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  1. Yves Caseau - Coupling Coarse Earth Model – February 2023 1/26 CCEM : Coupling Coarse Earth Models Yves Caseau National Academy of Technologies of France (NATF) March 2023 D R A F T Latest update : March 24th, 2023
  2. Yves Caseau - Coupling Coarse Earth Model – February 2023 2/26 Outline 1. Why : Global Warming Dynamic Games 2. M1 (first model): Energy Resource Model 3. M2: Energy Consumption Model 4. M3: Energy Transition Model 5. M4: GDP Model 6. M5: Ecological Redirection Model 7. Coupling these five models (M1 to M5 together: CCEM) In Memoriam
  3. Yves Caseau - Coupling Coarse Earth Model – February 2023 3/26 Global Warming Dynamic Games l Global Warming Games : (Wikipedia Definition) A global warming game, also known as a climate game or a climate change game, is a type of serious game. As a serious game, it attempts to simulate and explore real life issues to educate players through an interactive experience l Our CCEM model looks at the interaction between five “coarse” models: n Energy Production n Energy Consumption n Energy Transition (fossil fuel to clean) n Economy (value from energy) n Ecological Redirection : reaction of society to the outcome predicted by IPCC l My goal is to produce a « serious game » using GTES n You select a block (continent) n You select a strategy n GTES plays the role of the other players n Multiple scenarios based on beliefs about peak oil, energy transition and reserves. William Nordhaus (Wikipedia) Production Primary Energy Consommation/ Savings / Renouncements / Substitution Economy Value Growth Investments Gaia : Earth Ecosystem Oil Coal « Clean » Energy EU China Rest of World China Rest of World CO2 emission Global Warming Natural Disasters Societal Pressure Uses Energy dégradation C O 2 / e n e r g y f e e d b a c k Nat. Gas US US EU
  4. Yves Caseau - Coupling Coarse Earth Model – February 2023 4/26 Global Warming Dynamic Games: Preliminary Roadmap l 2008-2009: GWDG v1 l 2020 – 2021 : foundations (CLAIRE 4) l 2022 : GWDG v2 l 2023 : CCEM l 2024: GTES/Game Two goals for CCEM (2023): l clear/formal presentation (feedbacks / criticisms) l Meta-model that is wide enough to « capture »: n W. Nordhaus n P. Diamondis (Singularity) n JM Jancovici (Shift Project) Warning ! GWDG (CCEM as a tractable and meaningful computational model) feasibility is only a hypothesis at this point Iteration of despair & insights … will converge or not J « Coarse Model »: capture beliefs into a simple computational model
  5. Yves Caseau - Coupling Coarse Earth Model – February 2023 5/26 CCEM : Addressing Five “Known Unknowns” « How much energy will be available in the future ? At which costs? » « How much energy is needed and acceptable for the economy at a given cost ?» Example: At which speed can we add clean energy in the next 30 years ? EIA « How fast can we substitute one form of primary energy to another ? » « What will be the economical and societal consequences from the IPCCs predicted global warming ?» « which GDP growth can be expected from investment, technology, energy and workforce ? » Example: - How much energy subvention must/can governments afford ? Energy To GDP Example: What is the possible speed of transition fossile>green for industry ? 2050 Eco transition Plan Example: Impact of reduced energy availability on economical output ? GDP 2050 Example: - which damage to productive resources ? - Which redirection caused by fear ? Temp to GDP loss
  6. Yves Caseau - Coupling Coarse Earth Model – February 2023 6/26 CCEM : Simulation Model l Each model M1 to M5 represents a discrete one-year difference equation n Inputs: some of the state variables (at year n – 1) n Outputs: some of state variables (M1 to M5 partitioning) n 10 to 30 lines of code (each) 2010 State of the world Energy Sources Zones World Earth N = 40,90, … times 2050 / 2100 / … State(i) = ƒ (state(i-1),*) M1 M2 M3 M4 M5 Outcome = time-series GDP CO2 Energy
