A comparison of operational Lagrangian particle and adaptive puff models for plume dispersion forecasting

Transport and dispersion of pollutants in the lower atmosphere are predicted by using both a Lagrangian particle model (LPM) and an adaptive puff model (APM2) coupled to the same mesoscale meteorological prediction model PMETEO. LPM and APM2 apply the same numerical solutions for plume rise; but, for advection and plume growth, LPM uses a stochastic surrogate to the pollutant conservation equation, and APM2 applies interpolated winds and standard deviations from the meteorological model, using a step-wise Gaussian approach. The results of both models in forecasting the SO2 ground level concentration (glc) around the 1400 MWe coal-fired As Pontes Power Plant are compared under unstable conditions. In addition, meteorological and SO2 glc numerical results are compared to field measurements provided by 17 fully automated SO2 glc remote stations, nine meteorological towers and one Remtech PA-3 SODAR, from a meteorological and air quality monitoring network located 30 km around the power plant.