Standardised and scalable methods to quantify and characterise MNP in environmental compartments and matrices in the human body (ATHENA)

The ATHENA project - Standardised and scalable methods to quantify and characterise micro- and nanoplastics in environmental compartments and matrices in the human body - was conducted was to strengthen the scientific basis for assessing human health risks of micro- and nanoplastic (MNP) particles. This was achieved by developing and integrating (1) quantitative Quality Assurance/Quality Control (QA/QC) frameworks for literature data, and (2) statistical Probability Density Function (PDF) tools for harmonising heterogeneous exposure and toxicity datasets. The dataset contains results from large-scale literature screenings and AI-assisted data extraction covering over 7,000 exposure and 1,400 effect publications. Approximately 950 exposure studies (air, food, beverages) and 700 effect studies were retained for scoring. QA/QC criteria (13 for exposure; 18–24 for effect studies) evaluated reporting quality in particle characterisation, contamination control, experimental design, and risk-assessment relevance. The repository includes: Processed literature datasets (e.g., Table_S1_Literature Dataset.xlsx, META_SCORE.csv), AI-extracted data for classification, particles, thresholds, and exposure (Gemini_extracted_*.xlsx, GPT_extracted_*.xlsx), Validated concentration datasets for air, food, and beverages (Table_S6–S8.xlsx), Power-law and PDF fitting results (Table_S3_pwr_fitting_result.xlsx), Prompt files defining the modular AI extraction structure, and Human validation files (CHECK_87_upload_YODA.xlsx). Together, these datasets provide a harmonised, quality-ranked foundation for comparing MNP exposure and effect data across media and studies, thereby supporting the first quantitative human health risk assessments for microplastics.