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 Setúbal 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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References
Armstrong, M., Chetboun, G., Hubbert P., 1993, Kriging the rainfall in Lesotho, in A. Soares, ed., Geotatistics Tróia’92, Vol. 2: Kluwer Academic Publ., Dordrecht, p. 661–672.
Bilonick, R. A., 1985, The space-time distribution of sulfate deposition in the northeastern United States: Atmosph. Environment, v. 19, no. 11, p.1829–1845.
Bras, R.L., and Rodrigues-Iturbe, I, 1984, Randon Functions and hydrology: Addison-Wesley, Reading, MA, 559 p.
Eynon, B. P., and Switzer, P., 1983, The variability of rainfall acidity: Can. Jour. Statistics, V. 11, no. 1, p. 11–24.
Hohn, M.E., Liebhold, A. M., and Gribko, L.S., 1993, Geostatistical model for forecasting spatial dynamics of defoliation caused by the gypsy moth (Lepidoptera: Lymantriidae): Environmental Entomology, v. 22, no. 5, p.1066–1075.
Kyriakidis, P. C. and Journel, A. J., 1999 a), Stochastic Modeling of spatiotemporal distributions: Application to sulphate deposition trends over Europe, in J. Gomez-Hernandez, A. Soares, and R. Froidevaux ed., geoENV II— geostatistics for environmental Applications,: Kluwer Academic Publ., Dordrecht, p. 89–100.
Kyriakidis, P. C. and Journel, A. J., 1999 b), Geostatistical Space-Time models: A review, Mathematical Geology, Vol.31, no. 6.
Journel A., 1994, Modeling uncertainty: some conceptual thoughts, in Dimitrakopoulos, R., ed., Geostatistics for the next century: Kluwer Academic Pub., Dordrecht, The Netherlands, p.30–43.
Nunes C., Soares A. and Ferreira F., 1999, Evaluation of Environmental costs of SO2 emissions using Stochastic Images, in J. Gomez-Hernandez, A. Soares, and R. Froidevaux ed., geoENV II— geostatistics for environmental Applications,: Kluwer Academic Publ., Dordrecht, p. 113–124.
Nunes C. And Soares A, Geostatistical Space-Time Simulation Model, paper submitted to Environmetrics, 2002.
Rouhani, S., and Wackernagel, H., 1990, Multivariate geostatistical approach to space-time data analysis: water resources Res., V. 26, no 4, p. 585–591.
Santos E., Almeida J., Soares A., 2000, Geostatistical Characterisation of the migration Patterns and Pathways of the Wood Pigeon in Portugal, Geostatistics 2000, W.J. Kleingeld, D.G. Krige Ed., vol.2, P. 615–622.
Soares A., 2001, “Direct Sequential Simulation and Co-Simulation”, Mathematical Geology, Vol. 33, no.8, Pg. 911–926.
Soares, A., Patinha, P. J., and Pereira, M.J., 1996, Stochastic simulation on space-times series: Application to a river water quality modeling, in Srivastava, R.M., Rouhani, S., Cromer, M. V., Johnson, A.I., and Desbarats, a. J., eds., Geostatistics for Environmental and Geotechnical Applications: American society for Testing and Materials, west Conshohocken, Pa, p.146–161.
Solow, A. R., and Gorelick, S. M., 1986, Estimating monthly stream flow values by cokriging: Math. Geology, v. 18, no. 8, p.785–809.
Switzer, P., 1979, Statistical considerations in network design, Water Resources Res., v. 15, no. 6, p.109–123.
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Nunes, C., Soares, A. (2004). Geostatistical Space-Time Simulation Model for Characterization of Air Quality. In: Sanchez-Vila, X., Carrera, J., Gómez-Hernández, J.J. (eds) geoENV IV — Geostatistics for Environmental Applications. Quantitative Geology and Geostatistics, vol 13. Springer, Dordrecht. https://doi.org/10.1007/1-4020-2115-1_9
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DOI: https://doi.org/10.1007/1-4020-2115-1_9
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