Abstract

This work analyzes the evolution of an urban thermal environment using measurements, in the form of time series, of atmospheric pollutants (PM10, PM2.5, CO) and meteorological variables (temperature (T), relative humidity (RH) and magnitude of wind speed (WS)) of three periods, each of 3.25 years: 2010–2013, 2017–2020 and 2019–2022. The study region is the capital of Chile, Santiago de Chile, located in a rugged basin geography. Of the total communes that make up the capital, six communes that are at different heights from sea level were selected for this study, providing 3,074,004 data records. These communes have been subject to an intensive urban densification process. The time series are analyzed through the chaos theory, demonstrating that they are chaotic through the calculation of the parameters: Lyapunov exponent (λ > 0), correlation dimension (DC < 5), Kolmogorov entropy (SK > 0), Hurst exponent (0.5 < H < 1), Lempel–Ziv complexity (LZ > 0). Based on these parameters, the following is constructed for each commune: the CK ratio, which results from the ratio between the entropies of the meteorological variables and the entropies of the pollutants; the loss of information (<ΔI> < 0) using the Lyapunov exponent; the fractal dimension (D) using the Hurst exponent. It is verified, when comparing the three periods for the six communes, that: CK evolves declining with height, with a greater influence of pollutants; the loss of information is faster in urban meteorology; an increase in fractality. The estimation of the entropic flows, based on the Clausius equation, confirm the trend. The descriptive framework shows the weakness of the mitigation measures.

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