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

 

1. Introduction 

CCEM is a “system dynamics earth model” in the tradition of Jay Forrester and John Sterman. Our goal is to study/simulate ecological redirection when global warming occurs. Ecological redirection is a key concept proposed by Bruno Latour, based on complex system theory. Energy (production and consumption), Economy, Climate and societal reaction make for a truly complex system. Where “energy transition” makes sense because it is complicated and not so complex, and can be managed with roadmaps (investments, manufacturing, deployment, operations), it is almost impossible to forecast all the retroactions that will happen as global warming proceeds. Redirection is a set of actions that society may take at each given point of the future, based on the context: damages, fear but also means, or aspiring goals. Ecological redirection is a great framework to develop non-linear complex models of how the world and its economy will evolve when facing the consequence of climate change, one bifurcation at a time.

2024 has been a busy year for CCEM with two new versions (v5 and v6) being developed in response to a lot of feedback that I received while giving lectures about CCEM. You may have a look at my slideshare deck, or watch the AXA IM presentation that was recorded and made available on Vimeo. I also published a paper, “CCEM: A System Dynamics Earth Model for Capturing Beliefs Related to the Coupling of Energy, Economy and Global Warming”, at the Third IFAC Workshop on Integrated Assessment Modeling for Environmental Systems IAMES 2024, and I am currently working on a longer, journal-version of CCEM v6. CCEM has now its own website, http://modelccem.eu, where most of the material and explanations may be found, with a link to the GWDG github repository. CCEM is the foundation for a more ambitious project, that is to propose a serious game about the geopolitical simulation of world economy and global warming (GWDG stands for Global Warming Dynamic Games).

Since there is now a fair amount of information available on CCEM, including the various 2023/2024 posts in my other blog, this blog post will focus on what is new with CCEM v6 and why having an explicit agreement about any model’s hypothesis regarding future energy availability is so important. If this is the first time that you are reading about CCEM, a key feature of this model is to make explicit the hypotheses that are used a for set of key questions for which there is no consensus today, but that play a critical role when looking at possible outcomes (possible scenarios, or RPC: representative concentrations pathways). These are “known unknowns”, as popularized by United States Secretary of Defense Donald Rumsfeld in a famous 2002 speech, in the sense that the issues are well understood and documented, but there is no consensus about what the answers might be. In the remainder of this post, we call these “known unknowns” beliefs to emphasize the lack of consensus (and/or the variation of opinions over the past decades, as shown by the fossil energy reserves example). You may find in this blog post (or in the IFAC paper), examples that show that the same model may produce very different levels of CO2 emissions (hence warming) based on a few of those beliefs.

CCEM is a tool for geopolitical modeling, because it assumes that key blocks (major countries or continents with unified governance) have different goals and constraints when it comes to global warming. The long history of COP failed decisions and un-respected decisions is clear proof. CCEM is a tool, what will come in the next two years is a game-theorical approach to see if Nash equilibriums, or other forms of stable cooperations, may emerge from the tension between one shared planet and different political agendas. 2024 is also the year when Mario Draghi and his colleagues published “The Future of European competitiveness” where they declare that foundations of Europe competitiveness have been shaken, with a few obvious statements that are exactly similar to what CCEM v6 (see Section 4) makes obvious, when we compare EU GDP expressed in constant 2010 dollars, with the rest of the world:  “ To digitalise and decarbonize the economy and increase our defense capacity, the investment share in Europe will have to rise by 5% of GDP” (back to 60-70s levels)”; “Even though energy prices have fallen considerably from their peaks, EU companies still face electricity prices that are 2-3 times those of US”; “The productivity gar between the EU and the US is largely explained by the tech sector”.  The publication of Mario Draghi’s report has been a blessing for my CCEM presentation for two reasons: first, the dire competitive position of Europe and the dual lack of investments and return is now a commonly understood fact; second, the fact that EU needs to think its decarbonization strategy in an aggressive an competitive environment, with players that have very different goals, is now very clear (it has been true for a long time, but Donnald Trump’s election makes it more visible).

I have used 2024 to read a lot about other models, especially looking at the scenarios (set of beliefs) that claimed to produce “2050 net-zero” trajectories (i.e., how to reduce our emissions so much that what remains may be offset with some carbon sequestration method). I studied the various scenarios that were produced by IAMs commissioned by NGFS (Network for Greening Financial Systems). I looked at the IRENA (International Renewable Energy Agency) scenarios that were used for the conclusions of COP28. Looking at these “net-zero” model has started me to think, with a few colleagues from the NATF, about a possible “Energy Matters Modeling Manifesto”. This is the direct application of the principle of making “known unknowns” explicit, applied to energy, that is disclosing clearly hypotheses both about fossil and renewable energy. This manifesto is a set of 4 questions that you should get the answer to before giving too much credit about a representative concentration pathway for this century.

