Combined Use of Principal Component Analysis (PCA) and Chemical Mass Balance (CMB) for Source Identification and Source Apportionment in Air Pollution Modeling Studies

2010 ◽  
Vol 212 (1-4) ◽  
pp. 429-439 ◽  
Author(s):  
Selami Demir ◽  
Arslan Saral ◽  
Ferruh Ertürk ◽  
Levent Kuzu
Keyword(s):  
Principal Component Analysis ◽  
Air Pollution ◽  
Mass Balance ◽  
Source Apportionment ◽  
Source Identification ◽  
Principal Component ◽  
Component Analysis ◽  
Chemical Mass Balance ◽  
Combined Use ◽  
Pollution Modeling

Source identification of PCBs in sediments from the Milwaukee Harbor Estuary, USA

1998 ◽  
Vol 37 (6-7) ◽  
pp. 199-206 ◽  
Author(s):  
P. Rachdawong ◽  
E. R. Christensen ◽  
S. Chi
Keyword(s):  
Principal Component Analysis ◽  
Mass Balance ◽  
Source Identification ◽  
Principal Component ◽  
Chemical Mass Balance ◽  
Pollutant Sources ◽  
First Time ◽  
Nonnegative Constraints ◽  
Good Agreement

This work focuses on the determination of PCB source profiles and their contributions to sediments in the Milwaukee Harbor Estuary by a principal component analysis (PCA) model. The model was recently developed and, for the first time, applied to apportion pollutant sources in sediments. Factor loadings and scores were computed, rotated via nonnegative constraints, and matched with candidate Aroclor profiles. Contamination by Aroclors 1016, 1242, 1254, and 1260 were identified for cores VC 6, 9, and 12 based on a log Q2 criterion. The majority of PCB contribution was from a combination of Aroclors 1016 and 1242. Similarity between Aroclors 1016 and 1242 obscured resolution between the two profiles. Results from a chemical mass balance (CMB) model with known Aroclor profiles were in good agreement with the prediction from the PCA model.

Sign in / Sign up

Export Citation Format

Share Document