Model development to predict transformation of sulfonylureas in different matrices was carried out using multiple linear regression. Descriptors for lipophilicity and molecular topology, as well as quantum chemical descriptors for energy, geometry, polarity, charges and reactivity using MOPAC with three different Hamiltonians, AM1, PM3 and MNDO, were calculated. In addition, experimental descriptors were measured and taken from the literature. End-points were transformation rates of twelve sulfonylurea herbicides in buffers at different pH (4, 7 and 10), in sterile and native sediments, and in sterile and native soil. Inter-correlation of reaction rates indicated four different groups of transformation types, for which sum parameters were calculated. (1) Hydrolysis at pH 4 could be estimated with pKa and charges at a specific atom of the heterocycle. (2) Hydrolysis at pH 7 and 10, as well as transformation in sterile sediments and soil, could be described with descriptors for reactivity (polarisability and superdelocalisability) at specific atoms of the molecules. (3) For transformation in native sediments different models could be found, all based on descriptors for polarisability, superdelocalisability and charges at specific atoms. (4) Modelling of biotransformation in native soil led to diverse models with a variety of descriptors reflecting electronic properties and lipophilicity. Models confirmed previous findings on reaction mechanisms and thereby prove valuable not only for quantitative prediction of reaction rates, but also for studies on transformation pathways.
© 2002 Society of Chemical Industry
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