Second Ukrainian NDC to the Paris Agreement: Modelling Approach and ResultsIEA-ETSAP
Second Ukrainian NDC to the Paris Agreement: Modelling Approach and Results
Diachuk O., Poodles R., Chepelev M., Institute for Economics and Forecasting of National Academy of
Sciences of Ukraine
Planning a reliable power system with a high share of renewables in France by...IEA-ETSAP
Planning a reliable power system with a high share of renewables in France by 2050: a new multi-scale, multi-criteria framework
Mr. Yacine Alimou, Mines ParisTech
Development of 2050’s national long-term energy plans for carbon neutrality t...IEA-ETSAP
Development of national long-term energy plans, for 2050’s carbon neutrality targets, using the DESSTINEE model.
Dr. Gabriel David Oreggioni, Imperial College London
Germany is Europe’s biggest energy consumer. As a large and industrial country with moderate natural endowments, it sets an example of what can be done with a progressive energy policy. Germany leads the charge on renewables, has an ambitious energy efficiency policy, is committed to phasing out nuclear power generation and uses ETS revenues fully for the fight against climate change. However, the future of the German energy transition is rather uncertain. Are energy prices sustainable with the current high taxation rates? How to expand the high-voltage grid to integrate wind generation from the North? What will be the future role of coal and gas? In this discussion webinar, we will review the most important energy statistics for Germany, present a few highlights on its energy policy and conclude with a series of open discussion points.
Sustainable energy and climate mitigation pathways in the Republic of MauritiusIEA-ETSAP
nable strategies and low emission pathways in Small Island Developing States: a costoptimization approach for the integration of renewables in the Republic of Mauritius.
Ms. Anna Genave, Université de La Réunion
Second Ukrainian NDC to the Paris Agreement: Modelling Approach and ResultsIEA-ETSAP
Second Ukrainian NDC to the Paris Agreement: Modelling Approach and Results
Diachuk O., Poodles R., Chepelev M., Institute for Economics and Forecasting of National Academy of
Sciences of Ukraine
Planning a reliable power system with a high share of renewables in France by...IEA-ETSAP
Planning a reliable power system with a high share of renewables in France by 2050: a new multi-scale, multi-criteria framework
Mr. Yacine Alimou, Mines ParisTech
Development of 2050’s national long-term energy plans for carbon neutrality t...IEA-ETSAP
Development of national long-term energy plans, for 2050’s carbon neutrality targets, using the DESSTINEE model.
Dr. Gabriel David Oreggioni, Imperial College London
Germany is Europe’s biggest energy consumer. As a large and industrial country with moderate natural endowments, it sets an example of what can be done with a progressive energy policy. Germany leads the charge on renewables, has an ambitious energy efficiency policy, is committed to phasing out nuclear power generation and uses ETS revenues fully for the fight against climate change. However, the future of the German energy transition is rather uncertain. Are energy prices sustainable with the current high taxation rates? How to expand the high-voltage grid to integrate wind generation from the North? What will be the future role of coal and gas? In this discussion webinar, we will review the most important energy statistics for Germany, present a few highlights on its energy policy and conclude with a series of open discussion points.
Sustainable energy and climate mitigation pathways in the Republic of MauritiusIEA-ETSAP
nable strategies and low emission pathways in Small Island Developing States: a costoptimization approach for the integration of renewables in the Republic of Mauritius.
Ms. Anna Genave, Université de La Réunion
Assn 4:
Graph 1: ___________________________________________________________
Electricity Emissions (E1)
(Mt CO2e/y)
0
$/t
CO2e MAC1
MAC2
Deforestation Emissions (E2)
(Mt CO2e/y)
0
$/t
CO2e
0
0
Graph 2: ___________________________________________________________
Electricity Emissions (E1)
(Mt CO2e/y)
0
$/t
CO2e
MAC1
MAC2
Deforestation Emissions (E2)
(Mt CO2e/y)
Aggregate Emissions (E1)
(Mt CO2e/y)
0 0 0
MACAggregate
Econ2216 (2012): Assignment 4
Cap and Trade
Ruth Forsdyke
Due Date: Monday April 8th
This assignment is optional as your assignment grade is the best 3 out of 4 assignments. However, even if you do not hand in
the assignment, I recommend doing it, to 1) learn and 2) to help you to study for the final exam.
