News

February  25th, 2026 - CCEM v8 has been released

CCEM v8 is now available on GitHub.

Here is  short description of what is new with this model.

(1) A Variable Time Origin and a More General Model

CCEM v8 introduces a major architectural change: the simulation’s TimeOrigin is now a variable, allowing the model to start either in 1980 or 2010. This dual-origin capability required a systematic retuning of parameters and, in some cases, modifications to the underlying equations to ensure structural coherence across both historical baselines. Working from 1980 forces the model to reproduce four decades of observed macro-economic, energy and price dynamics, while starting in 2010 provides continuity with previous CCEM versions. The result is a more general and robust framework: the same structural model can now reproduce both late-20th-century fossil expansion and early-21st-century transition dynamics, while preserving long-term stability in 2200 simulations.

(2) A New Growth Model for Dual-Origin Consistency

Supporting two possible time origins led to a redesign of the economic growth model (M4). CCEM v8 introduces a more explicit value-creation structure in which growth depends on return on investment, infrastructure decay, and a refined set of competitiveness drivers: labor cost competitiveness, social expense ratio, energy costs, and a “tech & efficiency” factor capturing software leverage and innovation ecosystems. Carbon tax revenues are now reinjected into global investment rather than earmarked exclusively for energy investment, reflecting their macroeconomic nature. The model explicitly uses constant dollars with calibrated inflation, and—after careful consideration—does not adopt PPP adjustments, since high-skill labor, strategic materials, and high-tech components follow global price signals that PPP would distort at the macro scale.

(3) A Simplified and Recalibrated Energy Model

The energy supply side (M1 & M2) has been simplified to improve transparency and calibration. The key concept is the equilibrium price, now modeled as a Key Known Unknown (KNU), representing the price at which demand matches supply in the absence of shortages or surplus. This equilibrium price evolves roughly in line with production costs, while the CGE-style balancing mechanism continues to adjust prices dynamically when demand and supply diverge. Fossil reserves have been recalibrated using 2025 consensus estimates and retro-propagated to 1980 or 2010, shifting long-term production peaks compared with earlier versions. This approach reduces sensitivity to short-term volatility while preserving the essential signal role of prices in balancing global energy markets.

(4) Sector-Based Transition Matrices

CCEM v8 introduces explicit economic sectors—transport, industry, residential and others—to derive energy transition matrices in a more explainable manner. Energy consumption is first decomposed into these four sectors. For each sector, a sectoral transition matrix (modeled as a KNU) captures substitution pathways between energy vectors, including electrification, hydrogen shifts, and efficiency gains when direct heat-to-movement conversion can be avoided. Zone-level transition matrices are then generated automatically by weighting sector matrices according to each region’s structural profile and maturity. This sector-based architecture replaces the more opaque block-level matrices of v7, improving interpretability while maintaining systemic coherence.

(5) Reaction Delay and Policy Dynamics

Finally, CCEM v8 introduces an explicit reaction delay between the “pain” signal and policy action. In the model, societal pain—arising from climate damages, energy shortages, or economic slowdown—does not trigger immediate redirection. Instead, decisions concerning energy transition, forced sobriety, carbon taxation, or adaptation are taken with a configurable delay, implemented as a macro-parameter (painDelay). This seemingly simple addition profoundly changes dynamic behavior: anticipation gains strategic value, and delayed reactions amplify overshoot and instability risks. By explicitly modeling the lag from signal to decision to implementation, CCEM v8 moves closer to real-world political and institutional inertia, strengthening its capacity to explore long-term strategic trajectories.

What makes CCEM v8 quite interesting is twofolds :

1. CCEM has used genAI intensely for its calibration, doubling the benefits of the dual time origin as mentionned earlier.

2. CCEM v8 is now "AI-certified",  <explain>

The following figure describes this process. This is just the begining since the capabilities to do this code-to-spec matching have just matured recently. You can expect more documentation with the next releases of CCEM.

The next step is the update of the G2WS simulor (Web interface to play with CCEM) which is coming very soon.

