ALPS International Symposium
Toranomon Hills Forum
February 9, 2018

Climate change response strategy
toward long-term zero CO2emissions
Keigo AkimotoGroup Leader, Systems Analysis Group
Research Institute of Innovative Technology for the Earth (RITE)

Contents
1. Required long-term goal and uncertainties
in short/mid-term pathway
2. Mitigation costs − the gaps between the ideal
mitigation costs and real costs
3. Climate change mitigation measures under
different socioeconomic conditions
4. Co-benefits and trade-offs between climate change
and other sustainable development goals
5. Innovations and emission pathways
6. Conclusions

2

1. Required long-term goal anduncertainties in short/mid-term pathwayRelationship between cumulative CO2 emissions
and temperature rise4

Temperature response to emissions in 2010; theresponses are normalized by the amount ofcontribution of CO2 emission after 100 years past
Source) Synthesis report of IPCC AR5- Approximately linear relationship between cumulative CO2 emissions and temperaturerise can be observed.
- Nearly net zero CO2 emissions are necessary for the stabilization of global temperature
at any level.

History of climate sensitivity judgment by IPCC and thesensitivity employed in the scenario assessments of the
IPCC WG3 AR5

5Equilibrium climate sensitivity
Likely range (“best estimate” or “mostlikely value”)

Same “likely” range

Before IPCC WG1 AR4

1.5−4.5°C (2.5°C)

IPCC WG1 AR4

2.0−4.5°C (3.0°C)

IPCC WG1 AR5

1.5−4.5°C (no consensus)

Global mean temperature estimations for the long-term
scenarios in the IPCC WG3 AR5 (employing MAGICC)

2.0−4.5°C（3.0°C）[Based on the AR4][The related descriptions of the SPM of WG1 AR5]

Likely in the range 1.5 °C to 4.5 °C (high confidence)
Extremely unlikely less than 1 °C (high confidence)
Very unlikely greater than 6 °C (medium confidence)
No best estimate for equilibrium climate sensitivity can now be given because of a lack of agreement on values across assessed lines ofevidence and studies.

♦ The equilibrium climate sensitivity, which corresponds to global mean temperature increase inequilibrium when GHG concentration doubles, is still greatly uncertain.
♦ AR5 WG1 judged the likely range of climate sensitivity to be 1.5−4.5 °C, in which the bottom range
was changed to a smaller number than that in the AR4, based not only on CMIP5 (AOGCM) results but
also other study results.
♦ AR5 WG3 adopted the climate sensitivity of AR4, which has the likely range of 2.0−4.5 °C with the best
estimate of 3.0 °C, for temperature rise estimates of long-term emission scenarios.

Social Cost of Carbon (SCC)

Source) Interagency working group on social cost of carbon, 2016

- Social cost of carbon is the marginal damage costs of CO2 emissions.
- The estimation methods are very debatable, and the estimated distributions of thedamage costs vary widely depending on the assessment models, climate sensitivity,
discount rate etc. Therefore, it is not easy to determine the optimal temperature level.

6Global CO2 emission profiles toward 2300
for the 2 °C targets

7

50
Business as Usual (BaU)(the middle socioeconomic scenario)

CO2 emissionis [GtCO2/yr]

40

Submitted NDCs

30
+2℃ stabilization under climate
sensitivity of 2.5℃ (Noexceedance of 580 ppm)

20

+2℃ stabilization under climate
sensitivity of 3.0℃ (Noexceedance of 500 ppm)
450 ppm CO2eq stabilization

10

0

-10
2010

2050
2060

2100
2110

2300
2160

2210

2260

Submitted NDCs
Estimated by RITE using
MAGICC and DNE21+- The global CO2 emissions should be nearly zero for a long period of time in the far future
in any pathway to achieve temperature stabilization.
- On the other hand, the allowable global CO2 emissions toward the middle of this century
have a wide range according to the uncertainties in climate sensitivity (or achieving
probability) even when the temperature target level is determined as a 2 °C. We should use
this flexibility to develop several kinds of innovative technologies and societies.