Problem 1: Dire Predictions
a) We can see from the graphs on pg. 41 and 84 that both atmospheric CO2 concentrations and
temperatures have oscillated greatly throughout Earth’s history. Given this, some people argue that
anthropogenic climate change is not a great threat to Earth’s ecosystems and human civilizations as the
ecosystems have proven to be able to withstand such large changes. Provide two basic reasons why this
argument is wrong (see pg. 142 – 143).
b) Why can conserving and repairing ecosystems like forests help us to both mitigate and adapt to
climate change? Is adaptation a sufficient response to climate change or is mitigation also necessary?
(pg. 142) (pg. 195)
c)The social cost of carbon (SCC) is another name for the marginal damage. What are the ranges of
estimates for the SCC for first decade of the 21st century? (pg. 146).
d) Mann and Kump list some limitations of Nordhaus’s model. Please list. (Pg. 146)
e) Provide three ways to adapt to rising sea levels. Which nations will have more difficulty adapting?
(pg. 148-149)
* you may also want to read through the water management and agricultural adaptation strategies. Also,
note that conserving and re-establishing wetlands is important for minimizing damages from storm
surges.
f) Based on the IPCC estimates graphed on pg. 156 of DP (which seem low to me), at a carbon tax of 30
$/ tonne CO2e, how many emissions would be abated in each sector and in aggregate?
g) Did global aggregate emissions go down in any sector in 2004 relative to 1990? (pg. 159)
h) Which region has the highest energy consumption per capita? (pg. 161 map)
i) Which type of transport emissions, road, air or sea is responsible for most of transport emissions? Out
of this sector, rank the emissions from each type of transport.
j) Biofuels have the potential to be carbon neutral because once you combust the carbon in the plants,
you can recapture the carbon by photosynthesis as the plants grow. Although these technologies have
potential ...
Sensitivity of Ireland’s potential carbon budget pathways with varying social...IEA-ETSAP
Sensitivity of Ireland’s potential carbon budget pathways with varying social discount rates in an energy system optimization model
Mr. Jason Mc Guire, UCC
SMART2020: ICT & Climate Change. Opportunities or Threat? Chris Tuppen, BTcatherinewall
This is Chris Tuppen\'s presentation at the it@cork Green IT - Reduce CO2 Raise Profits Conference on Nov 26, 2008. Chris is the Director of Sustainable Development for BT
Variable Renewable Energy in China's TransitionIEA-ETSAP
Variable Renewable Energy in China's Transition
Ding Qiuyu, UCL Energy Institute
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
The Nordics as a hub for green electricity and fuelsIEA-ETSAP
The Nordics as a hub for green electricity and fuels
Mr. Till ben Brahim, Energy Modelling Lab, Denmark
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
The role of Norwegian offshore wind in the energy system transitionIEA-ETSAP
The role of Norwegian offshore wind in the energy system transition
Dr. Pernille Seljom, IFE, Norway
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Detail representation of molecule flows and chemical sector in TIMES-BE: prog...IEA-ETSAP
Detail representation of molecule flows and chemical sector in TIMES-BE: progress and challenges
Mr. Juan Correa, VITO, Belgium
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Green hydrogen trade from North Africa to Europe: optional long-term scenario...IEA-ETSAP
Green hydrogen trade from North Africa to Europe: optional long-term scenarios with the JRC-EU-TIMES model
Ms. Maria Cristina Pinto, RSE - Ricerca sul Sistema Energetico, Italy
Ms. Maria Cristina Pinto, RSE - Ricerca sul Sistema Energetico, Italy
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Optimal development of the Canadian forest sector for both climate change mit...IEA-ETSAP
Optimal development of the Canadian forest sector for both climate change mitigation and economic growth: an original application of the North American TIMES Energy Model (NATEM)
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Presentation on IEA Net Zero Pathways/RoadmapIEA-ETSAP
Presentation on IEA Net Zero Pathways/Roadmap
