Prediction of biodegradability of aromatics in water using QSAR modeling.

The study was aimed at developing models for predicting the biodegradability of aromatic water pollutants. For that purpose, 36 single-benzene ring compounds, with different type, number and position of substituents, were used. The biodegradability was estimated according to the ratio of the biochemical (BOD) and chemical (COD) oxygen demand values determined for parent compounds ((BOD/COD)), as well as for their reaction mixtures in half-life achieved by UV-C/HO process ((BOD/COD)). The models correlating biodegradability and molecular structure characteristics of studied pollutants were derived using quantitative structure-activity relationship (QSAR) principles and tools. Upon derivation of the models and calibration on the training and subsequent testing on the test set, 3- and 5-variable models were selected as the most predictive for (BOD/COD) and (BOD/COD), respectively, according to the values of statistical parameters R and Q. Hence, 3-variable model predicting (BOD/COD) possessed R=0.863 and Q=0.799 for training set, and R=0.710 for test set, while 5-variable model predicting (BOD/COD) possessed R=0.886 and Q=0.788 for training set, and R=0.564 for test set. The selected models are interpretable and transparent, reflecting key structural features that influence targeted biodegradability and can be correlated with the degradation mechanisms of studied compounds by UV-C/HO.