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Lagrangian particle model LAMBDA: evaluation against tracer data

2014; Inderscience Publishers; Linguagem: Inglês

10.1504/ijep.1995.028383

1741-5101

Enrico Ferrero, D. Anfossi, G. Brusasca, G. Tinarelli,

Air Quality Monitoring and Forecasting

The capabilities of the Lagrangian particle model LAMBDA in simulating tracer dispersion are shown. Two different datasets of experimental campaigns proposed in the Manno Workshop (Copenhagen and Lillestrom) are used to compare measured and calculated concentrations. LAMBDA, which is based on the Langevin equation, can use as input higher moments (like skewness and cross–correlations) of the atmospheric probability density function (p.d.f.). The model can take into account the time and space variation of all the input parameters and can use numerical schemes of different complexity depending on the number of available moments of the atmospheric p.d.f. However, it is able to correctly simulate pollutant dispersion using simpler input datasets and proper parametrisations, as was shown in previous papers. The comparisons of observed and predicted concentrations and the model evaluation indicate that LAMBDA can yield reasonably good results.