Application of Chaos Theory to Time-Series Urban Measurements of Meteorological Variables and Radon Concentration: Analysis and Interpretation

Abstract

Through chaos theory, experimental data of hourly time series are analyzed. These time series consist of Radon concentration levels and meteorological variables of temperature, pressure, and relative humidity within the boundary layer and very close to the ground. Results were obtained in two urban dwellings for family use and for two different periods of time, of the order of one month and one month plus one week, respectively. Each time series was subjected to a chaotic analysis showing the existence of the characteristic chaotic parameters in the appropriate ranges: Lyapunov coefficient (λ), correlation dimension (Dc), Kolmogorov entropy (SK), Lempel-Ziv complexity (LZ), Hurst coefficient (H), maximum predictability time (τ), lost information (<ΔI>) and fractal dimension (D). The studied processes show to be irreversible. From the chaotic parameters, it is shown that the ratio between the entropy of each meteorological variable and the radon concentration is very sensitive to relative humidity. Likewise, the meteorological variables that most affect the concentration of Radon are relative humidity and temperature. The concordance between the results obtained and those delivered by analyzes carried out through other methodologies in longer periods is verified.