A System Dynamics Model for Global Warming Impact, from Energy Transition to Ecological Redirection

Yves Caseau - CCEM : System Dynamics for Earth Model – December 2024 1/23
A System Dynamics Model for Global Warming Impact,
from Energy Transition to Ecological Redirection
Yves Caseau
National Academy of Technologies of France (NATF)
December 4th, 2024
FormAction Presentation
In Memoriam
http://modelccem.eu

Outline
1. Why : Yet Another Integrated Assessment Model ?
◼ System Dynamics, Integrated Assessment Models
◼ Known Unknowns as Parameters
2. CCEM Model Overview
◼ Coupling of 5 “coarse” models
◼ M1 to M5 Overview
3. Computational Scenarios
◼ Preliminary results
◼ Sensitivity analysis
4. So What : What are the first insights ?
◼ A possible new narrative of global warming
◼ Next Steps

Motivations for Yet Another Earth/Climate/Economy Model
• SCC (Social Cost of Carbon):
”Comprehensive evidence
implies a higher social cost
of CO2” (Reinert & al.)
• Qualitative assessment of
damages, but monetary
value is hard to agree on –
cf. IPCC Working Group II
(Impact, Adaptation &
Vulnerability)
• Double questioning of IAMs
regarding damage modeling :
level and non-linear tipping
points (Stern, Stiglitz and
Taylor, 2022)
Damages
• How much fossil energy will
be available, at which
extraction costs in the 21st
century ?
• How fast can we
manufacture and deploy
sustainable energies ?
• How fast can we electrify
the use of energy ?
• How will the energy intensity
(kWh / M$) trend evolve in
the next century ? For each
continent ?
Energy Future
• Damages will trigger societal
reactions as pain grows:
• Possible redirections
• Cancelation (renounce a CO2
producing activity)
• Acceleration (Energy transition,
Efficiency & carbon taxes)
• protectionism
Redirections
Part
I
-
Why
?

EM3: “Energy Matters” Modeling Manifesto
This (WIP) manifesto states that all IAMs should disclose their 2050 hypothesis for the following “Known Unknowns”
Oil Reserve Wind+Solar
Energy Density
Electrification
0
50
100
150
200
250
1980 2000 2020
Oil Reserve (Gt)
2050
New reserves
+ lower
consumption
0
1
2
3
4
5
2010 2013 2016 2020 2023
Wind+Solar(PWh)
1.3 PWh/y
CCEM
0.5 PWh/y
2023
2.5 PWh/y
COP28
Until 2030 !
0,0%
5,0%
10,0%
15,0%
20,0%
1950 1980 2000 2020
Electrification (%)
2050
Viscosity of
Energy
transition
Electricity
Production/
Total Energy
CCEM @ 30%
aggressive
Supposes
sobriety
2050
CAGR (negative)
- 3.6% past 40
years with
inflation
- Only -0.7%
when
inflation is
factored out
CCEM @ 0.5% is
conservative
(energy-poor
recession)
Net-zero
> 50%
Part
I
-
Why
?

The Complexity of Assessing Damages
⚫ What is the expected GDP loss associated to a warming of +3C ?
-3% for +3C -7% to -10% for +3C -15% to -25% for +3C
>= 10 years old >= 5 years old current
Part
I
-
Why
?
2050 (+1.7) impact is
very strong (-6%)
Swiss Re : $280B in 2023
$100B insured losses

1. SDEM (System Dynamics Earth Model)
◼ Closed, first-principle model with multiple feedback loops where each dimension
(energy / economy/ climate / population) impact each other
◼ Resource reserves (energy / steel) modelled with a price function (cf. critics of LtG)
2. Explicit beliefs
◼ Macro-parameters : ”known unknown” acknowledged as such
◼ CCEM may reproduce many conflicting views (just change the input beliefs)
3. Realistic energy transition
◼ Speed of deployment of clean energies (hard)
◼ Rate of change in primary/vectors energy flows, including intermittency & storage constraints
(harder)
4. Geopolitical Zones with different strategies
◼ Strategy : combination of GDP, happiness and global warming + time discounting
◼ CCEM acknowledges divergent interests and different priorities
5. Ecological redirection : how society reacts to warming and accelerate adaptation
◼ WIP : tuning strategy to tactical, warming damages to pain and impact
CCEM in a nutshell (current version v6)
Part
I
-
Why
?

