(373c) Mapping the Chemical Economy:Automating Material Flow Analysis Using Piot-Hub

Quantifying material and chemical flows across industrial sectors is essential for understanding the structure and dynamics of the physical economy. Traditional methods for material flow analysis (MFA) often rely on aggregated data and manual compilation, limiting the granularity and reproducibility of results. This study presents PIOT-Hub, a cloud-based platform designed to automate the generation of Physical Input-Output Tables (PIOTs) using mechanistic engineering models at the sectoral level.

PIOT-Hub integrates the Material Flow Data Extractor and Simulator (MFDES) engine to convert process-level simulation data into Physical Supply Tables (PSTs) and Physical Use Tables (PUTs). These are then transformed into PIOTs that capture the supply, use, emissions, and waste flows of individual materials and chemicals. The platform supports heterogeneous model inputs (e.g., Python-based or Aspen Plus simulations) and utilizes a collaborative Material Flow Characterization (MFC) database to map chemical compositions and track flows accurately.

We demonstrate the application of PIOT-Hub through case studies involving chemical-intensive sectors such as pharmaceuticals and agro-processing. The results highlight PIOT-Hub’s capability to extract and organize material flow data with high resolution and sectoral specificity. By automating the MFA process, PIOT-Hub offers a scalable and reproducible approach for tracking chemical flows, supporting industrial ecology, environmental modeling, and regional planning.