Enhancing Models and Measurements of Traffic-Related Air Pollutants for Health Studies Using Dispersion Modeling and Bayesian Data Fusion

Details

• Personal Author:
  Arunachalam, Saravanan ; Batterman, Stuart ; Berrocal, Veronica J. ; Gilani, Owais ; Milando, Chad ; Zhang, K. Max
• Description:
  Research Report 202 describes a study led by Dr. Stuart Batterman at the University of Michigan, Ann Arbor and colleagues. The investigators evaluated the ability to predict traffic-related air pollution using a variety of methods and models, including a line source air pollution dispersion model and sophisticated spatiotemporal Bayesian data fusion methods. Exposure assessment for traffic-related air pollution is challenging because the pollutants are a complex mixture and vary greatly over space and time. Because extensive direct monitoring is difficult and expensive, a number of modeling approaches have been developed, but each model has its own limitations and errors. Dr. Batterman and colleagues sought to improve model estimations by applying and systematically comparing the performance of different statistical models. The study made extensive use of data collected in the Near-road EXposures and effects of Urban air pollutants Study (NEXUS), a cohort study designed to examine the relationship between near-roadway pollutant exposures and respiratory outcomes in children with asthma who live close to major roadways in Detroit, Michigan. Description provided by NIOSH
• Subjects:
  • Aerosols
  • Air Pollutants, Occupational
  • Air Pollution
  • Occupational Health
  • Particulate Matter
  • Safety
• Keywords:
  • Air pollutants; Air pollution sampling; Air quality monitoring; Automotive emissions; Particulates; Aerosols; Exposure assessment; Statistical analysis
• ISSN:
  1041-5505
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Massachusetts ; Michigan ; New York ; North Carolina ; OSHA Region 1 ; OSHA Region 2 ; OSHA Region 3 ; OSHA Region 4 ; OSHA Region 5 ; Pennsylvania
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  82 pdf pages
• Issue:
  202
• NIOSHTIC Number:
  nn:20068567
• Citation:
  Res Rep Health Eff Inst 2020 Mar; 2020(202):1-63
• Contact Point Address:
  Dr. Stuart Batterman, 109 Observatory St., Ann Arbor, MI 48109-2029
• Email:
  stuartb@umich.edu
• Federal Fiscal Year:
  2020
• Performing Organization:
  University of Michigan, Ann Arbor
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Research Report (Health Effects Institute)
• End Date:
  20290630
• Download URL:
  https://stacks.cdc.gov/view/cdc/231555/cdc_231555_DS1.pdf
• File Type:
  [PDF - 3.31 MB]
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:7426cebb1c9f9645112e29fad6e914af796ffb75c3ce13106e07c0cdaeb156537f571fe48044c36c1429072d40c290003f3dbd55948aebac8cdf461f3cf5581b