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Brigham Young University - Provo
Bayesian and Positive Matrix Factorization approaches to pollution source apportionment
Abstract
dc:description.abstractThe 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
thesis:*- Name thesis:degree_name
- MS
- Grantor dc:publisher
- Brigham Young University - Provo
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Lingwall, Jeff William
Subjects
dc:subject × 5Rights
- Language dc:language
- English
Identifiers
dc:identifier.*- Repository record dc:identifier
- https://scholarsarchive.byu.edu/etd/430
- OAI identifier oai:identifier
- oai:scholarsarchive.byu.edu:etd-1429