New Models for Estimating the Sorption of Sulfonamide and Tetracycline Antibiotics in Soils

Abstract

Sulfonamides (SAs) and tetracyclines (TCs) are two classes of widely used antibiotics. There is a lack of easy models for estimating the parameters of antibiotic sorption in soils. In this work, a dataset of affinity coefficients (Kf and Kd) of seven SA/TC antibiotics (i.e., sulfachlorpyridazine, sulfamethazine, sulfadiazine, sulfamethoxazole, oxytetracycline, tetracycline, and chlortetracycline) and associated soil properties was generated. Correlation analysis of these data showed that the affinity coefficients of the SAs were predominantly affected by soil organic matter and cation exchange capacity, while those of the TCs were largely affected by soil organic matter and pH. Pedotransfer functions for estimating Kf and Kd were built by multiple linear regression analysis and were satisfactorily validated. Their performances would be better for soils having higher organic matter content and lower pH. These pedotransfer functions can be used to aid environmental risk assessment, prioritization of antibiotics and identification of vulnerable soils.