Boundary-Layer Meteorology

, Volume 169, Issue 1, pp 67–91 | Cite as

Plume Dispersion in Low-Wind-Speed Conditions During Project Sagebrush Phase 2, with Emphasis on Concentration Variability

  • D. FinnEmail author
  • R. G. Carter
  • R. M. Eckman
  • J. D. Rich
  • Z. Gao
  • H. Liu
Research Article


Eight short-range, open-terrain SF6 tracer tests in low wind speeds were conducted during Phase 2 of Project Sagebrush using continuous releases. Four tests were made during very unstable conditions in July and August 2016, and four during very stable conditions in October 2016. All tests featured 10-min averaging and 1-Hz sampling of tracer concentrations together with an extensive suite of meteorological measurements. We find that the uncertainty in well-mixed daytime measurements of tracer concentrations, using the absolute value of the relative percentage difference in collocated duplicate samplers, approaches a downwind limit of about 7–8%. Concentration variability in collocated sampling, due to stochastic factors and independent of measurement uncertainty, increases the total observational uncertainty closer to the source from about 20% (daytime) to 40% (very stable conditions). Longer averaging periods moderately reduce the concentration variability. The data indicate that the large increase in concentration variability is linked with the suppression of turbulent mixing, small eddy length scales, and meandering in very stable conditions. These results should be considered when comparing observations with model predictions in evaluations.


Observation uncertainty Probability distributions Small eddies Turbulent mixing Very stable conditions 



We wish to acknowledge Kirk Clawson, Shane Beard, Brad Reese, Donna Davis, Matt Brewer, and Devin Clinger from the Field Research Division of NOAA and Justine Missik and Raleigh Grysko from the Laboratory for Atmospheric Research at Washington State University for their contributions to the field campaign. Participation by Washington State University was supported by National Science Foundation AGS under Grants #1419614. The scientific results and conclusions, as well as any views or opinions expressed herein, are those of the author(s) and do not necessarily reflect the views of NOAA or the Department of Commerce.


