QSPR-based prediction of gas/particle partitioning of polychlorinated biphenyls in the atmosphere

• Published in: Chemosphere (Oxford) Vol. 66; no. 10; pp. 1807 - 1820
• Main Authors: Wei, Binnian, Xie, Shaodong, Yu, Miao, Wu, Lei
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 2007; Elsevier
• Subjects: Air Pollutants - analysis; Air Pollutants - chemistry; Applied sciences; Atmosphere - analysis; Atmosphere - chemistry; Atmospheric pollution; Exact sciences and technology; Gas-particle partitioning; Gases - chemistry; Models, Theoretical; Molecular descriptor; Particulate Matter - chemistry; PCB; Phase Transition; PM3; Pollutants physicochemistry study: properties, effects, reactions, transport and distribution; Pollution; Polychlorinated Biphenyls - analysis; Polychlorinated Biphenyls - chemistry; Quantitative Structure-Activity Relationship; Quantitative structure–property relationship; Gas-particle partitioning; Quantitative structure–property relationship; Molecular descriptor; PCB; PM3; Prediction; Partition coefficient; Volatile organic compound; Molecular volume; Low volatile compound; Polychlorobiphenyl; Organic chlorine compounds; Persistent organic pollutant; Electronic structure; Chlorocarbon; Aerosols; Air pollution; Quantitative structure-property relationship; Aromatic compound; Phase partition; Property structure relationship; Molecular mass; Organic compounds
• ISSN: 0045-6535; 1879-1298
• DOI: 10.1016/j.chemosphere.2006.09.029

By reviewing the existing models for describing gas/particle partitioning of semi-volatile organic compounds in the atmosphere, it was assumed that gas/particle partition coefficient, expressed as
K
p, may be predicted using molecular descriptors. Overall 14 molecular descriptors of each compound calculated using semi-empirical method parametric model 3 (PM3) were tested against log
K
p of selected PCBs to determine the best ones governing partitioning. Eight descriptors molecular weight (
M
w), molecular volume (
M
v), total energy (TE), electronic energy (EE), squared atom electron densities on carbon, hydrogen and chlorine atoms in a given molecule
(
∑
q
C
2
,
∑
q
Cl
2
,
∑
q
H
2
)
and average molecular polarizability (
α
m) were found to be highly correlated with log
K
p compared to other molecular descriptors. Using Partial Least-Squares Regression method (PLS), two-, three- and four-descriptor QSPR models with high fitting characters were successfully developed and their robustness and predictive power were further validated by internal cross-validation and external test. Finally, the gas/particle partition coefficients of all 209 PCBs were predicted for the first time.