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 μ g/m 3 (return period: 25 yr) was observed in the northwestern region of the study area.
journal_name
Int J Environ Res Public Healthauthors
Aguirre-Salado AI,Vaquera-Huerta H,Aguirre-Salado CA,Reyes-Mora S,Olvera-Cervantes AD,Lancho-Romero GA,Soubervielle-Montalvo Cdoi
10.3390/ijerph14070734subject
Has Abstractpub_date
2017-07-06 00:00:00issue
7eissn
1661-7827issn
1660-4601pii
ijerph14070734journal_volume
14pub_type
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