Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
REVIEW

Modelling smoke transport from wildland fires: a review

Scott L. Goodrick A D , Gary L. Achtemeier A , Narasimhan K. Larkin B , Yongqiang Liu A and Tara M. Strand C
+ Author Affiliations
- Author Affiliations

A USDA Forest Service, Southern Research Station, 320 Green Street, Athens GA 30602, USA.

B United States Forest Service, Pacific Northwest Research Station, 400 N 34th Street, #201, Seattle, WA 98103, USA.

C Scion Research, New Zealand Forestry Institute, 49 Sala Street, Rotrua 3046, New Zealand.

D Corresponding author. Email: sgoodrick@fs.fed.us

International Journal of Wildland Fire 22(1) 83-94 https://doi.org/10.1071/WF11116
Submitted: 12 August 2011  Accepted: 23 May 2012   Published: 31 August 2012

Abstract

Among the key issues in smoke management is predicting the magnitude and location of smoke effects. These vary in severity from hazardous (acute health conditions and drastic visibility impairment to transportation) to nuisance (regional haze), and occur across a range of scales (local to continental). Over the years a variety of tools have been developed to aid in predicting smoke effects. This review follows the development of these tools, from various indices and simple screening models to complex air quality modelling systems, with a focus on how each tool represents key processes involved in smoke transport.


References

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

Achtemeier GL (2005) Planned burn – Piedmont. A local operational numerical meteorological model for tracking smoke on the ground at night: model development and sensitivity tests. International Journal of Wildland Fire 14, 85–98.
Planned burn – Piedmont. A local operational numerical meteorological model for tracking smoke on the ground at night: model development and sensitivity tests.Crossref | GoogleScholarGoogle Scholar |

Achtemeier GL, Jackson W, Hawkins B, Wade D, McMahon C (1998) The smoke dilemma: a head-on collision! In ‘Transactions of the Sixty-Third North American Wildlife and Natural Resources Conference’, 20–24 March 1998, Orlando, FL. (Ed. KG Wadsworth) pp. 415–421. (Wildlife Management Institute: Washington DC)

Banta RM, Olivier LD, Holloway ET, Kropfli 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 Analyses’. (Ed. DA Haugen) pp. 59–111. (American Meteorological Society: Boston, MA)

Brown JK, Bradshaw LS (1994) Comparisons of particulate emissions and smoke impacts from presettlement, full suppression, and prescribed natural fire periods in the Selway-Bitterroot Wilderness. International Journal of Wildland Fire 4, 143–155.
Comparisons of particulate emissions and smoke impacts from presettlement, full suppression, and prescribed natural fire periods in the Selway-Bitterroot Wilderness.Crossref | GoogleScholarGoogle Scholar |

Byun DW, Ching J (1999). Science algorithms of the EPA Model-3 community multiscale air quality (CMAQ) modeling system. US EPA, 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 |

Choi Y-J, Fernando HJS (2007) Simulation of smoke plumes from agricultural burns: application to the San Luis/Rio Colorado airshed along the US/Mexico border. The Science of the Total Environment 388, 270–289.
Simulation of smoke plumes from agricultural burns: application to the San Luis/Rio Colorado airshed along the US/Mexico border.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXht1ShtLbL&md5=8f2780830a7aab2be4e28f08ef4973e8CAS |

Christopher SA, Gupta P, Nair U, Jones TA, Kondragunta S, Wu YL, Hand J, Zhang X (2009) Satellite remote sensing and mesoscale modeling of the 2007 Georgia/Florida Fires. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2, 163–175.
Satellite remote sensing and mesoscale modeling of the 2007 Georgia/Florida Fires.Crossref | GoogleScholarGoogle Scholar |

Clinton N, Gong P, Scott K (2006) Quantification of pollutants emitted from very large wildland fires in Southern California, USA. Atmospheric Environment 40, 3686–3695.
Quantification of pollutants emitted from very large wildland fires in Southern California, USA.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XltVyhtbw%3D&md5=fbe981354f1996d8563af41d86fb768aCAS |

