%0 Book Section %1 statphys23_0914 %A Diosdado, A. Munoz %A Coyt, G. Galvez %A Cruz, H. Reyes %A Hernandez, D. Bueno %A Correa, J.L. Del Rio %B Abstract Book of the XXIII IUPAP International Conference on Statistical Physics %C Genova, Italy %D 2007 %E Pietronero, Luciano %E Loreto, Vittorio %E Zapperi, Stefano %K analysis atmospheric detrended dynamics fluctuation multifractals nonlinear pollutants statphys23 topic-11 %T Nonlinear analysis of time series of atmospheric pollutants in Mexico City %U http://st23.statphys23.org/webservices/abstract/preview_pop.php?ID_PAPER=914 %X Atmospheric pollution is an important problem in the metropolitan area of Mexico City. Concentrations of ozone, sulfur dioxide, carbon monoxide, nitrogen dioxide and PM10 particles (particles smaller than 10 micrometers) have been measured in approximately thirty monitoring stations in different places of the city since 1986, although the data before 1990 are not very confident. Each hour a concentration measure is measured. In this work we have analyzed with nonlinear dynamics techniques the concentration time series of atmospheric pollutants since 1990 to 2005. We have used detrended fluctuation analysis (DFA) and the Higuchi's algorithm in order to characterize the correlations in these time series. We have found that there are long-large correlations in the time series of ozone, sulfur dioxide, carbon monoxide, nitrogen dioxide and PM10 particles. However, there are significant differences between the correlational dynamics of each pollutant; we have found greater correlations in the time series of PM10 and ozone. We have concluded that the permanence time of PM10 and ozone is greater than the permanence time of sulfur dioxide, carbon monoxide and nitrogen dioxide. We have also studied the annual variation of the correlation exponents and we have obtained that there is a qualitative correlation between the values of the correlation exponents and the concentration values of the pollutants. In order of better characterize the nonlinear properties of the time series of these complex systems; we analyzed the time series by using the Chhabra and Jensen multifractal formalism. All the time series (annual and total) are multifractal, however, the multifractality degree (the width of the multifractal spectrum) is different for each pollutant. The degree of multifractality has been associated with the complexity of the time series, in these sense we have encountered that time series of sulfur dioxide are more complex than time series of other pollutants. Although the width of the multifractal spectrum is not a measure of the concentration levels, when we analyzed the plots of the spectrum width of the annual time series versus the year, the greater values of the width coincide with the greater values of concentration of the atmospheric pollutants.

@incollection{statphys23_0914, abstract = {Atmospheric pollution is an important problem in the metropolitan area of Mexico City. Concentrations of ozone, sulfur dioxide, carbon monoxide, nitrogen dioxide and PM10 particles (particles smaller than 10 micrometers) have been measured in approximately thirty monitoring stations in different places of the city since 1986, although the data before 1990 are not very confident. Each hour a concentration measure is measured. In this work we have analyzed with nonlinear dynamics techniques the concentration time series of atmospheric pollutants since 1990 to 2005. We have used detrended fluctuation analysis (DFA) and the Higuchi's algorithm in order to characterize the correlations in these time series. We have found that there are long-large correlations in the time series of ozone, sulfur dioxide, carbon monoxide, nitrogen dioxide and PM10 particles. However, there are significant differences between the correlational dynamics of each pollutant; we have found greater correlations in the time series of PM10 and ozone. We have concluded that the permanence time of PM10 and ozone is greater than the permanence time of sulfur dioxide, carbon monoxide and nitrogen dioxide. We have also studied the annual variation of the correlation exponents and we have obtained that there is a qualitative correlation between the values of the correlation exponents and the concentration values of the pollutants. In order of better characterize the nonlinear properties of the time series of these complex systems; we analyzed the time series by using the Chhabra and Jensen multifractal formalism. All the time series (annual and total) are multifractal, however, the multifractality degree (the width of the multifractal spectrum) is different for each pollutant. The degree of multifractality has been associated with the complexity of the time series, in these sense we have encountered that time series of sulfur dioxide are more complex than time series of other pollutants. Although the width of the multifractal spectrum is not a measure of the concentration levels, when we analyzed the plots of the spectrum width of the annual time series versus the year, the greater values of the width coincide with the greater values of concentration of the atmospheric pollutants.}, added-at = {2007-06-20T10:16:09.000+0200}, address = {Genova, Italy}, author = {Diosdado, A. Munoz and Coyt, G. Galvez and Cruz, H. Reyes and Hernandez, D. Bueno and Correa, J.L. Del Rio}, biburl = {https://www.bibsonomy.org/bibtex/25f7f2e450c532cf709eb7830573d5cff/statphys23}, booktitle = {Abstract Book of the XXIII IUPAP International Conference on Statistical Physics}, editor = {Pietronero, Luciano and Loreto, Vittorio and Zapperi, Stefano}, interhash = {8922b33f29f9b05fd4c5b652861ce7bd}, intrahash = {5f7f2e450c532cf709eb7830573d5cff}, keywords = {analysis atmospheric detrended dynamics fluctuation multifractals nonlinear pollutants statphys23 topic-11}, month = {9-13 July}, timestamp = {2007-06-20T10:16:34.000+0200}, title = {Nonlinear analysis of time series of atmospheric pollutants in Mexico City}, url = {http://st23.statphys23.org/webservices/abstract/preview_pop.php?ID_PAPER=914}, year = 2007 }