Statistical modelling and prediction of pollutants in the urban atmosphere of Salamanca, Spain

 The primary aim of the present work is to describe and analyze the temporal trends of concurrent hourly observations and its daily averaged series of the pollutants CO, NO₂, NO and SO₂ in the urban area of the City of Salamanca (environmental survey station SA001) for the period between 1 December 1993 and 30 November 1994. Using daily series corresponding to different meteorological variables recorded at the same site for the same period (wind direction, relative humidity, pressure, radiation, temperature and wind speed), linear regression techniques are used to study the relationships of these variables with each of the polluntants on both an individual and multivariate basis. The results obtained explain 40% of the variance of the series for NO₂ and 66% in the case of SO₂. Finally, in the modelling phase it was observed that the series of polluntants themselves have sufficient ’’information’’ to enable, by means of autoregressive and integrated moving average techniques (A.R.I.M.A.), the determination of future pollution. Once predicted, these were contrasted with the measured or observed values to check the goodness of the model. Received: 9 December 1996 / Accepted: 24 January 1997