A Pseudo Individual Near Real-Time Measurement for Assessing Air Pollution Exposure in Selected Texas Cities

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dc.contributor.advisorLu, Yongmei
dc.contributor.authorFang, Tianfang Bernie
dc.contributor.committeeMemberZhan, F. Benjamin
dc.contributor.committeeMemberDixon, Richard W.
dc.contributor.committeeMemberFonstad, Mark A.
dc.contributor.committeeMemberLin, Ge
dc.date.accessioned2012-11-05T18:21:56Z
dc.date.available2012-11-05T18:21:56Z
dc.date.issued2012-12
dc.description.abstract<p>Air pollution causes severe health effects and economic loss. Many major air-pollution-related studies focus on place-based measures and simulation. Typical place-based air pollution studies cannot portray individuals’ air pollution exposure scenarios. In recent years, individual-based air pollution exposure measures have been developed rapidly.</p> <p>Based on an extensive literature review of place-based geography and people-based geography, air pollution exposure assessment methods (including place-based and individual-based ones), and health effects of air pollution exposure, this dissertation research aims to investigate an innovative modeling approach for assessing individual near real-time air pollution exposure. The first part of the model development is to design a series of near real-time space-time air pollution scenario cubes. Originating from time geography, space-time cubes provide an approach to integrate spatial and temporal air pollution information into a 3D space. The base of space-time cubes represents the variation of air pollution in a 2D geographical space while the height represents time. The second part of the model development is to geovisualize volunteers’ individual real-time space-time trajectories using 3D space-time path maps. The last part of the model development is to integrate space-time cubes and space-time trajectories to develop the pseudo individual near real-time air pollution monitoring (PIRAM in short) models and the derivative models – the integrated pseudo individual near real-time air quality index (PIRAQI in short) models and the integrated pseudo individual near real-time air pollution dose simulation (PIRADS in short) models. Volunteers’ individual diurnal ambient ozone (O3) pollution exposures in Houston, Austin, and San Antonio are modeled in this dissertation research.</p> <p>The contributions of this dissertation research are four-fold. First, it can help in understanding air pollution and individual exposure from a people-based geography perspective. Second, it enriches the individual-based air pollution exposure measure study by emphasizing individual travel behaviors in the individual air pollution exposure context. Third, its results can reveal the characteristics of the individual real-time air pollution exposure, which will contribute to local air pollution policy making. Fourth, the PIRAM platform only needs one handheld device terminal, such as a GPS smartphone, which ensure a good end user experience and potential commercial value.</p>
dc.description.departmentGeography and Environmental Studies
dc.formatText
dc.format.extent196 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationFang, T. B. (2012). <i>A pseudo individual near real-time measurement for assessing air pollution exposure in selected Texas cities</i> (Unpublished dissertation). Texas State University-San Marcos, San Marcos, Texas.
dc.identifier.urihttps://hdl.handle.net/10877/4365
dc.language.isoen
dc.subjectInformation technology
dc.subjectAir pollution
dc.subjectPersonal exposure assessment
dc.subjectNear real-time
dc.subjectSpace-time cube
dc.subjectLand Use Regression (LUR)
dc.subjectSpatial interpolation
dc.subject.lcshAir--Pollutionen_US
dc.subject.lcshAir--Pollution--Texasen_US
dc.subject.lcshAir--Pollution--Health aspectsen_US
dc.subject.lcshAir quality managementen_US
dc.titleA Pseudo Individual Near Real-Time Measurement for Assessing Air Pollution Exposure in Selected Texas Cities
dc.typeDissertation
thesis.degree.departmentGeography
thesis.degree.disciplineGeographic Information Science
thesis.degree.grantorTexas State University-San Marcos
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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