Use of Meteorological Data to Parameterize Statistical Dispersion Models

  • P. J. Barry
  • E. Robertson
Part of the NATO · Challenges of Modern Society book series (NATS, volume 10)


There is currently much interest in planning responses to accidental releases of toxic materials to the atmosphere. To do this effectively requires prior knowledge of the magnitudes and occurrence frequencies of potential exposures. This in turn requires some knowledge of what might be called the ‘climatology’ of air pollution events. Several workers have reported the frequency distributions of concentrations of tracer materials in urban centres or around single isolated stacks. Various well known statistical distributions have been fitted to such data to describe the observations in terms of a small number of parameters. Such studies dealt with observed concentrations but in the case of a new or planned installation, on-site data do not exist and it is then necessary to predict the ranges, particularly the upper ranges, of potential exposures in the surrounding area. Climatological data from which can be derived estimates of the occurrence frequencies of weather or stability classes, and a wind rose are used for the purpose.


Wind Speed Wind Direction Stability Class Climatological Data Cumulative Frequency Distribution 
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  1. Barry, P.J., 1971, “Use of argon-41 to study the dispersion of effluents from stacks,” in “Use of nuclear techniques in the measurement and control of environmental pollution ,” Int. Atom. Ener. Agency, Vienna.Google Scholar
  2. Barry, P.J., 1977, “Stochastic properties of atmospheric diffusivity in sulphur and its inorganic derivatives in the Canadian environment,”Assoc. on Sci. Crit. for Env. Quality, National Research Council Canada, NRCC, N 15015, Ottawa.Google Scholar
  3. Briggs, G.A., 1974, “Diffusion estimates for small emissions,” Environmental Research Laboratories Air Resources, Atmosphere, Turbulence and Diffusion Laboratory, Annual Report 1973 USAFC Report ATDL-106, National Oceanic and Atmospheric Administration.Google Scholar
  4. Hoffman, F.O., and Miller, C.W., 1983, “Uncertainties in environmental radiological assessment models and their implications,” presented at the Nineteenth Annual Meeting National Council on Radiation Protection and Measurements, Washington, D.C.Google Scholar
  5. Hosker, R.P. Jr., “Estimates of dry deposition and plume depletion over forests and grasslands,” in Proc. of IAEA Symnposium, Physical behaviour of radioactive contaminants in the atmosphere,” Vienna, November 1973, IAEA, Vienna (1974).Google Scholar
  6. IAEA, 1980, “Atmospheric dispersion in nuclear power plant siting,” A Safety Guide, Safety Series No. 50-SG-S3.Google Scholar
  7. Miller, C.W., and Little, C.A., 1982, “A review of uncertainty estimates associated with models for assessing the impact of breeder reactor radioactivity releases,” ORNL-5832, Oak Ridge National Laboratory, Oak Ridge, Tenn.CrossRefGoogle Scholar
  8. Mitchell, A.E. Jr., “Atmospheric stability class from horizontal wind fluctuation,” for presentation at the 72nd Annual Meeting of the Air Pollution Control Association, Cincinnati, Ohio, June 24–29, 1979.Google Scholar
  9. Whaley, H., Lee, G.K., 1982, “A comparison of a simple Gaussian plume dispersion model with measurements of pollutant concentration at ground level and aloft,” Atmospheric Environment, vol. 16, No. 4, pp. 871–876.Google Scholar

Copyright information

© Springer Science+Business Media New York 1986

Authors and Affiliations

  • P. J. Barry
    • 1
  • E. Robertson
    • 1
  1. 1.Chalk River Nuclear LaboratoriesChalk RiverCanada

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