This blog post is organized as follows. Section 2 will present a brief overview of Langdon Morris’ new book “Hello Future ! The World in 2035” because it is the best introduction that I know, both to system dynamics and to the complex interplay of possible dimensions of our earth ecosystem future. Section 3 presents EM3 (Energy matters modeling manifesto) separately because it is a simple and useful tool to make your opinion when reading about the future state of the 21st century. Section 4 gives a brief description of what is new with CCEM v6 and presents a few new computational results. This section will end with a revised narrative about warming that can be derived from multiple simulations. As CCEM is still in its infancy, these are just “food-for-thoughts” insights that a systemic simulation may propose, in the same spirit of the insights proposed by Langdon Morris in his book.

 

2. Hello Future !

I have known Langdon Morris for decades and I have quoted him many times in my own books. As a business and management thinker, he has published books such as “Managing the Evolving Corporation” that I consider visionary (a book published in 1995 that describes brilliantly what has happened in the next two decades). His new book is a one-of-its-kind book about the upcoming (2035) future, because it mixes a scenario-based approach (not uncommon) with a deep systemic analysis. This is how Langdon Morris describes his own book: “Part 1 explores how we think about the future. We begin here because our ways of thinking are so critically important to how we understand and interpret the information that comes to us, and how we then choose the actions we will take, which will then in turn create our own futures. Part 2 examines eight powerful driving forces of change that are moving us rapidly into the future, and then using “What if...” thought experiments, we explore thirty-two possible futures that we may encounter along the way to 2035 “. Throughout the book, making scenarios is not seen as a forecasting exercise (the what-if scenarios cover many sides of the same question) but as a method for analysis, for better understanding the world we live in. Landon Morris quote futurists Philip Tetlock and Dan Gardner: “Foresight isn’t a mysterious gift bestowed at birth. It is the product of particular ways of thinking, of gathering information, of updating beliefs”. He adds that his goal is not to make predictions but to see patterns of change: “ while prediction may be a fool’s errand, it is a strategist’s necessity”. Trying to make what-if prediction is by essence a causal analysis and a deep effort of systemic thinking. Langdon Morris proposes a systemic view with eight dimensions that influence each others: “ Thus, we see a powerful feedback loop, the accelerating changes of the world and the increasing cognitive and psychological impacts of these changes. They feed off of one another, changes in one causing change in the other, which only serves to amplify their impacts even more”.  The core of the book is a fully connected graph of “eight critical driving forces”:

• Culture
• Geopolitics
• Politics
• Climate
• Energy
• Science and Technology
• Economy
• Demographics

The graph (Figure 8 of the book) is fully connected because each driving force influences each other. CCEM is based on 6 of these 8 forces: energy, tech, demography, economy, climate and geopolitics; however, the interactions between the eight driving forces are everywhere in the CCEM model. For instance, the return on investment in China has started to slow down, as noticed by Langdon Morris: “And this is what has happened in China. In the past two decades, investment in China has continued to rise as rapidly as ever, even as it has progressively generated less and less value for each dollar [or Yuan] invested.”[57] Declining marginal returns has set in.” I will let you read the book’s explanation but it matches some of CCEM adjustment that we made to match the past data. Langdon Morris book is a great source of inspiration to extend CCEM with society cohesion and the handling of inequality.  The two forces that have been left aside in CCEM are culture and politics, which correspond to this book’s question “Can we all just get along ?”. This part of the book is especially interesting because culture, cohesion and inequality (think Gini coefficient) are missing, at the time being, from CCEM but are a key dimension of futurist thinking. The two major trends of the 21st century, global warming and AI/digital transformation are both intensifying the inequalities between poor and rich citizens of every country, poorer and richer countries, countries that are most exposed to global warming damages and countries that can afford to adapt (at least, to better adapt).

2.1 Systemic Insights

As noticed, the first part of the book gives a systemic description of the world and how to frame the questions about its future. In the great tradition of Peter Senge’s Fifth Discipline, this will both give you tools to better understand the complexity of the world, and a quick-survival-kit about systemic thinking and complex systems theory. Understanding complexity is key since our civilizations evolves towards ever-increasing complexity that brings new benefits as well as new challenges. Langdon Morris borrows from Joseph Tainter analysis of past civilizations: “Tainter’s core observations come from his engrossing study of past civilizations. He observes that as societies become more complex, they are forced to invest an increasing proportion of their resources in managing the complexity itself, but meanwhile the benefits have grown as well”.  This is also beautifully expressed by Buckminster Fuller: “The reward for being a good problem solver is to be heaped with more and more difficult problems to solve”. One of the truly complex subsystem of our Earth system is the energy system, and decarbonization of energy, that is moving away from fossil fuel to renewable energy is indeed a formidable challenge: “ The solution is apparently to adopt an even more complex global energy system, one based on non-fossil fuels, at a cost of tens of trillions of dollars. Whether or not this can actually be done, and the consequences of doing it or not doing it, are of fundamental significance to the future of civilization, and thus the subject of Chapter 11, on climate change”.  This is very close to Vaclav Smil’s thinking, which is quoted in “Hello Future!”.

