0f14944f9e12a46f1f1981CAS |

Meyer Y (1993) ‘Wavelets: Algorithms and Applications.’ (SIAM: Philadelphia, PA)

Markowicz KM, Flatau PJ, Kardas AE, Remiszewskaj J, Stelmaszcyk K, Wöste L (2008) Ceilometer retrieval of the boundary layer vertical aerosol extinction structure. Journal of Atmospheric and Oceanic Technology 25, 928–944.
Ceilometer retrieval of the boundary layer vertical aerosol extinction structure.Crossref | GoogleScholarGoogle Scholar |

Mikkelsen T, Jorgensen HE, Nielsen M, Ott S (2002) Similarity scaling of surface-released smoke plumes Boundary-Layer Meteorology 105, 483–505.
Similarity scaling of surface-released smoke plumesCrossref | GoogleScholarGoogle Scholar |

Morlet J, Arens G, Fourgeau E, Griad D (1982a) Wave propagation and sampling theory – part 1: complex signal and scattering in multilayered media. Geophysics 47, 203–221.
Wave propagation and sampling theory – part 1: complex signal and scattering in multilayered media.Crossref | GoogleScholarGoogle Scholar |

Morlet J, Arens G, Fourgeau E, Griad D (1982b) Wave propagation and sampling theory – part 2: sampling theory and complex waves. Geophysics 47, 222–236.
Wave propagation and sampling theory – part 2: sampling theory and complex waves.Crossref | GoogleScholarGoogle Scholar |

Müller D, Mattis I, Wandinger V, Ansmann A, Althausen D, Stohl A (2005) Raman LiDAR observations of aged Siberian and Canadian forest fire smoke in the free troposphere over Germany in 2003: microphysical particle characterization. Journal of Geophysical Research 110, D17201
Raman LiDAR observations of aged Siberian and Canadian forest fire smoke in the free troposphere over Germany in 2003: microphysical particle characterization.Crossref | GoogleScholarGoogle Scholar |

Münkel C, Emeis S, Müller WJ, Schäfer K (2004) Aerosol concentration measurements with a LiDAR ceilometer: results of a one year measuring campaign. Proceedings of SPIE 5235, 486–496.
Aerosol concentration measurements with a LiDAR ceilometer: results of a one year measuring campaign.Crossref | GoogleScholarGoogle Scholar |

Münkel C, Eresmaa N, Räsänen A, Karppinen A (2007) Retrieval of mixing height and dust concentration with LiDAR ceilometer. Boundary-Layer Meteorology 124, 117–128.
Retrieval of mixing height and dust concentration with LiDAR ceilometer.Crossref | GoogleScholarGoogle Scholar |

Pershin S, Hao WM, Susott RA, Babbitt RE, Riebau A (1999) Estimation of emission from Idaho biomass fires using compact eye-safe diode LiDAR. Proceedings of SPIE 3757, 60–66.
Estimation of emission from Idaho biomass fires using compact eye-safe diode LiDAR.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3cXkvFymsro%3D&md5=afcab3a3e69ad7947b48b72c18adecf9CAS |

Potter BE (2005) The role of released moisture in the atmospheric dynamics associated with wildland fires. International Journal of Wildland Fire 14, 77–84.
The role of released moisture in the atmospheric dynamics associated with wildland fires.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 2012]

Radke LF, Ward DE, Philip J, Riggan PJ (2001) A prescription for controlling the air pollution resulting from the use of prescribed biomass fire: clouds. International Journal of Wildland Fire 10, 103–111.
A prescription for controlling the air pollution resulting from the use of prescribed biomass fire: clouds.Crossref | GoogleScholarGoogle Scholar |

Raffuse S, Wade K, Stone J, Sullivan D, Larkin N, Tara S, 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. (Eds BE Potter, TJ Brown) Paper 5A.3. (American Meteorological Society) Available at https://ams.confex.com/ams/8Fire/techprogram/paper_156192.htm [Verified 26 August 2012]

