Abstract
Physical input–output tables (PIOTs) were first conceptualized in the 1990s but have not been widely adopted. However, with the increased emphasis on building a circular economy and understanding the resource nexus, PIOTs will become critical for optimizing resource flows and restructuring economies to close material loops. This necessitates a focus on improved methodologies for PIOT development to allow wider adoption. In this work, we propose and demonstrate a modular bottom-up approach for constructing PIOTs from process engineering models. The method was tested on a PIOT for nitrogen with a subset of sectors in Illinois (USA) and compared with a nitrogen PIOT developed earlier for the same time period, finding equal or higher confidence in sector balances. While the method has high initial costs, its suitability for automation enables it to allow the fast creation of PIOTs where technical coefficient matrices reflect underlying physical processes and relationships within and between sectors, thus capturing accurately the physical structure of the economy. We also demonstrate how the method can be extended for the creation of regional input coefficient matrices. While not implemented here, the method can potentially be used for the creation of hybrid IO tables, trend analysis through time series and combined with non-survey methods to fill data gaps. This will allow combining the strengths of complementary methodologies for constructing PIOTs and standardization of methods for better reliability.
Highlights
Introduction and motivationPhysical input–output tables (PIOTs) provide a key decision-making framework for optimizing material utilization while reducing the environmental impacts associated with production in the economy
While several researchers have highlighted the potential for PIOTs for material tracking and benefits of inclusion of more IO data in physical units (Altimiras-Martin 2014; Hubacek and Giljum 2003; Hoekstra and van den Bergh 2006; Duchin and Levine 2011; Merciai and Heijungs 2014), their adoption and development have lagged compared to material flow analysis (MFA) (Hoekstra 2010), Life Cycle Assessment (LCA), and Environmentally Extended Input–Output (EEIO) analysis
4.1 Comparison of PIOTs from process modeling versus empirical MFA approach The N PIOTs from the “process-to-PIOT” approach are shown in Tables 4 (RTC) and 5 (RIC)
Summary
Introduction and motivationPhysical input–output tables (PIOTs) provide a key decision-making framework for optimizing material utilization while reducing the environmental impacts associated with production in the economy. These flows form the basic inputs for construction of PIOTs. In this work, we utilize the strength of process engineering models to capture regional production, providing a reliable estimation of domestic supply of products, domestic consumption of intermediate products, raw materials, co-products and waste streams.
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