Assessing sorption of fluoroquinolone antibiotics in soils from a Kd compilation based on pure organic and mineral components

• Published in: Ecotoxicology and environmental safety Vol. 280; p. 116535
• Main Authors: Fabregat-Palau, Joel, Rigol, Anna, Grathwohl, Peter, Vidal, Miquel
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 15.07.2024; Elsevier
• Subjects: antibiotic resistance; cumulative distribution; data collection; desorption; ecotoxicology; Fluoroquinolones; human health; Humic substances; Metal oxides; Phyllosilicate minerals; Soil; Sorption; species; surface area; zwitterions; Fluoroquinolones; Sorption; Metal oxides; Soil; Humic substances; Phyllosilicate minerals
• ISSN: 0147-6513; 1090-2414; 1090-2414
• DOI: 10.1016/j.ecoenv.2024.116535

The presence of fluoroquinolone (FQ) antibiotics in soils may cause a threat to human health due to overexposure and the generation of antibiotic resistance genes. Understanding their sorption behavior in soils is important to predict subsequent FQ (bio) availability. Here, FQ sorption in pure soil organic (i.e., humic substances) and mineral (i.e., metal oxides; phyllosilicates) components is evaluated through a solid-liquid distribution coefficient (Kd (FQ)) dataset consisting of 243 entries originated from 80 different studies, to elucidate their respective contribution to the overall Kd (FQ) in bulk soils. First, different factors affecting FQ sorption and desorption in each of these soil phases are critically discussed. The strong role of pH in Kd (FQ), due to the simultaneous effect on both FQ speciation and surface charge changes, encouraged the derivation of normalized sorption coefficients for the cationic, zwitterionic and anionic FQ species in humic substances and in different phyllosilicates. Kd (FQ) in metal oxides revealed a key role of metal nature and material specific surface area due to complexation sorption mechanisms at neutral pH. Cumulative distribution functions (CDF) were applied to each dataset to establish a sorption affinity range for each phase and to derive best estimate Kd (FQ) values for those materials where normalized sorption coefficients to FQ species were unavailable. The data analysis conducted in the different soil phases set the basis for a Kd (FQ) prediction model, which combined the respective sorption affinity of each phase for FQ and phase abundance in soil to estimate Kd (FQ) in bulk soils. The model was subsequently validated with sorption data in well characterized soils compiled from the literature. •Sorption parameters of FQ in soil components are compiled from the literature.•pH-dependent normalized sorption coefficients for different FQ species and soil components are derived.•Sorption in metal oxides is ruled by complexation stability and specific surface area.•The sorption affinity in the different soil components is ranked through cumulative distribution functions.•Combining sorption affinity and abundance of soil components led to a good Kd (FQ) estimation.