International Series in Operations Research & Management Science

Quantitative Risk Analysis of Air Pollution Health Effects

Authors: Cox Jr., Louis Anthony

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  • Highlights recent advances in causal analytics, machine learning, and risk analysis models and methods to determine whether and by how much reducing exposures affects human health risks
  • Focuses on quantitative models used to assess and communicate health risks caused by air pollution
  • In-browser analytics software and data sets are available to allow readers to carry out the analyses described and apply the techniques to their own data
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eBook 89,99 €
price for India (gross)
  • ISBN 978-3-030-57358-4
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 109,99 €
price for India (gross)
  • ISBN 978-3-030-57357-7
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions & severe weather in the US may cause delays
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
About this book

This book highlights quantitative risk assessment and modeling methods for assessing health risks caused by air pollution, as well as characterizing and communicating remaining uncertainties. It shows how to apply modern data science, artificial intelligence and machine learning, causal analytics, mathematical modeling, and risk analysis to better quantify human health risks caused by environmental and occupational exposures to air pollutants. The adverse health effects that are caused by air pollution, and preventable by reducing it, instead of merely being statistically associated with exposure to air pollution (and with other many conditions, from cold weather to low income) have proved to be difficult to quantify with high precision and confidence, largely because correlation is not causation. This book shows how to use recent advances in causal analytics and risk analysis to determine more accurately how reducing exposures affects human health risks. 

Quantitative Risk Analysis of Air Pollution Health Effects is divided into three parts. Part I focuses mainly on quantitative simulation modelling of biological responses to exposures and resulting health risks. It considers occupational risks from asbestos and crystalline silica as examples, showing how dynamic simulation models can provide insights into more effective policies for protecting worker health.  Part II examines limitations of regression models and the potential to instead apply machine learning, causal analysis, and Bayesian network learning methods for more accurate quantitative risk assessment, with applications to occupational risks from inhalation exposures. Finally, Part III examines applications to public health risks from air pollution, especially fine particulate matter (PM2.5) air pollution. The book applies freely available browser analytics software and data sets that allow readers to download data and carry out many of the analyses described, in addition to applying the techniques discussed to their own data.

http://cox-associates.com:8899/

About the authors

Tony Cox is Professor of Business Analytics at the University of Colorado and President of Cox Associates, a Denver-based applied research company specializing in health, safety, and environmental risk analysis; epidemiology; policy analytics; data science; artificial intelligence; and operations research. Dr. Cox is Editor-in-Chief of Risk Analysis: An International Journal. He is Area Editor for Real World Applications for the Journal of Heuristics, and is on the Editorial Board of the International Journal of Operations Research and Information Systems. He has authored and co-authored over 200 journal articles and book chapters on these fields. His most recent books are Causal Analytics for Risk Analysis (Springer, 2018), Breakthroughs in Decision Science and Risk Analysis (Wiley, 2015), Improving Risk Analysis (Springer, 2013), and the Wiley Encyclopedia of Operations Research and Management Science (Wiley, 2011), which Dr. Cox co-edited. He has over a dozen U.S. patents on applications of artificial intelligence, signal processing, statistics and operations research in telecommunications. His current research interests include computational statistical methods for causal inference in public health risk analysis, data-mining, and advanced analytics for risk management, business, and public policy applications.

Table of contents (19 chapters)

Table of contents (19 chapters)
  • Scientific Method for Health Risk Analysis: The Example of Fine Particulate Matter Air Pollution and COVID-19 Mortality Risk

    Pages 3-26

    Cox Jr., Louis Anthony

  • Modeling Nonlinear Dose-Response Functions: Regression, Simulation, and Causal Networks

    Pages 27-61

    Cox Jr., Louis Anthony

  • Simulating Exposure-Related Health Effects: Basic Ideas

    Pages 63-77

    Cox Jr., Louis Anthony

  • Case Study: Occupational Health Risks from Crystalline Silica

    Pages 79-115

    Cox Jr., Louis Anthony

  • Case Study: Health Risks from Asbestos Exposures

    Pages 117-158

    Cox Jr., Louis Anthony

Buy this book

eBook 89,99 €
price for India (gross)
  • ISBN 978-3-030-57358-4
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 109,99 €
price for India (gross)
  • ISBN 978-3-030-57357-7
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions & severe weather in the US may cause delays
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Quantitative Risk Analysis of Air Pollution Health Effects
Authors
Series Title
International Series in Operations Research & Management Science
Series Volume
299
Copyright
2021
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-57358-4
DOI
10.1007/978-3-030-57358-4
Hardcover ISBN
978-3-030-57357-7
Series ISSN
0884-8289
Edition Number
1
Number of Pages
XIV, 544
Number of Illustrations
27 b/w illustrations, 88 illustrations in colour
Topics