  7. Yves Caseau - Coupling Coarse Earth Model – February 2023 7/26 CCEM : From Beliefs to Simulation to Outcomes Beliefs • Energy assets • Savings roadmap • GDP Energy- elasticity • Global Warming impacts • Expected growth if resources Foundations • CO2 -> temperature (IPCC) • Assets x Energy -> GDP -> investments -> delta(assets) • Production to Demand adjust through prices What you Give as An input Do not use CCEM if you disagree Levers • Energy Transition roadmap • CO2 Tax • Redistribution Outcome (make an excel Example) N iterations What you Play with during simulation True value : revisit your beliefs from observing outcomes GTES Game-Theory Evolutionary Simulation
  8. Yves Caseau - Coupling Coarse Earth Model – February 2023 8/26 Ecological Redirection (M5) M5 answers the question « What kinds of redirection should we expect from the IPCCs global warming consequences ?» Bruno Latour’s redirection concept tells that this is a non- linear coupling. There is no “point A to point B” trajectory, but reactions along the way, based on the catastrophic events that will unfold M5 is made of three components: l A simple projection from IPCC to link CO2 output (from M2-M3) to expected temperature rise (using RCP 4.5, 6 and 8.5) l A random, discrete function that define “pain thresholds” as CO2 & temperature rise l A redirection model (very naïve) with three components n Increase into energy redistribution (feedback to M2) n Increase CO2 tax (versus planned trajectory) n Economic crisis (feedback to M4) è Production capability damaged by warming (e.g. agriculture) è Workforce disruption (from strikes to massive death tolls of natural catastrophes and wars) IPCC model extraction T = f(CO2) CO2 concentration « pains » : weather catastrophes and cost of living « Redirection » Energy Redistribution & cancel acceleration Economy Damage (loss of resource) CO2 Tax Acceleration time CO2(PPM) Close Economy Branches Température (C°) catastrophe catastrophe Three drivers : fear (of future production loss), pain (less revenue) and compassion (disaster happening elsewhere)
  9. Yves Caseau - Coupling Coarse Earth Model – February 2023 9/26 Ecological Redirection Feedback l M5 Model of « World Feedback to Earth » 3 Loops (one large aggregation) CO2 ↗ T (C°) ↗ M2 Less energy available Loop 1: T to ”pain” to reaction M4 Loss of productive resources Loop 2: T to ”destruction” to economy loss M4 M2 CO2 tax ↗ cancel renunciation ↗ Re- distribution ↗ Composite Pain Loop 3: Economy contraction to pain to reaction canicules droughts floods fires Compassion WW misery Fear Future impact Pain Job & Property loss Death Displacements Agriculture Losses Economy Hits Aggregated into “T to pain” abstraction
  10. Yves Caseau - Coupling Coarse Earth Model – February 2023 10/26 Non-linear reaction Deaths, Displacements Agriculture Losses Economy Hits Less available energy Compassion WW misery Fear Future impact Pain Job & Property loss Composite Pain Loss of Productive Resources CO2 tax ↗ cancel renunciation ↗ Re- distribution ↗ time REACTION Température (C°) catastrophe catastrophe Aggregated into “T to pain” abstraction
  11. Yves Caseau - Coupling Coarse Earth Model – February 2023 11/26 CO2 ↗ T (C°) ↗ Ecological Redirection • More CO2 tax • Redistribution • Restrictions (renunciation) Composite Pain canicules droughts floods fires Deaths, Displacements Agriculture Losses Economy Hits Loss of Productive Resources Less available energy
  12. Yves Caseau - Coupling Coarse Earth Model – February 2023 12/26 Ecological Redirection (M5) M5 Inputs: CO2 yearly output in the atmosphere M5 Outputs: Four feedback signals to other models: energy redistribution, CO2 tax, cancel, damages to economy Fours steps l Computes CO2 concentration in the atmosphere, based on the ability of the Earth to absorb part of it. This should be updated to reflect that this ability will probably decline, by works as an approximation (CO2 in atmosphere = CO2 Output - 16Gt absorbed by forests, soil, ocean, …) l Use IPCC models to extract the expected temperature rise (note : the IPCC hypothesis about CO2 emissions in time are irrelevant here because they are computed by M1 to M4). l A “pain level” is derived from n Weather : floods, agriculture losses, fires, heat waves, … n Economic welfare: based on growth/recessions and cost of energy. Note: for the time being, redistribution is only modeled as “energy cost redistribution” – Another model M6 would be necessary to represent “economic redistribution / social justice / social unrest” l Pain drives “random, discrete” reactions (cf. illustration : step-wise pain-to-reaction functions) n Energy redistribution factor n CO2 tax acceleration n Cancel Acceleration (collective decision to ban some usages) n Loss of productive capacities and Loss of productive workforce are also captured through cancellation Pain level reaction MSc Strategy and Design for the Anthropocene Open Question: add a “capital destruction” feedback ? natural disaster repair reduce investments. Currently, this is captured in the M5->M4 productivity ratio
  13. Yves Caseau - Coupling Coarse Earth Model – February 2023 13/26 GDP Model (M4, World Economy) M4 represents the question: « which GDP is produced from investment, technology, energy and workforce ? » Description Economy is seen as a set of productive assets that require energy and human capital to operate Economy growth require investments that are a share of results We use a crude exponential growth model • Output is linked to energy (cf M2 + redistribution) • Demography is factored through energy consumption • Assets grow as a result of investment • Energy transition investments are subtracted from total investments to compute growth investments • GW Crises are modeled two ways : a reduction of productive assets and as an acceleration of « cancellation » • The model computes the consumption without savings that drives the GDP and the consumption with savings that drives CO2 emissions Productive Assets GDP (Results) Investments Energy Supply (Es) population Tech Innovation Energy transition Growth Invest Global Warming Natural Disasters Loss of resources (people, land, factories …) Energy Demand Open question (cf. O. Vidal) : model the “metal intensity” of value creation, either as a feedback loop for M4 or a constraint for transition (M3)
  14. Yves Caseau - Coupling Coarse Earth Model – February 2023 14/26 GDP Model (M4) M4 Inputs: energy consumptions with price levels, for each source and each block. Energy redistribution ratio (k : proportionality factor) Energy transition investments M4 Outputs: GDP (worldwide) and investments level l Economic result (R = GDP) depends on energy consumption Rn = R n-1 x (1 + Icn-1 × r) x (Esn / Edn)k × (Fn / Fn-1) 1. The GDP depends on the current level of productive assets, grown from previous year growth investments (r = ROI) 2. The output is adjusted to the actual energy available (Es: supply vs Ed: demand, Negawatts included) The exponent k represents the results of energy redistribution è without redistribution, k is derived from M2 (energy-to-value distribution), with complete redistribution, k = 1 (simplifying assumption !) 3. The productive assets are adjusted through ”global warming disasters” loss (Fn ) l Investments are computed from the GDP result and its variation using a linear regression: I n = x% × In-1 × (Rn / R n-1) + y% × (Rn - R n-1) l Energy transition investments Ien are produced by M3 model Growth investments are produced with the difference: Icn = In – Ien A negative value is interpreted as a loss of productive capacity l Carbon taxes are computed from energy consumption, but the model assumes that the value is recirculated into the economy (energy investments) without loss Another option would be to reinject CO2 to alleviate pains due to loss of economic activity Feedback from model 5 (loss of productive force) “redistribution” only applies to energy in version 3
