The Github Repository, https://github.com/jodhernandezbe/TRI4PLADS/tree/v1.0.0,, is publicly available and referenced in supplementary information. This GitHub repository describes the computational framework overview, software requirements, model use, model output, and disclaimer. This repository presents a multi-scale framework that combines data engineering with process systems engineering (PSE) to enhance the precision of chemical flow analysis (CFA) at the end-of-life (EoL) stage. The focus is on chemicals used in plastic manufacturing, tracing their flows through the supply chain and EoL pathways. Additionally, this study examines potential discharges from material recovery facilities to publicly owned treatment works (POTW) facilities, recognizing their relevance to human and environmental health. Tracking these discharges is critical, as industrial EoL material transfers to POTWs can interfere with biological treatment processes, leading to unintended environmental chemical releases. By integrating data-driven methodologies with mechanistic modeling, this framework supports the identification, quantification, and regulatory assessment of chemical discharges, providing a science-based foundation for industrial and policy decision-making in sustainable material and water management. The attached file CoU - Metadata File.xlsx contains the datasets to build Figure 3 and describe a qualitative flow diagram of methyl methacrylate from manufacturing to potential consumer products generated from the Chemical Conditions of Use Locator methodology (https://doi.org/10.1111/jiec.13626). The attached file "MMA POTW Dataset.xlsx" contains the datasets needed to run the Chemical Tracker and Exposure Assessor in Publicly Owned Treatment Works Model (ChemTEAPOTW) as described in the Github Repository https://github.com/gruizmer/ChemTEAPOTW. The attached file "Plastic Data-Calculations-Assumptions.docx" contains all calculations and assumption to estimate the methyl methacrylate (MMA) releases from plastic recycling. Finally, users can generate Figures 4 and 5 after following the step-by-step process described in main Github repository for the MMA case study. This dataset is associated with the following publication: Hernandez-Betancur, J.D., J.D. Chea, D. Perez, and G.J. Ruiz-Mercado. Integrating data engineering and process systems engineering for end-of-life chemical flow analysis. COMPUTERS AND CHEMICAL ENGINEERING. Elsevier Science Ltd, New York, NY, USA, 204: 109414, (2026).