Connecting material flows and the socio-economic, energy and land domains
CIRCOMOD will develop and apply improved analytical tools for quantitative, policy-relevant insights into CE economy strategies with unprecedented detail and scope. It will address the contribution of CE strategies to climate change mitigation across a wide range of materials, sectors, EU countries, and across the world. This requires insights into the use of materials and products, the services they provide , and modelling of their connection with energy, GHGs, and land use .
An overview of materials and products as part of the different stages of product lifecycles (extraction, production and manufacturing, use, and end-of-life) is shown in Figure A. Materials consumed in the EU today are largely produced from raw materials (e.g., metal ores, hydrocarbons, biomass) and disposed of after use, creating waste . However, primary resource reliance can be reduced using CE strategies such as re-use, re-manufacturing, and recycling, transform the supply chain in more, or even entirely, circular ways . Figure A indicates the key connections between material production, the overall economy, and the environment, including 1) the connection of materials to the economy through the products and services they provide, as well as the capital and labour they require; 2) how the consumption of materials can lead to resource scarcity and waste generation, and 3) the substantial amounts of energy and land needed to produce and use materials, contributing significantly to climate change.
The multidimensional system highlights the many different aspects of CE strategies. CE strategies, such as those in Figure A, are typically studied from different perspectives, including economics, material flow analysis, life cycle assessment, climate mitigation models, environmental impact analysis and behavioural sciences.
The project analytical framework will build a logical understanding of the main CE mechanisms and support information exchange between disciplines and research communities. The analytical framework will describe how material flows interact with the socio-economic system, energy and land-related systems, and the climate system. For example, several important feedbacks such as how production, collection, and recycling industries interact with the economy are not yet detailed. The analytical framework and a stylized model setup will serve as a guide to map knowledge gaps, organize model improvement efforts, and identify opportunities for exchanging information between work packages and models.
Figure A: Conceptual connections between material flows and the socio-economic, energynd land domain
Note: Materials are extracted, refined, and turned into products used and disposed of from left to right in the diagram. GHG emissions can result both from process-related emissions and from the use of energy & land.
Connecting modelling tools
A key focus and contribution of CIRCOMOD will be the collection and sharing of data. A comprehensive CE database will be developed based on substantial data available across different consortium members. A major research effort will be made to acquire additional quantitative information on circularity potential. The database collection effort will focus on adding CE-relevant information for products and processes, i.e., material efficiency potential in different sectors or CE options to reduce primary material consumption.
The database will be designed early in the project and in collaboration with key stakeholder requirements, including a specification of the various data fields (units, definitions). To operationalise data exchange, we will define interfaces between the different models involved and operationalise them. A central step towards working in the multi-model system is developing a common data protocol and its implementation in a project-wide database. The preliminary concepts and infrastructure such as data templates and database are already in place . Additional effort will focus on developing project-wide classifications for products, sectors, regions, etc., and the definition of aggregations and layer conversions (e.g., with price data) between them. All data and code that is not strictly proprietary will be made available under a permissive license to facilitate quality control and community-based improvement, cumulative science, and rapid availability to stakeholders (in, for example, WP7). Data collection will occur in various WPs depending on the data type
Developing database (Data Hub)
The next key aim in CIRCOMOD is to build the underlying dataset. These data can then be combined with new and extended modelling tools that will be developed during the project. This effort will include a review of existing literature and aims to significantly improve a set of existing industrial ecology and climate mitigation models; it will also integrate these models for the holistic assessments.
The Industrial Ecology (IE) models IMAGE-MAT and ODYM-RECC, offer a detailed description of materials cycles (including the stocks and flows) of the major end uses (such as vehicles and buildings) for multiple materials such as steel, concrete, copper, and aluminum. These models assess circular economy impacts for strategies such as re-use and recycling across the material system.
CIRCOMOD also includes several models to analyse climate change, global environmental challenges, and human development issues. These models include the Energy system model TIMES, the process-oriented energy/land Integrated Assessment Models (IAM) frameworks IMAGE and WITCH, and the Macro-Economic models (ME) ICES and GEM-E3.
While the first group of energy system models provides a detailed focus on the energy system, the second group of process-oriented models focuses more on the long-term dynamics of energy and land-system and key drivers. In contrast, the third group looks mostly into the dynamics of the system from a macro-economic perspective.
By extending and linking these models CIRCOMOD will be able to conduct novel and timely evaluations of circualr economy and climate mitigation interactions from different viewpoints. The analytical framework and data infrastructure will aid in the refinement, expansion and coupling of these different models.
Figure B. Current model types and potential data exchange across model interfaces.
Note: Each model type is colour coded and data flows from/to a different model type are colour coded on the basis of the model generating the data.
