La concentrazione di SO2 combinando i dati raccolti da centraline fisse e mobili: un modello state space

Given atmospheric measurement from a network of monitoring sites in the area of a city and over an extended period of time, an important problem is to identify the spatial and temporal structure of data. In this paper we focus on the identification and estimate of a statistical model to analyse the SO2 in the city of Padua, where data are collected by some fixed stations and some mobile stations moving without any specific rule in different new locations, staying in every location for a variable number of days. The proposed method divides the global variability in large scale and small scale using some stochastic process as component of variability. The estimate is provided using a state space formulation of the model. As applications of the model we propose the spatial and temporal prevision of the concentration of SO2 . Finally, an exercise is proposed to choose an optimal network for the mobiles monitoring stations for a fixed future time.