Nonlinearity and Prediction of Air Pollution
A presence of nonlinearity in time series of concentrations of air pollutants and in their relations to time series of meteorological variables is tested using information-theoretic functionals and the surrogate data approach. The results are discussed in relation to predictability of the pollutant concentrations aimed to alert smog episodes.
KeywordsMutual Information Diurnal Cycle Surrogate Data Instantaneous Amplitude Ground Level Ozone
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