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Bayesian And Positive Matrix Factorization Approaches To Pollution Source Apportionment, Jeff William Lingwall
Bayesian And Positive Matrix Factorization Approaches To Pollution Source Apportionment, Jeff William Lingwall
Theses and Dissertations
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.