Persistent Link:
http://hdl.handle.net/10150/289152
Title:
A geographical analysis of air pollution in the Tucson region
Author:
Diem, Jeremy Everett, 1972-
Issue Date:
2000
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
This dissertation presents a geographical analysis of air pollution in the Tucson region. Image processing, geographic information system (GIS), climatological, and statistical tools are used to develop and analyze air pollution-related databases. These databases are then used in conjunction with a limited number of spatial measurements of ozone concentrations to create accurate and theoretically sound ground-level ozone maps. High spatial resolution, gridded, multi-temporal, atmospheric emissions inventories (EIs) of ozone precursor chemical (i.e. volatile organic compounds (VOCs) and nitrogen oxides (NOₓ)) emissions are initially developed. GIS-driven "top-down" and "bottom-up" methods are employed to create anthropogenic VOC and NOx emissions inventories while satellite imagery and field surveys are employed to create biogenic VOC (BVOC) emissions inventories. Accounting for approximately 50% of the anthropogenic emissions, on-road vehicles are the dominant anthropogenic source. The forest and desert lands emit nearly all of the BVOCs within the entire Tucson region while exotic trees such as eucalyptus, pine, and palm emit most of the BVOCs within the City of Tucson. Relationships between VOC and NOₓ emissions, atmospheric conditions, and ambient ozone levels are determined by examining spatio-temporal variations in ozone levels, temporal variations in VOC and NOₓ emissions and atmospheric conditions, atmospheric conditions which are conducive to elevated ozone levels. In addition, the likelihood of ozone transport from Phoenix to Tucson is assessed. The highest ozone levels occur at "rural," downwind monitors, occur in August, and occur during the early afternoon hours. Atmospheric conditions conducive to elevated concentrations differ between the months while inter-city ozone transport is most likely to occur in June. Pooled, cross-sectional, times series, regression models are developed with the aid of cluster analysis and principal components analysis to spatially predict daily maximum 1-hr and 8-hr average ozone concentrations. Gridded, multi-temporal estimates of VOCs and NOₓ emissions are the primary predictor variables in the regression models. The pooled models are reasonably accurate with overall R² values from 0.90 to 0.92, 6 to 7% error, and predicted concentrations that are typically within 0.003 to 0.004 ppm of the observed concentrations. The predicted highest ozone concentrations occur in a monitorless area on the eastern edge of the City of Tucson.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Physical Geography.; Environmental Sciences.; Remote Sensing.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Geography and Regional Development
Degree Grantor:
University of Arizona
Advisor:
Comrie, Andrew C.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleA geographical analysis of air pollution in the Tucson regionen_US
dc.creatorDiem, Jeremy Everett, 1972-en_US
dc.contributor.authorDiem, Jeremy Everett, 1972-en_US
dc.date.issued2000en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThis dissertation presents a geographical analysis of air pollution in the Tucson region. Image processing, geographic information system (GIS), climatological, and statistical tools are used to develop and analyze air pollution-related databases. These databases are then used in conjunction with a limited number of spatial measurements of ozone concentrations to create accurate and theoretically sound ground-level ozone maps. High spatial resolution, gridded, multi-temporal, atmospheric emissions inventories (EIs) of ozone precursor chemical (i.e. volatile organic compounds (VOCs) and nitrogen oxides (NOₓ)) emissions are initially developed. GIS-driven "top-down" and "bottom-up" methods are employed to create anthropogenic VOC and NOx emissions inventories while satellite imagery and field surveys are employed to create biogenic VOC (BVOC) emissions inventories. Accounting for approximately 50% of the anthropogenic emissions, on-road vehicles are the dominant anthropogenic source. The forest and desert lands emit nearly all of the BVOCs within the entire Tucson region while exotic trees such as eucalyptus, pine, and palm emit most of the BVOCs within the City of Tucson. Relationships between VOC and NOₓ emissions, atmospheric conditions, and ambient ozone levels are determined by examining spatio-temporal variations in ozone levels, temporal variations in VOC and NOₓ emissions and atmospheric conditions, atmospheric conditions which are conducive to elevated ozone levels. In addition, the likelihood of ozone transport from Phoenix to Tucson is assessed. The highest ozone levels occur at "rural," downwind monitors, occur in August, and occur during the early afternoon hours. Atmospheric conditions conducive to elevated concentrations differ between the months while inter-city ozone transport is most likely to occur in June. Pooled, cross-sectional, times series, regression models are developed with the aid of cluster analysis and principal components analysis to spatially predict daily maximum 1-hr and 8-hr average ozone concentrations. Gridded, multi-temporal estimates of VOCs and NOₓ emissions are the primary predictor variables in the regression models. The pooled models are reasonably accurate with overall R² values from 0.90 to 0.92, 6 to 7% error, and predicted concentrations that are typically within 0.003 to 0.004 ppm of the observed concentrations. The predicted highest ozone concentrations occur in a monitorless area on the eastern edge of the City of Tucson.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectPhysical Geography.en_US
dc.subjectEnvironmental Sciences.en_US
dc.subjectRemote Sensing.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineGeography and Regional Developmenten_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorComrie, Andrew C.en_US
dc.identifier.proquest9972124en_US
dc.identifier.bibrecord.b40642653en_US
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