Langdon Morris provides and explains many key concepts that are useful to build your own model of the world. For instance, the distinction between deep structures, forces (that emerge from the structure transformations) and events that materialize forces, is used throughout the book to introduce the time-granularity of transformations. He also borrows punctuated evolution: “Evolutionary biologists refer to this as “punctuated evolution,” each punctuation being a step. Seen in this way, evolution can be visualized as a staircase”. I suggest that your read “On the multiscale dynamics of punctuated evolution” to get a sense of how punctuated evolution is a great framework to understand the combination of progressive transformation that is accelerated once in a while by non-linear bifurcation (this is a perfect model for ecological redirection, as proposed in the introduction). This other article, “Punctuated evolution: from species to elections, computers, or covid”, quotes Sergi Valverde: “The same evolutionary mechanism that leads to subtle changes can lead to drastic ones. This is what we have called punctuated evolution”. Punctuated evolution is also a great framework to understand the constant interplay between economy and technology, as noticed by economists Daron Acemoglu and James A. Robinson: “Sustained economic growth requires innovation, and innovation cannot be decoupled from creative destruction, which replaces the old with the new in the economic realm and also destabilizes established power relations in politics”. As Langdon Morris notices later on : “This makes for an exceptionally complex situation, and indeed it is a three-stage loop of increasing complexity: the vast scale and scope of economic activity makes it inherently difficult to grasp, the dynamics of positive feedback create behaviors that are essentially unpredictable, and the economy continues on as an endless creative-destructive process with no beginning and no end, just constant and sometimes even instantaneous change”.

 

2.2 What-If scenarios

I will let you read the book to discover the 28 what-if scenarios that are proposed to your analysis. I will pick five examples here as an illustration, to trigger your interest. There are many more interesting discussions that I could have selected, including the demography question and how robots may, or not, substitute for a declining workforce.

