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.
College and Department
Physical and Mathematical Sciences; Statistics
BYU ScholarsArchive Citation
Lingwall, Jeff William, "Bayesian and Positive Matrix Factorization approaches to pollution source apportionment" (2006). All Theses and Dissertations. 430.
pollution source apportionment, source attribution, statistics, air pollution