Abstract
Air-quality monitoring and analysis are initial parts of a comprehensive strategy to prevent air pollution in cities. In such a context, statistical tools play an important role in determining the time-series trends, locating areas with high pollutant concentrations, and building predictive models. In this work, we analyzed the spatio-temporal behavior of the pollutant PM10 in the Monterrey Metropolitan Area (MMA), Mexico during the period 2010–2018 by applying statistical analysis to the time series of seven environmental stations. First, we used experimental variograms and scientific visualization to determine the general trends and variability in time. Then, fractal exponents (the Hurst rescaled range and Higuchi algorithm) were used to analyze the long-term dependence of the time series and characterize the study area by correlating that dependence with the geographical parameters of each environmental station. The results suggest a linear decrease in PM10 concentration, which showed an annual cyclicity. The autumn-winter period was the most polluted and the spring-summer period was the least. Furthermore, it was found that the highest average concentrations are located in the western and high-altitude zones of the MMA, and that average concentration is related in a quadratic way to the Hurst and Higuchi exponents, which in turn are related to some geographic parameters. Therefore, in addition to the results for the MMA, the present paper shows three practical statistical methods for analyzing the spatio-temporal behavior of air quality.
Highlights
Since ancient times, the behavior of the different variables that interact in the atmosphere has drawn the attention of human beings, as these variables set the guidelines for the conditions of the environment in which daily activities are carried out
The time series corresponding to the parenthetical remarks (a) to (f), is compared with the time series corresponding to the Northwest2 station, because this environmental station differs from the others in some aspects
Seven time series of the air pollutant PM10 taken from environmental monitoring stations located in the Monterrey Metropolitan Area (MMA), Mexico, were analyzed, with the following results obtained:
Summary
The behavior of the different variables that interact in the atmosphere has drawn the attention of human beings, as these variables set the guidelines for the conditions of the environment in which daily activities are carried out. The study of pollutant behavior has become an important and relevant topic in a society that aspires to improve quality of life. Air pollution is defined as the presence of one or more chemical substances in the air at high concentrations that can damage human beings, animals, vegetation, and even materials [1,2,3,4]. The Norma Oficial Mexicana NOM-025-SSA1-2014 [5] describes PM as a mix of substances in a solid or liquid state that remains suspended in the atmosphere. To better study it, this material is classified into two groups according to its aerodynamic behavior— PM2.5 and PM10, which are less than 2.5 μm and 10 μm, respectively [4,6,7,8]
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