• There are several what-ifs regarding current war scenarios (e.g., Russia and Ukraine) and future possible ones, such as China invading Taiwan. For each scenario, the books starts with the most likely consequences, such as: “Global computer chip prices would double or triple overnight because Taiwan is the world’s largest producer, and the threat of a supply cut-off would spook the market” and “it’s also possible to foresee that TSMC’s plants in Taiwan would be blown up to keep them from falling under Chinese control. This would of course further disrupt the chip industry supplies and increase technology market turbulence”. I start with the war scenarios because conflicts are on the rise in the 21st century, and all systemic factors such as the fight for limited natural resources (water, energy, minerals, …) will push in the wrong direction. The book quotes historian Ian Morris, “We are approaching the greatest discontinuity in history. Either we will soon (perhaps before 2050) begin a transformation more profound than the industrial revolution, which may make most of our current problems irrelevant, or we will stagger into a collapse like no other. This means that the next forty years will be the most important in history”. From a futurist’s perspective, wars are the major disruption that may invalidate earth models such as CCEM: “We should also note that all these factors are generally shoved aside in the event of a major event such as war, pestilence, pandemic, or systemic collapse, all of which disrupt economic life in every way”.
• Another topic that is well covered, without surprise, is the rise of AI, as a force that will both transform society as we know it and wars between geopolitical blocks:  “Hence, the risk of unintended consequences grows enormously when tactical decisions made by AI warfighting systems in live battle action far surpasses the capacity of humans to grasp what’s going on, and exceeds the rhythm that diplomacy requires to reach accommodation”. Langdon Morris quotes a lot from two key books on the topic of AI and war, “The Age of AI and our Human Future”, by Daniel Huttenlocher, Eric Schmidt, and Henry Kissinger, and “The Coming Wave” by Mustafa Suleyman. The first book is actually more optimistic than the second: “AI is in the process of transforming machines – which until now have been our tools – into our partners”.  Langdon Morris gives some recent examples of AI being used in warfare : “Even more disturbing is the use in 2023 by the Israeli army of an AI system called “Lavender” to identify 37,000 suspected Hamas soldiers, who were then targeted with nearly indiscriminate bombings that also killed thousands of Palestinian civilians”. He gives many interesting insights about the use of AI and genAI such as : “Cornell University professors found that an AI system can improve creativity, the process by which people come up with new ideas, increasing the count of new ideas proposed in a fifteen-minute span from a mediocre 5 to an impressive 200“. But the real value of “Hello Future !” is the combination of all these dimensions and their interplay : “Reflecting on, and now adding to, the three prior chapters on Geopolitics, Politics, and Climate Change, we must now incorporate into our thinking this fourth major driver of change, and thus a fourth driver of society’s acceleration. Technology driven by science combines with an economy based on capitalism (next chapter) in a world struggling with climate change and a global energy system undertaking a fundamental transition away from fossil fuels”.
• The evolution of democracy and its confrontation with more authoritarian regimes is another key contribution of this book, which is remarkably timely when we consider the rise of polarization and so-called extreme political parties and opinions in the western democracies. As noticed by the author: “The world is currently experiencing a bout of democracy fatigue, and it causes deep concern because it suggests that many people are ready to get rid of established institutions and replace them with their own (arbitrary) preferences. It is a retreat into individualism”. I do not have the space here, and summary is not a great option  so I will encourage you to read about possible what-if scenarios about how democracy, may, or may not, fight back against the temptation for authoritarian leadership : “Hence, authors Steven Levitsky and Daniel Ziblatt have provided a detailed guide to authoritarian behavior in their book How Democracies Die, identifying four warning signs of emerging autocracy: 1. ​Rejection of democratic rules of the game. 2. ​Denying legitimacy of political opponents. 3. ​Tolerance of and encouragement of violence. 4. ​Readiness to curtail the civil liberties of opponents and media”.
• This books talks also about energy and climate change, borrowing to one author that I love to quote when presenting CCEM : “ We are, in the words of scientist and author Vaclav Smil, A fossil-fueled civilization whose technical and scientific advances, quality of life, and prosperity rest on the combustion of huge quantities of fossil carbon”. Although the 8 driving forces presented earlier makes for a complex inter-connected web, energy is the major fuel of world development as we have experienced in the past 2 centuries : “Hence, energy is the only universal currency.”[355] This is another way to view the importance of the energy system and its relation to the phenomenon of climate change as a consequence, as we explored in Chapter 10. It’s all connected”. Managing the transition from the existing fossil energy system to the next renewable energy system is the major “simple” (complicated but no so complex compared with all the other challenges) of this century : “For this we require an unprecedented level of global cooperation, which in and of itself poses a serious challenge to our ways governance and our geopolitics”. I will return to this fascinating question of world climate governance, where the question is the bet between designed consensus (think of COP) and reactive emergence (think of what has happened since Paris’ Agreements), in the conclusion of this blog post and I will borrow a quote from Pascal Baudry (found in “Hello Future!”).  The book is full of interesting figures … some of them should be double checked. It is true that US had reduced its coal consumption a lot, but at the expense of increased shale oil and gas. The news that “In 2023, Europe added solar panels at a rate equivalent to building one new nuclear power plant each week” does not match well (factor 8 missing) with the fact that in 2024, PV production is estimated at 50 TWh.  However, this conclusion about the geo-political view of energy consumption, seen from developing countries, matches very well the CCEM simulation of section 4 : “For them to achieve a dignified standard of living they will need to double or triple their energy consumption to boost their food supply and build a decent level of urban, industrial, and transportation infrastructures in the cities that people are continuing to crowd into. Hence, demand will continue to rise as the transition proceeds, so still more and more new generation capacity will be needed”.
• Last, let me mention briefly the key topic of global warming damages, one of the most interesting “known unknowns” of CCEM. Langdon Morris gives some figures collected by insurance companies: “From 2000 to 2009 there were three thunderstorms that cost the insurance industry more than $1 billion in claims. From 2010 to 2019 there were ten. From 2020 to 2024 there were six, so clearly the frequency is increasing”. The logical conclusion is that some regions will become inhabitable in this upcoming century : “At the end of the day, people who live in super-high-risk zones [including many parts of Florida] are going to have to move. And there’s going to be a lot of political bloodshed along the way”. To put these numbers in perspective, I will give you the numbers published in the last (2023) study from the reinsurer SwissRe. The global losses due to weather damages in 2024 were $280B, out of which $100B was insured (which represents 0.1% of the world GDP). This ratio has approximately doubled since 2000. You can see here the polarization about damages numbers: on the one hand it is still small as a fraction of GDP, on the other hand, it is growing fast. As told earlier, there is no way that a summary can do justice to all the “what-if” proposed scenarios, which all come with insightful data such as this one (about methane, which I had no clue about): “rice growing is itself a cause of significant methane emissions – producing about 12% of the world’s total methane, or about 1.5% of global greenhouse gas emissions. Vietnam’s rice paddies, for example, produce more greenhouse gasses than the nation’s transportation sector”.

