Pollution source apportionment using a priori information and positive matrix factorization

Chemometrics and Intelligent Laboratory Systems

Volumn 87, Issue 2, 2007, Pages 281-294

  Lingwall, Jeff W ^a   Christensen, William F ^b  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b BRIGHAM YOUNG UNIVERSITY   (United States)

Author keywords

Air pollution; Chemical mass balance; Multivariate receptor modeling; PMF; Source attribution

Indexed keywords

AIR POLLUTION; ARTICLE; DATA ANALYSIS; MEASUREMENT ERROR; POLLUTION CONTROL; PRIORITY JOURNAL; SIMULATION;

EID: 34248545804     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chemolab.2007.03.007     Document Type: Article

References (9)

1. Paatero P., and Tapper U. Environmetrics 5 (1994) 111-126
2. Paatero P. Chemometrics and Intelligent Laboratory Systems 37 (1997) 23-35
3. Eberly S. EPA PMF 1.1 Users Guide (2005), U.S. Environmental Protection Agency, Research Triangle Park, NC
4. Christensen W.F., Schauer J.J., and Lingwall J.W. Environmetrics 17 (2006) 663-681
5. Javitz H.S., Robinson N.F., and Watson J.G. Atmospheric Environment 22 (1988) 2309-2322
6. Christensen W.F., and Gunst R.F. Atmospheric Environment 38 (2004) 733-744
7. J.W. Lingwall, Bayesian and Positive Matrix Factorization approaches to pollution source apportionment. M.S. Thesis, Department of Statistics, Brigham Young University, Provo, UT, 2006.
8. Paatero P. Users Guide for Positive Matrix Factorization programs PMF2 and PMF3, Part 1: Tutorial (2004), University of Helsinki, Helsinki, Finland
9. Lee J.H., Hopke P.K., and Turner J.R. Journal of Geophysical Research 111 (2006) D10S10 10.1029/2005JD006329