Polymer‑specific hazard profiling and risk indexing of microplastics in coastal sediments of St. Martin’s Island: A multivariate and machine learning approach

• This study presents the first polymer-resolved evaluation of microplastic contamination in surface sediments from a small island ecosystem in the Bay of Bengal. • Microplastic assemblages were dominated by fibres and fragments, with polyethylene and polypropylene most abundant, reflecting persistent inputs from fishing gear and ropes. • We propose a novel Microplastic Pollution Risk Index (MPRI) that integrates polymer hazard scores with persistence, morphology, and color, providing a comprehensive hazard profile. • Tourism-exposed beaches exhibited higher diversity and shares of polystyrene, PET, and PVC, linking packaging and consumer waste to localized contamination hotspots. • Multivariate analyses (Pearson correlation, PCA, RDA, HCA) and machine learning models (Random Forest, SVM, KNN) clearly separated tourism and fishing sites, underscoring distinct contamination pathways.…