Matrix Overloading Effects on Size-Resolved Quantification of Low-Concentration Nanoplastics in Complex Environmental...

Size-resolved quantification is essential for a comprehensive understanding of the fate, transport, and potential toxicity of nanoplastics in natural waters. However, this has been hindered by the ultralow concentrations of environmental nanoplastics. On-channel preconcentration via asymmetric flow field-flow fractionation (AF4) offers a promising approach to separate and quantify ultratrace environmental nanoplastics with minimal sample disruption. Analytical artifacts that arise when developing size-resolved quantification methods for environmental nanoplastics remain unexplored. Herein, a size-resolved quantification analysis was achieved to determine concentrations of nanoplastics across 20-200 nm under environmentally relevant conditions using AF4-UV. While strong linear correlations were observed between concentration and peak area, the calibration slope exhibited particle dependence for different polystyrene beads, primarily due to their distinct UV absorption coefficients. The limits of detection (LODs) achieved were ∼17 ng (corresponding to 17 μg L^-1 for a 1 mL injection volume) in pristine water matrices. However, coenrichment of environmental matrices (e.g., dissolved organic matter) induces severe overloading, elevating LODs in complex matrices (e.g., 25 and 45 ng for bottled drinking water and Yangtze River water samples, respectively). The accumulation of matrix components (e.g., dissolved organic matter, suspended particles) with larger injection volumes exacerbates membrane overloading and reduces recovery rates, thereby elevating the detection threshold for target nanoplastics. Advances in channel dimensions would enable greater particle loading, mitigating matrix overloading, and further reducing LODs. Resolving matrix overloading effects would establish AF4-based methods as a definitive tool for investigating nanoplastic pollution dynamics, bridging the gap for ultralow-concentration monitoring.