Mobility and fate of carbetamide in an agricultural soil

Wide-range and accurate modeling of linear alkylbenzene sulfonate (LAS) adsorption/desorption on agricultural soil

In this paper, rigorous data and adequate models about linear alkylbenzene sulfonate (LAS) adsorption/desorption on agricultural soil are presented, contributing with a substantial improvement over available adsorption works. The kinetics of the adsorption/desorption phenomenon and the adsorption/desorption equilibrium isotherms were determined through batch studies for total LAS amount and also for each homologue series: C10, C11, C12 and C13. The proposed multiple pseudo-first order kinetic model provides the best fit to the kinetic data, indicating the presence of two adsorption/desorption processes in the general phenomenon. Equilibrium adsorption and desorption data have been properly fitted by a model consisting of a Langmuir plus quadratic term, which provides a good integrated description of the experimental data over a wide range of concentrations. At low concentrations, the Langmuir term explains the adsorption of LAS on soil sites which are highly selective of the n-alkyl groups and cover a very small fraction of the soil surface area, whereas the quadratic term describes adsorption on the much larger part of the soil surface and on LAS retained at moderate to high concentrations. Since adsorption/desorption phenomenon plays a major role in the LAS behavior in soils, relevant conclusions can be drawn from the obtained results.

Evaluation of Linear Alkylbenzene Sulfonate (LAS) behaviour in agricultural soil through laboratory continuous studies

The behaviour of Linear Alkylbenzene Sulfonate (LAS) in agricultural soil is investigated in the laboratory using continuous-flow soil column studies in order to simultaneously analyze the three main underlying phenomena (adsorption/desorption, degradation and transport). The continuous-flow soil column experiments generated the breakthrough curves for each LAS homologue, C10, C11, C12 and C13, and by adding them up, for total LAS, from which the relevant retention, degradation and transport parameters could be estimated, after proposing adequate models. Several transport equations were considered, including the degradation of the sorbate in solution and its retention by soil, under equilibrium and non-equilibrium conditions between the sorbent and the sorbate. In general, the results obtained for the estimates of those parameters that were common to the various models studied (such as the isotherm slope, first order degradation rate coefficient and the hydrodynamic dispersion coefficient) were rather consistent, meaning that mass transfer limitations are not playing a major role in the experiments. These three parameters increase with the length of the LAS homologue chain. The study will provide the underlying conceptual framework and fundamental parameters to understand, simulate and predict the environmental behaviour of LAS compounds in agricultural soils.

Do lab-derived distribution coefficient values of pesticides match distribution coefficient values determined from column and field-scale experiments? A critical analysis of relevant literature

In this study, we analyzed sorption parameters for pesticides that were derived from batch and column or batch and field experiments. The batch experiments analyzed in this study were run with the same pesticide and soil as in the column and field experiments. We analyzed the relationship between the pore water velocity of the column and field experiments, solute residence times, and sorption parameters, such as the organic carbon normalized distribution coefficient ( ) and the mass exchange coefficient in kinetic models, as well as the predictability of sorption parameters from basic soil properties. The batch/column analysis included 38 studies with a total of 139 observations. The batch/field analysis included five studies, resulting in a dataset of 24 observations. For the batch/column data, power law relationships between pore water velocity, residence time, and sorption constants were derived. The unexplained variability in these equations was reduced, taking into account the saturation status and the packing status (disturbed-undisturbed) of the soil sample. A new regression equation was derived that allows estimating the values derived from column experiments using organic matter and bulk density with an value of 0.56. Regression analysis of the batch/column data showed that the relationship between batch- and column-derived values depends on the saturation status and packing of the soil column. Analysis of the batch/field data showed that as the batch-derived value becomes larger, field-derived values tend to be lower than the corresponding batch-derived values, and vice versa. The present dataset also showed that the variability in the ratio of batch- to column-derived value increases with increasing pore water velocity, with a maximum value approaching 3.5.