Experimental data and modeling for sulfachloropyridazine and sulfamethazine adsorption/desorption on agricultural acid soils
Taking into account that certain soil components could retain sulfonamides, in this work 50 crop soils (as porous materials) were studied as regards their adsorption/desorption characteristics for two sulfonamide antibiotics, specifically sulfamethazine (SMT) and sulfachloropyridazine (SCP), using b...
| Autores: | , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad de Santiago de Compostela (USC) |
| Repositorio: | Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela |
| Idioma: | inglés |
| OAI Identifier: | oai:minerva.usc.gal:10347/38649 |
| Acceso en línea: | https://hdl.handle.net/10347/38649 |
| Access Level: | acceso abierto |
| Palabra clave: | Adsorption/desorption Antibiotics Crop soils Regression models Sulfonamides |
| Sumario: | Taking into account that certain soil components could retain sulfonamides, in this work 50 crop soils (as porous materials) were studied as regards their adsorption/desorption characteristics for two sulfonamide antibiotics, specifically sulfamethazine (SMT) and sulfachloropyridazine (SCP), using batch-type experiments. Both adsorption and desorption curves fitted well to the Linear and Freundlich equations. Adsorption parameters showed low values for both antibiotics, indicating that a high mobility can be expected for these compounds in soils. In addition, adsorption parameters were lower for SMT than for SCP, due to their different degree of hydrophobicity. Soil organic carbon (OC) content was the soil characteristic showing the highest influence on adsorption and desorption processes for both sulfonamides. In fact, those soils having the highest OC content were the ones presenting the highest adsorption and the lowest desorption results. As next step, multiple linear regression analyses were carried out, which were used to develop robust model functions to predict the values of adsorption and desorption parameters for SCP and SMT. Input variables used to feed models were easily determinable soil characteristics, such as OC, cation exchange capacity, and pH. These models could facilitate a rapid and low-cost screening to find vulnerable soils, which will be those with the lowest values for the adsorption parameters. Having that information derived from simulations, an appropriate management could be programmed for most vulnerable soils, to minimize the entry of pollutants in different environmental compartments and, finally, into the food chain, thus reducing risks and impacts on human and environmental health. |
|---|