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This book is for all graduate students who are specializing in any environmental issue and who wish to grasp the fundamentals of physics that are required in various fields of science and engineering. The book provides the structural concept of the system state equation and its dynamics, which can be applicable to numerical solutions in several important areas such as heat and mass transfer and fluid dynamics. As a first step, there is a description of how to solve a linear system by conducting an analysis of temperature distribution in an infinite soil as a practical example. This exercise helps readers to fully understand what time and space discretizations are, and how actual numerical solutions should work. Because the concept of the system state equation relies on a vector–matrix form, the book shows how that particular form is applicable to other practical procedures: linear multi regression analysis, the least square method, and others. The book also gives the solution to non-linear dynamical systems and their applications. Although this book may appear to take an unusual approach, the author believes it will be inspiring and greatly helpful for the beginner who seeks a solid understanding of the basis of mathematics and physics for any environmental problems.
A primer on modeling concepts and applications that is specifically geared toward the environmental field. Sections on modeling terminology, the uses of models, the model-building process, and the interpretation of output provide the foundation for detailed applications. After an introduction to the basics of dynamic modeling, the book leads students through an analysis of several environmental problems, including surface-water pollution, matter-cycling disruptions, and global warming. The scientific and technical context is provided for each problem, and the methods for analyzing and designing appropriate modeling approaches is provided. While the mathematical content does not exceed the level of a first-semester calculus course, the book gives students all of the background, examples, and practice exercises needed both to use and understand environmental modeling. It is suitable for upper-level undergraduate and beginning-graduate level environmental professionals seeking an introduction to modeling in their field.
This book presents an overview of modeling and simulation of environmental systems via diverse research problems and pertinent case studies. It is divided into four parts covering sustainable water resources modeling, air pollution modeling, Internet of Things (IoT) based applications in environmental systems, and future algorithms and conceptual frameworks in environmental systems. Each of the chapters demonstrate how the models, indicators, and ecological processes could be applied directly in the environmental sub-disciplines. It includes range of concepts and case studies focusing on a holistic management approach at the global level for environmental practitioners. Features: Covers computational approaches as applied to problems of air and water pollution domain. Delivers generic methods of modeling with spatio-temporal analyses using soft computation and programming paradigms. Includes theoretical aspects of environmental processes with their complexity and programmable mathematical approaches. Adopts a realistic approach involving formulas, algorithms, and techniques to establish mathematical models/computations. Provides a pathway for real-time implementation of complex modeling problem formulations including case studies. This book is aimed at researchers, professionals and graduate students in Environmental Engineering, Computational Engineering/Computer Science, Modeling/Simulation, Environmental Management, Environmental Modeling and Operations Research.
Mathematical Models in Environmental Problems
Using a systems analysis approach and extensive case studies, Environmental Remote Sensing and Systems Analysis shows how remote sensing can be used to support environmental decision making. It presents a multidisciplinary framework and the latest remote sensing tools to understand environmental impacts, management complexity, and policy implicatio
New statements of problems arose recently demanding thorough ana lysis. Notice, first of all, the statements of problems using adjoint equations which gradually became part of our life. Adjoint equations are capable to bring fresh ideas to various problems of new technology based on linear and nonlinear processes. They became part of golden fund of science through quantum mechanics, theory of nuclear reactors, optimal control, and finally helped in solving many problems on the basis of perturbation method and sensitivity theory. To emphasize the important role of adjoint problems in science one should mention four-dimensional analysis problem and solution of inverse problems. This range of problems includes first of all problems of global climate changes on our planet, state of environment and protection of environ ment against pollution, preservation of the biosphere in conditions of vigorous growth of population, intensive development of industry, and many others. All this required complex study of large systems: interac tion between the atmosphere and oceans and continents in the theory of climate, cenoses in the biosphere affected by pollution of natural and anthropogenic origin. Problems of local and global perturbations and models sensitivity to input data join into common complex system.
Can we coexist with the other life forms that have evolved on this planet? Are there realistic alternatives to fossil fuels that would sustainably provide for human society's energy needs and have fewer harmful effects? How do we deal with threats such as emergent diseases? Mathematical models—equations of various sorts capturing relationships between variables involved in a complex situation—are fundamental for understanding the potential consequences of choices we make. Extracting insights from the vast amounts of data we are able to collect requires analysis methods and statistical reasoning. This book on elementary topics in mathematical modeling and data analysis is intended for an undergraduate “liberal arts mathematics”-type course but with a specific focus on environmental applications. It is suitable for introductory courses with no prerequisites beyond high school mathematics. A great variety of exercises extends the discussions of the main text to new situations and/or introduces new real-world examples. Every chapter ends with a section of problems, as well as with an extended chapter project which often involves substantial computing work either in spreadsheet software or in the R statistical package.
The problems of interrelation between human economics and natural environment include scientific, technical, economic, demographic, social, political and other aspects that are studied by scientists of many specialities. One of the important aspects in scientific study of environmental and ecological problems is the development of mathematical and computer tools for rational management of economics and environment. This book introduces a wide range of mathematical models in economics, ecology and environmental sciences to a general mathematical audience with no in-depth experience in this specific area. Areas covered are: controlled economic growth and technological development, world dynamics, environmental impact, resource extraction, air and water pollution propagation, ecological population dynamics and exploitation. A variety of known models are considered, from classical ones (Cobb Douglass production function, Leontief input-output analysis, Solow models of economic dynamics, Verhulst-Pearl and Lotka-Volterra models of population dynamics, and others) to the models of world dynamics and the models of water contamination propagation used after Chemobyl nuclear catastrophe. Special attention is given to modelling of hierarchical regional economic-ecological interaction and technological change in the context of environmental impact. Xlll XIV Construction of Mathematical Models ...
This book teaches mathematical structures and how they can be applied in environmental science. Each chapter presents story problems with an emphasis on derivation. For each of these, the discussion follows the pattern of first presenting an example of a type of structure as applied to environmental science. The definition of the structure is presented, followed by additional examples using MATLAB, and analytic methods of solving and learning from the structure.
This book introduces numerical methods for processing datasets which may be of any form, illustrating adequately computational resolution of environmental alongside the use of open source libraries. This book solves the challenges of misrepresentation of datasets that are relevant directly or indirectly to the research. It illustrates new ways of screening datasets or images for maximum utilization. The adoption of various numerical methods in dataset treatment would certainly create a new scientific approach. The book enlightens researchers on how to analyse measurements to ensure 100% utilization. It introduces new ways of data treatment that are based on a sound mathematical and computational approach.