Abstract

AbstractIndustrial 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.

Highlights

  • Industrial ecology tools ideally test many what-if scenarios (Rizos, Tuokko, & Behrens, 2017; Sprecher, Reemeyer, Alonso, Kuipers, & Graedel, 2017b), for example, when performing sensitivity analysis or evaluating multiple scenarios with an extended parameter space (McCarthy, Dellink, & Bibas, 2018)

  • We develop and test a computational short-cut that can significantly reduce the computational time of commonly used industrial ecology tools, by up to multiple orders of magnitude

  • Computational times come into play when analyzing large systems with multiple interventions, as in circular economy scenarios, or requiring many runs, for example, Monte Carlo simulations

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Summary

INTRODUCTION

Industrial ecology tools ideally test many what-if scenarios (Rizos, Tuokko, & Behrens, 2017; Sprecher, Reemeyer, Alonso, Kuipers, & Graedel, 2017b), for example, when performing sensitivity analysis or evaluating multiple scenarios with an extended parameter space (McCarthy, Dellink, & Bibas, 2018). This is hindered by the significant computational time that these types of analyses require, especially when the models are large, for instance about economy-wide effects. The MATLAB codes supplementary to this study are located in a permanent repository on Zenodo.

BACKGROUND
TECHNOLOGICAL CHANGES AND THEIR ENVIRONMENTAL IMPACTS IN AN EEIOA FRAMEWORK
Optimization of changes in a single sector
Optimization of changes in multiple sectors
RESULTS
Demonstration on a small example system
Demonstration using the mrEEIO database EXIOBASE
Further exploration of performance scaling
DISCUSSIONS AND CONCLUSIONS
CONFLICT OF INTEREST
Full Text
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