Quantification of acetochlor degradation in the unsaturated zone using two novel in situ field techniques: comparisons with laboratory‐generated data and implications for groundwater risk assessments

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Abstract
Degradation of the herbicide acetochlor in the unsaturated zone was quantified using two unique in situ field techniques. The DT50 values generated at two different sites on surface soil and two subsoil depths using these techniques were compared with values generated under aerobic laboratory‐incubation conditions (typically 20 °C, 40% maximum water holding capacity). Additionally, laboratory‐degradation data were generated on surface and subsoils from four other sites. All subsoils were treated with acetochlor at 5% of the surface soil application rate. Acetochlor degradation in both field‐ and laboratory‐incubated subsoils was rapid and often exceeded surface soil rates. Field and laboratory DT50 values from all sites ranged from 2 to 88 days in subsoil, compared with a range of 1 to 18 days in surface soils. The DT50 results from in situ field techniques were comparable with those generated from laboratory incubations in the same soils, confirming the validity of performing laboratory‐based degradation studies to determine pesticide DT50 values in subsoils. Microbiological characterisation of selected soils revealed that subsoils had a viable and active population, although direct counts of bacteria were consistently lower in subsoil (108–109 g−1 dry soil) compared with surface soils (1010 g−1 dry soil). The leaching models used to perform groundwater risk assessments (eg PELMO, PESTLA, MACRO‐DB, PRZM and the FOCUS EU leaching scenarios) have provision for inclusion of subsoil degradation rates. However, conservative default estimates are typically used, as no other alternative is available. Results presented here show that these default values may significantly underestimate true subsoil degradation contributions, and therefore not accurately predict pesticide concentrations in groundwater. The degradation data generated for acetochlor were applied to the mathematical model PELMO to demonstrate the importance of the inclusion of subsoil degradation data in groundwater risk assessment models and thereby in the registration of pesticides in Europe. © 2001 Society of Chemical Industry