I will let you draw your own conclusions by reading the book, since the 28 scenarios explore an interesting fragment of the possible futures. As far as I am concerned, I closed the book with three major (obviously unanswered) questions:

1. To which degree are we leaving a livable planet to the future generations? Short-term, whether 2035, which is the horizon of this book, or 2050 when the inertia of the world deep structures makes for CCEM simulations that are surprisingly similar, seeing what is coming is not hard: “Hence, what we must expect by 2035 is a still-worsening climate, although perhaps the prospect of eventual improvement will also be evident in CO2 emissions statistics”. However, the 22nd century is a totally different question (not a black-and-white question, but a geo-sensitive question: which will be the livable Earth regions in 2100 ?).
2. Will the 21st century see the end of societal cohesion in many of its geopolitical blocks, caused by the unmanaged rise of inequality? As it occurred in the past (think great plague) this will co-exist at the end of the century with a context of population implosion: “we can now be sure that a completely new economic structure will develop due to the population implosion. It will be an entirely different form of capitalism than what we have experienced since the beginning of industrialization, because it will not have a steadily growing population to drive increasing demand, but instead an aging population that will be characterized by declining demand”.
3. Will the advent of technology in general and AI in particular create a dystopian world where most humans, in the world of Pierre-Noel Giraud, have become useless ? Even if the change is gradual, it may happen at a pace that we are not equipped to deal with: “Just as Toffler warned, many of us are not psychologically prepared to live in a rapidly changing world, but changing rapidly is exactly what our world has been doing, and will keep doing”.

3. “EM3” Manifesto

 

The following figure tries to group together four “Known Unknowns” about energy that everyone who is trying to understand the upcoming century should think about. Calling this list a “manifesto” is a call to all world modelers (especially IAM since they are playing a key decision role for policymakers) to disclose their hypotheses about what their model “believes” about energy consumption, across the four dimensions:

• Fossil Fuel Reserves: Here I have selected Oil Reserves, because it is the most discussed topic, but natural gas and coal are equally interesting. Obviously, it is a price-sensitive question: the answer should be a quantity (Gt) for an approximate plausible extraction cost. The first quadrant of the next figure shows the tension between depleting reserves (the doted green lines) and discovering new reserves. The red curve is, on purpose, quite unrealistic.

• Wind and Solar Deployment capacity: wind turbine and photovoltaic are the leading renewable energy sources for this century (at the time of writing). Manufacturing is a constraint this is being lifted as we go through benefits of (massive) scale, but deployment and operation is still a bottleneck.

• Electrification is a key ratio to follow here we measure the quantity of primary energy source production that is consumed as electricity. Sometimes you will find that energy sources that directly produce electricity are adjusted with a “Carnot” coefficient to distinguish from energies that require transformation (with a loss) to be converted from heat to electricity. It is simply a convention and does not change the big picture, which is – Vaclav Smil’s point, with many others – that this ratio is moving slowly.

• The last ratio is also very commonly discussed: energy density is the ratio of global energy consumed by world GDP, measured in kWh/$. It is very frequent to hear that this ratio has been declining steadily as we learn to create more value with less energy (blue curve). However, once we remove inflation (orange curve), the decline is still here but is quite slow. On this question, I find myself closer to Jean-Marc Jancovici who has been warning us for decades that the current world economy is driven by cheap and abundant energy.
  
  

 

I do not have the space here to demonstrates that “Energy Matters” and that these 4 KPIs are necessary to build a scenario for the 21st century. I will simply illustrate this with four examples, which all come with strong energy beliefs. More may be found in the CCEM presentations.