2. Mitigation costs − the gaps
between the ideal mitigation costs
and real costs

Huge costs are estimated for achieving the 2 °C target
9

Corresponding to 2 °C target

Source) IPCC WG3 AR5Corresponding to 2 °C target- According to the IPCC AR5, the CO2 marginal abatement costs(carbon prices) for the 430-530 ppm CO2eq (which areconsistent with the 2 °C target) are about 1000-3000 $/tCO2 (2575 percentile) and 150-8000 $/tCO2 (full range) in 2100.
- About 25% of the analyzed scenarios estimate global GDP
losses of over 10%.
- The feasibility of such scenarios should be carefully examinedin terms of various constraints in the real world.

CO2 marginal abatement costs of the NDCs
10

Average of 2025-2030
2030 (2025 for the U.S.)【World GDP loss due to mitigation】
NDCs:0.38%; the global least cost：0.06%
The least cost (equal marginal abatement costs)：6$/tCO2
Switzerland

380

Japan

378

EU28

210

Canada

166

Korea

144

New Zealand95

United States

85

NorwaySource: J. Aldy et al., Nature Climate Change, 201670

East Europe (Non-EU member)

58

Thailand54

Australia

33

Mexico27

Kazakhstan

14

Belarus12

Russia4South Africa

1

Turkey

0

India

0

Ukraine

0

China

0

0

50

100

150

200

250

300

350

CO2 marginal abatement cost ($/tCO2)

Source: K. Akimoto et al., Evol. Inst. Econ. Rev., 2016

- The estimated marginal abatement costs of NDCs are largely different among countries,
and the mitigation costs are much larger than those under the least cost measures due tosuch large regional differences in marginal abatement costs.

400

CO2 marginal abatement cost for the U.S, EU and Japanconsidering several kinds of policy constraints
CO2 marginal abatement cost ($/CO2)

500

11

II-c
I-d

400

III-d
III-c

I-c

300
II-b
II-a

200

III-b
III-a

100

I-b
I-a

0

I. US
I-a: -26%; the least costI-b: -28%; the least cost
I-c: -26%; power sector
according to CPP
I-d: -28%; power sector
according to CPP* CPP: Clean Power Plan

Source: estimated by RITE DNE21+

II. EU
II-a: the least costII-b: Brexit (-40% for UK)
II-c: splitting into ETS andnon-ETS sectors

III. Japan
III-a: the least cost undernuclear of maximum 20%
III-b: the least cost undernuclear of maximum 15%
III-c: following the NDC
including the energy mix(nuclear of 20%)
III-d: following the NDC
including the energy mix
but nuclear of 15%- It is not easy to achieve the least cost measures because there are various kinds of social andpolitical constraints in each nation.
- The mitigation costs constrained by other policies can be much higher than those under the
least cost measures.

3. Climate change mitigation
measures under different
socioeconomic conditions

Overview of Shared Socioeconomic Pathways (SSPs)
Fossil fuel price: low;
Fossil fuel resources: high;GDP: very highTech. improve.：high;Public acceptability oflarge-scale tech.: low;
Population: low;
GDP: highTech. improve: low;
Population: low;
GDP: low

Governance: low;
Price distribution offossil fuel energy prices
among countries: big

13

Relationship between SSPs and RCPs

RCP

14

Note 1) 2.6 W/m2 corresponds to below 2 °C in 2100 with >66% achieving probability; 3.4 W/m2
corresponds to below 2 °C in 2100 with >50% probability, and 4.5 W/m2 corresponds to below about 2.5°C with >50% probability.
Note 2) Carbon prices are shown as the converted values in 2010 by employing 5%/yr of discount rate.
The carbon price of 20 $/tCO2 as the 2010 value corresponds to about 1800 $/tCO2 for 2100.
K.Riahi et al., Global Environmental Change 42 (2017) 153–168

Energy Assessment Model: DNE21+

15♦ Linear programming model (minimizing world energy system cost)♦ Evaluation time period: 2000-2100
Representative time points: 2000, 2005, 2010, 2015, 2020, 2025, 2030, 2040, 2050,
2070, 2100

♦ World divided into 54 regions
Large area countries are further divided into 3-8 regions, and the world is divided
into 77 regions.

