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Highlights the successful use of both statistics and mathematics in important practical problems and presents practical methods for quantitative measurement and prediction. It is organised around four themes: spatial and temporal models and methods; environmental sampling and standards; atmosphere and ocean; and risk and uncertainty.
Preface.- Part I. Spatial and Temporal Models and Methods: Modeling Spatio-Temporally Misaligned Areal and Point Process Environmental Data. Space and Space-Time Modeling Using Process Convolutions. Multivariate Kriging for Interpolating Data from Different Sources.- Part II. Environmental Sampling and Standards: Distance Sampling: Recent Advances and Future Directions. Setting Environmental Standards: A Statistical Approach.- Part III. Atmosphere and Ocean: The Interpretation and Validation of Measurements of the Ocean Wave Directional Spectrum. Thermal Energy Emission and Propagation from Accidents. Development and Application of an Extended Methodology to Validate Short-Range Atmospheric Dispersion Models. Uncertainty and Sensitivity of Dispersion Model Results to Meteorological Inputs: Two Case Studies.- Part IV. Risk and Uncertainty: Statistics and the Environmental Sciences: Approaches to Model Combination. Bayesian Analysis of Computer Code Outputs. The Realities of Decision Making on Risks.