CIRCEE

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Revision as of 16:05, 16 April 2023 by Darius.corbier (talk | contribs)

General Scope and Connection with Climate Mitigation

  • Introduction

The decarbonization of our production processes and consumption of products and materials have a key role to play in achieving climate targets. Switching from a linear to a circular economic system that aims at increasing resource efficiency and reducing Green House Gas (GHG) emissions can address this challenge. The integration of circular economy poses many challenges to the IAM modelling community. Specifically, the integration of physical material flows, thermodynamics limits, and waste flows into IAM models is key to assess the potential of the circular economy in mitigating GHG emissions. Unequivocally, the controversy that opposed Georgescu-Roegen/Dally and Solow/Stiglitz the last century has never been as important as today as the climate modeling community is trying to bridge the gap between industrial ecology and economic concepts. CIRCEE (CIRCular Energy Economy), developed by the RFF-CMCC European Institute on Economics and the Environment, addresses these challenges by developing a stylized dynamic model. The stylized model will serve as a modeling starting point for the IAM community and will help mapping circular economy strategies into the existing climate scenarios.

  • Model Scope.

CIRCEE is a stylized dynamic general equilibrium model that monitors physical material and waste stock/flows and integrates key industrial ecology aspects to assess how the interaction between circular economy strategies and its enablers can reduce future GHG emissions and increase resource efficiency in resource-poor countries. CIRCEE will focus on countries that may become relatively less material-intensive in the long run thanks to the implementation of key circular economy strategies and new business models (sharing economy and digitalization).

The current geographical scope of CIRCEE includes Japan and South Korea. These countries are studied first by CIRCEE as they are two of the poorest countries in terms of resources among OECD countries. Circular economy and new business models are viewed as key in these countries to tackle climate change, to improve resource security and economic growth. More OECD countries are to be added in the future given data availability, though the users can add themselves other countries provided that enough data is available to calibrate the model.

CIRCEE can be simulated for as many years as the user wishes - 2018 serves as the base year value - provided that the users have a clear trajectory in mind for exogenous variables. The time step of the model is yearly.

Intratemporal and Intertemporal decisions between different types of goods and services and different input mix, Disaggregation into nine sectors, Aggregate Primary (Virgin) Material and Aggregate Secondary (Recycled) Material, 10 products. On the energy side, CIRCEE is soft-linked to WITCH xxxxxxx

The CIRCular Energy-Economy model visual representation
  • Specify: Stock or Flow.
  • Model documentation: in progress. Not yet available.
  • Model development status
  • Model source code (relative to milestone M24). The model uses the software platform Dynare (https://www.dynare.org). To run Dynare, you will need either Matlab, Julia or GNU Octave.

Circular Economy Features

  • R Words coverage and implemented in the model

CIRCEE provides a broad perspective on the economic and natural resource demand implications of a circular economy by integrating many different circular economy strategies.

  • CE strategies and connexion with climate change mitigation
  • Synergies and trade-off between the R word in the context of the stylized model

Insights for Analytical Framework

  • Key mechanisms and interactions within CE strategies that lead to changes in GHG emissions.
  • Tool exploration (demonstrating ideas before implementing them in large-scale quantitative models)
  • Communication key CE dynamics (to the broader audience)

Refinement and Integration

  • Explain the iterative process of refining the stylized models by incorporating results emerging from other models
  • Discuss how the stylized models can be integrated into larger modeling efforts to assess the potential of CE in climate change mitigation more comprehensively.