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Source contributions to ambient aerosol calculated by discriminat partial least squares regression (PLS)
Author(s) -
Vong Richard,
Geladi Paul,
Wold Svante,
Esbensen Kim
Publication year - 1988
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1180020406
Subject(s) - partial least squares regression , aerosol , orthogonality , linear regression , regression , regression analysis , linear discriminant analysis , set (abstract data type) , statistics , data set , mathematics , chemistry , computer science , geometry , organic chemistry , programming language
Partial least squares regression (PLS) is proposed for solving ir pollution source apportionment problems as an alternative method to the frequently used chemical mass balance technique. A discriminant PLS is used to calculate linear mixing proportions for a synthetic ambient aerosol data set where the truth is known. Without sacrificing orthogonality of the source profiles, PLS can resolve the emission sources and accurately predict the emission source contributions. Further extensions of the PLS approach to environmental receptor modelling are discussed.