Density separation-Raman spectroscopic quantification of microplastic-antibiotic co-contamination and transport in plastic-mulched agricultural soils.

Abstract

Plastic-mulched soils contain mineral particles, organic matter and weathered polymer fragments that complicate the joint measurement of microplastics and co-occurring antibiotics. We developed a matrix-adaptive workflow combining sequential Fenton-enzymatic digestion, ZnCl₂/NaI cascade density separation, silver-membrane collection, µ-Raman chemical imaging and isotope-dilution LC-MS/MS. Performance was evaluated with four agricultural soils, four mulch-relevant polymers, two particle-size fractions, pristine and aged surfaces, and tetracycline, ciprofloxacin and sulfamethoxazole. Across 2304 independent particle-spike observations, mean microplastic recovery was 93.72 ± 3.17% (95% confidence interval, 93.59-93.85%), within-laboratory relative standard deviations were 2.5-3.4%, and Raman classification accuracy was 96.25%. Antibiotic recovery across 432 observations was 95.31 ± 3.61%; matrix effects ranged from -14.2 to 5.3%, while matrix-matched calibration gave R² values of 0.9995-0.9998. Pyrolysis GC-MS confirmed Raman-derived mass estimates (R² = 0.9897), with a mean inter-platform bias of 0.022 mg. Aging increased XPS O/C ratios, AFM roughness and BET area and nearly doubled Langmuir capacities; aged polyamide reached 32.66 mg g^-1 for tetracycline. In saturated columns, pristine polyethylene slightly advanced breakthrough, whereas aged polyethylene and polyamide shifted the 50% breakthrough point from 2.34 pore volumes without microplastics to 2.86 and 3.22 pore volumes, respectively. Factorial and mixed-effects analyses, multiplicity-controlled contrasts, grouped cross-validation and an uncertainty budget supported the method's cross-matrix robustness. The workflow provides a quantitative basis for linking analytical recovery, particle surface chemistry and contaminant migration in complex agricultural soils.