♦ Bottom-up modeling for technologies both in energy supply and demandsides (about 300 specific technologies are modeled.)♦ Primary energy: coal, oil, natural gas, hydro&geothermal, wind,photovoltaics, biomass and nuclear power♦ Electricity demand and supply are formulated for 4 time periods:
instantaneous peak, peak, intermediate and off-peak periods♦ Interregional trade: coal, crude oil, natural gas, syn. oil, ethanol,hydrogen, electricity and CO2♦ Existing facility vintages are explicitly modeled.
- The model has regional and technological information detailed enough to analyze sectoral
measures. Consistent analyses among regions and sectors are obtained.

Global CO2 emissions in Baseline
16

Estimated by RITE DNE21+ model
Energy-related CO2 emission [GtCO2/yr]

120
Historical

SSP1

SSP2

SSP5

100

80

60

40

Estimated by otherresearch institutes

20

K.Riahi et al., Global Environmental Change (2017)01990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

- Baseline emissions are very different
depending on the future socioeconomic
conditions including technology improvements.

Marginal CO2 abatement costs (Carbon prices)
for the 2 °C target

17

SSP: “Shared Socioeconomic Pathways”

SSP2 (Middle of the Road)

SSP1 (Sustainability)+2°C stab.
under
climatesensitivityof 2.5°C+2°C stab.
under
climatesensitivity of
3.0°C

450 ppm
CO2eq stab.
(climatesensitivity of
3.4°C)+2°C stab.
under
climatesensitivityof 2.5°C+2°C stab.
under
climatesensitivityof 3.0°C

450 ppm
CO2eq stab.
(climatesensitivity of
3.4°C)

2050

12

135

604

14

117

518

2100

408

427

457

134

140

143

Unit: $/tCO2 (real price); Uniform carbon prices among all nations are assumed.
Source) estimated by RITE DNE21+--

The marginal abatement costs (carbon prices) for the 2 °C target were huge even under
the global least cost measures (uniform carbon prices) except in the case of low
climate sensitivity (2.5 °C) and by 2050.
The carbon price in SSP1 that energy demands in the end-use sectors are much smaller
than in SSP2 is much lower than that in SSP2.
Technological and social innovations are definitely required for the 2 °C target to beachieved in harmony with other SDGs. (Newly emerging technologies such as AI, IoT
etc. will induce social changes which may lower the energy demand.)Global primary energy supply
18

Estimated by RITE DNE21+ model
30000

Solar PV
Primary energy supply (Mtoe/yr)

25000

Wind power
Nuclear

20000

Hydro + Geothermal
Biomass (w/ CCS)
Biomass (w/o CCS)

15000

Gas (w/ CCS)
Gas (w/o CCS)

10000

Oil (w/ CCS)
Oil (w/o CCS)

5000

Coal (w/ CCS)
Coal (w/o CCS)

0
SSP1SSP2SSP5SSP1SSP2SSP5SSP1SSP2SSP5SSP1SSP2SSP5SSP1SSP2SSP5SSP1SSP2SSP5[3] +2℃
stabilization
under C.S. of
2.5℃
2010

2030

[1] 450 ppm
CO2eq
stabilization[3] +2℃
stabilization
under C.S. of
2.5℃
2050

[1] 450 ppm
CO2eq
stabilization[3] +2℃
stabilization
under C.S. of
2.5℃[1] 450 ppm
CO2eq
stabilization

2100- The energy supply is very different in 2050 according to the uncertainty in the climate
sensitivity and different socioeconomic scenarios.
- The total amount of energy supply in the SSP1 world is much smaller than that in the
SSP2 and SSP5.