  15. Yves Caseau - Coupling Coarse Earth Model – February 2023 15/26 Energy Resource Model (M1) M1 captures the answer to the questions « How much fossil resources do we have ? At which costs? » Four categories l Oil l Natural Gas l Coal l Others (“clean”: hydro/solar/wind/nuclear) Each resource is defined through: l For fossil energies, its inventory chart (available Toe according to sell price) l For clean energies, a growth potential curve (max capacity in the future year, according to manufacturing and resource constraints l A “max capacity” (yearly output) l A constraint about the speed at which this capacity may evolve Caracteristic chart: « Peak Oil » time Production Inventory GTep GToe Price : €/Toe 410$ Inventory chart (oil example) 242
  16. Yves Caseau - Coupling Coarse Earth Model – February 2023 16/26 Energy Resource Model (M1) M1 Inputs: 4 inventories / capacities / “capacity evolution” constraints M1 Outputs: a curve that describes (for each simulated year) the output for a given market price This is the simplest (parametric) model : for each possible sell price, l Compute the new inventory: n Available resources based on 3Y averaged price, n minus last year consumption l Determine new capacity goal, based on net demand of previous year (modulo a dampening factor to avoid oscillation) and operations capacity constraint (capacity growth factor is capped) l Output is a fraction (0 to 1) of max capacity, with price sensitivity that is extracted from past history GToe Price : €/Toe 410$ Production = f(price) 242 Max capacity = min (c0 x In/I0, cn-1 x min( maxGrowth, expectedGrowth) Local price elasticity There are two key aspects which are missing (first attempts to add into M1 failed) • Strategy of the resource owner to speculate on current price versus expected value (versus the naïve linear output model) • Time delay between decision to extract a new resource and actual operation is long (over 10 years) – versus the current capacity model that looks 3 years back
  17. Yves Caseau - Coupling Coarse Earth Model – February 2023 17/26 Energy Consumption Model (M2) M2 captures the answer to the question « How much energy is needed for the economy at a given cost ?» The heart of this model is (for each source) a histogram of value production: l Decomposition of value product (Y axis) l Over segments of energy usage (X axis) l This (virtual) decomposition is the base for telling how each actor will react to price increases The net behavior is represented by four curves : l Cancelation (% of activity that stops because price is too high) = f(p) l Economic loss due to cancelation l “Savings“ (energy efficiency) – reduction of consumption at iso-activity n Savings are a “policy” (decision ahead of time that gets implemented) -> similar to transition (M3) and defined as a function of time (f(t)) l Substitution towards another form of energy (using the matrix provided by M3) The last two options triggers associated investments Energy redistribution policy is a factor that lowers the pain of cancellation but reduces the economic efficiency Energy consumption for a given price decreases according to cancelation (upper histogram), energy savings and substitution (M3: one energy source to another) Share of the PNB that can be produced at a given price Evergy cost / value produced => Max price 100% Pmax1 Pmax10 Share Of energy S(Xi) = 100% X1 X2 X10 Energy consumtion savings cancel Substitution to« clean » Price / time 100% p0 100% Cancel Rate The loss of economic value due to Energy-based cancellation follows a convex law (lower value creation activities stop first)
  18. Yves Caseau - Coupling Coarse Earth Model – February 2023 18/26 Energy Consumption Model (M2) M2 Inputs: For each block, population and consumption history per energy source, M2 Outputs: Net demand for each energy source, for each geography block This is also parametric model (based on price) : l Iterate over energy resources (assumes a DAG order for substitution) n Computes the net energy need è Based on economy evolution (proportional [iso techno – improvement factored as “savings”]) è Based on population (1 + a(P/P0)) – a: share of energy consumption that is linked to pop growth n Distributes over energy sources using substitution that has been realized in the past years n Computes the resulting parametric (demand = f(price)) curves è Factoring cancellation according to the price è Savings “achieved so far” are also factored in M1 and M2 “coupling” means to find the price that adjust supply and demand Current instantiation of CCEM uses 4 blocks : US, China, Europe and RestOfWorld Note: A big oversimplification in the current model is to use the same cancel/saving curves for each source of energy (using a dumb ratio to account for different energy prices today)
