Examines antibiotic sorption in sewage sludge, indicating the influence of sludge characteristics on environmental outcomes.
The sorption behavior of antibiotics in wastewater treatment systems plays a critical role in determining their environmental fate and removal efficiency. In this study, the sorption of 15 antibiotics representing multiple classes was investigated using two sewage sludge samples with different physicochemical characteristics. Batch equilibrium experiments were conducted to evaluate time-dependent sorption behavior and to determine solid–water distribution coefficients (Kd). The results showed that sorption occurred rapidly, with most compounds approaching a stable concentration within 24 h. The Kd values varied widely depending on the compound, ranging from 74 to 737 L/kg. For 13 of the 15 investigated antibiotics, higher Kd values were observed in sludge B than in sludge A, with the largest difference observed for tiamulin (402 ± 53 and 737 ± 76 L/kg for sludge A and sludge B, respectively). Sludge B generally exhibited higher sorption capacity for most compounds than sludge A, despite having a lower specific surface area, indicating that sorption was governed primarily by chemical composition and pore structure rather than surface area alone. Elemental and morphological analyses suggested that differences in metal-associated components and pore structure may contribute to the higher sorption capacity observed in sludge B. However, the specific sorption mechanisms could not be directly confirmed by the present analyses. Comparison with previous studies confirmed that the measured Kd values fall within reported ranges but are generally higher for sulfonamides, suggesting enhanced sorption capacity of the investigated sludge matrices. Application of an equilibrium-based model demonstrated that sorption alone can account for approximately 20–70% of antibiotic removal under typical activated sludge conditions, depending on compound affinity. These findings highlight the importance of sludge-specific properties in controlling antibiotic partitioning and demonstrate that incorporating such characteristics into predictive models can improve the accuracy of environmental fate assessments in wastewater treatment systems.
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Shin et al. (2026) studied this question.
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