Bayesian hierarchical modeling of personal exposure to particulate matter |
| |
| Affiliation: | 1. Texas State University, Texas Center for Geographic Information Science, Department of Geography, San Marcos, TX 78666, USA;2. Texas A&M Health Science Center School of Public Health, Department of Epidemiology & Biostatistics, College Station, TX 77843-1266, USA;3. Birth Defects Epidemiology and Surveillance Branch, Texas Department of State Health Services, PO Box 149347, MC 1964, Austin, TX 78714-9347, USA;4. South Dakota State University, Department of Geography, Brookings, SD 57007, USA |
| |
| Abstract: | In the US EPA's 1998 Baltimore Epidemiology-Exposure Panel Study, a group of 16 residents of a single building retirement community wore personal monitors recording personal fine particulate air pollution concentrations (PM2.5) for 27 days, while other monitors recorded concurrent apartment, central indoor, outdoor and ambient site PM2.5 concentrations. Using the Baltimore panel study data, we develop a Bayesian hierarchical model to characterize the relationship between personal exposure and concentrations of PM2.5 indoors and outdoors. Personal exposure is expressed as a linear combination of time spent in microenvironments and associated microenvironmental concentrations. The model incorporates all available monitoring data and accounts for missing data and sources of uncertainty such as measurement error and individual differences in exposure. We discuss the implications of using personal versus ambient PM2.5 measurements in characterization of personal exposure to PM2.5. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
