Principal component analysis for particulate source resolution in cleanrooms

Yi Tian, Pratim Biswas, Sotiris E. Pratsinis, Walter M. Hsieh

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Principal component analysis (PCA) is applied to particulate size distributions measured at receptor sites in two cleanrooms. The principal components are determined by evaluating the rotated component patterns. Each component is then assigned to a source by comparing the principal components to the particle size distributions emitted by the sources. Hence, sources of particulate contamination in the cleanrooms are determined. Particle volume concentration balances are used to quantitatively apportion the contaminant levels at the receptor sites to each source. PCA can thus be used to identify contaminant particle sources and to develop strategies for improvement of the cleanroom cleanliness class.

Original languageEnglish (US)
Pages (from-to)22-27
Number of pages6
JournalJournal of Environmental Sciences
Volume32
Issue number6
StatePublished - Nov 1989
Externally publishedYes

ASJC Scopus subject areas

  • Environmental Science(all)

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