Quantitative predictive models for octanol-air partition coefficients of polybrominated diphenyl ethers at different environmental temperatures (T) were developed. Partial least squares (PLS) regression was used for model development. A list of 18 theoretical molecular structural descriptors was screened by PLS analysis. The optimal model was selected from the one containing nine theoretical molecular descriptors and 1/T as predictor variables. The crossvalidated Q(cum)(2) value for the optimal model is 0.975, indicating a good predictive ability and stability of the model. Intermolecular dispersive interactions play a leading role in governing the magnitude of logK(OA). The lower the E-LUMO (the energy of the lowest unoccupied molecular orbital), the greater the intermolecular interactions between octanol and PCB molecules, and thus the greater the logK(OA) values.