The community of Fresno, California is notable for a high prevalence of asthma among an ethnically diverse population, and for high levels of ambient air pollution, especially PM, making it an appropriate location to address questions of air pollution's impact on this vulnerable population. The Fresno Asthmatic Children's Environment Study (FACES) is focused on quantifying the relationship between air pollution and asthma in young children who reside in Fresno, California. An underlying premise of FACES is that observed health effects are associated with specific exposures or sets of exposures, and that there are subsets of the population of asthmatic children who are more responsive to different exposures. To define the exposure characteristics of the children who comprise these subsets, the exposure assessment program is targeted to accurately estimate the individual level exposures daily over several years. This dissertation applies spatial regression to model the concentrations of three types of air pollution data for use in personal exposure assessment: ambient elemental carbon (EC), ambient polycyclic aromatic hydrocarbons (PAH), and PAH in pine needles. The spatial and temporal distribution of EC samples and PAH samples collected during the FACES study were each evaluated and modeled for all participant locations and dates in the FACES study using mixed effects modeling in land use regression models. These models use a central monitoring site as the primary temporal source data for both EC and PAH, and supplement the information on temporal variability with meteorological data, e.g., wind speed, and season indicator variables. Spatial data included land use, traffic intensive and proximity, point source locations, and agricultural burning. Third, pine needles were collected in Fresno at 91 locations and analyzed for PAHs. This biomonitoring data was used to build a model of the spatial distribution of PAHs on a single day in Fresno. Cross-sectional land use regression models that were built from the pine needle data show that both traffic and other non-mobile sources are important for PAH estimation in the urban environment. The models from filter EC and PAH were applied to estimate daily personal exposures for all days and for all participants in the FACES study.
|Advisor:||Hammond, S. Katharine|
|School:||University of California, Berkeley|
|School Location:||United States -- California|
|Source:||DAI-B 70/10, Dissertation Abstracts International|
|Subjects:||Public health, Environmental science|
|Keywords:||Air pollution, Asthma, Elemental carbon, Polycyclic hydrocarbons|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be