December  30th, 2025 - Blog post about CCEM calibration

If you are curious about how CCE gets calibrated, you should read

informationsystemsbiology.blogspot.com/2025/12/ccem-system-dynamics-calibration.html 

You will see that I making heavy use of gen AI (GPT 5.2 mostly, but also Sonnet 4.5 and Gemini 3) to get a "median value" for the KNU.

This blog post is based on CCEM v8, which will be released soon (February).

December 1st, 2025 - Specialized CCEM GPT is online

Try it here  - You can ask any questions about CCEM to this specialized GPT and it does a good job at answering them :)

November  18th, 2025 - GLCE Journal article about CCEM is online

There is now a much better detailed reference about CCEM (version 6) : an article in the Journal of Green and Low Carbon Economy.

https://ojs.bonviewpress.com/index.php/GLCE/article/view/5069

August 18th, 2025 - NEW : G2WS's first MVP

CCEM (version 7) will be made available as a stand-alone Web page. 

G2WS (Geopolitical Global Warming Simulator) is a simple simulator that allows the user to experiment with the system dynamic model and see how it reacts (a) when you change the major system beliefs (the KNUs) (b) when you change the policies of the five geopolical blocks (US, EU, China, India, RestOfWord).

We are currently experimenting with a MVP (Minimum Viable Product), that is a public html file g2wsmvp
Warning : this is an ongoing experimentation, you may play with the Web page (clicking on the previous link) at your own risks.

• the Web user interface code for G2WS is brand new and not fully tested

• CCEM has much fewer bugs but is, by design, under construction and full of limitations. When playing with G2WS, one sees the limits very clearly (which is the purpose of exposing G2WS in an early stage).

• G2WS exposes a few KNUs (known unknowns) that you may experiment with (using a slider) but some other key model parameters are still hidden. This will change in the future, as G2WS evolves towards a digital product.

To learn more about G2WS, read the tutorial.

July 17th, 2025

Version CCEM v7 was completed and released on GitHub.
For french readers, you may find a story about v7 in my last blog post.

New Features in CCEM v7

1. Damages

CCEM v7 introduces a more detailed and better calibrated damage model, with damage types explicitly categorized and linked to temperature rise. The model includes:

• Property damage (based on insurance data), with causes such as loods, hurricanes, heatwaves, and droughts
  
  

• Loss of working hours, incapacitated workers, sickness, and mortality
  
  

• Agricultural losses, with bibliographic updates
  
  

• Impact on population dynamics,  both the increase of death rates and the lowering of birth rates.
  
  

The damage function now follows a tree structure, enabling differentiated responses by damage type and zone. The model also includes IPCC AR6-based recalibration to better connect CO₂ levels with temperature and resulting impacts.

2. Adaptation

A major improvement in v7 is the explicit modeling of adaptation as a form of investment. Adaptation:

• Reduces the effective damage from climate impacts
  
  

• Follows a return-on-investment (RoI) logic, with zone-specific attenuation curves
  
  

• Includes a cumulative benefit effect, highlighting the advantage of early investment
  
  

• Is implemented via a new “KNU” (known unknowns) representing strategic beliefs
  
  

Adaptation costs and effects are integrated into the local optimization ("tactic") engine, and results (adaptation spending and avoided damages) are tracked and displayed. The model captures realistic deployment constraints and includes a notion of volume discounts.

3. Energy Transition

The transition model in CCEM v7 reflects updated thinking from recent literature, particularly Greg de Temmerman’s work:

• Transition arcs between energy types now include efficiency gains, especially in electrification (Carnot principle)
  
  

• Efficiency ratios are defined per transition, allowing precise modeling (e.g., fossil → electric transition with reduced final energy need)
  
  

• Net effects include asymmetrical energy shifts (e.g., -100% fossil, +50% electricity)
  
  

• A bug in previous models related to transition cost allocation has been fixed
  
  

4. TCRE (Transient Climate Response to Cumulative Emissions)

In v7, CCEM replaces its former CO₂ concentration model with a TCRE-based warming function, linking cumulative anthropogenic emissions directly to temperature rise:

• Based on recent IPCC guidance (AR6), this approach eliminates the need to model atmospheric concentration dynamics
  
  

• Simplifies the climate feedback loop while maintaining sufficient realism
  
  

