Application and evaluation of the fay and rosenzweig long range transport model

An analytical model, which is suitable for application to climatological long range dispersion problems, was developed by Fay and Rosenzweig (1980, Atmospheric Environment, 14, 355–365). The model describes the concentration at a receptor due to emissions from a single localized source. Included in...

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Veröffentlicht in:Atmospheric environment 1986, Vol.20 (10), p.1913-1921
Hauptverfasser: Matthias, C.S., Lo, A.K.
Format: Artikel
Sprache:eng
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Zusammenfassung:An analytical model, which is suitable for application to climatological long range dispersion problems, was developed by Fay and Rosenzweig (1980, Atmospheric Environment, 14, 355–365). The model describes the concentration at a receptor due to emissions from a single localized source. Included in the model are processes of advection, diffusion, chemical transformation and dry and wet deposition. Because the dispersion equations are linear, the solutions due to many sources can be superimposed for a given receptor. The model was applied to eastern N America, and was evaluated using sulphur dioxide, sulphate and wet sulphur deposition data collected by several networks. A source inventory describing the distribution and strength of sources over N America during the same time period (1978) was used. The model is relatively simple and inexpensive to operate. For the range of parameters chosen, and for all sources acting simultaneously, the aggregate concentrations at those receptors used for evaluation were fairly insensitive to changes in vector wind speed and direction and to changes in diffusivity. A regression analysis of observed data on model estimates allows us to make an improved concentration estimate from a model estimate. A standard deviation for the estimate is given. Estimates of the variance between modelled and observed concentrations give an estimate of the uncertainty in the results of about 25, 35 and 40% for sulphate, wet S deposition and SO 2 concentrations, respectively.
ISSN:0004-6981
DOI:10.1016/0004-6981(86)90332-X