Partitioning Of Volatile Organic Compounds From Air Into Plant

Following predecessors' work, a new quantitative structure property relationship (QSPR) model was developed to predict the partitioning of some volatile organic compounds (VOCs) between the plant cuticular matrix and air based on theoretical linear solvation energy relationship (TLSER) and quantum chemical descriptors computed by MOPAC software.The model took all outfield electrons of compounds into account generally and employed a new descriptor Qmax that was defined as the net charge of the most negative atom of the compound. The results showed that with the new parameter employed, the various parameters used were less self-correlated and the predicted results were more accurate. The model had an excellent correlation and the results indicated that the model could successfully describe the partitioning of VOCs between the plant cuticular matrix and air. And also the model gave insight into the behavior of the plant cuticle.Furthermore, the partitioning of VOCs between plant organism and air in semi-natural situation was studied. Partitioning coefficients (KpA) of some VOCs between leaves of Chinese Rose (Rosa chinensis} and air were measured by headspace gas phase equilibrium. A theoretical predicting model was established using quantum chemical descriptorscomputed by PM3 based on TLSER. It could be concluded from the results that electrophilicity, molecular size, nucleophilicity of compounds played most important roles in the partitioning process. In the scope of the experiment, chemical compounds with larger molecular size were more prone to be taken in the leaves of Chinese Rose.The experiment and results proved that quantum parameters could be used successfully to predict the partitioning process.