Part II
◼ Coupling of 5 “coarse” models
◼ M1 to M5 Overview
Part
II
-
CCEM
Overview

CCEM : Coupling Five Coarse Models with System Dynamics
4 instances
• Oil
• Gas
• Coal
• Clean
5 instances:
• US
• Europe
• China
• India
• Rest of
World
M3 : Energy
Transition
inventory
capacity
revenue
Conso
CO2
tax
Societal
Pressure
CO2
emissions
Unknown Model
IPCC Forecasts
Temperature
Water rise
GDP/
person
demography
+
+
-
Price
cost
needs
Equivalent
Consumption
Energy
Invest
assets
Investments
Growth Invest
delay
delay
delay
Energy
policies
renouncement
+
+
savings
cancel
Tech
Progress
substitution
Rate of
CO2
catastrophes
crises
Wheat
Steel
Food/`
person
Land
Use
protectionism
M2: Energy
Consumption
M1: Energy Production M5: Ecological Redirection
M4: Economy
Part
II
-
CCEM
Overview
GDP

CCEM : Simulation Model
⚫ Each model M1 to M5 represents a discrete one-year difference equation
◼ Inputs: some of the state variables (at year n – 1)
◼ Outputs: some of state variables (M1 to M5 partitioning)
◼ 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
Works
For
grasping
« Gray
Rhinos »
More
than
« Black
Swans »
Part
II
-
CCEM
Overview

M1/M2 : Energy and M4:Economy
• Economy is seen as a set of productive assets that
require energy and human capital to operate
• Economy growth require investments that are a
fraction of results
• This model is applied to 5 “Blocks” :
US, CN, EU, India, RoW
• To represent the “material economy” we use two
“proxies” : steel and wheat productions
Economy
• A crude model for energy inventory (reserves) for
fossil fuels & capacity evolution
• A crude model (KNU) about the speed at which
solar & wind may be deployed
• A demand elasticity model that includes sobriety
(chosen), efficiency, transition and cancellation
(forced sobriety)
• CCEM matches demand & supply with macro price
setting.
Energy Model
Energy
consumption
Price / time
100%
p0
Part
II
-
CCEM
Overview Cf. Alain Grandjean
(Carbone 4) : Modele
de Solow (max out)
w energy constraints
+ Damages – cf
Jancovici)
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
Decay
Trade
Matrix

M3 (energy transition) & M5 (Ecological Redirection)
• CO2 emission is computed from energy
consumption by sources (adjusted)
• CO2 concentration is a naïve linear model
• Temperature follows IPCC RPCs
• Damages will trigger
societal reactions
as pain grows:
Redirections
• CCEM uses a transition matrix that reflects how
fast can energy consumption migrate from one
primary source to another
• This reflects the use of hydrogen, but mostly the
speed of electrification
• Country blocks may choose their transition speed
• CCEM bears similarities with WITNESS climate model
• Energy is critical to produce value
• Transition map defines
possible landscape
Energy Transition
Mobile storage
electricity Industry
transportation
Heat
Oll & Natural Gas
Coal
Clean Energy
Static storage
& distributed
Vectors
Part
II
-
CCEM
Overview
Both through
regulation and
stakeholders
pressure on
companies
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
”Transition
to Green”,
Efficiency
acceleration
Reduced
Agro-yield &
population &
Productivity
“CBAM”

Part III
◼ Preliminary results
◼ Sensitivity analysis
Part
III
-
Preliminary
Results

