RESUMEN

The addition of organic wastes is a common agronomic practice in some Mediterranean regions to increase soil organic matter. In addition, they consume high amounts of agrochemicals. Hand-packed soil columns were used to evaluate the effect of three different composted organic soil amendments (agro-forestry, agro-industrial and animal manure) on the leachability of eight persistent herbicides. A new leaching index based on the amounts recovered from leachates and referred as Experimental Leaching Index (ELI) is proposed according to the mean annual precipitation in a specific place. This index is compared with others such as Groundwater Ubiquity Score (GUS), Relative Leaching Potential Index (RLPI) and Leachability Index (LIX), which only include degradation (DT50) and sorption (KOC) parameters. According to ELI, metribuzin is very mobile in all cases, while terbuthylazine, chlorotoluron and isoproturon present high leachability only in unamended soil reducing their leaching potential in amended soils. Aclonifen, oxyfluorfen, trifluralin and pendimethalin behave in all cases as immobile (non-leacher) compounds.

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RESUMEN

In the present study, the structural parameters of 209 types of polymethoxylated diphenyl ethers (PMeODEs), 209 types of polyhydroxylated diphenyl ethers (PHODEs), seven types of methoxylated-polychlorinated diphenyl ethers (MeO-PCDEs) and seven types of hydroxylated-polychlorinated diphenyl ethers (HO-PCDEs) were calculated using the Gaussian 09 program at the B3LYP/6-311G** level. Using structural and positional parameters as descriptors, quantitative structure-property relationships (QSPR) models for the prediction of n-octanol/water partition coefficient (logKow) and soil sorption coefficient normalized to organic carbon (logKoc) were established and verified. The position parameters N2(6), N3(5) and N4 were the main positional factors influencing logKow and logKoc of PMeODEs and PHODEs. The molecular polarizability α was entered into the QSPR models of the logKow and logKoc of PMeODEs, PHODEs and MeO/HO-PCDEs, indicating that the molecular volume could influence the two environment-related properties of DEs significantly. All of the established QSPR models showed good goodness-of-fit, robustness, and predictive ability. The two models for all of the tested DEs are slightly inferior compared with the models for only a class of compounds. In addition, application domain analysis indicated that the models reliably predicted the logKow and logKoc of the mon- to hexa-DEs.

RESUMEN

We predict the soil sorption coefficient for a heterogeneous set of 643 organic non-ionic compounds by means of Quantitative Structure-Property Relationships (QSPR). A conformation-independent representation of the chemical structure is established. The 17,538 molecular descriptors derived with PaDEL and EPI Suite softwares are simultaneously analyzed through linear regressions obtained with the Replacement Method variable subset selection technique. The best predictive three-descriptors QSPR is developed on a reduced training set of 93 chemicals, having an acceptable predictive capability on 550 test set compounds. We also establish a model with a single optimal descriptor derived from CORAL freeware. The present approach compares fairly well with a previously reported one that uses Dragon descriptors.

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