  19. Yves Caseau - Coupling Coarse Earth Model – February 2023 19/26 Energy Transition Model (M3) M3 captures the answer to « How fast can we substitute one form of primary energy to another ? » Substitution matrix l Oil to Coal to Gas to Clean l 6 flows (N x N-1 / 2) l A substitution matrix as 6 coefficients (share of energy consumption that should be transitioned), depending on year (policy) l The matrix takes into account the “source to vector” possible paths (cf. illustration) – It should also factor the constraints from natural resources such as steel. Mobile storage electricity Industry transportation Heat Oll & Natural Gas Coal Clean Energy CTL Static storage & distributed gas Batteries, hydrogen Vectors The substitution matrix describes which substitution is feasible & desirable from an energy policy viewpoint (on the demand side) l Irreversible l When acted (a given year), generate the associated Investment (same for savings) Note: Models M1 / M2 focus on primary energy sources, M3 takes the energy vectors (electricity, hydrogen, …) into account to define which transitions are feasible Substitution Matrix Changes Energy Source Demand New Capacities and transfer Reflects the Energy Transition policy Speed of changed is capped (max from M1) Energy demand (M2) is balanced between 4 sources
  20. Yves Caseau - Coupling Coarse Earth Model – February 2023 20/26 Energy Transition Model (M3) M3 Inputs: Initial transition matrix, actual output for each energy source, actual market price (source dependent) M3 Outputs: transfer of energy consumption (yearly, starting on the date the decision is made), energy investments This model has two purposes: l For M2, to compute how much energy is consumed for a given price, using the current level of substitution (called the “substitution matrix”) l As a complement to M2, once the price is set and the energy consumption is known for a year n For each source and each block, n Once cancellation and savings have been applied, n Computes the new level of substitution using the transition matrix (reflect the zone policy) n The substitution matrix is adjusted (monotonous, always grow, and capped by maxGrowth parameter from M2) n Level of investment is adjusted based simple “energy investment costs” (cost to produce 1MWh) n M3 uses a parameter “technology efficiency” that reduces over the years the cost to transition l This model M3 also computes the CO2 yearly emissions for each energy source
  21. Yves Caseau - Coupling Coarse Earth Model – February 2023 21/26 GWDG Dynamic System (2008 view) Production Consumption Economy Gaia inventory capacity revenue Conso CO2 tax Societal Pressure CO2 emissions Unknown Model IPCC Forecasts Temperature Water rise GDP/person démography + + - - price cost needs Equivalent Consumption Invest E GDP M4 World Economy Investments Growth Invest M1 supply M2 demand M3 Energy transition M5 Ecological Redirection delay delay delay redistribution renouncement + + 4 instances • Oil • Gas • Coal • Clean 4 instances: • US • Europe • China • Rest of World savings cancel Tech Progress substitution Rate of CO2 catastrophies crises GWDG v3 One Economy
  22. Yves Caseau - Coupling Coarse Earth Model – February 2023 22/26 Conclusion l On-going work (this slide deck should be kept synchronized with the code) l First implementation (with CLAIRE) – to be translated to JavaScript for easier share l A tool to explore beliefs (mental models) and their combined effects WARMING/ ADAPTATION CARBON-NEUTRAL Finite World Radical Change Open World Continuous Change Temperature rises Technology changes the game W. Nordhaus Adjust to GW moderate GDP effects P. Diamandis Abundance JM Jancovici Carbon Shift P.Sevigne Collapse
