Abstract
The use of Positive Matrix Factorization (PMF) in pollution source apportionment (PSA) is examined and illustrated. A study of its settings is conducted in order to optimize them in the context of PSA. The use of a priori information in PMF is examined, in the form of target factor profiles and pulling profile elements to zero. A Bayesian model using lognormal prior distributions for source profiles and source contributions is fit and examined.
Degree
MS
College and Department
Physical and Mathematical Sciences; Statistics
Rights
http://lib.byu.edu/about/copyright/
BYU ScholarsArchive Citation
Lingwall, Jeff William, "Bayesian and Positive Matrix Factorization approaches to pollution source apportionment" (2006). Theses and Dissertations. 430.
https://scholarsarchive.byu.edu/etd/430
Date Submitted
2006-05-02
Document Type
Thesis
Handle
http://hdl.lib.byu.edu/1877/etd1295
Keywords
pollution source apportionment, source attribution, statistics, air pollution
Language
English