• Aligns well with observed data over the last 40 years (e.g., ~54% of CO₂ emissions accumulating in atmosphere)
  
  

• Supports new simulations for RCP 4.5 and RCP 6.0, with updated warming estimates (e.g., 2.7°C and 3.2°C respectively)
  
  

5. Best Response Optimization

The optimization routine in CCEM has been significantly improved:

• Previous local descent approaches have been replaced by sampling and nested search algorithms
  
  

• New tools such as topt and toptp explore tactical parameter space more robustly, escaping local minima
  
  

• Enables true Best Response calculations: finding the optimal tactic for one actor given the others’ strategies
  
  

• Demonstrated for regions like Europe and China: responses differ depending on external transition behavior
  
  

• Paves the way for Nash Equilibrium research in future CCEM v8

December 31st, 2024

• First post about CCEM in my English blog "Biology of Distributed Information System":

  • “Energy Matters Modeling Manifesto” : Energy Transition and Systems Dynamics Earth Models

  • this blog post presents:

    • Hello Future!,  a great book about 2035 by Langdon Morris

    • a short update on CCEM v6 (cf. below)

    • A manifesto (EM3) that advocates the disclosure of energy hypotheses (beliefs) when presenting 21st century scenario produced from a model (IAM, SDEM, etc.)

    • A short narrative that describes part of the content of the FormAction presentation of December 4th, 2024.

December 4th, 2024

• Presentation of CCEM to FormAction (on the invitation of Erik Grab) of a revised version of the DCAQ talk made in August : the slides are available on  Slideshare.

• This is the first presentation that used CCEM v6.  The narrative is similar to the previous talk, but using constant dollars figures makes for a more compelling presentation.

• CCEM v6 is now available on GitHub. Here is a short description of the main changes compared with v5:

  • The world in CCEM is divided into geopolitical blocks (also called zones). CCEM v6 has added India as a new zone, because of its size, its growing economy and its political strategy. CCEM has now five zones: Europe (27), USA, China, India and RoW (Rest of World).

  • The most significant change in CCEM v6 is the move from current to 2010 constant dollars to measure GDP. Switching to constant dollars changes the perspective significantly! First, as we show in Section 3, once you remove inflation, you see that energy density is progressing quite slowly over the past decades (with flat periods for some of the zones). Second, and most importantly, World GDP growth is very heterogenous: while US and China have been doing well for the past decade, Europe GDP has actually declined since 2010, a fate shared with “Rest of the Word” on average. Taking this perspective into account has required a significant overhaul of the economy (M4) model, with the introduction of “asset decay” (a feature that is borrowed from “Limit to Growth”) : if nothing is done, productive asset decline in time and their associated return slows down.

  • Dematerialization of the economy, that this the decline of energy density, has now a simpler but more robust model to accommodate the past 40 decades of historical data. CCEM distinguishes between “dematerialization” and “savings” (efficiency). Dematerialization captures the faster growth of “immaterial” economy (software, services, …) compared to “material” economy. Savings captures the possibility of doing the same economic activities with less energy through technology progress. CCEM works with two beliefs: the first one is an energy density trend that is projected from past data, the second one is a “savings” roadmap (part of the energy transition) where investments into new technology may reduce energy consumption at iso-activity. One way to think of it is that the first belief is the “business as usual” trend of energy density decline, whereas the second parameter is a possible political decision of investing into efficiency

  • Because 2024 has been used to study the impact of actual fossil fuel reserves and understand how net-zero scenarios could work, the energy supply equations of M1 (energy production model) have evolved to provide a more robust model of adaptation (to energy shortage, to energy abundance, to price increases) as to avoid oscillations (which were present in v4 and v5). Let us recall that energy prices in CCEM are a demand/supply signal and cannot reproduce the fluctuation observed in an open market.

  • CCEM now includes a set of feedback loops that link “pain” to the economy. Let us recall that pain is a synthetic KPI made of decline of GDP/person, shortages of energy, decline in food/person (using the proxy of wheat production), impacts of global warming. The first feedback loops says that productive labor hours will decline as pain rises (for a multiplicity of causes, such heatwaves, social unrest and strikes, loss of productivity because of engagement decline – a key issue when you listen to workforce sociologists, etc.). The second feedback loop says that pain will lower population growth (or accelerate its decline) both because mortality will increase and because the causes of “pain” will slow down the birth rate.