• The IEA Net Zero roadmap is a key report that “set out a narrow but feasible pathway for the global energy sector to contribute to the Paris Agreement’s goal of limiting the rise in global temperatures to 1.5 °C above pre-industrial levels. The Net Zero Roadmap quickly became an important benchmark for policy makers, industry, the financial sector and civil society”. To make such a scenario feasible, one must at the same time expect a lot of growth for renewable energy deployment (#2) and very strong progress with electrification (#3). Since the reports comes from IEA, energy consumption is supposed to grow significantly from 2000 to 2050, with complete coverage in 2050 with renewables (76 000 TWh expected in 2050, which represents 60PWh of renewable added in 28 years).
• The IRENA trajectory that was used by COP 28, “Tripling renewable power and doubling energy efficiency by 2030: Crucial steps towards 1.5°C”, is similar but expects less growth in total energy consumed but very vast deployment of renewables (25PWh added from 2022 to 2030). It also assumes an electrification ratio of 80% in 2050.
• The NGFS scenarios for central banks and supervisors, is a collection of scenarios, ranging from “net zero” scenarios, that  are very similar to IEA and IRENA, to BAU (business as usual) and “hot house” scenarios where a lot of carbon is emitted during the 21st century, yielding global warming over +3C. NGFS commissions many of the best IAM teams to generate these scenarios, with a set of constraints that require to tune the models to produce the expected trajectory (for instance, asking for a net-zero trajectory requires the modelling scientist to tune the EM3 KPI to make this feasible). I recommend reading the AXA IM note “What energy transition scenarios are and how they can be used or misused” from Olivier Eugene, to understand that these scenarios do come with their own beliefs (hence the use of EM3 to understand how realistic these assumptions are).
• Last, the En-Roads simulator (which is a wonderful tool that I will try to emulate in 2025) gives another example of a “pessimistic by default” scenario which assumes more fossil fuel reserves than what is known today. This is a perfectly fine belief, but it is worth mentioning (what the manifesto asks for). This “BAU” scenario supposes a 21st century consumption of 19 000 EJ from Oil (approximately 450Gt), versus the known reserves of 230 Gt.

 

4. CCEM v6 update 

 

If you know about CCEM you may forward to section 4.1. CCEM (Coupling Coarse Earth Models) is a comprehensive, closed system model that utilizes first principles and multiple feedback loops to analyze the interplay between energy, economy, climate, and population. Explicitly acknowledging "known unknowns," CCEM can simulate conflicting perspectives by altering input beliefs, enabling exploration of diverse geopolitical strategies based on GDP, happiness, global warming, and time discounting. The model emphasizes realistic energy transitions, addressing challenges in clean energy deployment, intermittency, storage constraints, and the rate of change in energy flows. Additionally, CCEM incorporates societal reactions to climate warming, examining ecological redirection and adaptation. Still a work in progress, it aims to refine tactical strategies and quantify the societal pain and impact of climate damage.

A System Dynamics Earth Model (SDEM) is a type of earth system model designed to study the interconnected relationships between energy production, economic activity, and climate impacts, particularly CO₂ emissions from economic processes. Unlike Integrated Assessment Models (IAMs), which are primarily data-driven and rely on statistical tools to derive relationships from past observations, SDEMs are "first principles" models that use equations to represent a modeler's understanding of the world system. These equations are calibrated to align with historical observations and aim to capture causality through systemic feedback loops and dynamic interactions. Originating from models like "Limits to Growth" by Meadows et al., SDEMs are abstract, macro-level tools that excel at understanding systemic behaviors and reproducing historical trends. Despite their abstraction, SDEMs have proven effective in modeling complex dynamics, inspiring more detailed hybrid models like CCEM, which integrates SDEM principles with the data-focused precision of IAMs to address energy production and consumption in greater depth.

A model like CCEM is not a forecast model (cf. the arguments made by Langdon Morris in Section 2), it cannot be expected to foresee “Black Swans”  but it is a great tool to study “Gray Rhinos” , that are large scale transformation which are coming with high probability.  To better understand how SDEM work, I recommend reading “La Piece Manquante de la Transition Ecologique Française” by Christophe Mangeant.

4.1 V6 model changes

This blog post will not describe CCEM (see references in introduction) but propose a quick summary of what is new in “version 6” before showing some new computational results and insights.

• 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. Here, the investment differential pointed out by Mario Draghi’s report becomes critical to understanding the various “GDP by zone” trajectories.
  
  
• 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 is fairly naïve, but manages to reproduce a few axioms such as : “you cannot sell the energy that you do not have”, “total consumption should match total production”, “you cannot afford energy price increases that are higher than your margins”, “most economy outcome requires energy to run” … which is not true of all models.
• 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.

 

4.2 New Computational Results

I will show here some new results with CCEM v6, that are extracted from the slideshare presentation mentioned in the introduction. The outcomes presented the next figure illustrate the results of a CCEM simulation, showing key indicators such as GDP, primary energy production, CO₂ emissions, and temperature trends, alongside performance metrics derived from the Kaya identity, including GDP per capita, energy density, and CO₂ intensity of energy. If you have seen previous results from earlier CCEM versions, you may notice that looking at GDP in constant 2010 dollars is surprising, not to say frightening. While detailed metrics like GDP loss due to energy shortages or global warming damages are excluded from this picture for simplicity, these factors are significant in such a simulation: the impact of global warming is the in 5%-8% range (loss of GDP) while the impact of the energy global shortage is much stronger (-30% GDP compared with an “energy as usual” scenario and -50% compared with an “energy abundance” scenario). If we look at the results under the prism of Kaya Equation, we notice the progress of GDP/person with a dual caveat: the growth becomes slower than past decades and is very heterogeneous geographically. We may also notice the slow but steady trend toward decarbonization as described by Vaclav Smil. Demographic forecasts also reflect considerations such as declining male fertility (possibly linked to pollution) and the influence of female education.

