Bayesian and Positive Matrix Factorization approaches to pollution source apportionment

Research output: Types of ThesisDoctoral thesis

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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.

Original languageAmerican English
QualificationDoctor of Philosophy
StatePublished - 2 May 2006
Externally publishedYes

Keywords

  • air pollution
  • pollution source apportionment
  • source attribution
  • statistics

EGS Disciplines

  • Statistics and Probability

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