supporting_information

Chemical structures.pdf: Supplementary plate compiling the chemical structures of the pharmaceuticals detected in this study, including CAS Registry Numbers and the corresponding µ-Raman–based identifications, with emphasis on compounds showing statistically significant co-occurrence with microplastics (MP). P1_Raman.pdf: Set of µ-Raman spectra (and, where applicable, associated particle images/metadata) for samples/particles analyzed at sampling point P1, providing supporting evidence for polymer and co-contaminant assignments. P2_Raman.pdf: Equivalent set of µ-Raman spectra for samples/particles analyzed at sampling point P2, documenting spectral “fingerprints” used to support polymer and associated compound identifications. df.xlsx (Data frame): Spreadsheet containing the study’s consolidated analytical dataset (data frame; e.g., sampling point, polymer type, pharmaceutical identity/class, occurrence/frequency, and categorical variables), serving as the primary input for statistical analyses (e.g., CA/χ²/ASR) and ensuring transparency and reproducibility. graphical_abstract.jpg: Graphical abstract summarizing the study design (study area and sampling), the analytical workflow (µ-Raman), and the main findings (MP occurrence and pharmaceutical co-occurrence patterns). script.py (Script of Correspondence Analysis): Python source code implementing the Correspondence Analysis and related procedures (e.g., contingency table construction, χ² testing, adjusted standardized residuals/ASR, and figure generation), supporting computational reproducibility.