Relationship between PM2.5 Collected at Residential Outdoor Locations and a Central Site

Regression models are developed to describe the relationship between ambient PM 2.5 (particulate matter [PM] ≤2.5 μm in aerodynamic diameter) mass concentrations measured at a central-site monitor with those at residential outdoor monitors. Understanding the determinants and magnitude of variability...

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Bibliographic Details
Published in:Journal of the Air & Waste Management Association (1995) 2010-09, Vol.60 (9), p.1094-1104
Main Authors: George, Barbara Jane, Whitaker, Donald A., Gilliam, Robert C., Swall, Jenise L., Williams, Ronald W.
Format: Article
Language:English
Subjects:
Aerodynamics
Air Pollutants - chemistry
Exposure
Fluid flow
Kinetic energy
Logistic Models
Models, Theoretical
Monitors
Outdoor
Particle Size
Particulate Matter - chemistry
Regression
Time Factors
Turbulent flow
Uncertainty
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Summary:Regression models are developed to describe the relationship between ambient PM 2.5 (particulate matter [PM] ≤2.5 μm in aerodynamic diameter) mass concentrations measured at a central-site monitor with those at residential outdoor monitors. Understanding the determinants and magnitude of variability and uncertainty in this relationship is critical for understanding personal exposures in the evaluation of epidemiological data. The repeated measures regression models presented here address temporal and spatial characteristics of data measured in the 2004-2007 Detroit Exposure and Aerosol Research Study, and they take into account missing data and other data features. The models incorporate turbulence kinetic energy and planetary boundary layer height, meteorological data that are not routinely considered in models that relate central-site concentrations to exposure to health effects. It was found that turbulence kinetic energy was highly statistically significant in explaining the relationship of PM 2.5 measured at a particular stationary outdoor air monitoring site with PM 2.5 measured outside nearby residences for the temporal coverage of the data.
ISSN:1096-2247
2162-2906
DOI:10.3155/1047-3289.60.9.1094