Uwe Remme, IEA
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Flexibility with renewable(low-carbon) hydrogenIEA-ETSAP
Flexibility with renewable hydrogen
Paul Dodds, Jana Fakhreddine & Kari Espegren, IEA ETSAP
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Bioenergy in energy system models with flexibilityIEA-ETSAP
Bioenergy in energy system models with flexibility
Tiina Koljonen & Anna Krook-Riekola, IEA ETSAP
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Reframing flexibility beyond power - IEA Bioenergy TCPIEA-ETSAP
Reframing flexibility beyond power
Mr. Fabian Schipfer, IEA Bioenergy TCP
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Decarbonization of heating in the buildings sector: efficiency first vs low-c...IEA-ETSAP
Decarbonization of heating in the buildings sector: efficiency first vs low-carbon heating dilemma
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Mr. Andrea Moglianesi, VITO, Belgium
The Regionalization Tool: spatial representation of TIMES-BE output data in i...IEA-ETSAP
The Regionalization Tool: spatial representation of TIMES-BE output data in industrial clusters for future energy infrastructure analysis
Ms. Enya Lenaerts Vito/EnergyVille, Belgium
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Synthetic methane production prospective modelling up to 2050 in the European...IEA-ETSAP
Synthetic methane production prospective modelling up to 2050 in the European Union
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Ms. Marie Codet, Centre de mathématiques appliquées - Mines ParisTech; France
Energy Transition in global Aviation - ETSAP Workshop TurinIEA-ETSAP
Energy Transition in global Aviation - ETSAP Workshop Turin
Mr. Felix Lippkau, IER University of Suttgart, Germany
16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino
Integrated Energy and Climate plans: approaches, practices and experiencesIEA-ETSAP
Integrated Energy and Climate plans: approaches, practices and experiences
VO: reduce the distance between modellers and DM,
VO: the work process
- Making modifications collaboratively,
- Running the model,
- Reports and collaborative analysis
VedaOnline
Mr Rocco De Miglio
16–17th november 2023, amit kanudia, etsap meeting, etsap winter workshop, italy, kanors-emr, mr rocco de miglio, mr. amit kanudia kanors-emr, november 2023, politecnico di torino, semi-annual meeting, torino, turin, vedaonline
Updates on Veda provided by Amit Kanudia from KanORS-EMRIEA-ETSAP
Veda online updates - Veda for open-source models
TIMES and OSeMOSYSBrowse, Veda Assistant
VEDA2.0, VEDAONLINE, VEDA
Mr. Amit Kanudia KanORS-EMR
16–17th november 2023, etsap meeting, etsap winter workshop, italy, mr. amit kanudia kanors-emr, november 2023, politecnico di torino lingotto, semi-annual etsap meeting, torino, turin
Energy system modeling activities in the MAHTEP GroupIEA-ETSAP
Energy system modeling activities in the MAHTEP Group
Dr Daniele Lerede, Politecnico di Torino
16–17th november 2023, dr daniele lerede, etsap meeting, etsap winter workshop, italy, mathep group, november 2023, politecnico di torino, semi-annual meeting, turin
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...2023240532
Quantitative data Analysis
Overview
Reliability Analysis (Cronbach Alpha)
Common Method Bias (Harman Single Factor Test)
Frequency Analysis (Demographic)
Descriptive Analysis
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
A Generalized Equilibrium Approach to Balance the Residual Abatements Resulting from COP-21 Agreement
1. A Generalized Equilibrium Approach to Balance the
Residual Abatements Resulting from COP-21
Agreement
Frédéric Babonneau, Alain Haurie and Marc Vielle
ETSAP Workshop - Cork
May 30-31, 2016
1 / 21
2. Contents
1 Context and Objectives
2 A Dynamic meta-game model for climate negotiations
3 INDCs evaluation
4 Fair agreements for additional efforts
5 Conclusion
2 / 21
3. Context and Objectives
1 Context and Objectives
2 A Dynamic meta-game model for climate negotiations
3 INDCs evaluation
4 Fair agreements for additional efforts
5 Conclusion
3 / 21
4. Context and Objectives
Adressed questions
1 What do INDCs mean? And what are the economic impacts of INDC
implementation?
