Spatiotemporal Analysis Of Air Pollution And Its Application In Public Health

Spatiotemporal Analysis of Air Pollution and Its Application in Public Health reviews, in detail, the tools needed to understand the spatial temporal distribution and trends of air pollution in the atmosphere, including how this information can be tied into the diverse amount of public health data available using accurate GIS techniques. By utilizing GIS to monitor, analyze and visualize air pollution problems, it has proven to not only be the most powerful, accurate and flexible way to understand the atmosphere, but also a great way to understand the impact air pollution has in diverse populations. This book is essential reading for novices and experts in atmospheric science, geography and any allied fields investigating air pollution. Introduces readers to the benefits and uses of geo-spatiotemporal analyses of big data to reveal new and greater understanding of the intersection of air pollution and health Ties in machine learning to improve speed and efficacy of data models Includes developing visualizations, historical data, and real-time air pollution in large geographic areas

Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus provides a holistic, conceptual and quantitative framework for Environmental Health Modelling in space-time. The holistic framework integrates two aspects of Environmental Health Science that have been previously treated separately: the environmental aspect, which involves the natural processes that bring about human exposure to harmful substances; and the health aspect, which focuses on the interactions of these substances with the human body. Some of the fundamental issues addressed in this work include variability, scale, uncertainty, and space-time connectivity. These topics are important in the characterization of natural systems and health processes. Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus explains why modern stochastics is the appropriate mechanical vehicle for addressing such issues in a rigorous way. In particular, modern stochastics incorporates concepts and methods from probability, classical statistics, geostatistics, statistical mechanics and field theory. The authors present a synthetic view of environmental health that embraces all of the various components and focuses on their mutual interactions. Spatiotemporal Environmental Health Modeling: A Tractatus Stochasticus includes new material on Bayesian maximum entropy estimation techniques and space-time random field estimation methods. The authors show why these methods have clear advantages over the classical geostatistical estimation procedures and how they can be used to provide accurate space-time maps of environmental health processes. Also included are expositions of diagrammatic perturbation and renormalization group analysis, which have not been previously discussed within the context of Environmental Health. Finally, the authors present stochastic indicators that can be used for large-scale characterization of contamination and investigations of health effects at the microscopic level. This book will be a useful reference to both researchers and practitioners of Environmental Health Sciences. It will appeal specifically to environmental engineers, geographers, geostatisticians, earth scientists, toxicologists, epidemiologists, pharmacologists, applied mathematicians, physicists and biologists.

Mathematical probability and statistics are an attractive, thriving, and respectable part of mathematics. Some mathematicians and philosophers of science say they are the gateway to mathematics’ deepest mysteries. Moreover, mathematical statistics denotes an accumulation of mathematical discussions connected with efforts to most efficiently collect and use numerical data subject to random or deterministic variations. Currently, the concept of probability and mathematical statistics has become one of the fundamental notions of modern science and the philosophy of nature. This book is an illustration of the use of mathematics to solve specific problems in engineering, statistics, and science in general.

Innovative and smart mobility systems are expected to make transportation systems more sustainable, inclusive, and safe. Because of changing mobility paradigms, transport planning and design require different methodological approaches. Over twelve chapters, this book examines and analyzes Mobility as a Service (MaaS), travel behavior, traffic control, intelligent transportation system design, electric, connected, and automated vehicles, and much more.

This book focuses on a range of geospatial applications for environmental health research, including environmental justice issues, environmental health disparities, air and water contamination, and infectious diseases. Environmental health research is at an exciting point in its use of geotechnologies, and many researchers are working on innovative approaches. This book is a timely scholarly contribution in updating the key concepts and applications of using GIS and other geospatial methods for environmental health research. Each chapter contains original research which utilizes a geotechnical tool (Geographic Information Systems (GIS), remote sensing, GPS, etc.) to address an environmental health problem. The book is divided into three sections organized around the following themes: issues in GIS and environmental health research; using GIS to assess environmental health impacts; and geospatial methods for environmental health. Representing diverse case studies and geospatial methods, the book is likely to be of interest to researchers, practitioners and students across the geographic and environmental health sciences. The authors are leading researchers and practitioners in the field of GIS and environmental health.

Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.

Traffic-Related Air Pollution synthesizes and maps TRAP and its impact on human health at the individual and population level. The book analyzes mitigating standards and regulations with a focus on cities. It provides the methods and tools for assessing and quantifying the associated road traffic emissions, air pollution, exposure and population-based health impacts, while also illuminating the mechanisms underlying health impacts through clinical and toxicological research. Real-world implications are set alongside policy options, emerging technologies and best practices. Finally, the book recommends ways to influence discourse and policy to better account for the health impacts of TRAP and its societal costs. Overviews existing and emerging tools to assess TRAP’s public health impacts Examines TRAP’s health effects at the population level Explores the latest technologies and policies--alongside their potential effectiveness and adverse consequences--for mitigating TRAP Guides on how methods and tools can leverage teaching, practice and policymaking to ameliorate TRAP and its effects