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a Dep. of Soil Science, North Dakota State Univ., Fargo, ND 58105
b USDA-ARS, Animal Metabolism-Agricultural Chemicals Research, Biosciences Research Lab., Fargo, ND 58105
* Corresponding author (francis.casey{at}ndsu.edu)
Received for publication October 16, 2006. Testosterone is an endocrine disruptor that is released into the environment from natural and anthropogenic sources. The objective of this study was to achieve a better understanding of the complex fate and transport of this labile compound in an undisturbed agricultural soil (a Hamar Sandy, mixed, frigid typic Endoaquolls). This was done by using batch and miscible-displacement experiments, and by using a chemical nonequilibrium transport model. Sorption and transformations of testosterone were discerned using various batch experiments. The batch experiments indicated that the aqueous phase concentrations of testosterone rapidly decreased from 12 to 15% of the initial aqueous concentration within 5 h, but then gradually increased through time and reached 28 to 29% of the initial aqueous concentration at 168 h. The increase in the aqueous concentration was explained by mineralization and biodegradation. Multiple first-order models were used to describe batch experiments where simultaneous degradation and sorption processes occurred. An evolutionary global optimization strategy was used to estimate the process parameters from these batch experiments and there was high confidence in these parameter estimates. The result of column experiments also showed that 23.4% of testosterone was mineralized to CO2 as it transported through the column. Combustion analyses of extracted soil from inside the columns showed that most of the 14C retained in the column (6974%) was sorbed in the top 5 cm. The independently determined batch parameters were incorporated into a chemical nonequilibrium transport model, which provided an excellent description of the hormone in the effluent, and vertical redistribution in the soil column.
Abbreviations: LO, local optimization OC, organic carbon ODE, ordinary differential equation SRES, stochastic ranking evolutionary strategy SSQ, sum-of-squares residuals TLC, thin-layer chromatography
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