Abstract

We describe a method to estimate pollution profiles and contribution levels for distinct prominent pollution sources in a region based on daily pollutant concentration measurements from multiple measurement stations over a period of time. In an extension of existing work, we will estimate common source profiles but distinct contribution levels based on measurements from each station. In addition, we will explore the possibility of extending existing work to allow adjustments for synoptic regimes—large scale weather patterns which may effect the amount of pollution measured from individual sources as well as for particular pollutants. For both extensions we propose Bayesian methods to estimate pollution source profiles and contributions.

Degree

MS

College and Department

Physical and Mathematical Sciences; Statistics

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2012-03-12

Document Type

Selected Project

Handle

http://hdl.lib.byu.edu/1877/etd5085

Keywords

Pollution Source Apportionment, Bayesian Methods, Multivariate Receptor Modeling

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