Special Issue on COVID-19 Aerosol Drivers, Impacts and Mitigation (XIII)

Giovanni A. Salini This email address is being protected from spambots. You need JavaScript enabled to view it.1, Patricio R. Pacheco This email address is being protected from spambots. You need JavaScript enabled to view it.2, Eduardo Mera2, María C. Parodi3 

1 Departamento de Matemática y Física Aplicadas, Facultad de Ingeniería, Universidad Católica de la Santísima Concepción, Alonso de Ribera 2850, Concepción, Chile
2 Departamento de Física, Universidad Tecnológica Metropolitana, Las Palmeras 3360, Ñuñoa Santiago, Chile
3 Departamento de Industria, Facultad de Ingeniería, Universidad Tecnológica Metropolitana, José Pedro Alessandri 1242, Ñuñoa, Santiago, Chile


Received: July 23, 2020
Revised: December 9, 2020
Accepted: January 14, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.4209/aaqr.200434  

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Cite this article:

Salini, G.A., Pacheco, P.R., Mera, E., Parodi, M.C. (2021). Probable Relationship between COVID-19, Pollutants and Meteorology: A Case Study at Santiago, Chile. Aerosol Air Qual. Res. 21, 200434. https://doi.org/10.4209/aaqr.200434


HIGHLIGHTS 

  • Meteorology and pollutants can dissipate a pandemic by increasing its complexity.
  • Urban heat island, crowding and urban canyons favor the spread COVID-19 pandemic.
  • Low quality of life in urban settlements promotes spread of pandemics.
  • Air pollution gives sustainability to the accumulated growth of infected people.
  • Entropic link between air pollution and meteorology favors the pandemic spread. 
 

ABSTRACT


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 variables—temperature, 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. For all time-series, the Lempel-Ziv complexity turned out to be between 0 and 1 which is indicative of connectivity and chaos. The largest Lyapunov exponent as well as the Kolmogorov entropy were positive which also exhibits chaos. The Hurst exponent was found to be greater than 0.5 and less than 1 for all time-series, indicating positive long-term autocorrelation. Finally, the correlation dimension was less than 5, revealing that new time-series constructed are not random.


Keywords: Coronavirus, Air pollution, Entropy, Chaos, SARS-CoV-2



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