Pragmatic Estimation of a Spatio-Temporal Air Quality Model with Irregular Monitoring Data

Details

• Personal Author:
  Kaufman JD ; Lindström J ; Sampson PD ; Sheppard L ; Szpiro AA
• Description:
  Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in "land use" regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation. [Description provided by NIOSH]
• Subjects:
  Air Pollution Environmental Monitoring Occupational Health Particulate Matter Safety
• Keywords:
  Air Monitoring Air Pollution Author Keywords: Exposure Estimation Hierarchical Model Nonstationary Spatial Covariance Partial Least Squares Particulate Matter Particulates Statistical Analysis Universal Kriging
• ISSN:
  1352-2310
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  OSHA Region 10 ; Washington
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  45
• Issue:
  36
• NIOSHTIC Number:
  nn:20054957
• Citation:
  Atmos Environ 2011 Nov; 45(36):6593-6606
• Contact Point Address:
  Paul D. Sampson, Department of Statistics, University of Washington, Box 354322, Seattle, WA 98195-4322, USA
• Email:
  pds@stat.washington.edu
• Federal Fiscal Year:
  2012
• Performing Organization:
  University of Washington
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Atmospheric Environment
• End Date:
  20250630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:b38ebed67dfce05cd99774f3f5e2b88577a156f4d3edb935aacdcaeb760731209b35ecd69caf6bef8d06db68201bc3964e9a59855683256903d2f9aabba62f95
• Download URL:
  https://stacks.cdc.gov/view/cdc/217363/cdc_217363_DS1.pdf
• File Type:
  [PDF - 1.61 MB ]