From separation to identification: Microplastic detection and analyses in soils

Abstract

Microplastics (MPs) detection in soil environments presents unique analytical challenges due to matrix complexity and diverse particle characteristics. This review comprehensively examines current technologies and methodological approaches for detecting and characterizing MPs in soil matrices. Sample preparation techniques, including physical pretreatment, chemical digestion, and various separation methods such as density-based, electrostatic, oil-based, and magnetic separation, are critically evaluated. The review highlights how different analytical methods, from traditional microscopy to advanced spectroscopic techniques, complement each other in MP identification and quantification. Recent developments in artificial intelligence and deep learning applications for automated MP analysis are also discussed. The distribution patterns of MPs across different soil environments reveal significant variations, with agricultural soils showing concentrations ranging from 420–1290 particles/kg, urban soils containing 1750–12,200 particles/kg, and specialized ecosystems exhibiting unique MP profiles. Regional hotspots of MP contamination are identified, particularly in areas with intensive agricultural practices and inadequate waste management. The review emphasizes how both anthropogenic activities and natural factors influence MP abundance and characteristics in soils, with polymer types predominantly consisting of polyethylene, polypropylene, and polyvinyl chloride. This comprehensive analysis provides insights into current methodological advances while highlighting areas requiring further research and standardization in soil MP analysis.