2 How an international carbon market might affect climate agreements?
3 How to share additional efforts on 2015-2050 to reach the 2o
C target in 2100?
How to design a fair agreement among groups of countries?
4 How each country will use its allocations on the horizon 2015-2050? What will
be the associated costs for each country?
4 / 21
5. Context and Objectives
Methodology
Propose a meta-game approach for assessing burden sharing agreements for the
attainment of 2050 climate target.
Methodology:
1 Identify a global emissions budget on 2015-2050 compatible with a 2o
C
temperature increase in 2100
2 Estimate abatement cost functions for each group of countries using simulations
of the Computable General Equilibrium model GEMINI-E3
3 Define a meta-game in which each country minimizes its costs according to a
global share of allocations. Each country decides strategically the timing of its
emissions.
5 / 21
6. A Dynamic meta-game model for climate negotiations
1 Context and Objectives
2 A Dynamic meta-game model for climate negotiations
3 INDCs evaluation
4 Fair agreements for additional efforts
5 Conclusion
6 / 21
7. A Dynamic meta-game model for climate negotiations
Meta-games for climate negotiations
Global emissions
Budget
US EU China
Coopera8ve
Interna8onal emissions trading scheme
Non Coopera8ve
7 / 21
8. A Dynamic meta-game model for climate negotiations
Meta-games for climate negotiations
Global emissions
Budget
US EU China
Coopera8ve
Interna8onal emissions trading scheme
Non Coopera8ve
The payoff (welfare loss) of player j at equilibrium satisfies :
min
ωj
T−1
t=0
β
t
j (π
t
j (e
t
j (Ω
t
)) − p
t
(Ω
t
)(ω
t
j − e
t
j (Ω
t
)))
,
subject to actions chosen by the other players and under the budget
sharing constraint
T−1
t=0
ω
t
j ≤ θj Bud.
7 / 21
9. A Dynamic meta-game model for climate negotiations
Meta-games for climate negotiations
Global emissions
Budget
US EU China
Coopera8ve
Interna8onal emissions trading scheme
Non Coopera8ve
The payoff (welfare loss) of player j at equilibrium satisfies :
min
ωj
T−1
t=0
β
t
j (π
t
j (e
t
j (Ω
t
)) − p
t
(Ω
t
)(ω
t
j − e
t
j (Ω
t
)))
,
subject to actions chosen by the other players and under the budget
sharing constraint
T−1
t=0
ω
t
j ≤ θj Bud.
Applying standard Kuhn-Tucker multiplier method, with multipliers νj ,
we obtain the following first order necessary conditions for a Nash
equilibrium:
νj = β
t
j (p
t
(Ω
t
) + p
t
(Ω
t
)(ω
t
j − e
t
j (Ω
t
))) ∀t∀j
0 = νj (θj Bud −
T−1
t=0
ω
t
j )
0 ≤ θj Bud −
T−1
t=0
ω
t
j
7 / 21
10. A Dynamic meta-game model for climate negotiations
Meta-games for climate negotiations
Global emissions
Budget
US EU China
Coopera8ve
Interna8onal emissions trading scheme
Non Coopera8ve
The payoff (welfare loss) of player j at equilibrium satisfies :
min
ωj
T−1
t=0
β
t
j (π
t
j (e
t
j (Ω
t
)) − p
t
(Ω
t
)(ω
t
j − e
t
j (Ω
t
)))
,
subject to actions chosen by the other players and under the budget
sharing constraint
T−1
t=0
ω
t
j ≤ θj Bud.
