massimo tavoni. assessing optimal mitigation policies with a game theoretic, optimal growth model -...

8/7/2019 Massimo Tavoni. Assessing Optimal Mitigation Policies with a Game Theoretic, Optimal Growth Model - Witch

1/38

Assessing Optimal Mitigation Policieswith a Game Theoretic, Optimal Growth Model:

WITCH

Massimo Tavoni: CMCC, FEEM and Princeton University

Asian Development Bank, Kuala Lumpur, January 2011


2/38

Basic Facts of the Climate Change Problem

Key issues of the Climate Change problem:

Global dimension: GHG emissions are a perfect global externality Emissions originate from a wide range of countries, activities and

sources

Long-term dimension: Large inertia of climate system Large inertia of energy systems

Strategic incentives to free-ride on: Emissions

Technology Use of fossil fuels


3/38

The WITCH Model: An overview


4/38

Background info

World Induced Technical Change Hybrid model:

Developed at FEEM in 2004, from a previous model that wasutilized at FEEM since the mid 90s.

Employed in several projects (>20), commissioned by EuropeanCommission, International Organizations (OECD, EBRD),

Private Sector (Deutsche Bank), Governmental (Italian Ministryof Environment,UK DECC) and NGOs (WWF)

Member of international modeling fora (Energy ModelingForum, Asian Modeling Exercise, IPCC related ones)

Led to extensive reporting and publication in the peerreviewed literature

More info at www.witchmodel.org


5/38

WITCH as an Integrated Assessment Model

Socio-Economic System

Environmental system

Adaptation


6/38

STRATEGIC INTERACTIONS IN WITCH


7/38

Regional disaggregation


8/38

Mitigation options in each region

7

- Essential mitigation options for energy related CO2 (about 15

technologies), which is hard linked in the model

- Reduced Deforestation and Land Degradation (REDD),afforestation, use of residue biomass for land use relatedCO2, using marginal abatement costs

- Non-CO2 Kyoto gases (methane, N2O, fluorinated gases),using marginal abatement costs

- Technological change, both via diffusion (e.g. learning bydoing) and innovation (e.g. R&D), subject to internationalspillovers


9/38

Modeling capacity and output


10/38

Potential use

The model features are ideal for analyzing:

- The investment dynamics of low carbon strategies

- Second best policies under multiple externalities

- Technological innovation and policies

- Uncertainty


11/38

Mitigation strategies


12/38

-20%

0%

20%

40%

60%

80%

100%

0% 20% 40% 60% 80% 100%

Energy Intensity Improvement

Decarbonization

450550

BAU

past 30 yrs

Changes in Energy and Carbon Intensities

Energy savings and efficiency should be pursued vigorously in the short term, but

decarbonisation is essential from 2030 onwards already.

2030

20502100

2030

2050

2100

2100

2050

2030

550650


13/38

Broad mitigation portfolio is needed

0

2000

4000

6000

8000

10000

12000

14000

16000

S1 S2 S3 S4 S5 S6 S7 S8 S9

Cumulatve

PrimaryEnergy(EJ)

BIOMASS

ADVANCED FUELS

WIND+SOLAR

COAL w CCS

NUCLEAR

ENERGY CONSUMPTION

REDUCTION


14/38

Mitigation costs strongly depend on climate target

S1

S2S3

S5

S6

S7

S8

S9

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

1.501.701.902.102.302.502.702.903.103.303.50

GDPlo

ssesinNPV(at5%d.r.)

Temperature rise in 2100 (C)


