Quantitative structure-property relationships (QSPR) were developed using a genetic algorithm (GA)-based variable-selection approach with quantum chemical descriptors derived from AM1-based calculations (MOPAC7.0). With the QSPR models, the aqueous solubility of 71 aromatic sulfur-containing carboxylates, including phenylthio, and phenylsulfonyl carboxylates were efficiently estimated and predicted. Using GA-based multivariate linear regression (MLR) with cross-validation procedure, the most important descriptors were selected from a pool of 28 quantum chemical semi-empirical descriptors, including steric and electronic types, to build QSPR models. The molecular descriptors included molecular surface

Polychlorinated organic compounds (PCOCs) were analyzed in Yangtse River sediments. The results show that the concentrations of PCOCs in Yangtse River sediments followed the order of DDTs >HCB>HCHs >PCBs. High PCOCs concentrations were detected in sediments from station Y02a and Y02b, which are located in the main input of the Yangtse River (Nanjing section). Results also show that the PCOCs values were highly correlated with organic carbon content and heavy metal contamination.

The combination of ultrasound (US) and photochemistry has been used to degrade an aqueous solution of phenol. It was considerably more effective than ultrasound or ultraviolet (UV) light alone. Based on the results of total organic carbon (TOC) removal, it was shown that the synergistic action of ultrasound and ultraviolet light existed. Identification of the first intermediates of the reaction (hydroquinone, catechol, benzoquinone and resorcin) indicates that OH radicals are involved in the photosonochemical degradation mechanisms. The effects of parameters such as pH, saturating gases, and Fe2+on the photosonochemical degradation have been studied. The experimental results have shown that lower pH and higher concentration of dissolved oxygen favor the phenol degradation and that the presence of Fe2+enhanced TOC removal of phenol solutions

The photocatalytic degradation performance of photocatalysts TiO2 supported on 13-X, Na-Y, 4A zeolites with di erent loading content was evaluated using the photocatalytic oxidation of dyes direct fast scarlet 4BS and acid red 3B in aqueous medium. The results showed that the best reaction dosage of TiO2-zeolite catalysts is about 2g/l and the photocatalytic kinetics follows

Polychlorinated biphenyls (PCBs) congeners with various degrees of chlorination and substitution patterns are among the most widespread and persistent man-made organic pollutants. They are toxic, lipophilic and tend to be bioaccumulated. The knowledge of the physico-chemical properties is very useful to explain the environmental behavior of PCBs and to perform an exposure assessment. In this paper, we have used a new molecular representation, the molecular hologram, to generate quantitative structure-property relationship models to predict the physico-chemical properties of biphenyl and all of its chlorinated congeners. The investigated properties include 1-octanol/water partition coefficient (log Kow), aqueous solubility (log Sw), aqueous activity coefficient (log Yw), Total molecular surface area, Henry s law constant (logH). The results show that this new quantitative structure-activity relationship approach presents highly predictive models for important physico-chemical properties of PCBs.