title: Modeling environmental noise exceedances using non-homogeneous Poisson processes.
abstract: In this work a non-homogeneous Poisson model is considered to study noise exposure. The Poisson process, counting the number of times that a sound level surpasses a threshold, is used to estimate the probability that a population is exposed to high levels of noise a certain number of times in a given time interval. The rate function of the Poisson process is assumed to be of a Weibull type. The presented model is applied to community noise data from Messina, Sicily (Italy). Four sets of data are used to estimate the parameters involved in the model. After the estimation and tuning are made, a way of estimating the probability that an environmental noise threshold is exceeded a certain number of times in a given time interval is presented. This estimation can be very useful in the study of noise exposure of a population and also to predict, given the current behavior of the data, the probability of occurrence of high levels of noise in the near future. One of the most important features of the model is that it implicitly takes into account different noise sources, which need to be treated separately when using usual models.
authors.affiliation: Department of Industrial Engineering, University of Salerno, Salerno, Italy.
authors.forename: Claudio
authors.initials: C
authors.lastname: Guarnaccia
authors.affiliation: Department of Industrial Engineering, University of Salerno, Salerno, Italy.
authors.forename: Joseph
authors.initials: J
authors.lastname: Quartieri
authors.affiliation: Facultad de Ciencias, Universidad Nacional Autónoma de México, 04510 Ciudad de México, Federal District, Mexico.
authors.forename: Juan M
authors.initials: JM
authors.lastname: Barrios
authors.affiliation: Instituto de Matemáticas, Universidad Nacional Autónoma de México, 04510 Ciudad de México, Federal District, Mexico.
authors.forename: Eliane R
authors.initials: ER
authors.lastname: Rodrigues