The next figure presents regional results for GDP, energy consumption, and CO₂ emissions, highlighting disparities in economic and energy strategies across zones. The left side illustrates GDP trajectories in current dollars with a 2% inflation assumption, though these figures are less meaningful due to the uncertainty of long-term inflation and the abstract nature of "2100 dollars." The major interest of projecting GDP with inflation in the future is that we can see tha inflation hides the reality (in the charts, not in real life). The right-side details energy use and CO₂ contributions, revealing that the U.S., despite benefiting from a dematerialized economy, faces economic challenges later in the century due to its reliance on oil and gas. In contrast, China's mixed strategy of transitioning from coal to clean energy while minimizing oil and gas dependence proves more resilient to energy price shocks. The EU and the "Rest of the World" zone are heavily impacted by energy constraints, with the inflation-adjusted view exposing underlying recessions, a dynamic already observed between 2010 and 2020

For lack of space, I will only touch briefly to topic of CCEM sensitivity to its “belief” input, focusing on the EM3 KPI introduced in Section 3. First, the availability of fossil energy reserves significantly influences economic growth and climate outcomes. Larger reserves lead to more abundant and cheaper energy, directly boosting economic growth, particularly in the U.S. and Europe, which are more reliant on oil and gas compared to China’s coal-based strategy. However, even with abundant reserves, fossil fuel consumption peaks around 2050 before declining, due to advances in efficiency and dematerialization. Second, as shown in the following figure (left part), we can see the effect of clean energy deployment and electrification rates. In scenarios with slower growth in renewables and electrification, energy scarcity hampers GDP growth, while higher acceleration scenarios show improvements but still fall short of the electrification levels needed for "net-zero" scenarios. Importantly, developing higher capacities for clean energy does not drastically reduce fossil fuel consumption due to the model’s assumption of constrained total energy availability (you may have to read this sentence twice to get it, as it is counter-intuitive). The right part of the following figure assesses the possible impact of carbon taxes. A $50/t carbon tax applied solely in Europe reduces its fossil fuel consumption and CO₂ emissions, but the surplus energy is consumed elsewhere, negating the global impact on warming. When the same tax is applied worldwide, the effects on CO₂ emissions and GDP are profound, particularly for coal-dependent economies like China, where such a tax would triple coal prices (at 2010 prices), creating significant economic disruption. This simulation (with its detailed results) help to understand why this scenario will not happen (back to the fact that different zones have very different interests and contexts). This result underscores the model’s emphasis on the strong link between energy availability and economic performance, differing from other models that downplay the economic consequences of carbon taxes. Together, these scenarios highlight the complex interplay between energy, economy, and climate in shaping global outcomes

 

4.3 A Few Thoughts

When you run multiple (hundreds of) simulations, you start to see a few insights emerge. I will share a few thoughts, knowing that CCEM is still in its infancy:

1. Borrowing from Hannah Richie’s great book, what you see through these simulations is “not the end of the world”. The scary scenarios with +3.5C or +4C (so-called BAU: business as usual) are difficult to reproduce because there is not enough cheap oil and gas left. The state of the world (cf Hannah’s book) is more what could be called “slow transformation as usual” : the energy transition has already begun, focusing on clean energy adoption, efficiency improvements, and air quality advancements. Natural disaster mortality rates have drastically decreased, and water and natural resource conservation efforts, along with agricultural yield improvements, showcase progress over the past century. Standing back, decarbonization and greenhouse gas reductions present opportunities for greater synergy with nature, healthier food systems, and a shift toward a more serene, slower lifestyle. Technological innovation, driven by initiatives like the Solar Impulse Foundation and exponential growth in NBIC technologies, is expected to play a critical role in this transformation, reinforcing that sustainable progress is achievable.
2. However, there seems to be a critical time gap between the peak of fossil fuel reliance and the widespread availability of clean energy at sufficient levels. This gap underscores the importance of fossil reserves and the pace of clean energy development; its size is unknown but seems significant (couple of decades). Such a gap will lead to economic strain caused by energy shortages. Realistically, global temperatures are expected to rise by 2.5°C or more, with significant deviations from the 20th-century average and pre-industrial benchmarks.
3. This leads to the idea that it may not be the end of the world, but the end of our 20th century world is definitely coming (as is beautifully explained by Langdon Morris). Sustained global warming with severe impacts necessitates adaptation, while the era of cheap energy has ended, leading to energy shortages, market distortions, and regional disparities intensified by conflicts. The era of sustained worldwide growth is also over, exacerbating inequality and societal tensions. Resource constraints are predicted to fuel aggressive competition, resulting in conflicts, wars, trade protectionism, and cyber-espionage.
4. Faced with this perspective, we should both avoid the use of stress as a motivator and making promises (such as Paris’ Agreement) that we may not keep.  For Europe, and this aligns perfectly with Mario Draghi’s report, we need to act quickly on an aggressive decarbonation strategy, not to save the planet, but to save our economic competitiveness. European companies face electricity costs significantly higher than in the U.S., with a widening productivity gap largely due to lagging technology sectors. To digitalize, decarbonize, and strengthen defense capacity, Europe must increase its investment share to 1970s levels (5% of GDP). Anticipation, while costly, broadens the scope for mitigation and averts the dire consequences of reactive strategies, including skyrocketing energy prices and severe global warming damages.

