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Computational and Numerical Challenges in Environmental Modeling
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  • Computational and Numerical Challenges in Environmental Modeling
ID: 171413
Zahari Zlatev, Ivan Dimov
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Many large mathematical models, are described by systems of partial differential equations. The discretization of the large differential equations. These systems contain many millions of equations. Furthermore, many scenarios are as a rule to be run. This is the situation that is enormous. Therefore, it is necessary to select fast numerical methods; to develop parallel codes and what is the most important problem in a proper way.

The last item (which is very often underestimated but, let us re-iterate, which is very important) is a major topic of this book. In fact, the proper organization of different numerical methods and different parallel devices. The development of such templates is described in the book. It is also a highly-qualified project that is perfectly organized. Thus, this book will help the reader to understand better, while it is very important to select the fast numerical methods as well as are really very large. In the latter case, it is also crucial to exploit the computing process.

- Use of templates in connection with the treatment of very large models
- Performance of comprehensive environmental studies
- Obtaining reliable and robust information about pollution levels
- Studying the impact of future climatic changes on high pollution levels
- Investigating events related to critical levels of pollution

Preface
acknowledgments
Contents
1. PDE systems emerging in air pollution modeling and the need for high speed computers
2. Using splitting techniques in the treatment of air pollution models
3. Treatment of the advection-diffusion phenomena
4. Treatment of the chemical part: general ideas and major numerical methods
5. Error analysis of the partitioning procedures
6. Efficient organization of the matrix computations
7. Parallel computations
8. Studying high pollution levels
9. Impact of future climate changes on high pollution levels
10. Implementation of variational data assimilation
11. Discussion of some open questions
Appendix A: Color plots
Bibliography
Table symbol
Author Index
Subject Index
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