We present here a study about the possible spread of covid-19 pandemic between human's beings through aerosols contained in urban air polluted by respirable particulate matter and tropospheric ozone, as well as the incidence of local meteorology in an area with orographic basin characteristics and in a certain period of time. Hourly time-series data of three meteorological variablestemperature, relative humidity, wind speed-and three pollutants-PM10, PM2.5 and O3-were considered together with hourly data from the highest number accumulated sick's in seven communes-chosen at random-in Santiago, Chile, studying a probable link between them. From the epidemic perspective, the infected patients number was linked to the hourly time-series of meteorological and pollutant variables, generating new time-series. Nonlinear analysis and the chaos theory formalism was applied to these new time-series, obtaining the largest Lyapunov exponent, correlation dimension, Kolmogorov entropy, Hurst exponent and the Lempel-Ziv complexity. Our preliminary results show meteorological and air pollution variables can be part of the elements fraction that give sustainability to the accumulated growth of infected patients and favor the pandemic spread, making the accumulated sick's curve chaotic and complex. In addition, environmental pollution could worsen disease conditions like coronavirus (COVID-19) infection.

This research examines the persistence of a pandemic in urban environments subjected to intensive densification processes, applying chaotic analysis tools to hourly time series constructed by relating accumulated patients with meteorological and pollutant variables (measured at ground level). To investigate this objective, seven communes of the metropolitan region of Santiago de Chile that present intensive urbanization processes that affect urban micrometeorology, favoring the concentration of pollutants, were considered. Quotients were constructed between the number of hourly patients with SARS-CoV-2 that accumulated in each commune over a period of two years and the hourly variables of urban micrometeorology (temperature, magnitude of wind speed, relative humidity) and pollutant concentration (tropospheric ozone, particulate material of 2.5 and 10 μm) constituting a new family of time series. Chaos theory was applied to these new time series, obtaining the chaotic parameters Lyapunov coefficient, correlation entropy, Lempel–Ziv complexity, Hurst coefficient and the fractal dimension in each measurement commune. The results showed that the accumulated patients (2020–2022), of the order of 400,000, belonged to the five communes (with a built area of approximately 300,000 m2 in recent years) that had the highest urban densification, which affected urban meteorology, favored the concentration of pollutants and made the SARS-Cov-2 pandemic more persistent. The “ideal” density of built housing should balance a pandemic and nullify its expansion.

This study examines the consequences of human activity on the atmospheric boundary layer considering (i) atmospheric pollution, (ii) urban micrometeorology, (iii) three geographic morphologies (mountain, basin and coast) and (iv) surface change of roughness due to buildings. Qualitative relationships are established between the four issues mentioned using measurements from different periods, urban meteorology and pollutants, in the boundary layer of the three geographic morphologies, all with large urban settlements. The measurements per hour and at ground level correspond to the variables: temperature, magnitude of wind speed, relative humidity and concentration of anthropogenic pollutants (PM10, PM2.5 and CO). The measurements form time series, demonstrating their chaoticity through the parameters: Lyapunov coefficient, correlation dimension, Hurst coefficient, Lempel–Ziv complexity, information loss, fractal dimension and correlation entropy. The results, according to each parameter, allow us to characterize the effect of human activity on geographical morphologies and its meteorology, showing a lower impact on mountain and coastal areas. Calculating, for each geographical configuration, the quotient between the total correlation entropy of the meteorological variables and that of the pollutants, the basin entropy is less than one, which shows, for the study period, the entropic domain of atmospheric pollutants unlike mountain and coast.

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.

The possibilities of micrometeorological resilience in urban contexts immersed in a basin geographical configuration are investigated. For this purpose, time series data with measurements of meteorological variables (temperature, magnitude of wind speed and relative humidity) and atmospheric pollutants (PM2.5, PM10, CO) are analyzed through chaos theory, calculating the coefficient of Lyapunov (λ), the correlation dimension (Dc), the Hurst coefficient (H), the correlation entropy (SK), the fractal dimension (D) and the Lempel–Ziv complexity (LZ). Indicators are built for each measurement period (2010–2013 and 2017–2020), for each locality studied and located at different heights. These indicators, which correspond to the quotient between the entropy resulting from the meteorological variables and that of the pollutants, show sensitivity to height. Another important indicator, for identical measurement conditions, arises from the calculation of the fractal dimensions of the meteorological variables and that of the pollutants, which allows for comparative studies between the two periods. These indicators are conclusive in pointing out that, in a large city with basin geographical characteristics, subjected to an intensive urbanization process, there is no micrometeorological resilience and a great variation occurs in the initial conditions.