Dr. Salini-Calderon, Giovanni

We have made a comparative study about the nonlinear behaviour of PM2.5 hourly average concentrations, which were measured at some of the most polluted mid-sized cities located in the South of Chile. The chosen cities were Chillán, Coyhaique and Temuco where high PM2.5 concentrations concentrated in the winter season are caused by the intensive use of wood for heating. The city of Cochabamba, Bolivia, has also been included in this study, due to its very high level of atmospheric pollution by PM10 (especially in the winter season).This city is at a greater height compared to the Chilean cities. Using nonlinear tools, as Wavelet, Recurrence Plots, and Phase Portrait we have investigated the behaviour of PM2.5 and PM10 (hourly) concentrations. Wavelet spectrum and global amplitude for the more polluted cities in study was calculated. Spectral descomposition was performed in time-frecuency through Morlet’s wavelet transform and their global amplitud in time and energy, concentrated around the most importants peaks. On the other hand, a graphical tool that shows typical patterns of dynamic behaviour is the recurrence graph allowing extraction of qualitative characteristics from time series. This method was applied for all cities in study showing patterns that differ from a noisy or random signal. Also the technique of phase-portrait analysis was implemented, showing typical dynamical patterns of non-linear time series, different to a noisy signal pattern. Finally, it was found that hourly airborne particle concentrations exhibit a possible chaotic behaviour, related to short-term predictability some hours ahead.

We present here a study about the limitations found when trying to develop an accurate atmospheric particulate matter forecasting model based on real data, and evidence that the time series of fine particulate matter concentration exhibit deterministic chaotic behavior. We have calculated the Lyapunov exponents of PM2.5 time series obtained from measurements from four monitoring stations located in the city of Santiago, Chile, in recent years. Values obtained for the largest Lyapunov exponents turned out to be positive and ranging between 0.3 and 0.5 which, according to the theory of chaos, is a condition for the presence of deterministic chaos and random behavior in time series. Given the shape of decay of autocorrelation functions and values of correlation dimension and Hurst exponents, random behavior can be discarded: we therefore conclude that the series are chaotic and very sensitive to initial conditions. The study presented here can be replicated in other mid-sized cities that present similar situations to the city of Santiago, where complexity of topography, meteorology and seasonal trends favor the generation of high concentration episodes of atmospheric particulate matter and where a reliable air quality forecasting model may be important for environmental management.

En este documento se presenta un estudio de series temporales de PM10 que muestran la mala calidad del aire en Cochabamba, mediante parámetros estadísticos usados en estudios sobre dinámica no lineal. El promedio diario de PM10 sigue patrones similares al de grandes ciudades que poseen altos índices de contaminación ambiental. Uno de los parámetros resultó del mismo orden y característica que los presentados en trabajos similares sobre el estudio de caoticidad en variables de contaminación como ozono, PM2.5, y CO, demostrando el origen caótico de estos datos. Nuestros resultados contribuyen a la literatura puesto que introducen un análisis metodológico más detallado de la naturaleza no lineal del contaminante PM10.

Desde la perspectiva de la teoría del caos, se analizan series de tiempo de contaminantes como material particulado fino y grueso y de monóxido de carbono junto a las variables meteorológicas, humedad relativa, velocidad del viento y temperatura. Las series surgen de mediciones en seis estaciones de monitoreo ubicadas en Santiago de Chile, de las cuales se seleccionaron dos, para un periodo de 3.25 años. Aplicando la segunda ley de la termodinámica, que es un principio general que impone restricciones a la dirección de la transferencia de calor, y a la eficiencia posible de la denominada máquina térmica (natural y artificial), se estudia la actividad antropogénica y su conexión con la dinámica meteorológica atmosférica. Las entropías de correlación permiten explicar esta conectividad, así como, el efecto de la proximidad geográfica en el proceso de difusión de los contaminantes.