A key benefit of reading Hello Future! is to understand that we do not live in a global world civilization but in a tightly coupled network of federated subsystems. This question is at the core of Damian Carrington’s paper, “We need dramatic social and technological changes’: is societal collapse inevitable?” where the thoughts of Danilo Brazovic, and many other research scientists that are quoted in Langdon Morris books, are analyzed with respect to the possible collapse of “our civilization”. If you think about one civilization, it is likely to collapse. As noticed in the article, “There is a problem, however, in attempting to draw insight for the future: past collapses were local or regional. “But we live in a global and extremely complex society,” says Brozović. “[Nonetheless], one very important insight is that, regardless of the cause of collapse, how a society reacts seems crucial”. In a federated and distributed heterogeneous word, “collapse” becomes a collection of rough transformations and reinventions, some being really tough and some being more progressive, as explained by Damian Carrington. The conclusion of the article still holds: we need dramatic social and technological change to go through “the end of the current world” into a “turbulent transformations” leveraging as much anticipation as possible through systemic and brave decisions.  Jared Diamons  famous example of Tokugawa shoguns handling of deforestation is a great example of such long-term-thinking action.

 

5. Conclusion 

To conclude this post, which is already far too long, let me emphasize that CCEM is on-going research project, with a Web site that will be regularly updated as progress is being made. The next step – mid 2025 – is to propose CCEM as a web-based simulator, following the lead of En-ROADS. En-ROADS is a SDEM that is freely available on the Web and that I strongly recommend. Thanks to Michelin DCAQ Summer University this year, I had to chance to participate to “serious games” work sessions organized around En-ROADS, with the help of a professional session organizer. You may not understand the value and interest of SDEM simulator until you are left alone to play with all the factors and see how they interact. Giving a few results, as I did in Section 4, does not do justice to the fascinating problem of global warming, nor to what complex system modelling can do for you. Obviously, the most exciting feature of the upcoming CCEM simulator (Geopolitical Global Warming Simulator) will be the possibility of playing the role of each geopolitical block and looking for the best strategy for each player.

A longer-term goal for CCEM and GWDG is to explore the use of SDEM to understand the possible emergence of global warming cooperation. As mentioned earlier, CCEM is built under the assumption that different blocks have different interests and will play different strategies. This makes designing a unified, top-down, world governance for global warming very difficult, as the various COP have demonstrated. Emergent cooperation, borrowing on the work of Robert Axelrod, happens when different interests may combine into a collective action towards a common goal, despite the differences in goals and in context. Let met give you the quote from Hello Future! that I mentioned earlier: “  Here is Pascal Baudry on this type of emergence:  “All emergences come as a relative surprise (otherwise we would be back in the realm of mechanistic prediction) and can be either favorable or unfavorable. We must therefore identify the necessary conditions for favorable emergences, or the mechanisms of selection by which we retain only those that are desirable”. The next major step for our work is the integration of the CCEM simulation with the GTES (Game Theory and Evolutionary Simulation) framework to tackle complex models with numerous unknowns and multiple interacting players. Developed two decades ago, GTES combines Monte Carlo sampling, Nash Equilibrium search, and local search techniques to analyze models by learning through example). It focuses not just on equilibrium but also on the dynamic path toward it, making it suitable for economic and strategic modeling in multi-player systems. GTES identifies three categories of unknown parameters: environmental factors sampled through Monte Carlo simulations, strategic goals guiding actors’ decisions, and tactical parameters optimized through evolutionary algorithms to align with strategic objectives. GTES should enhance CCEM by addressing uncertainties, modeling regional differences in goals and constraints, and supporting multi-player interactions. By enabling adaptive strategies and exploring Nash Equilibriums, GTES will help refine world modeling while incorporating the interdependence of regional actions and reactions.