CCEM : Six KNUs (Key kNown Unknowns)
⚫ These 6 KPI provide the best characterization of the CCEM “known unknowns”
◼ what creates the heavier debate, for instance speed of Clean energy growth vs fossil reserve
◼ These KPI can be compared with other published values from prospective institutes ☺
◼ When looking at a simulated forecast, one should always ask for these 6 hypotheses
Clean Energy Growth Rate
KPI1: PWh added in 10 years
Default value : 13 PWh
IRINA 1.5C scenario: 25 PWh
Energy Intensity
KPI2: CAGR decrease of E/GDP
Default value : 0.5% (2010-2050)
0.7% between 1980 and 2020
in constant dollars (3.6 % with inflation)
IRINA 1.5C scenario: 2.7%
Energy to price elasticity
KPI3: long-term elasticity demand to price
Default value : -0.3
Values from Reed : -0.05 short-
term and -0.3 long-term
Electrification of Energy
KPI4: electricity(TWh) / total energy
Default value : 30% in 2050
16% in 2020
IRINA 1.5C scenario: 80%
Return on Investment
KPI5: world average of RoI
(yearly GDP increase / investment)
Default value : 13% (2010-2050)
Calibrated from past + guess ☺
Global Warming Impact
KPI6: GW damages, as % of GDP for +3C
Default value : -6.7% at +2.6C
approximate SCC at 270$/t
Values picked from Schroders: 8% at 3C
Ask GPTo1 or Claude
3.5 about these 6
questions …
Part
III
-
Preliminary
Results

“Median KNU Belief” Scenario
Inertia of
non-electric
fossil energy
Growth of
immaterial
service
economy
Reflects
latest
forecasts
Part
III
-
Preliminary
Results
CO2 @
609 ppm
2010
constant
dollars
+2.5C vs
20th c.
average

Median Scenario : Zone views
⚫ Reproducing interdependent zone economies is key to play geopolitical scenarios
Part
III
-
Preliminary
Results
Inflation is likely in a world constrained in resources …
Current dollars are hard to evaluate
US and CB will grow, EU is slightly declining and the rest of
the World suffers a recession
Constant but slow progress of
decarbonation
CO2 emissions start to reduce because of
Gas + Oil peak
GDP is well explained by available energy: US
progresses (dematerialization), CN “Coal to
Green” strategy delivers, EU is declining and the
Rest of the world is strangled by high energy costs
2%
inflation
assumption
47%
electrification
in 2100
Peak CO2
emission
in 2040
China de-carbonation
(long-term) strategy
works well

Sensitivity analysis
⚫ All parametric beliefs have an impact, some more than others
The more energy-intensive and the cheaper the
current energy mix is, the higher the CO2 tax
impact is
- rebound effect when EU is leading alone
- Unrealistic scenario for world unified tax (CN)
Peak oil and available fossil fuels have both an impact on GDP
(significant) and on warming (moderate, because of accumulation)
Faster Deployment of clean energy has a
strong impact on GDP (energy shortage is
reduced) but not so on warming
55%
electrification
43%
electrification
Same fossil
consumption,
same warming
Unrealistic
economic
impact

Part IV
◼ A possible new narrative of global warming
◼ Next Steps
Part
IV
-
First
Insights

“Not the End of The Word”
⚫ “Business as Usual” should be
”slow transformation as usual”
Factoring Peak Oil/Gas, there is not enough
fossil fuel for +4C scenario, +3C is hard/unlikely
⚫ Transition has started (cf. Hannah Richie’s book):
◼ Clean energy transition; energy savings / efficiency
➔ Continuous progress for air quality in Europe over a century
◼ “Death rates from natural disasters have fallen 10
folds in a century”
◼ Water/natural resource conservation progresses +
Crops yield has improved for 50 years
⚫ “Decarbonation / GHG” transformation brings opportunities together with challenges
◼ Better synergy with nature, healthier food, more serenity with slower lifestyle, …
⚫ Technology and innovation will definitely help along the way
◼ Lots of paths are visible (cf. Solar Impulse foundation, Bertrand Piccard)
◼ Exponential NBIC growth is not a myth ☺
Following
current IPCC
consensus on
CO2 to T
Part
IV
-
First
Insights