  1. Banta RM, Mahrt L, Vickers D, Sun J, Balsley BB, Pichugina YL, Williams EJ (2007) The very stable boundary layer on nights with weak low-level jets. J Atmos Sci 64:3068–3091. CrossRefGoogle Scholar
  2. Barad ML (ed) (1958) Project prairie grass, a field program in diffusion, volume I–II of geophysical research papers no. 59. Technical report AFCRC-TR-58-235, Air Force Cambridge Research Center, USAF, Bedford, MAGoogle Scholar
  3. Chang JC, Hanna SR (2004) Air quality model performance evaluation. Meteorol Atmos Phys 87:167–196. CrossRefGoogle Scholar
  4. Chatwin PC (1982) The use of statistics in describing and predicting the effects of dispersing gas clouds. J Hazard Mater 6:213–230CrossRefGoogle Scholar
  5. Cionco RM, Kampe W, Biltoft C, Byers JH, Collins CG, Higgs TJ, Hin ART, Johansson PE, Jones CD, Jorgensen HE, Kimber JF, Mikkelsen T, Nyren K, Ride DJ, Robson R, Santabarbara JM, Streicher J, Thykier-Nielsen S, van Raden H, Weber H (1999) An overview of MADONA: a multinational field study of high-resolution meteorology and diffusion over complex terrain. Bull Am Meteorol Soc 80(1):5–19.;2 CrossRefGoogle Scholar
  6. Clawson KL, Carter RG, Lacroix DJ, Biltoft CA, Hukari NF, Johnson RC, Rich JD, Beard SA, Strong T (2005) Joint urban 2003 (JU03) SF6 atmospheric tracer field tests. NOAA technical memorandum OAR ARL-254, Air Resources Laboratory, Idaho Falls, IdahoGoogle Scholar
  7. Clawson KL, Eckman RM, Johnson RC, Carter RG, Finn D, Rich JD, Hukari NF, Strong TW, Beard SA, Reese BR (2009) Roadside sound barrier tracer study 2008. NOAA technical memorandum OAR ARL-260, Air Resources Laboratory, Idaho Falls, IdahoGoogle Scholar
  8. Department of Defense (2002) Department of Defense Quality Systems Manual for Environmental Laboratories, Final Version 2. U.S. Department of Defense, Environmental Data Quality Workgroup, Department of the Navy, Lead ServiceGoogle Scholar
  9. Dinar N, Kaplan H, Kleiman M (1988) Characterization of concentration fluctuations of a surface plume in neutral boundary layer. Boundary-Layer Meteorol 45:157–175CrossRefGoogle Scholar
  10. Environmental Protection Agency (1999) Summary of the U.S. EPA workshop on the relationship between exposure duration and toxicity. Technical report EPA/600/R-99/081, U.S. Environmental Protection AgencyGoogle Scholar
  11. Environmental Protection Agency (2000a) Guidance for data quality assessment—practical methods for data analysis. Technical report QA/G-9, EPA/600/R-96/084, U.S. Environmental Protection AgencyGoogle Scholar
  12. Environmental Protection Agency (2000b) Quality systems. National environmental laboratory accreditation conference (NELAC). Technical report QA/G-9, EPA/600/R-00/084, NTIS PB2001-104049, U.S. Environmental Protection AgencyGoogle Scholar
  13. Fairhurst S, Turner RM (1993) Toxicological assessments in relationship to major hazards. J Hazard Mater 33:215–227CrossRefGoogle Scholar
  14. Finn D, Clawson KL, Carter RG, Rich JD, Biltoft C (2010) Analysis of urban atmosphere plume concentration fluctuations. Boundary-Layer Meteorol 136:431–456. CrossRefGoogle Scholar
  15. Finn D, Clawson KL, Eckman RM, Carter RG, Rich JD, Strong TW, Beard SA, Reese BR, Davis D, Liu H, Russell E, Gao Z, Brooks S (2015) Project sagebrush phase 1. NOAA technical memorandum OAR ARL-268, Air Resources Laboratory, Idaho Falls, Idaho.
  16. Finn D, Clawson KL, Eckman RM, Liu H, Russell ES, Gao Z, Brooks S (2016) Project Sagebrush: revisiting the value of the horizontal plume spread parameter σy. J Appl Meteorol Clim 46:2019–2037. Google Scholar
  17. Finn D, Clawson KL, Eckman RM, Carter RG, Rich JD, Reese BR, Beard SA, Brewer M, Davis D, Clinger D, Gao Z, Liu H (2017) Project sagebrush phase 2. NOAA technical memorandum OAR ARL-275, Air Resources Laboratory, Idaho Falls, Idaho.
  18. Flaherty JE, Lamb B, Allwine KJ, Allwine E (2007) Vertical tracer concentration profiles measured during the Joint Urban 2003 dispersion study. J Appl Meteorol Clim 46:2019–2037. CrossRefGoogle Scholar
