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Source contributions to ambient aerosol calculated by discriminat partial least squares regression (PLS) |
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| Authors: | Richard Vong Paul Geladi Svante Wold Kim Esbensen |
| Institution: | 1. Group for Statistical Analysis of Natural Resources Data (SAND). Norwegian Computing Centre, N-0314 Blindern, Oslo 3, Norway
NTNF Senior Visiting Scientist.;2. Group for Statistical Analysis of Natural Resources Data (SAND). Norwegian Computing Centre, N-0314 Blindern, Oslo 3, Norway Group for Statistical Analysis of Natural Resources Data (SAND). Chemometrics Research Group, Umeå University, S-901 87 Umeå, Sweden;3. Group for Statistical Analysis of Natural Resources Data (SAND). Chemometrics Research Group, Umeå University, S-901 87 Umeå, Sweden;4. Group for Statistical Analysis of Natural Resources Data (SAND). Norwegian Computing Centre, N-0314 Blindern, Oslo 3, Norway |
| Abstract: | 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. |
| Keywords: | Partial least squares Receptor modelling Colinearities |