Prediction of the retentions of polybrominated dibenzo-p-dioxins (PBDDs) by using the retentions of polychlorinated dibenzo-p-dioxins (PCDDs)

The retention equations In k' = A + B/T of 49 polychlorinated dibenzo-p-dioxins (PCDDs) and 4 polybrominated dibenzo-p-dioxins (PBDDs) in gas chromatography (GC) have been investigated to evaluate the properties of regression coefficients A and B. The quantitative relationships between A and B values of PCDDs and those of PBDDs are found. The regression equations derived have correlation coefficients greater than 0.997. The A, B values of any PBDD can be predicted by using the A, B values of the PCDD according to these relationships. Using these predicted A and B values, the retention times of all PBDDs can be predicted at any temperature program. It is very useful to identify the peak position of any PBDD because at present there are only a few standards of PBDDs available.     

Peak identification for PCDD/Fs in environmental samples at different temperature programs

A method has been developed for peak recognition of 136 polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) at different temperature programs. Their retention behaviours are predicted on the basis of an identification database of retention values (A, B) of gas chromatography. By the retention times of 13C labelled 2,3,7,8-substituted PCDD/F internal standards, the retentions of all PCDDs and PCDFs can be calculated. After comparison with the retentions of practical environmental samples, the predicted values have been proved to be very accurate.     

A new method of predicting of gas chromatographic retention indices for polychlorinated dibenzofurans (PCDFs)

A new method has been developed to describe the quantitative relationship between molecular structures of PCDFs and their gas chromatographic retention indices on a 30-m fused silica column coated with DB-5 stationary phase. The regression equation is derived with a multiple correlation coefficient greater than 0.9995. The highest residual is 20 index units. The standard deviation is less than 7 index units. Using this regression equation, the retention indices of PCDFs for which data is not available have also been predicted.     

Octanol–air partition coefficients of polybrominated biphenyls

The octanol–air partition coefficients (K_OA) for PBB15, PBB26, PBB31, PBB49, PBB103 and PBB153 were determined as a function of temperature using a gas chromatographic retention time technique with 1,1,1-trichloro-2,2-bis (4-chlorophenyl) ethane (p,p′-DDT) as a reference substance. The internal energies of phase change from octanol to air (Δ_OAU) were calculated for the six compounds and were in the range from 74 to 116 kJ mol⁻¹. Simple regression equations of log K_OA versus relative retention times (RRTs) on gas chromatography (GC), and log K_OA versus molecular connectivity indexes (MCI) were obtained, for which the correlation coefficients (r²) were greater than 0.985 at 283.15 K and 298.15 K. Thus the K_OA values of the remaining PBBs can be predicted by using their RRTs and MCI according to these relationships.     

Prediction of octanol--air partition coefficients of semivolatile organic compounds based on molecular connectivity index

A new method has been developed to describe the quantitative relationship between the octanol-air partition coefficients and molecular connectivity indexes of semivolatile organic compounds such as polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated naphthalenes (PCNs), polycyclic aromatic hydrocarbons (PAHs), chlorobenzenes (CBs), polybrominated diphenyl ethers (PBDEs). The stepwise multiple linear regression was used to derive six equations with correlation coefficients greater than 0.99 except for PBDEs' (0.96). The largest relative error is 4.6%, and the standard deviation is less than 1.83 log units. Compared with the data obtained from the relevant experiments, the results of prediction are very accurate.     

Correlation relationships between physico-chemical properties and gas chromatographic retention index of polychlorinated-dibenzofurans

Correlation relationships between physico-chemical properties including vapor pressures (P), water solubilities (S), Henry's law constants (H(c)), n-octanol-water partition coefficients (K(ow)), sediment-water partition coefficient (K(pw)) and biotic lipid-water partition coefficient (K(bw), bioconcentration factor) of polychlorinated-dibenzofurans (PCDFs) and their gas chromatographic retention indices (GC-RIs) were established. A model equation between GC-RIs (= RI) and these physico-chemical properties (K) of PCDFs was in a form of log K = aRI2 + bRI + c with correlation coefficients (R2) greater than 0.94, except H(c). These equations were derived from six experimental data (five experimental data for log K(bw)) in each physico-chemical properties of PCDFs reported previously. The values of log P, log S, log H(c), log K(ow), log K(pw) and log K(bw) of PCDFs predicted by these equations based on their GC-RIs in the present study derviated from those calculated by the solubility parameters for fate analysis method in a previous study by 0.49, 0.32, 0.11, 0.34, 0.14 and 0.22 log units, respectively.     