Cunningham P, Goodrick SL (2012) High-Resolution Numerical Models for Smoke Transport in Plumes from Wildland Fires. In ‘Remote Sensing and Modeling Applications to Wildland Fires’. (Eds JJ Qu, W Sommers, R Yang, A Riebau, M Kafatos) pp. 74–88. (Springer-Verlag, Tsinghua University Press)

Cunningham P, Reeder M (2009) Severe convective storms initiated by intense wildfires: numerical simulations of pyro-convection and pyro-tornadogenesis. Geophysical Research Letters 36, L12812
Severe convective storms initiated by intense wildfires: numerical simulations of pyro-convection and pyro-tornadogenesis.Crossref | GoogleScholarGoogle Scholar |

Cunningham P, Goodrick SL, Hussaini MY, Linn RR (2005) Coherent vortical structures in numerical simulations of buoyant plumes from wildland fires. International Journal of Wildland Fire 14, 61–75.
Coherent vortical structures in numerical simulations of buoyant plumes from wildland fires.Crossref | GoogleScholarGoogle Scholar |

Draxler RR, Rolph GD (2003) HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) Model access via NOAA ARL READY. (NOAA Air Resources Laboratory: Silver Spring, MD) Available at http://www.arl.noaa.gov/ready/hysplit4.html [Verified 23 July 2012]

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 |

Garcia–Menendez F, Yano A, Hu Y, Talat Odman M (2010) An adaptive grid version of CMAQ for improving the resolution of plumes. Atmospheric Pollution Research 1, 239–249.
An adaptive grid version of CMAQ for improving the resolution of plumes.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhtlelsL7F&md5=cdc452314380662b37a01191edff0937CAS |

Grell GA, Peckham SE, McKeen S, Schmitz R, Frost G, Skamarock WC, Eder B (2005) Fully coupled ‘online’ chemistry within the WRF model. Atmospheric Environment 39, 6957–6975.
Fully coupled ‘online’ chemistry within the WRF model.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXhtFGht7vK&md5=bd0c019e85d2328dbdf88f8770b99f87CAS |

Grell G, Freitas SR, Stuefer M, Fast J (2010) Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts. Atmospheric Chemistry and Physics Discussion 10, 30 613–30 650.
Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts.Crossref | GoogleScholarGoogle Scholar |

Herzog M, Graf H-F, Textor C, Oberhuber JM (1998) The effect of phase changes of water on the development of volcanic plumes. Journal of Volcanology and Geothermal Research 87, 55–74.
The effect of phase changes of water on the development of volcanic plumes.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1MXktlemug%3D%3D&md5=e9b0a4e70ad747571b1bd649490b3844CAS |

Hodzic A, Madronich S, Bohn B, Massie S, Menut L, Wiedinmyer C (2007) Wildfire particulate matter in Europe during summer 2003: meso-scale modeling of smoke emissions, transport and radiative effects. Atmospheric Chemistry and Physics Discussion 7, 4705–4760.
Wildfire particulate matter in Europe during summer 2003: meso-scale modeling of smoke emissions, transport and radiative effects.Crossref | GoogleScholarGoogle Scholar |

Hu Y, Odman MT, Chang ME, Jackson W, Lee S, Edgerton ES, Baumann K, Russell AG (2008) Simulation of air quality impacts from prescribed fires on an urban area. Environmental Science & Technology 42, 3676–3682.
Simulation of air quality impacts from prescribed fires on an urban area.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXksFaktbk%3D&md5=7c0825386ae0aee6141274912b9d16bfCAS |

Jackson WA, Achtemeier GL, Goodrick SL (2007). A Technical Evaluation of Smoke Dispersion from the Brush Creek Prescribed Fire and the Impacts on Asheville, North Carolina. Available at http://www.nifc.gov/smoke/documents/Smoke_Incident_Impacts_Asheville_NC.pdf [Verified 25 July 2012]

Jain R, Vaughan J, Kyle H, Ramosa C, Clalborn C, Maarten S, Schaaf M, Lamb B (2007) Development of the ClearSky smoke dispersion forecast system for agricultural field burning in the Pacific Northwest. Atmospheric Environment 41, 6745–6761.
Development of the ClearSky smoke dispersion forecast system for agricultural field burning in the Pacific Northwest.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhtVKrurbJ&md5=60925e5ff20e574e8c03503b464ef8e2CAS |

