Prediction of gas-particle partitioning of polycyclic aromatic hydrocarbons based on M5' model trees

• Main Authors: Radonić Jelena R., Ćulibrk Dubravko R., Vojinović-Miloradov Mirjana B., Kukić Branislav P., Turk-Sekulić Maja M.
• Format: Article
• Language: English
• Published: VINCA Institute of Nuclear Sciences 2012-01-01
• Series: Thermal Science
• Subjects: ambient air; high volume sampling; gas-particle partitioning; polycyclic aromatic hydrocarbons; M5'model trees; data mining
• Online Access: http://www.doiserbia.nb.rs/img/doi/0354-9836/2012/0354-98361202551R.pdf

During the thermal combustion processes of carbon-enriched organic compounds, emission of polycyclic aromatic hydrocarbons into ambient air occurs. Previous studies of atmospheric distribution of polycyclic aromatic hydrocarbons showed low correlation between the experimental values and Junge-Pankow theoretical adsorption model, suggesting that other approaches should be used to describe the partitioning phenomena. The paper evaluates the applicability of multivariate piece-wise-linear M5' model-tree models to the problem of gas-particle partition­ing. Experimental values of particle-associated fraction, obtained for 129 ambient air samples collected at 24 background, urban, and industrial sites, were compared to the prediction results obtained using M5' and the Junge-Pankow model. The M5' approach proposed and models learned are able to achieve good correlation (cor­relation coefficient >0.9) for some low-molecular-weight compounds, when the target is to predict the concentration of gas phase based on the particle-associated phase. When converted to particle-bound fraction values, the results, for selected compounds, are superior to those obtained by Junge-Pankow model by several or­ders of magnitude, in terms of the prediction error.