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EXPOSURE MONITORING COMPONENT FOR DETROIT CHILDREN'S HEALTH STUDY ( DCHS )
Citation:
MUKERJEE, S. EXPOSURE MONITORING COMPONENT FOR DETROIT CHILDREN'S HEALTH STUDY ( DCHS ). Presented at Windsor/Detroit Studies Workshop, Detroit, MI, October 21, 2005.
Impact/Purpose:
Overall Goal: To develop spatial analyses using limited network-based air quality and GIS and other ancillary spatial information to estimate exposures for epidemiological analyses in urban populations.
Goal of NERL Contribution: To develop ambient-GIS regression-based spatial models using said ambient measures and ancillary information to predict such exposures at unmonitored locations and assess neighborhood differences in air pollutant concentrations.
Specific Objectives:
1. To determine spatial associations among measured levels of VOC, NO2, and (possibly) PM from mobile and other urban sources in Detroit/Dearborn. Spatial variability in air pollutant concentrations will be determined using the ambient measurements at the schools and available surrogates of motor vehicle and other urban emissions (from GIS databases). These measured or predicted spatial associations will then be used by NHEERL to ultimately assess impact of these pollutants on children's exposures in schools.
2. To evaluate accuracy of VOC, NO2 and PM measurements using passive devices versus collocated FRM devices. In addition, to evaluate precision of collocated passive devices.
Description:
Conventional, regulatory-based air monitoring is expensive and, thus, conducted at one or few locations in a city. This provides limited info on intra-urban variability and spatial distribution of air pollution. Research-oriented urban network monitoring has progressed with increased use of passive diffusion sampling and advances in sampler portability. Spatial analysis studies of ambient air pollutants have been conducted to assess traffic influence and its possible impact on respiratory health. This research has been enhanced by incorporation of ancillary variables from geographic and demographic sources to assess neighborhood differences of air pollution; approach has been termed land-use regression (LUR) modeling. The LUR modeling effort for the Detroit Children's Health Study will be discussed.