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.
College and Department
Physical and Mathematical Sciences; Statistics
BYU ScholarsArchive Citation
Christensen, Jonathan Casey, "Bayesian Pollution Source Apportionment Incorporating Multiple Simultaneous Measurements" (2012). Theses and Dissertations. 3005.
Pollution Source Apportionment, Bayesian Methods, Multivariate Receptor Modeling