Models used by CIRCOMOD
Materia Flow and Industrial Ecology models
The ODYM-RECC model is a modular depiction of major end-uses and the material cycles for the climate-relevant bulk materials. It describes the use-phase in products) and the material cycle stages mining, primary production, manufacturing, waste management, scrap recovery and recycling. The parameters describing the various processes are based on engineering calculations and life cycle assessment. Product categories such as buildings or cars are represented by archetypes. CE strategies affect process parameters, e.g., waste collection rate, and parameterize the archetypes, e.g., material composition.
The IMAGE-MAT model describes stocks and flows of several materials (e.g., steel, concrete, copper, aluminum, glass, wood) linked to key applications (buildings, electricity system, vehicles and household appliances) based on projections of sectoral drivers (expressed in functional parameters such as floor area) with material intensities. It calculates inflows (material demand) and outflows (waste generation) and captures re-use and recycling strategies. The model is soft coupled to IMAGE. Supply chains are currently not included.
Process Integrated Assessment Models
IMAGE is an IAM simulating the environmental consequences of human development (mostly in terms of energy and land use) and impacts on the earth system (e.g. climate change, land cover). IMAGE scenarios have been extensively used by the IPCC. The model already has a stock/flow representation for several human activities (e.g. residential buildings, and transport vehicles) and covers the supply chain of several materials, including steel, cement, biomass, energy resources, plastics and pulp and paper.
WITCH is a dynamic global model integrating the interactions between the economy, technological options, and climate change. The model describes the energy sector and some of the associated material flows associated. WITCH models the climate change mitigation and adaptation for dozens of macro-regions over the next century. Climate change mitigation scenarios projected by WITCH have been extensively used by the IPCC.
TIMES is an energy-economic-environment model. It is used to explore the optimized, least-cost evolution pathways of the energy system. JRC-EU-TIMES represents the energy system of European countries and has been used to analyze different pathways for meeting European energy and climate goals. The key model outputs include a highly detailed annual stock and activity of energy supply and demand technologies, associated costs, energy flows, and GHG emissions. A national application of the TIMES model for Portugal (TIMES_PT) was used to model the impact of CE strategies on GHG emissions.
The GEM-E3 model is a multi-regional, multi-sectoral, recursive dynamic CGE model that details the macro-economy and its interaction with the environment and the energy system. GEM-E3 allows for a consistent comparative analysis of policy scenarios. Particularly valuable are model insights into the distributional aspects of long-term structural adjustments. GEM-E3 is extensively used as a tool for policy analysis and impact assessment.
ICES is a recursive-dynamic, multi-sector, multi-country CGE model calibrated on the last GTAP (Global Trade Analysis Project) database. Currently, it is used for the macro-economic assessment of climate change impacts and policies (mitigation and adaptation). Advanced modules include a description of the EU economic system at a high spatial resolution (NUTS2), an improved public sector representation, and renewable energy production by the energy sector.
Developing new scenarios highlighting the possible contribution of CE ideas
Scenarios play an important role in advising policymakers on different mitigation strategies, including relevant emission reduction targets. CIRCOMOD will develop a set of scenarios analysing the potential impact of CE strategies of mitigation. Several models used in CIRCOMOD have been used to develop the scenarios currently used for climate policy analysis. For example, The Shared Socio-economic Pathways (SSPs) combined with different temperature goals (the Representative Concentration Pathways, RCPs) describe the future scenarios used in IPCC reports. Their emission trajectories are also used to force climate models.
The first scenario (current climate & more linear economy policies) will specifies the persistence of today’s climate and CE policy efforts. This scenario will be based on the policies officially implemented by different countries (based on the current policy database used for climate policy analysis). The other two scenarios explore the two main goals formulated in the Paris Climate Agreement, i.e. well below 2oC and 1.5oC
Figure C: CIRCOMOD scenario matrix on Climate and Circular Economy policy.
note: Darker colours represent greater ambition
 Görg, C., et al., Challenges for Social-Ecological Transformations: Contributions from Social and Political Ecology. Sustainability, 2017. 9(7): p. 1045.
 Pauliuk, S., et al., Global scenarios of resource and emission savings from material efficiency in residential buildings and cars. Nature Communications, 2021. 12(1): p. 5097.
 Mayer, A.S., et al., Measuring Progress towards a Circular Economy: A Monitoring Framework for Economy-wide Material Loop Closing in the EU28. Journal of Industrial Ecology, 2019. 23(1): p. 62-76.
 Gallaud, D. and B. Laperche, Circular Economy, Industrial Ecology and Short Supply Chain, Volume 4. 2016, London: iSTE/Wiley.
 Pauliuk, S., et al., A general data model for socioeconomic metabolism and its implementation in an industrial ecology data commons prototype. Journal of Industrial Ecology, 2019. 23(5): p. 1016-1027