Global electricity generation
19

Estimated by RITE DNE21+ model

140000Hydrogen (H2 from waterelectrolysis)
Hydrogen (H2 from otherproduction proccess)Solar PV (Water electrolysis
w/o grid connection)
Solar PVElectricity generation (TWh/yr)

120000100000Wind power
80000

NuclearHydro + Geothermal

60000
Biomass (w/ CCS)
Biomass (w/o CCS)

40000

Gas (w/ CCS)
Gas (w/o CCS)

20000

Oil (w/ CCS)0
SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5
[1] 450 ppm CO2eq[1] 450 ppm CO2eq[1] 450 ppm CO2eq[3] +2℃[3] +2℃[3] +2℃
stabilization
stabilization
stabilization
stabilization understabilization understabilization under
C.S. of 2.5℃
C.S. of 2.5℃
C.S. of 2.5℃
2010

2030

2050

Oil (w/o CCS)
Coal (w/ CCS)
Coal (w/o CCS)2100

- CO2 emissions from power sector in most of the scenarios for the 2 °C target are nearlyzero or negative after the second half of this century.
- The total amounts of electricity for the 2 °C target will increase with deeper emission
reductions due to substitution for fossil fuel use in other sectors.

Global CO2 capture and storage (CCS)
20

Estimated by RITE DNE21+ model
45
BECCS

CO2 storage [GtCO2/yr]

40
35
30

Iron and Steel sector,
Hydrogen production

25
20

Gas power

15
10

Oil power

5[3] +2℃
stabilization
under C.S. of
2.5℃[1] 450 ppm
CO2eq
stabilization

2030[3] +2℃
stabilization
under C.S. of
2.5℃[1] 450 ppm
CO2eq
stabilization

2050[3] +2℃
stabilization
under C.S. of
2.5℃

SSP5

SSP2

SSP1

SSP5

SSP2

SSP1

SSP5

SSP2

SSP1

SSP5

SSP2

SSP1

SSP5

SSP2

SSP1

SSP5

SSP2

SSP1

0
Coal power[1] 450 ppm
CO2eq
stabilization

2100- The total amount of CCS is also very different in 2050 according to the uncertainty in the
climate sensitivity and different socioeconomic scenarios.
- In 2100, large amounts of CCS including BECCS are required for all of the emission
pathways for 2 °C target.

Global transportation (automobile)
21

Estimated by RITE DNE21+ model
Passenger transportation service demand (billion p-km/yr)

100

FCV

90

BEV
80
70

Plug-In HEV (Highconcentration bio fuel)60

Plug-In HEV

50

HEV (Highconcentration bio fuel)

40

HEV

30

ICEV (Highconcentration bio fuel)

20
10

ICEV

0
SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5
[3] +2℃
stabilization under
C.S. of 2.5℃
2010

2030

[1] 450 ppm
CO2eq
stabilization[3] +2℃
stabilization under
C.S. of 2.5℃
2050

[1] 450 ppm
CO2eq
stabilization[3] +2℃
stabilization under
C.S. of 2.5℃

[1] 450 ppm
CO2eq
stabilization

2100- The technology options in automobile are also very different in 2050 according to theuncertainty in the climate sensitivity and different socioeconomic scenarios.
- In 2100, large shares of EVs and FCVs are required as well as HVs are required for all of
the emission pathways for 2 °C target.

