The theory of dispersion models straddles both statistics and probability, and involves an encyclopedic collection of tools, such as exponential families, asymptotic theory, stochastic processes, Tauber theory, infinite divisibility, and stable distributions. The Theory of Dispersion Models introduces the reader to these models, which serve as error distributions for generalized linear models, and looks at their applications within this context.

A single reference to all aspects of contemporary air dispersion modeling The practice of air dispersion modeling has changed dramatically in recent years, in large part due to new EPA regulations. Current with the EPA's 40 CFR Part 51, this book serves as a complete reference to both the science and contemporary practice of air dispersion modeling. Throughout the book, author Alex De Visscher guides readers through complex calculations, equation by equation, helping them understand precisely how air dispersion models work, including such popular models as the EPA's AERMOD and CALPUFF. Air Dispersion Modeling begins with a primer that enables readers to quickly grasp basic principles by developing their own air dispersion model. Next, the book offers everything readers need to work with air dispersion models and accurately interpret their results, including: Full chapter dedicated to the meteorological basis of air dispersion Examples throughout the book illustrating how theory translates into practice Extensive discussions of Gaussian, Lagrangian, and Eulerian air dispersion modeling Detailed descriptions of the AERMOD and CALPUFF model formulations This book also includes access to a website with Microsoft Excel and MATLAB files that contain examples of air dispersion model calculations. Readers can work with these examples to perform their own calculations. With its comprehensive and up-to-date coverage, Air Dispersion Modeling is recommended for environmental engineers and meteorologists who need to perform and evaluate environmental impact assessments. The book's many examples and step-by-step instructions also make it ideal as a textbook for students in the fields of environmental engineering, meteorology, chemical engineering, and environmental sciences.

To comply with legal and other standards, businesses and regulators are increasingly required to make decisions based on risk assessments of the potential effects of their activities on the environment. Atmospheric dispersion modelling is a cost-effective method, allowing various scenarios to be explored before expensive investment takes place. This guide offers advice on this environmental management tool. Unlike much of the previous literature, it doesn't focus excessively on the mathematical theory behind the modelling or on modelling for specific regulatory purposes. Instead, it offers an understanding of the background to the methodologies, providing exercises to develop the skills to carry these out and including examples of the use of commercially available models to enable the reader to assess the results of modelling for risk assessment.

Proceedings of the Twenty-Second NATO/CCMS International Technical Meeting held in Clermont-Ferrand, France, June 2-6, 1997

This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.

Finishing this book is giving me a mixture of relief, satisfaction and frus tration. Relief, for the completion of a project that has taken too many of my evenings and weekends and that, in the last several months, has become almost an obsession. Satisfaction, for the optimistic feeling that this book, in spite of its many shortcomings and imbalances, will be of some help to the air pollution scientific community. Frustration, for the impossibility of incorporating newly available material that would require another major review of several key chap ters - an effort that is currently beyond my energies but not beyond my desires. The first canovaccio of this book came out in 1980 when I was invited by Computational Mechanics in the United Kingdom to give my first Air Pollution Modeling course. The course material, in the form of transparencies, expanded, year after year, thus providing a growing working basis. In 1985, the ECC Joint Research Center in Ispra, Italy, asked me to prepare a critical survey of mathe matical models of atmospheric pollution, transport and deposition. This support gave me the opportunity to prepare a sort of "first draft" of the book, which I expanded in the following years.

First published by Wiley in 1978, this book is being re-issued with a new Preface by the author. The roots of the book lie in the writings of RA Fisher both as concerns results and the general stance to statistical science, and this stance was the determining factor in the author's selection of topics. His treatise brings together results on aspects of statistical information, notably concerning likelihood functions, plausibility functions, ancillarity, and sufficiency, and on exponential families of probability distributions.