  23. Yves Caseau - Coupling Coarse Earth Model – February 2023 23/26 Preliminary results l These are the outcome associated to the previous “three sets of beliefs” 33,8 65 84 104 128 154 165 198 208 212214 389 533 606 684 758 833 816 917 874 807 732 14,5 14,6 14,8 15,2 15,6 16 16,3 16,5 16,6 16,816,8 25 34 39,6 42,6 45,5 48,8 45,2 50,2 45,8 39,9 33 0 100 200 300 400 500 600 700 800 900 1000 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Energy-Rich Scenario GDP (T$) Energy (EJ) Temperature(C) CO2(Gt/y) 33,8 65 81 100 119 133 144 156 169 180 197 389,2 533 567 650 676 662 611 571 521 467 427 14,5 14,6 14,8 15,1 15,4 15,6 15,8 15,9 16 16 15,9 25 34 36,6 38,3 35,3 31,5 26,1 21,9 17,6 13,7 10,3 0 100 200 300 400 500 600 700 800 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Exponential Technologies Scenario GDP (T$) Energy (EJ) Temperature(C) CO2(Gt/y) 33,8 65 77 90 94 97 94 92 90 88 90 389,2 533 532 580 541 502 430 375 325 289 269 14,5 14,6 14,8 15 15,3 15,5 15,6 15,6 15,6 15,5 15,4 25 34 34,3 35,1 30,2 26,2 20,3 15,4 11 8 6,2 0 100 200 300 400 500 600 700 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Stick to Paris Agreement GDP (T$) Energy (EJ) Temperature(C) CO2(Gt/y)
  24. Yves Caseau - Coupling Coarse Earth Model – February 2023 24/26 Median Belief Scenario (WIP) l Key PKI for CCEM outcome + Kaya coefficients 33,8 65 84 106 119 124 130 136 146 154 160 389,2 533 605 697 706 671 636 600 567 538 516 14,5 14,6 14,8 15,2 15,5 15,9 16,2 16,4 16,4 16,5 16,5 25 34 39,5 43,2 42,3 38,7 35,2 31,3 27,5 24,3 21,6 0 100 200 300 400 500 600 700 800 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Median Belief Scenario GDP (T$) Energy (EJ) Temperature(C) CO2(Gt/y) 6,6 7,3 8,1 8,9 9 9,2 9,2 9,3 9,4 9,3 9,2 25 34 39,5 43,2 42,3 38,7 35,2 31,3 27,5 24,3 21,6 240 239 232,6 221 214 206,1 198 186,3 173,1 161,8 150,1 319 227,9 199,1 182,4 164,2 149,9 135,5 121,7 107,7 96,8 89,4 5,12 9,8 12,8 16 18,1 18,8 19,7 20,7 22,1 23,4 24,2 0 50 100 150 200 250 300 350 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Kaya Identity Pop (G) CO2(Gt/y) gCO2/KWh e-intensity (Wh/$) / 10 GDP/p (k$)
  25. Yves Caseau - Coupling Coarse Earth Model – February 2023 25/26 Similar Earth Models Nordhaus: DICE Model ACCL (Banque de France) MIT Integrated Global System Modeling (IGSM) Framework SOS Trades The IGSM framework consists primarily of two interacting components—the Economic Projection and Policy Analysis (EPPA) model and the MIT Earth System model (MESM). The EPPA model simulates the evolution of economic, demographic, trade and technological processes involved in activities that affect the environment at multiple scales, from regional to global. SoSTrades is a web-based, multi-user, interactive publication-quality graph simulation platform. It allows users to drop new modules without additional coding, and provides embedded advanced numerical capabilities for simulation and multi-disciplinary optimization. It also has built-in collaborative capabilities to allow different experts to work together. The economic model we will explore here is based on a model created by William Nordhaus of Yale University, who is considered by many to be the leading authority on the economics of climate change. His model is called DICE, for Dynamic, Integrated Climate and Economics model. It consists of many different parts … we can carry out some experiments with this model to explore the consequences of different policy options regarding the reduction of carbon emissions. A tool to build climate change scenarios to forecast Gross Domestic Product (GDP), modelling both GDP damage due to climate change and the GDP impact of mitigating measures. It adopts a supply-side, long-term view, with 2060 and 2100 horizons. It is a global projection tool (30 countries / regions), with assumptions and results both at the world and the country / regional level. Five different types of energy inputs are taken into account according to their CO2 emission factors., Total Factor Productivity (TFP), which is a major source of uncertainty on future growth and hence on CO2 emissions, is endogenously determined,