Conde Cid, ManuelNóvoa Muñoz, Juan CarlosNúñez Delgado, AvelinoFernández Sanjurjo, María J.Arias Estévez, ManuelÁlvarez Rodríguez, Esperanza2025-01-162025-01-162019Conde-Cid, M., Nóvoa-Muñoz, J. C., Núñez-Delgado, A., Fernández-Sanjurjo, M. J., Arias-Estévez, M., & Álvarez-Rodríguez, E. (2019). Experimental data and modeling for sulfachloropyridazine and sulfamethazine adsorption/desorption on agricultural acid soils. Microporous and Mesoporous Materials, 288, 1-10. https://doi.org/10.1016/j.micromeso.2019.109601https://hdl.handle.net/10347/38649This is the author’s version of the work. The definitive version was published in Microporous and mesoporous materials, vol. 288 (2019), available online at: https://doi.org/10.1016/j.micromeso.2019.109601Taking 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.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Adsorption/desorptionAntibioticsCrop soilsRegression modelsSulfonamidesjournal article10.1016/j.micromeso.2019.1096011873-3093open access