15/38

.. and on the availability of mitigation options


16/38

Innovation


17/38

Copenhagen (and Cancun) pledges


18/38

Investing in clean energy R&D

0.00%

0.02%

0.04%

0.06%

0.08%

0.10%

0.12%

0.14%

1970 1980 1990 2000 2010 2020 2030 2040 2050

E.E. R&D

Total Energy R&D

BAU

Historical Public Energy R&D

Advanced Techs R&D

Energy Intensity R&D


19/38

Mitigation Costs with and wout breakthrough innovation

-8.0

-7.0

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

2007 2012 2017 2022 2027 2032 2037 2042 2047 2052 2057 2062 2067 2072 2077 2082

%c

ha

ngeinGDPwithrespecttoba

seline

550ppm w ith backstops

550ppm


20/38

Forestry

U i b k t t t t i l d f t ti


21/38

Forestry Emissions

-0.5

0

0.5

1

1.5

2

2005

2015

2025

2035

2045

2055

2065

2075

2085

2095

GtC

Using carbon markets to stop tropical deforestation

Forest Carbon Seq estration


22/38

Forest Carbon Sequestration

Table 1: Regional Forest Carbon Sequestration, 2025, 2055, 2095

2022 2052 2092

MtC/yr

OECD

USA 42 144 193

OLDEURO 37 82 132

NEWEURO 8 18 29

CAJANZ 31 115 125

Total OECD 118 360 479

NON OECD

KOSAU 25 27 36TE 179 117 134

MENA 73 49 31

SSA 270 175 106

SASIA 34 57 32

CHINA 109 155 431

EASIA 451 481 371

LACA 391 326 330

Total Non-OECD 1649 1746 1950Total Global 1766 2105 2429

C Price $57 $113 $271



23/38


Table 3: Change in Forestland area and Change in annual timber harvests compared to the baseline.

2022 2052 2092 2022 2052 2092

Million Hectares % Change in Ann. Harvest

OECD

USA 1.5 23.1 94.2 1.2% -9.0% 48.5%

OLDEURO 11.5 34.9 51.9 -5.3% 12.1% 0.3%

NEWEURO 2.6 7.8 11.6 -5.3% 12.1% 0.3%

CAJANZ -4.0 24.5 99.0 -3.8% -3.3% 167.3%

Total OECD 11.6 90.3 256.7 -3.3% 3.0% 54.1%

NON OECD

KOSAU 5.1 17.7 49.1 11.3% 34.5% 42.1%

TE 19.0 52.2 102.7 -20.8% 8.9% -26.1%MENA 10.3 24.9 38.4 -63.9% -45.9% -6.7%

SSA 37.2 90.7 137.0 -70.1% -52.9% -9.0%

SASIA 5.2 18.8 32.3 -3.7% -3.9% 13.0%

CHINA 8.6 41.9 115.4 -20.1% 0.0% -98.8%

EASIA 25.6 66.0 111.9 -63.3% -57.2% -48.9%

LACA 42.9 129.3 262.4 -24.8% -7.1% 15.5%

Total Non OECD 153.8 441.5 849.2 -31.9% -15.4% -14.9%

Total 165.4 531.8 1105.9 -14.5% -3.3% 25.9%


24/38


25/38

Uncertainty

What should we do if we are uncertain about future policies?


26/38

0

2

4

6

8

10

12

14

16

18

20

2005

2015

2025

2035

2045

2055

2065

2075

2085

2095

GtC

no tgt

550

optimal

450

What should we do if we are uncertain about future policies?


27/38

Planning and resources

Building future commitments into current planning


28/38

Building future commitments into current planning

Emissions in China for a carbon tax from 2030

onwards.Anticipating future commitments allows to save25% of the costs

0

2

4

6

8

10

12

14

2000 2010 2020 2030

BillionTonsCO2

No policy

Future

commitments

beginning in

2030

Financial transfers in an international carbon market


29/38

2

8

Financial transfers in an international carbon market

A limit to the use of emission trading to 10% of totalabatement would keep the amount of transferredresources around 100 USD Billion

Financial transfers from OECD

0

100

200

300

400

500

600

700

2020 2025 2030 2035 2040

USDBillion

Full trade v20% v15% v10%

CurrentOECDGasImports

Current OECD OImports @

70$/bblCurrent

OECD OImports@ 50$/b


30/38

Mitigation vs Adaptation

Timing of adaptation and mitigation


31/38

3

0

Timing of adaptation and mitigation

0

500

1000

1500

2000

2500

3000

3500

4000

4500

2010

2015

2020

2025

2030

2035

2040

2045

2050

2055

2060

2065

2070

2075

2080

2085

2090

2095

2100

U

S$Billion

Residual Damage Adaptation Mitigation

Reactive and Proactive Regional Adaptation


32/38

eact e a d oact e eg o a daptat o


33/38

What to expect from this model

What WITCH is best at:


34/38

What WITCH is best at:

Long term dynamics of mitigation strategies

International climate negotiations

Regional strategic incentives

Deal with uncertainty

Innovation mechanisms and policies

Mitigation and adaptation interplay

What WITCH is not best at:

Country level analysis

Detailed technology roadmaps

Sectoral implications and feedbacks

Short term


35/38

Thanks!

[email protected]

2030: number of people who emit > 10tCO2/capita


36/38

p p p

0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

Co-benefits of mitigation


37/38

g

Energy security

Local pollution

Biodiversity and ecosystems

Co-damages of mitigation

Land competition (also with food) from renewablesand biofuels

Nuclear proliferation

CCS inefficiency and coal mining

Potentially regressive distributive impacts


38/38

Thanks!

[email protected]

massimo tavoni. assessing optimal mitigation policies with a game theoretic, optimal growth model -...

Documents