Developing a Hierarchical Model for the Spatial Analysis of PM 10 Pollution Extremes in the Mexico City Metropolitan Area

Alejandro Ivan Aguirre-Salado, Humberto Vaquera-Huerta, Carlos Arturo Aguirre-Salado, Silvia Reyes-Mora, Ana Delia Olvera-Cervantes, Guillermo Arturo Lancho-Romero and Carlos Soubervielle-Montalvo
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Alejandro Ivan Aguirre-Salado: Department of Physics and Mathematics, Universidad Tecnológica de la Mixteca, 69000 Huajuapan de León, Oax., Mexico
Humberto Vaquera-Huerta: Department of Statistics, Colegio de Postgraduados, Campus Montecillo, Texcoco, 56230 Montecillo, Mex., Mexico
Carlos Arturo Aguirre-Salado: Faculty of Engineering, Universidad Autónoma de San Luis Potosí, 78280 San Luis Potosí, S.L.P., Mexico
Silvia Reyes-Mora: Department of Physics and Mathematics, Universidad Tecnológica de la Mixteca, 69000 Huajuapan de León, Oax., Mexico
Ana Delia Olvera-Cervantes: Department of Physics and Mathematics, Universidad Tecnológica de la Mixteca, 69000 Huajuapan de León, Oax., Mexico
Guillermo Arturo Lancho-Romero: Department of Physics and Mathematics, Universidad Tecnológica de la Mixteca, 69000 Huajuapan de León, Oax., Mexico
Carlos Soubervielle-Montalvo: Faculty of Engineering, Universidad Autónoma de San Luis Potosí, 78280 San Luis Potosí, S.L.P., Mexico

IJERPH, 2017, vol. 14, issue 7, 1-15

Abstract: We implemented a spatial model for analysing PM 10 maxima across the Mexico City metropolitan area during the period 1995–2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV) distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM 10 maxima in space and time. We evaluated the statistical model’s performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM 10 maxima and the longitude and latitude. The relationship between time and the PM 10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM 10 maxima presenting levels above 1000 ? g/m 3 (return period: 25 yr) was observed in the northwestern region of the study area.

Keywords: air pollution; particulate matter; extreme value theory; Markov Chain Monte Carlo (MCMC); nonstationary (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:14:y:2017:i:7:p:734-:d:103882

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