Abstract
The characterization of spatial uncertainty has been addressed in earth sciences using spatial models, based on stochastic simulation algorithms. Dynamic processes are characterized by two components — space and time. These usually have quite different levels of uncertainty: on the one hand, the heterogeneity of the static component — normally related to the space — can sometimes not be compared with the complexity of the dynamic part of the process; on the other hand, the available knowledge is usually quite different for these two components. This is possibly the main reason why the development of simulation algorithms for spatial processes with a time component is still at an early stage. The main goal of this study is to present a simulation model for the characterization of space-time dispersion of air pollutants. The objective of this model is to predict critical scenarios to support air quality control and management. This space-time simulation approach is applied to assess the particles contamination of Setubal Peninsula (South of Lisbon — Portugal); a study, that is part of a project for the evaluation of regional air quality risk maps.
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