Real-time forecast of air pollution episodes in the Venetian region. Part 2: The Kalman predictor

Fronza G, Spirito A, & Tonielli A (1979). Real-time forecast of air pollution episodes in the Venetian region. Part 2: The Kalman predictor. Applied Mathematical Modelling 3 (6): 409-415. DOI:10.1016/S0307-904X(79)80022-0.

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Abstract

Real-time prediction of air pollution means forecast of future ground-level concentrations on the basis of current information about meteorology, emission and concentrations themselves. The paper illustrates how the episode forecast performance of the advection-diffusion model (described in Part 1) can be improved by: (i) embedding the model into a stochastic version, by introducing into the numerical solution scheme of the advection-diffusion equation proper random terms (noises), specified in a statistical sense and representative of all the inaccuracies of the model itself (wrong inputs, numerical errors, simplifications of the actual physical mechanism, ...); (ii) applying the well-known Kalman prediction technique for real-time forecast to such stochastic version of the model. The results of such a procedure have been satisfactory in the case of the Venetian lagoon sulphur dioxide pollution. In particular, the four-hour ahead forecasts of episodes have been drastically improved with respect to those obtained by means of the "deterministic predictor" illustrated in Part 1.

Item Type: Article
Research Programs: Resources and Environment Area (REN)
Bibliographic Reference: Applied Mathematical Modelling; 3(6):409-415 (December 1979) (Published online 12 January 2007)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 01:45
Last Modified: 25 Feb 2016 09:51
URI: http://pure.iiasa.ac.at/1001

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