  19. Fox DG (1984) Uncertainty in air quality modeling. Bull Am Meteorol Soc 65:27–36.<0027:UIAQM>2.0.CO;2 CrossRefGoogle Scholar
  20. Goulart A, Degrazia G, Acevedo O, Anfossi D (2007) Theoretical considerations of meandering wind in simplified conditions. Boundary-Layer Meteorol 125:279–287CrossRefGoogle Scholar
  21. Gryning S-E, Batchvarova E, Rotach MW, Christen A, Vogt R (2005) Roof-level SF6 tracer experiments in the city of Basel. Zurcher Klima-Schriften 85:83Google Scholar
  22. Hanna SR (1983) Lateral turbulence intensity and plume meandering during stable conditions. J Clim Appl Meteorol 22:1424–1430CrossRefGoogle Scholar
  23. Hanna SR (1984) Concentration fluctuations in a smoke plume. Atmos Environ 18:1091–1106CrossRefGoogle Scholar
  24. Hanna SR, Baja E (2009) A simple urban dispersion model tested with tracer data from Oklahoma City and Manhattan. Atmos Environ 43(4):778–786. CrossRefGoogle Scholar
  25. Hanna SR, Britter R, Franzese P (2003) A baseline urban dispersion model evaluated with Salt Lake City and Los Angeles tracer data. Atmos Environ 37:5069–5082. CrossRefGoogle Scholar
  26. Hanna SR, White J, Zhou Y (2007) Observed winds, turbulence, and dispersion in built-up downtown areas of Oklahoma City and Manhattan. Boundary-Layer Meteorol 125:441–468. CrossRefGoogle Scholar
  27. Hendricks EA, Diehl SR, Burrows DA, Keith R (2007) Evaluation of a fast-running urban dispersion modeling system using Joint Urban 2003 field data. J Appl Meteorol Clim 46:2165–2179. CrossRefGoogle Scholar
  28. Hiscox AL, Miller DR, Nappo CJ (2010) Plume meander and dispersion in a stable boundary layer. J Geophys Res 115:D21105. CrossRefGoogle Scholar
  29. International Organization on Standardization (ISO) (1990) General requirements for the competence of calibration and testing laboratories. ISO/IEC Guide 25-1990Google Scholar
  30. Irwin JS, Hanna SR (2005) Characterising uncertainty in plume dispersion models. Int J Environ Pollut 25:16–24. CrossRefGoogle Scholar
  31. Klein PM, Young DT (2011) Concentration fluctuations in a downtown urban area. Part I: analysis of Joint Urban 2003 full-scale fast-response measurements. Environ Fluid Mech 11:23–42. CrossRefGoogle Scholar
  32. Kodavanti UP, Costa DL, Giri SN, Starcher B, Hatch GE (1997) Pulmonary structural and extracellular matrix alterations in Fischer 344 rats following subchronic phosgene exposure. Fundam Appl Toxicol 37:54–63CrossRefGoogle Scholar
  33. Lewellen WS, Sykes RI (1986) Analysis of concentration fluctuations from lidar observations of atmospheric plumes. J Clim Appl Meteorol 25:1145–1154.;2 CrossRefGoogle Scholar
  34. Luhar AK, Hurley PJ (2012) Application of a coupled prognostic model to turbulence and dispersion in light-wind stable conditions, with an analytical correction to vertically resolved concentrations near the surface. Atmos Environ 51:56–66. CrossRefGoogle Scholar
  35. Mahrt L (2014) Stably stratified atmospheric boundary layers. Annu Rev Fluid Mech 46:23–45. CrossRefGoogle Scholar
  36. Mole N, Jones CD (1994) Concentration fluctuation data from dispersion experiments carried out in stable and unstable conditions. Boundary-Layer Meteorol 67:41–74. CrossRefGoogle Scholar
  37. Mortarini L, Ferrero E, Falabino S, Trini Castelli S, Richiardone R, Anfosi D (2013) Low-frequency processes and turbulence structure in a perturbed boundary layer. Q J R Meteorol Soc 139:1059–1072. CrossRefGoogle Scholar
  38. Mortarini L, Stefanello M, Degrazia G, Roberti D, Trini Castelli S, Anfossi D et al (2016a) Characterization of wind meandering in low-wind-speed conditions. Boundary-Layer Meteorol 161:165–182. CrossRefGoogle Scholar
  39. Mortarini L, Maldaner S, Moor L, Stefanello M, Acevedo O, Degrazia G, Anfossi D (2016b) Temperature auto-correlation and spectra functions in low-wind meandering conditions. Q J R Meteorol Soc 142:1881–1889. CrossRefGoogle Scholar
  40. Mylne K (1992) Concentration fluctuation measurements in a plume dispersing in a stable boundary layer. Boundary-Layer Meteorol 60:15–48. CrossRefGoogle Scholar
