Identifying indicator polymers for traffic marking paint- and road-derived microplastics in environmental waters...

Reliable detection and source attribution of tire- and road-associated microplastics derived from polymer-modified asphalt and traffic marking paints (TRAMP-MPs) remain challenging in aquatic environments, despite increasing concern regarding their environmental occurrence. In this study, we present the first evaluation of an automated microplastic pretreatment (AMP) system for quantifying microplastics (MPs) and identifying low-abundance TRAMP-MPs in surface waters. The performance of AMP was assessed against a conventional general manual pretreatment (GMP) method using 10 surface-water samples collected from rivers affected by road runoff, a lake, and coastal sites in Tokyo Bay. The concentrations and size distributions of 17 polymer types larger than 300 μm were determined, and polymer compositions from 23 sampling sites were analyzed using principal component analysis (PCA). Total MP concentrations obtained by AMP closely agreed with those determined by GMP, ranging from 0.06 to 25.8 pieces m^-3. Notably, AMP enabled the consistent detection of low-abundance TRAMP-MPs, particularly polyethylene-ethyl acrylate copolymer (PEA) and urethane alkyd (UA), which are characteristic components of asphalt modifiers and traffic marking paints, respectively. PCA resolved three source-related polymer groups associated with road pavements, traffic marking paints, and general consumer products. River waters showed substantially higher concentrations of TRAMP-MPs (PEA + UA) than lake and coastal waters, with concentrations ranging from 0.02 to 9.9 pieces m^-3 and representing 0.23-45.2% of total MPs. Furthermore, estimated annual TRAMP-MP loads discharged into Tokyo Bay were significantly correlated with paved road areas within the corresponding catchments. These findings demonstrate that AMP provides a robust approach for characterizing MP compositions in low-concentration surface waters. The results also indicate that PEA and UA can serve as potential indicator polymers for tracing traffic-related MP pollution in aquatic environments.