QSPR prediction of chromatographic retention times of pesticides: Partition and fractal indices

The high‐performance liquid‐chromatographic retentions of red‐wine pesticide residues are modeled by structure–property relationships. The effect of different types of features is analyzed: geometric, lipophilic, etc. The properties are fractal dimensions, partition coefficient, etc., in linear and nonlinear correlation models. Biological plastic evolution is an evolutionary perspective conjugating the effect of acquired characters and relations that emerge among the principles of evolutionary indeterminacy, morphological determination and natural selection. It is applied to design the co‐ordination index that is used to characterize pesticide retentions. The parameters used to calculate the co‐ordination index are the molar formation enthalpy, molecular weight and surface area. The morphological and co‐ordination indices barely improve the correlations. The fractal dimension averaged for non?buried atoms, partition coefficient, etc. distinguishes the pesticide molecular structures. The structural and constituent classification is based on nonplanarity, and the number of cycles, and O, S, N and Cl atoms. Different behavior depends on the number of cycles.     

A noval method of predicting soil organic carbon content normalized adsorption coefficients (Koc) of polybrominated biphenyls (PBBs)

By a soil column liquid chromatograph (SCLC) method, the soil organic carbon content normalized adsorption coefficients (K(oc)) of six polybrominated biphenyls (PBB15, PBB26, PBB31, PBB49, PBB103 and PBB153) are determined. Based on the similarity between the molecular structures of PBBs and PCBs, a simple linear predictive model has been developed with the correlation coefficient R=0.9812 and standard error SE=0.19. The logK(oc) values of any PBB congeners can be predicted by using the logK(oc) values of the corresponding PCBs according to this model. Using the published data for logK(oc) values of PCB congeners, logK(oc) values of all 209 PBB congeners have been for the first time predicted. Compared with the data obtained from the experiment, the results of prediction are very accurate.     

Alternatives for the determination of the soil adsorption coefficient, KOC, of non-ionicorganic compounds - a review

The determination of the soil adsorption behaviour of an environmental chemical is very important to the evaluation of potential dangers for man and nature. One of the major problems for European regulators working in the field of environmental protection and risk assessment is the lack of complete and comparable soil sorption data, e.g. K_oc values. The large number of existing chemicals makes it necessary to develop and apply fast methods as an alternative to classical batch or column studies. Based on this context numerous approaches to estimate K_oc have been published during the past two decades.

In this paper more than 200 existing relationships for K_oc estimations have been reviewed and divided into four categories. Regression equations for the most important classes of non-ionic organic environmental chemicals able to estimate soil adsorption coefficients are summarised, and the advantages and drawbacks of the different approaches are discussed briefly.

Due to the fact that a broad application of the proposed approaches is limited by the quality and comparability of the underlying experimental K_oc values reference soils are postulated to create a common basis for the comparison of soil adsorption coefficients.     

酯类化合物对四膜虫毒性的拓扑研究

提出了拓扑方法,即考虑分子图顶点的性质,直接用酯类化合物的分子碎片的特征值为主元来构建邻接矩阵。定义并计算了酯类化合物的修正的氢连接性指数^mHA及其倒指数^mHB,分析了30个酯化合物对四膜虫的毒性与分子结构之间的关系,结果表明由酯化合物对四膜虫毒性与^mH的回归方程得出的估算值与实验测定值之间能较好地吻合,平均误差为0．22。     

Solvophobic approach for predicting sorption of hydrophobic organic chemicals on synthetic sorbents and soils

The application of a solvophobic approach for predicting the sorption of hydrophobic organic compounds (HOC) was evaluated with data collected using synthetic sorbents and soils. The experimental data consisted of batch equilibrium sorption coefficients (K_D), as well as soil-TLC and reversed-phase liquid chromatographic (RPLC) retention factors (κ′). All data were collected using aqueous solutions and binary or ternary solvent mixtures of water, methanol, acetone, and acetonitrile. As predicted by the theory, the chromatographic retention factors and sorption coefficients for HOC decreased log-linearly with increasing fraction of organic cosolvent in binary solvents. Model parameters estimated from the binary solvent data could be used to predict sorption (or retention) from ternary solvents. Reasonable agreement was found between model parameters reported in the literature and those estimated using the data from batch sorption, soil-TLC, and RPLC studies.     

Chromatographic retention-activity relationships for prediction of the toxicity pH-dependence of phenols

An investigation of the use of the chromatographic retention (log k) as an in vitro approach for modeling the pH-dependence of the toxicity to Guppy of phenols is developed. A data set of 19 phenols with available experimental toxicity-pH data was used. The importance of the mechanism of toxic action (MOA) of phenols was studied. log k data at three pH values were used for the phenols classification and two groups or 'MODEs' were identified. For one 'MODE' a quantitative retention-activity relationship (QRAR) model was calculated. Finally, the model was used to assess the toxicity to Guppy of phenols at different pH values. The results of this investigation suggest that chromatographic retention data allows fish toxicity modeling, in the 5.5-8 pH range of interest.