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G. Finzi
,
P. Bonelli
, and
G. Bacci

Abstract

Wind speed in the lower layers of the atmosphere is a relevant factor in pollutant dispersion and therefore its forecast is an essential datum for any reliable real-time predictor of ambient concentrations. Here a stochastic model for one-day forecasts of the surface daily wind speed at a site is described. According to the model, this speed is a linear combination of the surface wind speed of the previous day, the daily variation of the 500 mb wind speed over the site, the daily variation of the 500 mb geopotential over the site, and noise. Moreover, the coefficients of the linear combination are assumed to depend both on a “synoptic category” (defined in light of the prevailing synoptic circulation) and on the 500 mb wind direction over the site. The forecast performance is satisfactory for the two sites in the Po Valley (northern Italy) where the model has been tested. Furthermore, it is much better than the performance of a simple autoregressive model. Since such a model uses recent values of the forecast variable (surface daily wind speed) as its only information, the difference in performance shows the importance of using additional meteorological information (500 mb wind and geopotential, and “synoptic category”) for obtaining a reliable forecast.

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P. Bacci
,
P. Bolzern
, and
G. Fronza

Abstract

This paper illustrates a stochastic model of sulphur dioxide dispersion around a power plant. Precisely, the model describes the diurnal dynamics of a variable taken as representative of ground-level pollution [viz., the 2 h Dosage Area Product (DAP) in the sector of prevailing pollutant fallout]. Model exogenous inputs are power generated from the plant (regarded as an indirect measure of the emission), wind direction, and a properly defined atmospheric stability class, which depends on total radiation since sunrise, wind speed and Pasquill category at the end of the previous night.

From the stochastic model, a real-time pollution predictor is derived, namely, a recursive relationship which, at the beginning of each time step, supplies forecasts of future DAP levels. The performance of such a predictor is tested on historical data and, in particular, the quality of the forecast in the presence of fumigation phenomena is pointed out.

The basic difficulty in the actual implementation of the DAP predictor is due to the circumstance that it requires future radiation, wind direction and speed to be forecast separately at each time step. Such forecasts are supplied by three simple “meteorological predictors” which are also illustrated in detail.

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