Transitions and Delays
⚫ There is a time gap between the fossil peak and
the advent of clean energy at the expected level
◼ This is why the value of fossil reserves and the
possible speed of green energy transition matter so much
◼ This (left) illustration is not the median scenario but
the optimistic version (cf. Vaclav Smil)
⚫ The interest of geopolitical zones are very different, a
scenario of worldwide sobriety (to close the gap) is
unrealistic
◼ This creates a period of economic strangulation by lack of
energy
⚫ “Carbon neutral 2050” / Paris Agreement / net-zero COP:
“deader than a doornail” - James Hansen
◼ unless carbon sequestration becomes efficient,
scalable and affordable
⚫ Get ready for 2.5 C° +/- x (vs 20th century average)
◼ 2.7 C° vs IPCC pre-industrial reference
This is a critical graph
irrespectively of the
model or the source
Part
IV
-
First
Insights

“Not the End of the World” … but end of the 20th century World
1. Sustained Global Warming, severe impacts to be expected,
◼ Adaptation is mandatory
2. Cheap Energy is gone, busts of energy shortages
◼ No longer a free market, large zone discrepancies (already started, intensified with conflicts)
3. End of sustained worldwide growth
◼ Will reinforce the perception and the pains of inequality
4. Resource constraints will trigger aggressive competition
◼ Conflicts rise, probable wars
◼ Trade wars (protectionism, this is only the beginning)
◼ Cyber-espionage (cf. UK expert warning)
5. Prepare for surprises and redirection (political reactions pushed by societal fears)
◼ Read “Hello Future!” from Langdon Morris
Part
IV
-
First
Insights

A “new narrative”:
Avoiding stress as a motivator, Avoiding a promise that we may not keep
⚫ « The Future of European competitiveness» :
Very consistent with CCEM simulation ! “foundations of Europe competitiveness have
been shaken”
◼ “Even though energy prices have fallen considerably from their peaks,
EU companies still face electricity prices that are 2-3 times those of US”
◼ “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)
◼ “The productivity gar between the EU and the US is largely explained by the tech
sector”
⚫ Europe playbook : Accelerate anticipation to get out faster from
« the pricey fossil fuel tunnel »
Not to avoid the end of the world, but to avoid the end of Europe
(as a major economy player)
◼ cf Mario Draghi’s joint plan for decarbonation and competitiveness
⚫ Anticipate versus React :
Energy sobriety will be forced upon us either way
Anticipation has a cost, but it broadens the cone of possible mitigation
Efficiency
Acceleration
Energy Source Transition
Sobriety
Policies
regulations
GW
Damages
Energy
Price
increases
Carbon
taxes
ANTICIPATE
Towards
decarbonation
Tech Digital
Too little,
too late
☺

Green
Production
Electri-
ficaton
REACT
Electrification (of
energy consumption)
favors efficiency
Balance green production and consumption
Time / energy de-carbonation
Price
of
energy
☺
☺ 
Happy decades of
growth thanks to
cheap fossil energy
Unhappy decades of
lack of competitiveness
because of energy
scarcity
Possible bright future
where Europe enjoys
the fruits of early-
mover advantage to
decarbonated economy
Part
IV
-
First
Insights

Next Step: Global Warming, Geopolitics and Game-Theory
• Do not assume that blocks
have similar goals …
• What is the benefit of
an “EU green policy”
facing D. Trump and
Xi Jinping ?
• Is there an anticipation
benefit ?
(“suffer earlier, suffer less”) ?
• What are the levers for player to influence
each others (trade barriers, CBAM, …) ?
• Could world population indignation yield a
significant systemic change ?
Evolutionary Game-Theory
• A Method developed 15 years ago for Telco
markets equilibrium
• 3G and 4G licenses
• Free introduction
• Combines
• Monte-Carlo simulation for uncertain
KNU (from curves to cones)
• Local optimization
for tactical
adaptation (BR)
• Search for Nash
Equilibriums
Strategy = goals for each zone
GDP, Pain level, World temperature
GTES
Part
IV
-
First
Insights

Conclusion
⚫ CCEM is a tool to explore beliefs (mental models)
and their combined effects
◼ Tune your own mental models from simulation feedback loops
◼ Way of use : beliefs → simulation → one outcome that seems
possible (then repeat)
◼ Antifragile System Dynamics Modeling:
Grows from criticism and conversations (v3 to v4 to v5 to v6)
⚫ Five Key questions (Key Known Unknown)
1. What is a plausible energy trajectory ? (cf. EM3)
2. In a word constrained by lack of energy, should one-sided
consumption reduction reduce CO2 emissions?
3. What is a plausible elasticity scenario,
so that demand lowers to possible supply ?
4. What is the expected outcome of +2.5C warming ?
5. What is the best way to adapt (to protect ourselves) ?
⚫ 2025: Explore “the complexity of cooperation”
◼ “Will human governance and cooperation on global warming be
designed or emergent ?”
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

Appendix
https://github.com/ycaseau/GWDG

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 fossil>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
Part
I
-
Why
?

