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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
"This report presents an evaluation of the current methods used to generate air emissions information from all freight transportation activities and discusses their suitability for purposes such as health and climate risk assessments, prioritization of emission reduction activities (e.g., through State Implementation Plans), and public education. The report is especially valuable for (1) its identification of the state of the practice, gaps, and strengths and limitations of current emissions data estimates and methods and (2) its conceptual model that offers a comprehensive representation of freight activity by all transportation modes and relationships between modes. This report will better inform the near-term needs of public and private stakeholders regarding the quality of emissions data and guide future research that links freight activities with air emissions."--pub. desc.