The use of operational models to control local air pollution episodes around single point sources usually requires extensive testing over long periods time and/or specific calibration of the models. In addition, uncertainties in the input data, especially measured or forecast meteorological data, can introduce significant errors. We have obtained the information required to test the performance of the Lagrangian adaptive plume model (APM) that has been used operationally since 1994. The model has been used to analyze and forecast dispersion of a plume from the 1400 MW As Pontes Power Plant in Northwestern Spain. During the first 4-years, the main effort was directed toward:
(1) assuring that the model operated properly, and that we had adequate emissions and meteorological measurements in real time, and
(2) improving the meteorological predictions used for air pollution forecasts.
The problem is particularly difficult because of the complex terrain surrounding the plant; hills rise to 700 m, the sea is within 20 km and the stack height above the surrounding terrain is 356.5 m.
We report on the testing of a new version of the adaptive plume model, APM-2, using data from the As Pontes Power Plant, before and after the model had been calibrated. Model calculated concentrations have been compared with continuous ground level measurements at 17 locations around the power plant. Results from the uncalibrated and calibrated models are given for the summer period, which is the season with the least favorable weather conditions.
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