Análisis de la predictibilidad de las concentraciones anuales de PM2.5 en Quito, aplicando la entropía de Kolmogórov-Sinai.

Abstract

The particulate material of 2.5 microns known as PM2.5 is found in urban air, mainly due to vehicular contamination. The health effects are irreversible because by their size it can permanently lodge in the pulmonary alveoli. The objective of the research was to analyze the predictability of PM2.5 concentrations in Quito-Ecuador (0-13'12.46"S, 78'30'36.97" O, height 2830 m), using the entropy of Kolmogórov-Sinai. The historical data of the concentrations of PM2.5, recorded by the Quito Metropolitan Atmospheric Monitoring Network from 2005-2016, were used. Prior to the predictivity analysis, the time delay parameters, the fit dimension and the Lyapunov exponents that determine the system dynamics, were calculated. The Tisian model is used to process the data. The largest number of positive exponents of Lyapunov are found in 2011, 2013 and 2016. Kolmogorov-Sinai entropy has a tendency to increase over the course of the 12 years analyzed, which implies a decrease in the predictability of PM2.5 data, due to the loss of information over the course of the system evolution.