Abstract

Using chaos theory, maximum entropies are calculated for 108 time series, each consisting of 28,463 hourly data of urban meteorology and pollutants. The series were measured with standardized and certified instruments (EPA) in six locations at different heights and in three periods (2010/2013, 2017/2020, and 2019/2022) in a basin geomorphology. Each urban meteorology series corresponds to relative humidity (RH), temperature (T), and wind speed magnitude (WS), and each pollutant series corresponds to 10 mu m particulate matter (PM10), 2.5 mu m particulate matter (PM2.5), and carbon monoxide (CO). These pollutants are in the top three places of presence in the studied geomorphology and in incidence in population diseases. From the calculated entropies, a quotient is constructed between the entropies of each of the first two urban meteorology variables (RH and T) and the sum of maximum entropies of the time series of anthropogenic pollutants, demonstrating the gradual decay in time of the quotient that is dominated by the maximum entropies of the pollutants. The latter leads to a more excited and warm boundary layer, due to thermal transfers, which makes it more unpredictable, increasing its capacity to contain water. It is verified that the diffusion is anomalous with alpha < 1 and that the contamination has a high probability, using a heavy-tailed probability function, of causing extreme events by influencing urban meteorology.