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Statistical persistence of air pollutants (O3,SO2,NO2 and PM10) in Mexico City

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  • Meraz, M.
  • Rodriguez, E.
  • Femat, R.
  • Echeverria, J.C.
  • Alvarez-Ramirez, J.

Abstract

The rescaled range (R/S) analysis was used for analyzing the statistical persistence of air pollutants in Mexico City. The air-pollution time series consisted of hourly observations of ozone, nitrogen dioxide, sulfur dioxide and particulate matter obtained at the Mexico City downtown monitoring station during 1999–2014. The results showed that long-range persistence is not a uniform property over a wide range of time scales, from days to months. In fact, although the air pollutant concentrations exhibit an average persistent behavior, environmental (e.g., daily and yearly) and socio-economic (e.g., daily and weekly) cycles are reflected in the dependence of the persistence strength as quantified in terms of the Hurst exponent. It was also found that the Hurst exponent exhibits time variations, with the ozone and nitrate oxide concentrations presenting some regularity, such as annual cycles. The persistence dynamics of the pollutant concentrations increased during the rainy season and decreased during the dry season. The time and scale dependences of the persistence properties provide some insights in the mechanisms involved in the internal dynamics of the Mexico City atmosphere for accumulating and dissipating dangerous air pollutants. While in the short-term individual pollutants dynamics seems to be governed by specific mechanisms, in the long-term (for monthly and higher scales) meteorological and seasonal mechanisms involved in atmospheric recirculation seem to dominate the dynamics of all air pollutant concentrations.

Suggested Citation

  • Meraz, M. & Rodriguez, E. & Femat, R. & Echeverria, J.C. & Alvarez-Ramirez, J., 2015. "Statistical persistence of air pollutants (O3,SO2,NO2 and PM10) in Mexico City," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 202-217.
  • Handle: RePEc:eee:phsmap:v:427:y:2015:i:c:p:202-217
    DOI: 10.1016/j.physa.2015.02.009
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    References listed on IDEAS

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    1. Valdés-Parada, Francisco J. & Varela, Juan R. & Alvarez-Ramirez, José, 2012. "Upscaling pollutant dispersion in the Mexico City Metropolitan Area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 606-615.
    2. Tabak, Benjamin M. & Cajueiro, Daniel O., 2007. "Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility," Energy Economics, Elsevier, vol. 29(1), pages 28-36, January.
    3. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    4. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo & Fernandez-Anaya, Guillermo, 2008. "Time-varying Hurst exponent for US stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6159-6169.
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    Cited by:

    1. Amato, Federico & Laib, Mohamed & Guignard, Fabian & Kanevski, Mikhail, 2020. "Analysis of air pollution time series using complexity-invariant distance and information measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    2. Anderson Palmeira & Éder Pereira & Paulo Ferreira & Luisa Maria Diele-Viegas & Davidson Martins Moreira, 2022. "Long-Term Correlations and Cross-Correlations in Meteorological Variables and Air Pollution in a Coastal Urban Region," Sustainability, MDPI, vol. 14(21), pages 1-12, November.
    3. Gajardo, Gabriel & Kristjanpoller, Werner, 2017. "Asymmetric multifractal cross-correlations and time varying features between Latin-American stock market indices and crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 121-128.
    4. Luis Alberiko Gil-Alaña & Carlos Pestana Barros & Zhongfei Chen, 2016. "The persistence of air pollution in four mega-cities of China," NCID Working Papers 04/2016, Navarra Center for International Development, University of Navarra.
    5. Meraz, M. & Alvarez-Ramirez, J. & Echeverria, J.C., 2017. "Asymmetric correlations in the ozone concentration dynamics of the Mexico City Metropolitan Area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 377-386.
    6. Cárdenas-Moreno, P.R. & Moreno-Torres, L.R. & Lovallo, M. & Telesca, L. & Ramírez-Rojas, A., 2021. "Spectral, multifractal and informational analysis of PM10 time series measured in Mexico City Metropolitan Area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).

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