PIOT‐Hub ‐ A collaborative cloud tool for generation of physical input–output tables using mechanistic engineering models

Abstract

AbstractMapping material flows in an economy is crucial to identifying strategies for resource management toward lowering the waste and environmental impacts of society, a key objective of research in industrial ecology. However, constructing models for mapping material flows at a sectoral level, such as in physical input–output tables (PIOTs) at highly disaggregated levels, is tedious and relies on a large amount of empirical data. To overcome this challenge, a novel collaborative cloud platform PIOT‐Hub is developed in this work. This platform utilizes a Python‐based simulation system for extracting material flow data from mechanistic models, thus semi‐automating the generation of PIOTs. The simulation system implements a bottom‐up approach of utilizing scaled engineering models to generate physical supply tables (PSTs) and physical use tables (PUTs) which are converted to PIOTs (described in (Vunnava & Singh, 2021)). Mechanistic models can be uploaded by users for sectors on PIOT‐Hub to develop PIOTs for any region. Both models and resulting PST/PUT/PIOTs can be shared with other users utilizing the collaborative platform. The automation and sharing features provided by PIOT‐Hub will help to significantly reduce the time required to develop PIOT and improve the reproducibility/continuity of PIOT generation, thus allowing the study of the changing nature of material flows in regional economy. In this paper, we describe the simulation system MFDES and PIOT‐Hub architecture/functionality through a demo example for creating PIOT in agro‐based sectors for Illinois. Future work includes scaling up the cloud infrastructure for large scale PIOT generation and enhancing the tool compatibility for different sectors in economy.