Energy Resource Model (M1)
M1 captures the answer to the questions « How much fossil resources do we have ? At which costs? »
Four categories
⚫ Oil
⚫ Natural Gas
⚫ Coal
⚫ Clean (hydro/solar/wind/nuclear)
Each resource is defined through:
⚫ For fossil energies, its inventory chart
(available PWh according to sell price)
⚫ For clean energies, a growth potential curve
(max capacity in the future year, according to
manufacturing and resource constraints)
⚫ A “max capacity” (max yearly output)
⚫ A constraint about the speed at which this capacity
may evolve + a heuristic formula that adjusts the
capacity each year
Gtoe/y
Price : $/PWh
410$
Fossil Fuel Production = f(price)
Max capacity
- matches expected growth
- Yearly growth is constrained
- Declines when reserves decline
Local price elasticity
4 Gt
cmax
Gtoe/y
Price : $/PWh
$
Clean Energy Production = f(price)
Max capacity =
cn-1 x min( maxGrowth,
expectedGrowth)
unconstrained target price trends
follows world GDP

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 & each zone)
a histogram of value production:
⚫ Decomposition of value product (Y axis)
⚫ Over “segments” of energy usage (X axis), sorted by energy
intensity
⚫ This (virtual) decomposition is the base for telling how each world
zone will react to price increases
The net behavior is represented by three curves :
⚫ Economy dematerialization trend (kW/$)
⚫ Cancelation (% of activity that stops because price is too high)
⚫ Economic loss due to cancelation (GDP impact of cancel)
In addition, we represent the expected efficiency gains:
⚫ “Savings“ (energy efficiency) – reduction of consumption at iso-activity
◼ Savings are a “policy” (decision ahead of time that gets implemented)
⚫ Substitution towards another form of energy (using the matrix provided by M3)
⚫ The last two options triggers associated investments
Energy redistribution policy is a factor that lowers the pain of cancellation but
reduces the economic efficiency
Energy consumption for a given price
decreases according to cancelation
(upper histogram), energy savings and
substitution (M3: one energy source to
another)
Value (GDP) of each slice of
economy sorted by value/toe
Value
(T$)
100%
Current
Cost of
energy
Energy
consumption
Price / time
100%
p0 The loss of economic value due to
Energy-based cancellation follows
a convex law (lower value creation
activities stop first)
Evolution of
distribution
represents the
dematerialization
of the zone economy
(kW/$)
Cancel Rate
100%
GDP
impact

Energy Transition Model (M3)
M3 captures the answer to « How fast can we substitute one form of primary energy to another ? »
Substitution matrix
⚫ Oil to Coal to Gas to Clean
⚫ 6 flows (N x N-1 / 2)
⚫ A substitution matrix as 6 coefficients (share of
energy consumption that should be transitioned),
depending on year (policy)
⚫ 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
Flows, e.g.,
electricity Industry
transportation
Heat
Oll & Natural Gas
Coal
Clean Energy
Static storage &
distributed
Vectors
The substitution matrix describes which substitution is feasible &
desirable from an energy policy viewpoint (on the demand side)
⚫ Irreversible
⚫ 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

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
fraction of results
We use a crude exponential growth model
and constant 2010 dollars
• Output is linked to energy (cf. M2 + redistribution)
• Demography is factored through energy consumption
• Two trajectories : maxout (based on invest + RoI), results (reduced by
available energy, population and GW damages)
• Assets grow as a result of investments, and they also decay (1%)
• Energy transition investments + growth investments = total investment
• GW Crises reduce productive assets and yield ”redirections ” (M5)
• The model computes the consumption without savings that drives the GDP and
the consumption with savings that drives CO2 emissions
• This model is applied to 5 “Blocks” : US, CN, EU, India, RoW
US
T$ 15
CN
T$ 6
EU
T$ 14.5
RoW
T$ 30
248
360
167 900 1080
1200
1300
90
2010 world economy crude decomposition (trade in G$)
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
Decay
Trade
Matrix