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 |

Lavdas LG (1986). An Atmospheric Dispersion Index for Prescribed Burning. USDA Forest Service, Southeastern Forest Experiment Station, Research Paper SE-256. (Macon, GA)

Lavdas LG (1996). Program VSMOKE – users manual. USDA Forest Service, Southeastern Forest Experiment Station, General Technical Report SRS-6. (Macon GA)

Lettau HH (1970) Physical and meteorological basis for mathematical models of urban diffusion processes. In ‘Proceedings, Symposium on Multiple Source Urban Diffusion Models’. (Ed. AC Stern) US Environmental Protection Agency, Number AP-86, pp. 2.1–2.26. (Research Triangle Park NC)

Liu Y-Q (2005) Atmospheric response and feedback to radiative forcing from biomass burning in tropical South America. Agricultural and Forest Meteorology 133, 40–53.
Atmospheric response and feedback to radiative forcing from biomass burning in tropical South America.Crossref | GoogleScholarGoogle Scholar |

Liu Y, Goodrick S, Achtemeier G, Jackson W, Qu J, Wang W (2009) Smoke incursions into an urban area: simulation of a Georgia prescribed burn. International Journal of Wildland Fire 18, 336–348.
Smoke incursions into an urban area: simulation of a Georgia prescribed burn.Crossref | GoogleScholarGoogle Scholar |

Liu YQ, Achtemeier GL, Goodrick SL, 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 |

Luderer G, Trentmann J, Winterrath T, Textor C, Herzog M, Graf H-F, Andreae MO (2006) Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part II): sensitivity studies. Atmospheric Chemistry and Physics 6, 5261–5277.
Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part II): sensitivity studies.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXht1eit7w%3D&md5=99c6a71559302c7c63d93f425ddce880CAS |

Manins PC (1979) Partial penetration of an elevated inversion layer by chimney plumes. Atmospheric Environment 13, 733–741.
Partial penetration of an elevated inversion layer by chimney plumes.Crossref | GoogleScholarGoogle Scholar |

McGrattan KB, Baum HR, Rehm RG (1996) Numerical simulation of smoke plumes from large oil fires. Atmospheric Environment 30, 4125–4136.
Numerical simulation of smoke plumes from large oil fires.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK28XmtFaru7g%3D&md5=6f1229dcdc71036beb73f531574cf7b1CAS |

McKenzie D, O’Neill SM, Larkin NK, Norheim RA (2006) Integrating models to predict regional haze from wildland fire. Ecological Modelling 199, 278–288.
Integrating models to predict regional haze from wildland fire.Crossref | GoogleScholarGoogle Scholar |

Meagher JF, Cowling EB, Fehsenfeld FC, Parkhurst WJ (1998) Ozone formation and transport in southeastern United States: overview of the SOS Nashville/Middle Tennessee Ozone Study. Journal of Geophysical Research 103, 22 213–22 223.
Ozone formation and transport in southeastern United States: overview of the SOS Nashville/Middle Tennessee Ozone Study.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1cXmsV2ltLY%3D&md5=48837fe2a94d554d897ab7b3693daee4CAS |

Mobley HE (1989) Summary of smoke-related accidents in the South from prescribed fire (1979–1988). American Pulpwood Association, Technical Release 90-R-11. (Rockville, MD) Available at https://fp.auburn.edu/fire/additionalsmokerealtedaccidents.htm [Verified 25 July 2012]

O’Neill SM, Larkin NK, Hoadley J, Mills G, Vaughan JK, Draxler R, Rolph G, Ruminski M, Ferguson SA (2009) Regional real-time smoke prediction systems. In ‘Developments in Environmental Science’, Wildland Fires and Air Pollution, vol. 8. (Eds A Bytnerowicz, MJ Arbaugh, AR Riebau, C Andersen) Vol. 8, pp. 499–534, (Elsevier B.V.: Oxford, UK)