Riebau AR, Fox D (2010) The Joint Fire Science Program Smoke Science Plan. JFSP project 1–C-01–01 Available at http://www.firescience.gov/documents/smoke/2010_JFSP_Smoke_Science_Plan_Final_Version_without_Appendix_B_1.0.pdf [Verified 26 August 2012]

Rogers RR, Brown WOJ (1997) Radar observation of a major industrial fire. Bulletin of the American Meteorological Society 78, 803–814.
Radar observation of a major industrial fire.Crossref | GoogleScholarGoogle Scholar |

Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, Huang X-Y, Wang W, Powers JG (2008) A description of the advanced research WRF Version 3, NCAR Technical Note 475, available at: http://www.mmm.ucar.edu/wrf/users/docs/arwv3.pdf [Verified 26 August 2012]

Stein AF, Rolph GD, Draxler RR, Stunder B, Ruminski M (2009) Verification of the NOAA smoke forecasting system: model sensitivity to the injection height. Weather and Forecasting 24, 379–394.
Verification of the NOAA smoke forecasting system: model sensitivity to the injection height.Crossref | GoogleScholarGoogle Scholar |

Steyn DG, Baldi M, Hoff RM (1999) The detection of mixed layer depth and entrainment zone thickness from LiDAR backscatter profiles. Journal of Atmospheric and Oceanic Technology 16, 953–959.
The detection of mixed layer depth and entrainment zone thickness from LiDAR backscatter profiles.Crossref | GoogleScholarGoogle Scholar |

Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 79, 61–78.
A practical guide to wavelet analysis.Crossref | GoogleScholarGoogle Scholar |

Trentmann J, Andreae MO, Graf H-F, Hobbs PV, Ottmar RD, Trautmann T (2002) Simulation of a biomass-burning plume: Comparison of model results with observations. Journal of Geophysical Research 107, 4013
Simulation of a biomass-burning plume: Comparison of model results with observations.Crossref | GoogleScholarGoogle Scholar |

Tsai PS, Frasier SJ, Goodrick S, Achtemeier G, Odman MT (2009) Combined LiDAR and radar observations of smoke plumes from prescribed burns. In ‘Fourth Symposium on LiDAR Atmospheric Applications’, 10–16 January 2009, Phoenix, AZ. (Eds BB Demoz, J Comstock, A Behrendt) Paper 2.1. (American Meteorological Society) Available at https://ams.confex.com/ams/89annual/techprogram/paper_147257.htm [Verified 26 August 2012]

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 |

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 | 1:CAS:528:DC%2BC3cXjsl2ru7g%3D&md5=ff48f3c6e3c323565a13e4261436d304CAS |

Wade DD, Brock BL, Brose PH, Grace JB, Hoch GA, Patterson WA III (2000) Fire in eastern ecosystems. In ‘Wildland Fire in Ecosystems: Effects of Fire on Flora’. (Eds JK Brown, JK Smith) USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-42, Ch. 4, vol. 2, pp. 53–96. (Ogden, UT)

Wang WT, Qu J, Hao XJ, Liu YQ, Sommers WT (2007) An improved algorithm for small and cool fire detection using MODIS data: a preliminary study in the southeastern United States. Remote Sensing of Environment 108, 163–170.
An improved algorithm for small and cool fire detection using MODIS data: a preliminary study in the southeastern United States.Crossref | GoogleScholarGoogle Scholar |

Weil JC (1988) Plume rise. In ‘Lectures on Air Pollution Modeling’. (Eds A Venkatram, JC Wyngaard). pp. 119–166. (American Meteorological Society: Boston, MA)

Winker D, Vaughan M, Hunt W (2006) The CALIPSO mission and initial results from CALIOP. Proceedings of the Society for Photo-Instrumentation Engineers 6409, 640902
The CALIPSO mission and initial results from CALIOP.Crossref | GoogleScholarGoogle Scholar |

Western Regional Air Partnership (2005) 2002 Fire emission inventory for the WRAP Region Phase II. Essential Documentation. (Air Sciences, Inc.) Available at http://www.wrapair.org/forums/fejf/documents/wrap_2002_phii_ei_report_20050722.pdf [Verified 26 August, 2012]