An Algorithm to Estimate Field Concentrations in the Wake of a Power Plant Complex under Nonsteady Meteorological Conditions from Wind-Tunnel Experiments

Abstract

Highest concentrations of pollutant at ground level are often produced from surface sources with stable or unstable atmospheric conditions and near calm erratic winds. This paper describes a weighted data methodology developed to predict surface concentrations from stationary wind-tunnel measurements and actual meteorological wind fields. Field measurements made downwind of the Rancho Seco Nuclear Power Station in 1975 have been compared against a set of wind-tunnel measurements around a 1:500 scale model of the same facilities. The weighted data algorithm was realistic in both predicting centerline concentration values as well as the horizontal spread of the plume. On the average the wind-tunnel data combined with the weighting algorithm was some 40 times more accurate in predicting field data than the conventional Pasquill-Gifford formulas.