Geostatistical space-time simulation model for air quality prediction

In recent decades there has been a growing interest in modelling and simulating natural phenomena, in environmental sciences, motivated by the large amount of data from monitoring activities and by the necessity of answering important environmental problems. Most natural phenomena can be seen as a space–time process, and space–time modelling has recently become an active area of research. However, and probably because these space–time relationships have usually quite different characteristics and levels of uncertainty, the simultaneous integration of space and time has not been easy, and further developments are clearly required. The main goal of this study is to present a simulation model for the characterization of space–time dispersion of air pollutants. A space–time methodology, based on the simultaneous integration of space and time air pollutant dispersion characteristics, is applied to assess the particle contamination of the Setúbal Peninsula (South of Lisbon, Portugal)—a study that is part of a project for the evaluation of regional air quality risk maps and air quality control and management.