Contaminación del aire en Puerto Vallarta, México

Hernández, Julio César Morales; López, Ana Lexie Montes; Martínez, Óscar Frausto; Romero, Bartolo Cruz; Mercado, Cynthia Lizeth González; González, Fátima Maciel Carrillo

doi:10.15446/bitacora.v31n2.87800

Cited by 1 publication

(1 citation statement)

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“…Regarding standards and other studies undertaken in Mexico, air pollution has been considered a serious and complex issue in this country since the 1970s, which has resulted in the design new techniques to study this phenomenon [31][32][33]. Among these researches, Audelo-Vucovich et al [34] stand out, having used the Hurst exponent and other tools to determine the persistence of PM 10 concentrations and their correlation with environmental pre-contingency, observing that the probability of reaching a pre-contingency event increases when Hrs > 0.3.…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis of PM10 Concentration in the Monterrey Metropolitan Area, Mexico (2010–2018)

et al. 2022

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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 [d=R1]time-series trendstrend of time series, locating areas with high [d=R1]pollutant concentrationsconcentration of pollutants, 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. [d=R1]First, weWe 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[d=R1]. The, with the autumn-winter period [d=R1]wasas the most polluted and the spring-summer period [d=R1]wasas 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, [d=R1]in additionadditionally to the results for the MMA, the present paper shows three [d=R1]practicaluseful statistical methods for analyzing the spatio-temporal behavior of air quality.

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Section: Introductionmentioning

confidence: 99%