Global CO2 emissions by sector
22

Estimated by RITE DNE21+ model120

LULUCF
Residential and commercial sector

100International bunker emission
Other transportation sector(domestic)
Road transportation sector

CO2 emission [GtCO2/yr]

80

Industrial process emission
60

Other industrial sector
Chemical sector

40

Petrochemical sector
Pulp and paper sector

20

Cement sector
Iron and steel sector

0

Other energy conversion sector
Power sector-20
SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5 SSP1 SSP2 SSP5
BaU

2010

[3] +2℃
stabilization under
C.S. of 2.5℃
2050

[1] 450 ppm
CO2eq
stabilization

BaU[3] +2℃
stabilization under
C.S. of 2.5℃

[1] 450 ppm
CO2eq
stabilization

2100- In order to achieve zero CO2 emissions, negative emissions in power sector by BECCS
and large-scale of afforestation are required.
- Low energy demand scenario such as SSP1 will reduce the requirements of BECCS.

4. Co-benefits and trade-offs
between climate change and othersustainable development goals

Harmonization among climate change issues andother SDGs needed- We have multiple agendas to be tackled. Harmonization among climate change issues
and other SDGs are necessary.

24

Climate Change Mitigation & Food Access (1/2)

25

Food access index (Amounts of food consumption／GDP)
686

400

Food Access Index[amounts of food consumptions/GDP](US.Y2000=100)

Bioenergy and forestation
effects

651 715754
1315 655 745

801

916

w.o. Bioenergy andforestation effects

350
300

Deeper Vulnerable
emission
reductions

250
200
150
100
50

2000

2050

2100
China

2000

2050

2100
India

2000

2050

2100

2000

Other Asia

2050

2100

Sub-saharan Africa

A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0
A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0

A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0
A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0

A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0
A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0
A-baseline
A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0
A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0

A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0
A-baseline
A-CP6.0
A-CP4.5
A-CP3.7
A-CP3.0

0

2000

2050
L. America

Source) K. Akimoto et al., Natural Resources Forum, 36(4), 231-244, 2012

- Vulnerabilities of food access will decrease in most countries and regions in thelong-term under any emission scenarios, because future incomes are expected toincrease.
- Large-scale forestation and bioenergy use slightly increase vulnerabilities of foodaccess.

2100

Climate Change Mitigation & Food Access (2/2)

26

Food access index (amounts of food consumption/GDP) in 2050 by factor
Source) estimated by RITE (2012)

30%

Change rates of food access(%, relative to the baseline)

25%

worse

－△(GDP)/GDP : due to climate damage

20%－△(GDP)/GDP : due to climate mitigation

15%
10%

△(Food consumptions)/(Food consumptions):
due to land-use changes for "bioenergy
production and afforestation"

5%△(Food consumptions)/(Food consumptions):
due to land-use changes for "food production"

0%△(Food consumptions/GDP)/(Foodconsumptions/GDP)-5%

CP4.5 CP3.7 CP3.0 CP4.5 CP3.7 CP3.0 CP4.5 CP3.7 CP3.0 CP4.5 CP3.7 CP3.0 CP4.5 CP3.7 CP3.0
China

India

Midde-East &N.Africa

Subsahara Africa

Latin America

CP4.5: about 650 ppm CO2eq
CP3.7: about 550 ppm CO2eq
CP3.0: about 450 ppm CO2eq- Factor decomposition shows that climate change mitigation brings about
small positive impacts on the food access index in certain aspects, butworsens the index in total.

Climate Change Mitigation & Water Access (1/2)
Water consumption
Water consumption (km3 yr-1)

No climate change case
1,200

Livestock
1,000

Consumption-to-availability ratio
20102050 No climate change
2050 Baseline
2050 +2 °C stab. under C.S. 3.0 °C
2050 450 ppm CO2 eq stab.

United States
Western Europe
Japan

Irrigation

800

China

600

Other
industrial use

400

Electricity
generation

200

Municipal use
2095

2085

2075

2065

2055

2045

2035

2025

2015

2005

0

Irrigation is a major consumption.

27

India
AFG & Pakistan
the Arabian Peninsula
TurkeyNorth Africa
South Africa
Eastern Africa

Source) A. Hayashi et al., Mitig Adapt Strateg Glob Change, 2018

Western Africa
BrazilParaguay et al.