Applying standard Kuhn-Tucker multiplier method, with multipliers νj ,
we obtain the following first order necessary conditions for a Nash
equilibrium:
νj = β
t
j (p
t
(Ω
t
) + p
t
(Ω
t
)(ω
t
j − e
t
j (Ω
t
))) ∀t∀j
0 = νj (θj Bud −
T−1
t=0
ω
t
j )
0 ≤ θj Bud −
T−1
t=0
ω
t
j
Abatement cost functions π are estimated through statistical emulation on a large set of
GEMINI-E3 simulations
7 / 21
11. A Dynamic meta-game model for climate negotiations
A noncooperative meta-game approach
Input Global budget Bud and allocations among countries (i.e., θj )
Model Minimize the economic impacts for each country by deciding:
1 How to use the budget on the horizon
2 Permit sales and buyings on the trading market
Output Emissions, Permit exchanges, Permit prices, Percentage of welfare losses, ...
⇒ By testing different allocations, one can find a fair burden sharing. For example if
we adopt a Rawlsian approach to distributive justice, the optimal game design
problem consists in finding the θj ’s in such a way that one minimizes the largest
welfare loss among the countries.
8 / 21
12. A Dynamic meta-game model for climate negotiations
Estimation of the abatement cost functions
We use the CGE model GEMINI-E3 as a the provider of data for the estimation
of the abatement cost functions for each group of countries
Estimations are based on statistical emulations of a sample of 200 GEMINI-E3
numerical simulations (4 periods ×11 = nb estimations)
The abatement costs are polynomial functions of degree 4 in the country
abatement level
ACj (t) = αj
1(t) qj (t) + αj
2 qj (t)2
+ αj
3(t) qj (t)3
+ αj
4(t) qj (t)4
. (1)
0 5 10 15 20 25 30 35 40 45 50 55
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Abatement (%)
MAC
USA
EU
UMB
CHI
IND
RUS
OPE
ROW
ASI
LAT
LDC
9 / 21
13. INDCs evaluation
1 Context and Objectives
2 A Dynamic meta-game model for climate negotiations
3 INDCs evaluation
4 Fair agreements for additional efforts
5 Conclusion
10 / 21
14. INDCs evaluation
INDC analysis and consolidation
Difficulties to convert INDCs in consistent emissions abatements in 2030:
Objectives are related to different reference emissions (Historical emissions,
BAU emissions, Intensity target, etc)
Conditional and unconditional targets
Objective year: from 2025 to 2035
Missing information and unsubmitted INDCs
⇒ We use conventional target related to GEMINI-E3 BAU scenario.
11 / 21
15. INDCs evaluation
INDC targets in Mt CO2-eq in 2030
Unconditional Conditional Reduction compared to GEMINI-E3 BAU
USA 4’045 3’796 -47%
EUR 3’230 3’230 -25%
UMB 2’510 2’499 -14%
CHI 17’748 15’860 0%
IND 6’681 6’482 0%
RUS 2’649 2’473 -1%
OPE 3’834 3’456 -2%
ROW 3’688 3’465 -13%
ASI 5’491 4’975 0%
LAT 4’245 4’059 0%
LDC 4’713 4’423 0%
World 58’833 54’718
12 / 21
16. INDCs evaluation
INDCs impacts on welfare losses on [2015, 2030]
Without International carbon market With International carbon market
Welfare loss CO2 prices in $ /t Welfare loss CO2 prices in $ /t
in % of disc. HC 2020 2030 in % of disc. HC 2020 2030
USA 0.37 53 71 0.08 3.6 5
EUR 0.02 27 36 -0.01 3.6 5
UMB 0.03 7 10 0.03 3.6 5
CHI -0.09 - - -0.11 3.6 5
IND 0.01 - - -0.02 3.6 5
RUS -0.03 - - -0.07 3.6 5
OPE 0.10 - - 0.06 3.6 5
ROW 0.03 2 3 0.03 3.6 5
ASI -0.02 - - -0.03 3.6 5
LAT -0.01 - - -0.02 3.6 5
LDC -0.08 - - -0.11 3.6 5
World 0.08 0.04
International carbon market has a positive impact on global and all individual
costs.