Oberhuber JM, Herzog M, Graf H-F, Schwanke K (1998) Volcanic plume simulation on large scales. Journal of Volcanology and Geothermal Research 87, 29–53.
Volcanic plume simulation on large scales.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1MXktlemtQ%3D%3D&md5=e70d305de3dbe37983e65d64d2f0ffcbCAS |

Odman MT, Khan MN, McRae DS (2001) Adaptive grids in air pollution modeling: towards an operational model. In ‘Air Pollution Modeling and its Application XIV, Proceedings of the 24th (Millennium) NATO/CCMS International Technical Meeting on Air Pollution Modeling and its Application’, 15–19 May 2000, Boulder, CO. (Eds SE Gryning, FA Schiermeier) pp. 541–549. (Kluwer Academic/ Plenum Publishers: New York)

Pasquill F (1961) The Estimation of the dispersion of windborne material. Meteorological Magazine 90, 33–49.

Pasquill F (1974). ‘Atmospheric Diffusion: The Dispersion of Windborne Material from Industrial and Other Sources’, 2nd edn. (Wiley: New York)

Pharo JA, Lavdas LG, Bailey PM (1976). Smoke Transport and Dispersion. In ‘Southern Forestry and Smoke Management Guidebook’. (Ed. HE Mobley) USDA Forest Service, Southeastern Research Station, General Technical Report SE-10, Chap. 5, pp. 45–55. (Ashville, NC)

Reiquam H (1970) An atmospheric transport and accumulation model for airsheds. Atmospheric Environment 4, 233–247.
An atmospheric transport and accumulation model for airsheds.Crossref | GoogleScholarGoogle Scholar |

Riebau AR, Fox D (2001) The new smoke management. International Journal of Wildland Fire 10, 415–427.
The new smoke management.Crossref | GoogleScholarGoogle Scholar |

Riebau A, Larkin N, Pace T, Lahm P, Haddow D, Spells C (2006) BlueSkyRAINS West (BSRW) Demonstration Project, Final Report. Available at www.airfire.org/pubs/BlueSkyRAINS_West_November_2006.pdf [Verified 23 July 2012]

Rodean H (1996). Stochastic Lagrangian models of turbulent diffusion. In ‘Meteorological Monographs’, vol. 26, number 48. (American Meteorological Society, Boston, MA)

Rolph GD (2003) Real-time environmental applications and display system (READY). (NOAA Air Resources Laboratory: Silver Spring, MD) Available at http://www.arl.noaa.gov/ready/hysplit4.html [Verified 23 July 2012]

Rolph GD, Draxler RR, Stein AF, Taylor A, Ruminski MG, Kondragunta S, Zeng J, Huang H, Manikin G, McQueen JT, Davidson PM (2009) Description and verification of the NOAA smoke forecasting system: the 2007 fire season. Weather and Forecasting 24, 361–378.
Description and verification of the NOAA smoke forecasting system: the 2007 fire season.Crossref | GoogleScholarGoogle Scholar |

Sandberg DV, Hardy CC, Ottmar RD, Snell JAK, Acheson A, Peterson JL, Seamon P, Lahm P, Wade D (1999) National strategy plan: modeling and data systems for wildland fire and air quality. USDA Forest Service, Pacific Northwest Research Station, General Technical Report PNW-GTR-450. (Portland OR)

Scire JS (2000) CALPUFF: Overview of capabilities. In ‘Technical Highlights of EPA’s 7th Conference on Air Pollution Modeling’, 1 August 2000. (North Carolina State University) Available at http://www.epa.gov/scram001/7thconf/information/t029day1.pdf [Verified 25 July 2012]

Sestak ML, Riebau AR (1988) SASEM, Simple approach smoke estimation model. US Bureau of Land Management, Technical Note 382.

