4.7 Article

Rate constants of hydroxyl radical oxidation of polychlorinated biphenyls in the gas phase: A single-descriptor based QSAR and DFT study

Journal

ENVIRONMENTAL POLLUTION
Volume 211, Issue -, Pages 157-164

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.envpol.2015.12.044

Keywords

PCBs; Single-descriptor based QSAR; Polarizability; DFT; Hydroxyl radical

Funding

  1. National Nature Science Foundation of China [21507167]
  2. Hunan Provincial Key RD program [2015WK3014]

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The second order rate constants (k) of hydroxyl radical (center dot OH) with polychlorinated biphenyls (PCBs) in the gas phase are of scientific and regulatory importance for assessing their global distribution and fate in the atmosphere. Due to the limited number of measured k values, there is a need to model the k values for unknown PCBs congeners. In the present study, we developed a quantitative structure-activity relationship (QSAR) model with quantum chemical descriptors using a sequential approach, including correlation analysis, principal component analysis, multi linear regression, validation, and estimation of applicability domain. The result indicates that the single descriptor, polarizability (alpha), plays an important role in determining the reactivity with a global standardized function of lnk = -0.054 x alpha - 19.49 at 298 K. In order to validate the QSAR predicted k values and expand the current k value database for PCBs congeners, an independent method, density functional theory (DFT), was employed to calculate the kinetics and thermodynamics of the gas phase center dot OH oxidation of 2,4',5-trichlorobiphenyl (PCB31), 2,2',4,4'-tetrachlorobiphenyl (PCB47), 2,3,4,5,6-pentachlorobiphenyl (PCB116), 3,3',4,4',5,5'-hexachlorobiphenyl (PCB169), and 2,3,3',4,5,5',6-heptachlorobiphenyl (PCB192) at 298 K at B3LYP/6 -311++G**//B3LYP/6-31 G** level of theory. The QSAR predicted and DFT calculated k values for center dot OH oxidation of these PCB congeners exhibit excellent agreement with the experimental k values, indicating the robustness and predictive power of the single-descriptor based QSAR model we developed. (C) 2015 Elsevier Ltd. All rights reserved.

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