Expectations and Experience in Diffusion Model Validation
Historically, model validation, and usually model development as well, have been closely associated with programs in which the pollutant measurements and the meteorological data were obtained at a particular site for a specific source-receptor configuration. Typical examples of such data-model relationships include the original small-scale studies conducted at Porton (Sutton, 1947), in which he tested the Gaussian statistical diffusion model and established values for its parameters, and the Brookhaven National Laboratory program (Smith & Singer, 1966) which resulted in adjustment of the Gaussian plume parameters for an elevated source. Investigations of similar nature have continued on a much more elaborate scale in recent years. The detailed studies of diffusion at power plants (Martin and Barber, 1966 and Weil and Brower, 1982) and the excellent tracer studies at Karsruhe (Thomas et al, 1976) are examples of such efforts.
It is probably true that each of these programs was perceived to have transfer value, both by the researchers directly involved and by others. It was reasonable to assume that the models and the expressions for the diffusion parameters would respresent similar sites under similar conditions elsewhere. I know from my own experience that the products of the BNL tower studies were applied with confidence to similar situations, as were the expressions for the diffusion parameters obtained close to the ground in Nebraska (Barad, 1958).
On the other hand, I believe that it is doubtful that any of the researchers involved in these programs anticipated the widespread application of their products to a wide variety of sites and situations. However, this is precisely what happened in the United States after the passage of the first Clean Air Act in 1970. This regulatory strategy, which fortunately appears to have been confined to the United States, resulted in the application of specific models, such as CRSTER AND MPTER, to represent many different situations with no attempt to determine their suitability for these diverse applications. I am quite sure, in respect to this situation, that both Pasquill and Gifford have been appalled rather than flattered to find their expressions for ay and az become law in the United States. Furthermore, the predictions of these models were often allowed to supersede the predictions of other models adapted specifically for the sites in question.
Many in the scientific community, particularly those like myself who had backgrounds in both research and practical application, became quite disturbed at this wholesale use of a limited number of models to situations on which they had never been tested, particularly when it was obvious that some of the predictions were quite inaccurate. This concern eventually became focused and resulted in 1979 in the establishment of a cooperative agreement between the AMerican Meteorological Society (AMS) and the Environmental Protection Agency (EPA), in which the Society took the responsibility for advising and assisting the Agency with dispersion modeling problems. The first major report of this new Committee implementing the program (AMS, 1981) consisted of a broad review of diffusion modeling, and it included specific recommendations that EPA make a concer ted effort to validate the models it was using for regulatory applications.
Many of the contributors to this document expected that this validation work, if conscientiously done, would reveal the weak spots in the models and provide either adjustments for old models or entirely new models that would more faithfully represent the typical problems encountered in the regulatory situations.
At this point a digression is in order, to mention that the concern of the scientists also helped produce several excellent and elaborate field evaluations in the United States, namely the investigations of the utility stacks conducted by the Electric Power Research Institute and the complex terrain studies pursued under the sponsorship of EPA. Such studies will undoubtedly improve further regulatory modeling in the United States, but it is both premature and inappropriate to report on these projects now. Their results have not yet had a noticeable impact on the regulatory scene. Even these studies, as will be noted later in this paper, will not solve some of the problems that plague us.
KeywordsEnvironmental Protection Agency Committee Member Complex Terrain Cooperative Agreement Inherent Uncertainty
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- Amer. Met. Soc, 1981: Air Quality Modeling and the Clean Air Act: Recommendations to EPA on Dispersion Modeling for Regulatory Applications. AMS, Boston, Mass.Google Scholar
- Amer. Met. Soc, 1983: Synthesis of the Rurual Model Reviews, Amer. Met. Soc. (Submitted to EPA as part of Cooperative Agreement)Google Scholar
- Amer. Met. Soc, 1984: Review of the Attributes and Performance of Six Urban Diffusion Models, Amer. Met. Soc., (Submitted to EPA as part of Cooperative Agreement).Google Scholar
- Amer. Met. Soc, 1985: Summary of Complex Terrain Model Evaluation, Amer. Met. Soc. (Submitted to EPA as part of Cooperative Agreement).Google Scholar
- Barad, M.L., 1958, Project Prairie Grass, a field program in diffusion, Geophysical Research Paper No. 59, Vols. I & II, G.R.D., A.F.C.R.C., Bedford, Mass.Google Scholar
- Martin, A. & Barber, F.R., 1966, Investigations of Sulphur Dioxide Pollution Around a Modern Power Plant, Jour. Inst. Of Fuel 39, 294Google Scholar
- Thomas P., et al, (1976), Experimental Determination of the Atmospheric Dispersion Parameters Over Rough Terrain, Part I, Measurements at the Karlsruhe Nuclear Research Center, Gesellschaft Fur Kernforschung, M.B.H., KarlsruheGoogle Scholar
- Weil, J. C., and Brower, R. B., 1982, The Maryland PPSP Dispersion Model for Tall Stacks. Prepared by Environmental Center; Martin Marietta Corporation, for Maryland Department of Natural Resources. (Ref. No. PPSP-MP-36.)Google Scholar