Efficient computation of environmentally extended input–output scenario and circular economy modeling

Journal of Industrial Ecology, vol. 24, pp. 976–985

Abstract

Abstract Industrial ecology tools are increasingly being used in ways that require high computational times. In the policy arena, this becomes problematic when practitioners want to live‐test various alternatives in a responsive and web‐based platform. In research, computational times come into play when analyzing large systems with multiple interventions or when requiring many runs for, for example, Monte Carlo simulations. We demonstrate how the computational time of a number of commonly used industrial ecology tools can be reduced significantly, potentially by multiple orders of magnitude. Our case study was the optimization of scenario calculations in Environmentally Extended Input–Output Analysis (EEIOA). Instead of recalculating the Leontief inverse after individual changes to the interindustry relations, as is done traditionally in EEIOA scenario analysis, we give formulations to find the total value of the change in the environmental indicators in one calculation step. We illustrate these novel formulations both for a simple hypothetical system and for the full EXIOBASE EEIO model. The use of explicit formulas decreases the computational time to the degree that it becomes possible to carry out these analyses in live or web‐based environments. For our case study, we find an improvement of up to four orders of magnitude.

Authors 4

1. Hale Çetinay corresponding Aachen Institute of Environmental Sciences (CML) Department of Industrial Ecology Leiden University Leiden The Netherlands Department of Industrial Ecology

   Leiden University

   Affiliation as printed

   Asset Management, Grid Analytics Stedin Rotterdam The Netherlands

   Institute of Environmental Sciences (CML), Department of Industrial Ecology Leiden University Leiden The Netherlands

   Asset Management, Grid Analytics, Stedin, Rotterdam, The Netherlands

   Institute of Environmental Sciences (CML), Department of Industrial Ecology, Leiden University, Leiden, The Netherlands

2. Franco Donati Aachen Institute of Environmental Sciences (CML) Department of Industrial Ecology Leiden University Leiden The Netherlands Department of Industrial Ecology

   Leiden University

   Affiliation as printed

   Institute of Environmental Sciences (CML), Department of Industrial Ecology Leiden University Leiden The Netherlands

   Institute of Environmental Sciences (CML), Department of Industrial Ecology, Leiden University, Leiden, The Netherlands

3. Reinout Heijungs Aachen Institute of Environmental Sciences (CML) Department of Industrial Ecology Leiden University Leiden The Netherlands Department of Industrial Ecology

   Leiden University · Vrije Universiteit Amsterdam

   Affiliation as printed

   Department of Econometrics and Operations Research Vrije Universiteit Amsterdam Amsterdam The Netherlands

   Institute of Environmental Sciences (CML), Department of Industrial Ecology Leiden University Leiden The Netherlands

   Department of Econometrics and Operations Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

   Institute of Environmental Sciences (CML), Department of Industrial Ecology, Leiden University, Leiden, The Netherlands

4. Benjamin Sprecher Aachen Institute of Environmental Sciences (CML) Department of Industrial Ecology Leiden University Leiden The Netherlands Department of Industrial Ecology

   Leiden University

   Affiliation as printed

   Institute of Environmental Sciences (CML), Department of Industrial Ecology Leiden University Leiden The Netherlands

   Institute of Environmental Sciences (CML), Department of Industrial Ecology, Leiden University, Leiden, The Netherlands