Source apportionment of PAH in Hamilton Harbour suspended sediments: Comparison of two factor analysis methods

A total of 26 suspended sediment samples collected over a 5-year period in Hamilton Harbour, Ontario, Canada and surrounding creeks were analyzed for a suite of polycyclic aromatic hydrocarbons and sulfur heterocycles. Hamilton Harbour sediments contain relatively high levels of polycyclic aromatic compounds and heavy metals due to emissions from industrial and mobile sources. Two receptor modeling methods using factor analyses were compared to determine the profiles and relative contributions of pollution sources to the harbor; these methods are principal component analyses (PCA) with multiple linear regression analysis (MLR) and positive matrix factorization (PMF). Both methods identified four factors and gave excellent correlation coefficients between predicted and measured levels of 25 aromatic compounds; both methods predicted similar contributions from coal tar/coal combustion sources to the harbor (19 and 26%, respectively). One PCA factor was identified as contributions from vehicular emissions (61%); PMF was able to differentiate vehicular emissions into two factors, one attributed to gasoline emissions sources (28%) and the other to diesel emissions sources (24%). Overall, PMF afforded better source identification than PCA with MLR. This work constitutes one of the few examples of the application of PMF to the source apportionment of sediments; the addition of sulfur heterocycles to the analyte list greatly aided in the source identification process.