Application of Multivariate Analysis to Study Polycyclic Aromatic Hydrocarbons Distribution Associated to Airborne Particulate Matter

MARINO D., CASTRO E.A., MASSOLO L., MUELLER A., HERBARTH O., AND RONCO A.E.

CHEMOSPHERE

Año: 2008

0045-6535

ENVIADO       Since a long time ago researchers are studying the Polyciclic Aromatic Hidrocarbons (PAHs) behaviour, concentration and relevant sources. Several previous studies performed in La Plata, Argentina and Leipzig, Germany analyzed PAHs bound to particulate matter (PM) according to particle size in winter and summer seasons. In the present study statistical methods based on multivariate analysis such as Descriptive Discriminant Analysis (DDA) and Principal Component Analysis (PCA) were applied to the data sets from La Plata and Leipzig in order to obtain relationships among particle sizes and the composition of the associated semi-volatile compounds, besides to evaluating these observations in relation to the emission sources and regional environmental factors. Results from the DDA showed that the PAHs distributions contained in the PM10 and PM<0.49 µm permits a better discrimination within the areas at the different study levels, while the PAH distribution in intermediate particle fractions incorporate noise in the statistical analysis. The PCA was useful in identifying main emission sources in each study area. It showed that in La Plata city the most important pollution sources are traffic emissions and the industrial activity associated to oil and petrochemical plants. In Leipzig the main sources are those associated to traffic and also from a power plant. The combined PCA and DDA methods applied to PAHs distributions is a valuable tool in characterizing type of emission burdens and also obtaining a differentiation of sample types according to characteristic profiles, as well as the weigh of distributions in each place on the total regional data.