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1

Thermodynamic and physico-chemical descriptors of chloronaphthalenes: an attempt to select features explaining environmental behaviour and specific toxic effects of these compounds

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Falandysz J., Puzyn T., Szymanowska B., Kawano M., Markuszewski M., Kaliszan R., Skurski P., Blazejowski J., Wakimoto T.
Polish Journal of Environmental Studies
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2001
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tom 10
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nr 4
35 physico-chemical descriptors were used to characterize all 75 congeners of chloronaphthalene in terms of their environmental stability and specific dioxin-like toxicity. A prepared basic thermodynamic and physico-chemical property data matrix of PCNs was interpreted using Principal Component Analysis (PCA). The PCA of the thermodynamic and physico-chemical data matrix created a four-dimensional model that explained 76% (58% + 9% + 5% + 4%) of the total variance. The loading plot shows that the first PC is influenced by variables describing degree of chlorination, molecular weight, polarizability and lipophilicity. The best positively correlated descriptors are: retention time, standard molar entropy, heat capacity, a first-order molecular connectivity index, logarithm of octanol-water partition coefficient, the Wiener Index, specific polarizability, a third order shape index for molecules, the sum of absolute of the charges on each atom of the molecule, molecular weight, polarizability, refractivity, solvent-accessible surface, van der Waals surface, solvent-accessible volume, van der Waals volume. Negatively correlated descriptors are: standard enthalpy of formation and energy of HOMO. The second PC is strongly influenced by energy of LUMO, while substitution pattern parameters, number of chlorine atoms at a-positions and vicinal (adjacent) carbon atoms substitution pattern are less important parameters. The third PC depends on dipole moment and the largest negative charge, and on substitution at position 2 of naphthalene nuclei, while the symmetry group parameter is determined by PC4. There are small groups consisting of compounds which have similar values of LUMO energy and substitution pattern. The congeners of CN substituted with chlorine at positions 1, 2, 3, 6 and 7 (Fv/Fv PCN congeners), and next those substituted at positions 1, 2, 3 and 6 or 7 (Fr/Fv PCB congeners) are considered to be most potent in terms of dioxin-like toxicity, and followed by those substituted at four positions (Fr[Fv), at three positions (Tr/Fv) and so on. The thermodynamic stability of the congeners of CN depends on the number of attached chlorine and structure of the molecule. Among the 75 congeners of CN only a few, like PCN nos. 42, 560, 61, 66/67, are relatively resistant to biodegradation and biomagnify in animals occupying a higher position in the marine food web, and with a particular homologue group they are characterised by the lowest absolute values of energy of LUMO.
2

Isomer specific analysis of polychlorinated naphthalenes in pine trees [Pinus thunbergi Parl.] and [Pinus densiflora Sieb. et Zucc] needles around Tokyo Bay, Japan

100%
Hanari N., Horii Y., Taniyasu S., Falandysz J., Bochentin I., Orlikowska A., Puzyn T., Yamashita N.
Polish Journal of Environmental Studies
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2004
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tom 13
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nr 2
63 congeners of chloronaphthalene represented by 53 peaks fractionated and separated using two-dimensional HPLC and DB-17 capillary column were quantified using HRMS in ten samples of pine needles collected in 1999 around Tokyo Bay in Japan. Similarities and differences of chloronaphthalene concentrations and patterns between 10 sampling sites were studied using multivariate analysis. Total PCN concentrations ranged from 250 to 2100 pg/g wet weight. Except for one site, tri- and tetra-CNs highly dominated (from 54 to 80%) in CN homologue patterns of pine needles. At the easternmost site near the town of Tateyama in Chiba Prefecture the contribution from octaCN was ~20 %, while that of tri- and tetra-CNs ~42 %. Pine needles sampled from the sites around the innermost part of Tokyo Bay showed the highest load of PCNs. A multivariate analysis using the three most significant principal components explained 91% of the total variance in the measurement data. The greatest positive loading to PC1 is from the CN congeners nos. 13, 14/21/24, 15, 16, 17, 18, 19, 20, 22/23, 25, 26, 27, 28/36, 29, 30/32, 31, 33/34/37, 35, 40, 42, 43/45, 44, 47, 49, 50, 51, 52/60, 53, 57, 58, 59, 61, 62, 64, 65, 66/67, 68, 69, 71 and 72, and explains 65% variance in the data set. For PC2 the largest positive loading is from CNs nos.74 and 75, and negative load from CN nos. 38, 41, 46 and 48, which explains 17% of the variance. In case of PC3 the largest negative load is from CNs nos. 54, 56, 63, 70 and 73. A profile of the combustion process related CN congeners measured such as nos. 44, 48 and 54 didn’t show any specific trend implying pollution from diffused sources of various types.
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