COVID-19 Update: We are currently shipping orders daily. However, due to transit disruptions in some geographies, deliveries may be delayed. To provide all customers with timely access to content, we are offering 50% off Science and Technology Print & eBook bundle options. Terms & conditions.
Spatiotemporal Analysis of Air Pollution and Its Application in Public Health - 1st Edition - ISBN: 9780128158227, 9780128165263

Spatiotemporal Analysis of Air Pollution and Its Application in Public Health

1st Edition

Editors: Lixin Li Xiaolu Zhou Weitian Tong
Paperback ISBN: 9780128158227
eBook ISBN: 9780128165263
Imprint: Elsevier
Published Date: 13th November 2019
Page Count: 328
Sales tax will be calculated at check-out Price includes VAT/GST
Price includes VAT/GST

Institutional Subscription

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.


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.

Key Features

  • 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


Researchers, students and practitioners in Atmospheric Science and other related sciences studying impacts of Air Pollution

Table of Contents

1. Introduction to Spatiotemporal Variations of Air Pollutants and related Public Health Impacts
2. Illustrations of Statistical Analysis for Air Pollution Data
3. Case Study: Does PM2.5 Contribute to the Incidence of Lung and Bronchial Cancers in the U.S.?
4. Bayesian Modeling for Linkage between Air Pollution and Population Health
5. Machine Learning for Spatiotemporal Big Data in Air Pollution
6. Integrate Machine Learning and Geostatistics for High Resolution Mapping of Gound-level PM2.5 Concentrations
7. Spatiotemporal Interpolation Methods  for Air Pollution
8. Sensing Air Quality: Spatiotemporal Interpolation and Visualization of Real-time Air Pollution Data in the Contiguous U.S.
9. Assessment Methods for Air Pollution Exposure
10. Applying LUR Model to Estimate Spatial Variation of PM2.5 in Greater Bay Area, China
11. Analysis of Exposure to Ambient Air Pollution: the Link Between Environmental Exposure and Children’s School Performance in Memphis, TN
12. Concentrating Risk? The Geographic Concentration of Health Risk from Industrial Air Toxins Across America
13. Travel-related exposure to air pollution and its socio-environmental inequalities: Evidence from a week-long GPS-based travel diary dataset


No. of pages:
© Elsevier 2019
13th November 2019
Paperback ISBN:
eBook ISBN:

About the Editors

Lixin Li

Lixin Li is a tenured Professor in the Department of Computer Science at Georgia Southern University. She received her Ph.D. degree in Computer Science from the University of Nebraska-Lincoln in 2003. Her research focuses on spatiotemporal interpolation methods, air pollution, and GIS applications

Affiliations and Expertise

Professor, Department of Computer Sciences, Georgia Southern University

Xiaolu Zhou

Xiaolu Zhou received his Ph.D. degree from University of Illinois at Urbana-Champaign in 2014. His research interests include geospatial analytics in spatial big data and human mobility analysis based on user generated content and smartphone sensing.

Affiliations and Expertise

Assistant Professor, Department of Geography, Texas Christian University

Weitian Tong

Weitian Tong received his Ph.D. degree in Computer Science from the University of Alberta in 2015. His research interests include data science and optimization algorithm design.

Affiliations and Expertise

Assistant Professor, Department of Computer Science, Eastern Michigan University

Ratings and Reviews