| Abstract: | Partial least squares (PLS) techniques are used in the re-analysis of NOAA hydrocarbon data previously investigated in Mudge (2002). New data have been provided for coal and oil signatures and these have been investigated further. The effects of zeros (less than the limit of detection) in the dataset can be overcome by addition of small values at approximately half of this limit; this then enables logarithms to be taken of the entire dataset which greatly improved the usefulness of principal component analysis (PCA). Source samples collected close to each other had different signatures, probably due to their environmental histories which was also seen when aliphatic hydrocarbons were included in the signatures. Key compounds describing each could be seen in Coomans' Plots. Signatures developed from formation oils, riperian oils and coals from the eastern Gulf of Alaska (GoA) provided mean fits to subtidal samples within PWS of 22, 19 and 38% respectively. This suggests mixed and variable sources across the sampling area. The overall conclusion must be a question regarding the partitioning between oil and coal source materials as they look very similar in this particular location. |