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:
⚫ A simple projection from IPCC to link CO2 output (from M2-M3) to
expected temperature rise (using RCP 4.5, 6 and 8.5)
⚫ A composite discrete function that define “pain thresholds” as CO2
& temperature rise
⚫ A redirection model (very naïve) with four components
◼ Increase into energy redistribution, acceleration of transition
and efficiency investments
◼ Increase CO2 tax (versus planned trajectory) and CO2-based
protectionism (CBAM)
◼ Economic crisis (feedback to M4)
➔ Production capability damaged by warming
(e.g. agriculture)
➔ 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
”Transition
to Green” &
Efficiency
acceleration
Reduced
Agro-yield &
population &
Productivity
“CBAM”
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)

M4: Physical versus Immaterial GDP
⚫ The model uses “constant dollars” as monetary unit (for GDP and energy price)
◼ 2% inflation used to display “current dollars” results … but ”2100 dollars” is an abstract notion ☺
⚫ High GDP growth in the past 30 years reflects the growing importance of “immaterial” economy
⚫ The “CCEM4” model (4th iteration) adds two outputs to evaluate the “material” side:
◼ Steel production and Wheat production (including the agriculture land use)
Steel production (proxy of material goods) Wheat production (proxy of Agriculture)
Energy
Resource
Energy
extraction
(M2)
Energy
Production
Iron
Resource
Ore
extraction
+ process
Iron
production
GDP
production
(M4’)
New
Energy
Capacity
Grain
Production
(M4’)
Agriculture
Land use
Catastrophes
Global
Warming
(M5)
Grain
production
/ inhabitant
GDP production
(M4)
Living
Health
Energy
Production
Agro
Efficiency
CO2
concentration
Global
Mood (M5)

Global Warming Damages
Canicules
Droughts
Lack of
water
Floods
inc. coastal
Fires Death & Severe Health
Issues
Population Displacements
Agriculture
Losses
Economy Hits
loss of assets &
workforce
workforce
Simplified categories of impacts
• Destruction of properties
• Health – loss of productive workforce
• Lack of water
• Loss of agricutural surface
• Loss of efficiency
•Diaz, D.B. Estimating global damages from sea
level rise with the Coastal Impact and Adaptation
Model (CIAM). Climatic Change 137, 143–156
(2016).
•Anticipating Climate Change Across the United
States! 2023, Adrien Bilal, Esteban Rossi Hansberg
New science of climate change impacts
on agriculture implies higher social cost
of carbon. Frances C. Moore, Uris Baldos,
Thomas Hertel, Delavane Diaz,
Nature Communications, 8:107
• The economics of climate change: inaction is not
an option - April 2021 - Swiss Re Institute
• The impact of climate change on the global
economy - Wade and all, Schroders, 2016
• The economic implication of climate change –
June 2019 - Moody’s Analytics
• The Social Cost Carbon Explorer - GIVE Model -
RFF-Berkeley Green House Gas Impact Value
Estimator
Cromar et al.,
Systematic Reviews, Annals ATS, July 2022

NGFS Scenarios for central banks and supervisors
⚫ Produced by the best IAM teams in Europe…
⚫ ... With a purpose / message !
⚫ Net Zero (and its cousins)
◼ Similar to IEA NZE …
◼ Search for the three « amazing beliefs »
in this illustration ☺
1. Rate of green electricity growth
2. Electrification (otherwise green
electricity has small impact)
3. Total amount of energy available for economy
(you better believe in dematerialization economy !)
◼ As noticed in AXA IM Note
« What energy transition scenarios are and how they can be used or misused »
⚫ Hot House World
◼ BAU scenarios
(pessimistic bordering on unrealistic)
◼ Damage model is strongly opiniated
1
3
2
Part
IV
-
First
Insights

A System Dynamics Model for Global Warming Impact, from Energy Transition to Ecological Redirection

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