Polychlorinated biphenyls(PCBs), an important kind of toxic pollutant, are persistent in the environment and accumulative in many species. In this paper, based on the general interaction properties function (GIPF) family descriptors computed at the B3LYP/6-31G* level in Gaussian98 software, a significant quantitative structure-property relationships (QSRRs) models for the high resolution gas chromatographic relative retention time (HRGC-RRT) of all PCB congeners (N = 209) on 18 different HRGC capillary columns were constructed by using best multiple linear regression (BMLR) analysis, following the guidelines for development and validation of QSRR models. By means of the elimination selection stepwise regression algorithms, the molecular surface average local ionization energy was selected as one-parameter linear regression to develop a QSRR model for prediction of GC-RRT of PCBs on each stationary phase with a square correlation coefficient (R2) between 0.8691 and 0.9819. The root mean squares errors (RMSEs) over different 18 phases were within the range of 0.0135-0.0494. Also, the calculated molecular surface average local ionization energy showed a significant correlation with the number and positions (ortho, meta and para) of the chlorine substitutions, with leave-one-out cross-validation regression coefficient (R2cv) = 0.9857 and RMSE = 0.0085. Furthermore, the accuracy of all developed models was confirmed using procedures of Y-randomization, external validation through an odd-even number and division of the entire dataset into training and test sets. A successful interpretation of the complex relationship between HRGC-RRIs of PCBs and the chemical structures was achieved by QSRR.
