Estimating the number of ozone peaks in Mexico City using a non-homogeneous Poisson model

In this paper, we consider the problem of estimating the number of times an air quality standard is exceeded in a given period of time. A non-homogeneous Poisson model is proposed to analyse this issue. The rate at which the Poisson events occur is given by a rate function lambda(t), t >= 0. This rate function also depends on some parameters that need to be estimated. Two forms of lambda(t), t >= 0 are considered. One of them is of the Weibull form and the other is of the exponentiated-Weibull form. The parameters estimation is made using a Bayesian formulation based on the Gibbs sampling algorithm. The assignation of the prior distributions for the parameters is made in two stages. In the first stage, non-informative prior distributions are considered. Using the information provided by the first stage, more informative prior distributions are used in the second one. The theoretical development is applied to data provided by the monitoring network of Mexico City. The rate function that best fit the data varies according to the region of the city and/or threshold that is considered. In some cases the best fit is the Weibull form and in other cases the best option is the exponentiated-Weibull. Copyright (C) 2007 John Wiley & Sons, Ltd.

Bathymetric distribution of the shrimp Rimapenaeus constrictus (Stimpson, 1874) (Decapoda, Penaeidae) in two locations off the southeastern Brazilian coast

The distribution of benthic organisms is directly or indirectly associated with the physical and chemical properties of the water and sediment. This study analysed the spatial and temporal distribution of Rimapenaeus constrictus in unconsolidated sublittoral sediments of two areas off the northern coast of the state of Sao Paulo, Brazil. We also analysed the association of environmental factors with the occurrence of this species. Shrimp were collected monthly from July 2001 to June 2003, with a fishing boat equipped with two double-rig nets, in the regions of Ubatuba (UBA) and Caraguatatuba (CA). The collections were made during the day, along five transects with mean depths of 5, 10, 15, 20, 25, 30, and 35 m. We obtained a total of 5478 individuals, 3403 (UBA = 2025 and CA = 1378) during the first year, and 2075 (UBA = 875 and CA = 1200) during the second year. Significant differences in abundance were observed in relation to depth, season of the year, and also in the interaction between region and depth. Higher abundances occurred in fall and winter, independently of the sampling year. The largest numbers of shrimp were caught on the 20-m transect in UBA and the 25-m transect in CA. It is concluded that the distribution pattern of this species is closely related to environmental factors, and the temperature of the bottom water and the sediment texture were the most significant variables affecting the distribution.

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.