Skamarock WC, Klemp JB, Dudhia J (2001). Prototypes for the WRF (Weather Research and Forecasting) model. In ‘Preprints, ninth conference on mesoscale processes’, 29 July–2 August 2001, Fort Lauderdale, FL. pp. J11–J15. (American Meteorological Society: Boston, MA) Available at https://ams.confex.com/ams/pdfpapers/23297.pdf [Verified 25 July 2012]

Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Wang W, Powers JG (2005) A description of the advanced research WRF version 2. National Center for Atmospheric Research, Technical Note, NCAR/TN-468+STR. (Boulder, CO)

Stohl A, Thomson DJ (1999) A density correction for Lagrangian particle dispersion models. Boundary-Layer Meteorology 90, 155–167.
A density correction for Lagrangian particle dispersion models.Crossref | GoogleScholarGoogle Scholar |

Strand TM, Larkin N, Rorig M, Krull C, Moore M (2011) PM2.5 measurements in wildfire smoke plumes from fire season 2005–2008 in the northwestern United States. Journal of Aerosol Science 42, 143–155.
PM2.5 measurements in wildfire smoke plumes from fire season 2005–2008 in the northwestern United States.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXjsFWmsL0%3D&md5=8d7118b9aa4da9beedf965c55e195505CAS |

Strand TM, Larkin NK, Solomon R, Rorig M, Craig K, Raffuse S, Sullivan DC, Wheeler N, Pryden D. Analyses of BlueSky Gateway PM2.5 predictions during the 2007 southern and 2008 northern California fires. Journal of Geophysical Research,
Analyses of BlueSky Gateway PM2.5 predictions during the 2007 southern and 2008 northern California fires.Crossref | GoogleScholarGoogle Scholar | in press

Thomson DJ (1987) Criteria for the selection of stochastic models of particle trajectories in turbulent flows. Journal of Fluid Mechanics 180, 529–556.
Criteria for the selection of stochastic models of particle trajectories in turbulent flows.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaL2sXltlKltbo%3D&md5=f7e9cb383734c164a4a621dc2253c4f6CAS |

Tian D, Wang Y, Bergin M, Hu Y, Liu YQ, Russell AG (2008) Air quality impacts from prescribed forest fires under different management practices. Environmental Science & Technology 42, 2767–2772.
Air quality impacts from prescribed forest fires under different management practices.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXislKqt7g%3D&md5=20052b708965679da02c1858b5165e60CAS |

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 |

Trentmann J, Luderer G, Winterrath T, Fromm MD, Servranckx R, Textor C, Herzog M, Graf G-F, Andreae MO (2006) Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part I): reference simulation. Atmospheric Chemistry and Physics 6, 5247–5260.
Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part I): reference simulation.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXht1eit78%3D&md5=9ddbf92700d1b89b97f1fdd037092b2fCAS |

Turner DB (1970) Workbook of atmospheric dispersion estimates. US Environmental Protection Agency, Office of Air Programs, Publication Number AP-26. (Research Triangle Park, NC)

Valente J, Miranda AI, Lopez AG, Borrego C, Viegas DX, Lopes M (2007) Local-scale modelling system to simulate smoke dispersion. International Journal of Wildland Fire 16, 196–203.
Local-scale modelling system to simulate smoke dispersion.Crossref | GoogleScholarGoogle Scholar |

Wang J, Christopher SA, Nair US, Reid JS, Prins EM, Szykman J, Hand JL (2006) Mesoscale modeling of central American smoke transport to the United States: 1. ‘Top-down’ assessment of emission strength and diurnal variation impacts. Journal of Geophysical Research 111, D05S17
Mesoscale modeling of central American smoke transport to the United States: 1. ‘Top-down’ assessment of emission strength and diurnal variation impacts.Crossref | GoogleScholarGoogle Scholar |

Ward DE, Hardy CC (1991) Smoke emissions from wildland fires. Environment International 17, 117–134.
Smoke emissions from wildland fires.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK3MXktlCltr4%3D&md5=0940f4621e28b04fd4321b10afe25d71CAS |

Wilson JD, Sawford BL (1996) Review of Lagrangian stochastic models for trajectories in the turbulent atmosphere. Boundary-Layer Meteorology 78, 191–210.
Review of Lagrangian stochastic models for trajectories in the turbulent atmosphere. 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 | 1:CAS:528:DC%2BD3cXislertLY%3D&md5=a82b155d866b65585267d82ba003143dCAS |