- There are no large impacts of climatechange and the mitigation on water
consumption-to-availability ratio (CAR) in
most regions/countries in total.

Russiaworse

Annex I of FUSSR
Other FUSSR

0

0.1

0.2

0.4

0.6

1

CAR

1.5

2

2.5

Climate Change Mitigation & Water Access (2/2)
Consumption-to-availability
ratio (CAR)

0.5

2000

2050

0.3

worse

0.2
0.1

Change rate (% yr-1)

India

0.4

CAR

1.2
1.0
0.8
0.6
0.4
0.2
0.0

2000

2050

2100

1.0
0.8
0.6
0.4
0.2
0.0
-0.4

2010- 2030- 2050- 20702030
2100
2050 2070

0.4

0.4

0.2

0.2

0.0
-0.2
-0.4
-0.6
-0.8
-1.0
-1.2

0.0

1.2

∆CAR
∆' Municipal use∆' Other industrial use∆' Electricity generation∆' Irrigation∆' Livestock−∆Runoff

-0.2

-0.2

2100

0.5

1.4

1.4

-0.4

0.0

450 ppm CO2 eq stab. case
Change rate (% yr-1)

Baseline+2 °C stab. under C.S. 3.0 °C
450 ppm CO2 eq stab.
No Climate Change

Baseline

Change rate (% yr-1)

1.0Change rate (% yr-1)

1.5

CAR

Change rates of CAR and the factors

Afghanistan,
Pakistan

2.0

28

2010- 2030- 2050- 20702030
2050 2070 2100

2010- 2030- 2050- 20702030
2050 2070
2100

0.0
-0.2
-0.4
-0.6
-0.8
-1.0
-1.2

2010- 2030- 2050- 20702050 2070
2030
2100

Source) A. Hayashi et al., Mitig Adapt Strateg Glob Change, 2018

- Deep emission reductions will worsen the consumption-to-availability ratio (CAR) in
some regions through increase in water use for BECCS etc., but the impacts are small.

5. Innovations and emission
pathways5th Science and Technology Basic Plan of Japan- “Society 5.0” (“Super Smart Society”) -30

Source) Japanese Government

Source) Gendai Business”http://gendai.ismedia.jp/articles/-/50859”

AI + IoT + big data + ….
Operation ratio of automobiles
is about 4%, for example. The
large room for the improvement
exists.

- Wide range of technological innovations andtheir integrations are required for improving
our welfare and sustainable development.
- AI, IoT, big data etc. will be able to stimulate
such innovations.

Potential Socioeconomic Impacts oftechnology improvements of AI, IoT etc.
by RITE

31

Technology improvements of such as• AI• AI car• IoT• AI robot• ICT• Big data
Impacts onsocial life

Impacts on industry
and employment

Great improvements of:- Sharing economy- Teleworking- E-commerce, Net shopping

Several kinds of machineries
with AI substitute for many
human works, andproductivity increase inalmost all industries.

etc.

Decrease inGood redistribution ofenergydemands?
Decrease in materialized products andincome and work sharing
Yenergy demands
YN

Decrease in passenger travels, but
increase in freight?

SSP1

SSP1
N

Increase in materialized products and energy
demands (large rebound effects)
SSP5

Increase inleisure timeand rich life

SSP4

Increase in
unemployment
and classed
societyImage of standard scenario by models and realworld scenarios for deep cuts
Model world:
Ordinary technology progress

Carbonprice

Carbon price/
Marginal abatement cost

Realistic world requirement:
Innovations stimulated & implemented
Carbonprice

Baseline scenario(like SSP5 and SSP2)

Implicit or explicit carbon price/
Marginal abatement cost

Baseline scenario(like SSP1 or more drasticallyautonomous demand reductions)
By technology
and social
innovations

CO2
emission

CO2
emissionIntervention scenario

32Intervention scenario

Explicit high carbon prices such as over 100$/tCO2 in real price are infeasible in a realworld. Technology and social innovations resulting in low (implicit or explicit) carbon
prices (including coordination of secondary energy prices) are key for deep emission cuts
to be implemented and for realizing sustainable development.

