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- W2726890089 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." @default.
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- W2726890089 date "2017-07-06" @default.
- W2726890089 modified "2023-10-14" @default.
- W2726890089 title "Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area" @default.
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- W2726890089 doi "https://doi.org/10.3390/ijerph14070734" @default.
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