Deriving parametric and probabilistic K_d values for fluoroquinolones in soils.

Area of Science:

• Environmental Chemistry
• Soil Science
• Pharmaceutical Science

Background:

• Fluoroquinolone antibiotics (FQs) are emerging contaminants with potential environmental mobility.
• Accurate assessment of FQ sorption in soils is crucial for predicting their environmental fate.
• Solid-liquid distribution coefficients (K_d) are key parameters for evaluating FQ sorption affinity.

Purpose of the Study:

• To develop predictive tools for K_d (FQ) in soils.
• To construct a comprehensive K_d (FQ) sorption dataset from literature and new experimental data.
• To investigate the influence of soil properties and FQ characteristics on sorption behavior.

Main Methods:

• Compiled a dataset of 312 K_d (FQ) entries from literature and experimental data.
• Conducted sorption and desorption experiments for norfloxacin, ciprofloxacin, enrofloxacin, and ofloxacin in diverse soils.
• Developed a Partial Least Square (PLS) regression model incorporating soil properties (pH, CEC, OC, texture) and FQ properties (cationic fraction).
• Utilized cumulative distribution functions (CDFs) to derive probabilistic K_d (FQ) best estimates.

Main Results:

• Norfloxacin sorption isotherms were linear; desorption increased with lower sorption.
• Comparable K_d (FQ) values were observed among the tested FQs.
• PLS model successfully predicted K_d (FQ) values based on soil and FQ properties.
• Probabilistic estimates provided more representative K_d (FQ) values with lower variability.
• Strong FQ sorption (K_d > 1000 L kg^-1) was predicted for acidic to neutral soils.
• Lower sorption and higher mobility were predicted for alkaline soils with low organic carbon and high sand content.

Conclusions:

• Soil properties significantly influence FQ sorption and environmental mobility.
• Predictive models and probabilistic approaches enhance the assessment of FQ fate in soils.
• Understanding FQ sorption is vital for managing risks associated with antibiotic contamination in the environment.