  41. Mylne K, Mason PJ (1991) Concentration fluctuation measurements in a dispersing plume at a range of up to 1000 m. Q J R Meteorol Soc 117:177–206Google Scholar
  42. Nappo C, Miller D, Hiscox A (2010) A note on turbulence stationarity and wind persistence with the stable planetary boundary layer. Boundary-Layer Meteorol 136(1):165–174. CrossRefGoogle Scholar
  43. Nironi C, Salizzoni P, Marro M, Mejean P, Grosjean N, Soulhac L (2015) Dispersion of a passive scalar fluctuating plume in a turbulent boundary layer. Part I: velocity and concentration measurements. Boundary-Layer Meteorol 156:415–446. CrossRefGoogle Scholar
  44. Oettl D, Goulart A, Degrazia G, Anfossi D (2005) A new hypothesis on meandering atmospheric flows in low wind speed conditions. Atmos Environ 39:1739–1748. Google Scholar
  45. Ramsdell JV Jr, Hinos WT (1971) Concentration fluctuations and peak-to-mean concentration ratios in plumes from a ground-level continuous point source. Atmos Environ (1967) 5:483–495. CrossRefGoogle Scholar
  46. Ride DJ (1984) An assessment of the effects of fluctuations on the severity of poisoning by toxic vapours. J Hazard Mater 9:235–240CrossRefGoogle Scholar
  47. Sagendorf JF, Dickson CR (1974) Diffusion under low windspeed, inversion conditions. NOAA Technical memorandum ERL ARL-52, Air Resources Laboratory, Idaho Falls, IDGoogle Scholar
  48. Sawford BL, Frost CC, Allan TC (1985) Atmospheric boundary-layer measurements of concentrations statistics from isolated and multiple sources. Boundary-Layer Meteorol 31:249–268. CrossRefGoogle Scholar
  49. Singer IA (1967) Steadiness of the wind. J Appl Meteorol 6(6):1033–1038.<1033:SOTW>2.0.CO;2 CrossRefGoogle Scholar
  50. Slade DH (1968) Meteorology and atomic energy: U.S. Atomic Energy Commission, Office of Information Services. Available as TID-24190 from National Technical Information ServiceGoogle Scholar
  51. Sun J, Mahrt L, Banta R, Pichugina YL (2012) Turbulence regimes and turbulence intermittency in the stable boundary layer during CASES-99. J Atmos Sci 69:338–351. CrossRefGoogle Scholar
  52. Sun J, Mahrt L, Nappo C, Lenschow D (2015) Wind and temperature oscillations generated by wave-turbulence interactions in the stably stratified boundary layer. J Atmos Sci 72:1484–1503. CrossRefGoogle Scholar
  53. ten Berge WF, Zwart A, Appelman LM (1986) Concentration-time mortality response relationship of irritant and systematically acting vapours and gases. J Hazard Mater 13:301–309CrossRefGoogle Scholar
  54. Venkatram A, Isakov V, Pankratz D, Heumann J, Yuan J (2004) The analysis of data from an urban dispersion plume experiment. Atmos Environ 38:3647–3659. CrossRefGoogle Scholar
  55. Venkatram A, Isakov V, Pankratz D, Yuan J (2005) Relating plume spread to meteorology in urban areas. Atmos Environ 39:371–380. CrossRefGoogle Scholar
  56. Wilson DJ (2010) Concentration fluctuations and averaging time in vapor clouds. Wiley, Hoboken. ISBN 0-8169-0679-3Google Scholar
  57. Witschi H (1999) Some notes on the history of Haber’s Law. Toxicol Sci 50:164–168CrossRefGoogle Scholar
  58. Yee E, Biltoft C (2004) Concentration fluctuation measurements in a plume dispersing through a regular array of obstacles. Boundary-Layer Meteorol 111:363–415. CrossRefGoogle Scholar
  59. Yee E, Kosteniuk PR, Chandler GM, Biltoft CA, Bowers JF (1993) Statistical characteristics of concentration fluctuations in dispersing plumes in the atmospheric surface layer. Boundary-Layer Meteorol 65:69–109. CrossRefGoogle Scholar
  60. Yee E, Chan R, Kosteniuk PR, Chandler GM, Biltoft CA, Bowers JF (1994) Experimental measurements of concentration fluctuations and scales in a dispersing plume in the atmospheric surface layer obtained using a very fast response concentration detector. J Appl Meteorol 33:996–1016.;2 CrossRefGoogle Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply  2018

Authors and Affiliations

  1. 1.NOAA Air Resources Laboratory, Field Research DivisionIdaho FallsUSA
  2. 2.Laboratory for Atmospheric ResearchWashington State UniversityPullmanUSA

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