Low welfare losses clearly reflect a lack of ambition of INDCs.
13 / 21
17. INDCs evaluation
Decomposition of welfare losses
-0.2 -0.1 0 0.1 0.2 0.3 0.4
USA
EUR
UMB
CHI
IND
RUS
OPE
ROW
ASI
LAT
LDC
Abatement Costs
GTT
-0.2 -0.1 0 0.1 0.2 0.3 0.4
USA
EUR
UMB
CHI
IND
RUS
OPE
ROW
ASI
LAT
LDC Abatement Costs
Quotas buying
GTT
14 / 21
18. Fair agreements for additional efforts
1 Context and Objectives
2 A Dynamic meta-game model for climate negotiations
3 INDCs evaluation
4 Fair agreements for additional efforts
5 Conclusion
15 / 21
19. Fair agreements for additional efforts
Emissions budget on 2015-2050
16 / 21
20. Fair agreements for additional efforts
Global welfare loss on 2015-2050
17 / 21
21. Fair agreements for additional efforts
Example #1 of fair agreement (2o
C target) on [2015,
2050]
Region Emissions budget Welfare loss Abatement cost Permit buying GTT
in Mt CO2-eq in % of discounted household consumption
USA 166852 0.7 0.5 0.1 0.2
EUR 80240 0.8 0.2 0.7 -0.2
UMB 63602 0.7 0.3 0.2 0.1
CHI 264910 0.7 2.3 -1.0 -0.7
IND 73986 0.7 1.4 -0.7 0.0
RUS 57230 0.7 1.4 -0.6 -0.2
OPE 100890 0.7 1.1 -1.2 0.9
ROW 101480 0.7 0.9 -0.3 0.2
ASI 105020 0.8 0.8 0.1 -0.2
LAT 86730 0.7 0.3 0.4 -0.1
LDC 79060 0.7 0.8 0.2 -0.3
World 1’180’000 0.8
18 / 21
22. Fair agreements for additional efforts
Example #2 of fair agreement (2o
C target) on [2015,
2050]
Region Emissions budget Welfare loss Abatement cost Permit buying GTT
in Mt CO2-eq in % of discounted household consumption
USA 153046 0.9 0.5 0.3 0.2
EUR 69620 0.9 0.2 0.9 -0.2
UMB 56640 0.9 0.3 0.5 0.1
CHI 273760 0.5 2.3 -1.2 -0.7
IND 76346 0.5 1.4 -0.9 0.0
RUS 58882 0.5 1.4 -0.9 -0.2
OPE 103250 0.5 1.1 -1.4 0.9
ROW 105020 0.5 0.9 -0.5 0.2
ASI 109150 0.5 0.8 -0.1 -0.2
LAT 90270 0.5 0.3 0.3 -0.1
LDC 84016 0.0 0.8 -0.5 -0.3
World 1180000 0.8
19 / 21
23. Conclusion
1 Context and Objectives
2 A Dynamic meta-game model for climate negotiations
3 INDCs evaluation
4 Fair agreements for additional efforts
5 Conclusion
20 / 21
24. Conclusion
Conclusion and Perspectives
Conclusion
INDCs commitments are weak.
It is possible to design fair agreements (eg, equalizing welfare costs between
coalitions)
The implementation of a tradable permits market is crucial as it allows to
equalize marginal abatement costs and to reduce welfare losses
Perspectives
Extend the model to robust optimization to take into consideration statistical
errors in the calibration of abatement cost functions
Apply meta-game on alternative economic models (eg. TIMES)
21 / 21