6. Conclusions

Conclusions

34♦ Nearly zero CO2 emissions are required in the long-term.
♦ But there are lots of uncertainties, and we should recognize these

uncertainties to manage the total risks in a better way.
♦ Potential increase in mitigation costs: political factors (large
differences in MAC across nations, Trump Administration etc.), social
constraints of technology deployment, inefficient policies etc.
♦ Potential decrease in mitigation costs (future unknown innovations)♦ Pursuing co-benefits in line with several objectives of sustainable
development. But some are trade-offs. Our resources are limited andtotal risk management is required.
♦ Innovations are almost prerequisite for achieving zero emissions. The
demand side revolutions induced by IT, AI etc. will be highly expected
as one of the innovations for reducing energy consumptions andtoward deep emission reductions (but currently uncertain) .
♦ Paradoxically, the high carbon price world, which seems required
reasonably for deep emission reductions, can never achieve deep
emission reductions, but it is the low carbon price world that is
capable to achieve them in the real world.

Appendix

Region divisions of DNE21+

36

Technology Descriptions in DNE21+
37

Industry

Fossil fuels
Coal
Oil (conventional, unconv.)
Gas (conventional, unconv.)

Energy conv.
processes(oil refinery, coalgasification, bioethanol, gas
reforming, waterelectrolysis etc.)

Unit
production
cost

Iron & steel
CementPaper & pulp
Chemical (ethylene, propylene,ammonia)

Aluminum
Cumulative production

Solid, liquid and gaseous fuels, andelectricity <Top-down modeling>

Renewable energies
Hydro power & geothermalWind power
Photovoltaics
Biomass

ElectricPower
generation

Unit
supplycost

Transport
vehicleSolid, liquid and gaseous fuels, andelectricity <Top-down modeling>

Residential & commercial
Annual production

Nuclear power

CCS

Refrigerator, TV, air conditioner
etc.
Solid, liquid and gaseous fuels, andelectricity <Top-down modeling>Global GHG emission profiles toward 2100
for the 2 °C target
70

Business as Usual (BaU)

GHG emissions [GtCO2eq/yr]

60

Submitted NDCs

+14%

50

+2℃ stabilization underclimate sensitivity of 2.5℃
(No exceedance of 580 ppm)
+2℃ stabilization underclimate sensitivity of 3.0℃
(No exceedance of 500 ppm)
450 ppm CO2eq stabilization

40
-42%

30
20

-74%

Historical

10
Submitted NDCs

0
1990

38

2010

2030

2050

2070

2090

2100

Estimated by RITE using MAGICC, DNE21+ and non-CO2 GHG models- The corresponding GHG emission trajectories for the 2 °C target vary widely
particularly in 2050.
- There are large gaps between the expected emissions under the submitted NDCs andthe 450 ppm CO2eq pathway.

Climate Change Mitigation & Energy Security
39

(

)

(

c gas
coil
2
2
⋅
+
⋅
ESI =
r
S
r
S
∑ i i, oil TPES ∑i i i, gas
TPES i
Share of imported oil in TPES

Political risks of region i)

Dependence on region i

ESI : energy security index, TPES: total primary energy supply
Note: index based on IEA, 2007
10,000Vulnerable

Energy security index

2000
7,500

2050 A-Baseline
2050 A-CP4.5

5,000

2050 A-CP3.0

2,500

0
US

W. Europe

Japan

China

India and S. Asia

Source) K. Akimoto et al., Natural Resources Forum, 36(4), 231-244, 2012

While the energy security index of Japan decreases (less vulnerable) for CP3.0 (synergy
effects), those of China and India increase (more vulnerable) for deeper emission
reductions due to increase in imported gas shares (adverse side effects).