THERMAL SCIENCE
International Scientific Journal
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PREDICTION OF GAS-PARTICLE PARTITIONING OF PAHS BASED ON M5’ MODEL TREES
ABSTRACT
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. This article has been retracted. Link to the retraction 10.2298/TSCI121205224E
KEYWORDS
ambient air, high volume sampling, gas-particle partitioning, polycyclic aromatic hydrocarbons, M5' model trees, data mining
PAPER SUBMITTED: 2010-08-09
PAPER REVISED: 2010-11-25
PAPER ACCEPTED: 2010-12-24
DOI REFERENCE: https://doi.org/10.2298/TSCI1202551R
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