Spatio-Temporal Analysis of Mexico City Ozone Levels

Gabriel Huerta
University of New Mexico

We consider hourly readings of ozone concentrations over Mexico City and propose a statistical model for spatial as well as temporal interpolation and prediction. The model is based on regressing the observed readings on a meteorological variable, such as temperature. A few harmonic components are added to account for the main periodicities that ozone presents during a given day and that are not explained through a single covariate. The model incorporates spatial covariance structure for the observations and the parameters that define the harmonic components. Additionally, we propose a new approach for space-time modeling of extreme values that are measured in time and space. We assume that the observations follow a Generalized Extreme Value (GEV) distribution for which the location parameter defines the space-time structure. We show how to produce temporal and spatial estimates of our models via customized Markov Chain Monte Carlo (MCMC) simulation.

*Joint work with Bruno Sanso, University of California, Santa Cruz and Jonathan R. Stroud, University of Pennsylvania .