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Activity Number:
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386
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #309811 |
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Title:
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Identification of Pollution Source Directions via MCMC
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Author(s):
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Basil Williams*+ and William Christensen
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Companies:
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Brigham Young University and Brigham Young University
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Address:
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414 River Meadow Drive, Alpine, UT, 84004,
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Keywords:
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pollution source apportionment ; PSA ; circular data ; bayesian regression ; directional data
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Abstract:
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Pollution source apportionment (PSA) is the practice of identifying and describing pollution sources and their contributions. PSA frequently requires the identification of source directions, often as a post-analysis check to ensure that the contribution estimates are reasonable. This paper develops a method of identifying source directions using Bayesian regression. MCMC is used to evaluate the complex relationship among observed pollutant concentrations, available meteorological information, and unknown source direction parameters. The method is flexible enough to identify multiple source directions for cases in which a species or source type of interest is emitted at more than one location.
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