Regressing gas/particle partitioning data for polycyclic aromatic hydrocarbons

Abstract

Polycyclic aromatic hydrocarbons (PAHs) were measured in the rural atmosphere of Southern Ontario, Canada from October 2001 to November 2002. Sixty seven pairs of gaseous and particle-bound concentrations of PAHs were determined concurrently in a forest and a clearing. The gas/particle partitioning behavior of the PAHs was investigated by fitting the original Junge-Pankow equation to the fraction in the particle phase φ for each set of measured data, either allowing the slope m to deviate from -1 (two-parameter model) or not (one-parameter model). This fitting procedure was judged more robust than linear logarithmic regressions involving the gas/particle partition coefficient, because the latter is sensitive to the applied blank correction, tends to ignore a significant amount of analytical information, and gives undue weight to more uncertain data points. The experimental data fit was good for both nonlinear models, and discrepancies between experimental data and models and between models are mostly related to sampling/experimental artifacts. In particular, samples taken close to the freezing point appear to suffer from blow-off artifacts. Applying slopes m different from -1 appears only justified if it can be assured that a second parameter indeed provides a better fit and that this better fit is not due to experimental, analytical, or statistical artifacts. The magnitude of the differences in the model fitting parameters between sampling events is consistent with the reported variability in the nature and concentration of atmospheric particles. Statistical tests on the regression results indicate that the gas/particle partitioning was not significantly different between the forest and the clearing. © 2006 American Chemical Society.