  • Ecological redirection is defined in the CCEM model as the portfolio of possible reactions that geopolitical blocks may take. Roughly speaking there are three groups of redirection implemented in CCEM v6: sobriety (voluntary energy consumption reduction through regulation), acceleration of energy transition (three parts: efficiency, renewable energy production and electrification) and taxes (both as carbon tax applied locally and as protectionist measures, such as Europe CBAM: Carbon Border Adjustment Mechanism).

  • To evaluate the efficiency of redirection, CCEM implements the concept of “Strategy” associated to each zone, which a cost function (evaluation function) that is defined independently for each zone as a combination of GDP growth, Pain minimization, global warming minimization (optional). To evaluate a time-series of future result, we introduce (classical with all IAMs that are defined as optimization problems, such as DICE) future discounting (future results – good or bad – are slightly less important than present ones). This way, long-term thinking (or the absence of) may be easily capture for each zone. The question of what a proper time discount should be is a very hot topic amongst futurists.

  • The code for searching the demand/supply equilibrium (see game.cl) has been improved through a dichotomic search. As a consequence CCEM v6 is significantly faster than CCEM v5.

  • KNUs have been introduced as "cones" (that is defined by 3 piecewise linear functions : median, min and max), preparing for randomization of beliefs that will be implemented in 2025.

August 30th, 2024

• Another presentation of "A System Dynamics Model for Global Warming Impact, from Energy Transition to Ecological Redirection" was made to Michelin DCAQ summer university, with a focus about En-ROADS. 

• CCEM v5 released on GitHub. Here are CCEM v5 main changes compared to v4 (IAMES paper is based on v4, while the two last presentations are based on v5)

  • Change of energy unit : move to PWh from toe (ton of oil equivalent). This change was suggested by my colleagues from NATF, to reflect the 21st century move towards Electricity as the main energy vector. Note that many IAMs use EJ (exa joules) as their main energy unit.

  • GreenGrowth is a yearly roadmap (not based on prices) to represent possible acceleration and the political nature of the industrial roadmap.

  • Since electrification is a key KPI (part of a KNU = Key kNown Unknown), CCEM v5 computes the growth of electricity production to produce an approximate value for the electrification KPI

  • CCEM v5 implements a Feedback loop "less people -> less production", with a “AI factor” that reduces the impact (0 -> AI absorbs the reduction of workforce, or older non-productive people are more targeted). This is a new Key Known Unknown !

  • CCEM v5 uses a new, simpler CO2 concentration model, where a faction of emitted CO2 is absorbed (ocean, forrest, land ...) and the rest (54%) is added to the atmosphere

    • The previous model based on a fixed absorbtion capacity does not match the existing data

    • this rough approximation matches the Wikipedia page on the cycle of CO2 ...

    • building a better model will be a goal of CCEM v7.

  • Protectionism (import taxes, CBAM or public boycott) is now implemented: Each zone may decide to reduce import/export based on difference in CO2/Energy and CO2 taxes

  • Energy transition is a political decision (a factor from 0 to 100% = fastest possible transition based on belief)

Here is a crude roadmap of CCEM versions and how they fit into the global plan of producing "serious games".

• • GW2S stands for "Geopolitical Global Warming Simulation", it is meant to be similar to En-ROADS.

  • GW3S stands for "Geopolitical Game of Global Warming Simulation" : it extends GW2S with the game theoretical aspects using the GTES framework.

Note that the IAMES paper, "CCEM: A System Dynamics Earth Model for Capturing Beliefs Related to the Coupling of Energy, Economy and Global Warming", is now available on line as an IFACS publication.

June 24th, 2024

• Presentation "A System Dynamics Model for Global Warming Impact, from Energy Transition to Ecological Redirection"  to AXA IM 

• Slides are available here

• Video capture is available on Vimeo.

May 26th; 2024

• Launch of this web site (http://modelccem.eu). 
  Stay tuned, this is "work in progress".

• CCEM presentation to IAMES 2024

• paper may be found here.