ALPS International Symposium
Otemachi Sankei-Plaza
February 27, 2015

Evaluations on Emission Reduction
Efforts of the Nationally Determined
Contributions for the Post-2020 Periods
Keigo AkimotoGroup Leader, Systems Analysis Group
Research Institute of Innovative Technology for the Earth (RITE)

Contents
1. Background and objective

2. Candidate Indexes for Reviews of the INDCs
to Evaluate Emission Reduction Efforts (Exante
and Expost Reviews)
3. Examples of Indexes in Expost Evaluations(historical data and their analyses)
4. Examples of Exante Evaluations for Tentative
INDCs Including Comparisons with HistoricalData
5. Toward COP21

2

Background and objective

Trajectory of Global GHG Emission by Source
4

Source) IPCC AR5, 2014

The global emission after 2000 increased more rapidly. The Kyoto Protocol was not able toexert large effects.

Trajectory of Global CO2 Emission by Region
5

Consumption-based
CO2 emissions are not
High income able to be decreased
countries
even in HIC.
($12,616 and more)

Upper middle income countries($4,086 to $12,615)(China, Brazil, Iran, Malaysia, South
Africa etc.)
Rapid increase in CO2 emissions

Lower middle income countries($1,036 to $4,085)(India, Indonesia, Philippine, Egypt etc.)

Tackling poverty; less priority
of CO2 emission mitigation

Low income countries($1,035 and less)

Source) IPCC AR5, 2014

Background and objectives of ALPS projectand its major topics of study

6

Climate change is a very complex issue. Effective response measures in the real world areimportant. The aim of the ALPS project is to support the developments of internationalframeworks to realize green growth and effective response measures through better
understandings for technologies, economics, policies etc. and quantitative analyses andevaluations.
【major topics】
 Risk management strategy for climate change responses- Estimates of climate change damages, adaptations, and mitigation costs and theiruncertainties- Long-term target and the emission pathways- Risk management strategy for climate change responses under uncertainties etc.
Economical better understandings and analyses for real green growth- Considering the possibilities and limitations of removing energy saving barriers,
endogenous technology learning for green growth- International secondary energy prices and their drivers, and the impacts on international
competitiveness and green growth- Analyses for international constraint for funding to coal poweretc.



Climate change mitigation measures, particularly the systems measures.
- hydrogen systems (total systems including supply, transport, consumption)- systems of building, and transportationsetc.



Analyses regarding international frameworks, discussions and policy interests- Review methods for post-2020 emission reduction targets of INDCs- Contributions to international model comparison projectsetc.

Regarding evaluations of efforts ofemission reductions for post-2020

7

 The global emission reductions were decided first and then theemission allocations among Annex I countries (developed countries)
were decided and the decided targets had legal forces under the
Kyoto Protocol. However, this approach failed.
 The post-2020 international framework for emission reductions will
be pledge & review type (P&R).
 It is important to make peer-review systems for the pledged emission
targets for effective emission reduction efforts through theestablishment of the PDCA cycle.
 The INDCs (Intended Nationally Determined Contributions) will
include the targets having different base year, intensity targets, andemission reduction ratio relative to BaU emissions.
 It is important to employ appropriate indicators to enable to measureemission reductions in order to realize emission reduction potentials
for evaluating emission reduction efforts comparably among
countries.
 Each indicator has both strong and weak points. Multiple indicators
are required.

Establishment of the PDCA Cycle
in the VAP of Keidanren

8

Source: Keidanren

Keidanren and Japanese government established the PDCA cycle in the VAP, which havereview processes by the government, Keidanren, and each business association. The peerpressures to stimulate emission reductions worked weill in the VAP.

Candidate Indexes for Reviewsof the INDCs to Evaluate
Emission Reduction Efforts(Exante and Expost Reviews)

Candidate Indicators in Exante and Expost Evaluations
10

Exante evaluatione.g.,1) level of CO2 and energy intensity of GDP >> affected by industrial structures etc.
2) improvement rate of CO2 and energy intensity of GDP >> in general, the improvement
room is small in countries that have already achieved high intensity levels.
3) emission reduction ratio from baseline emission >> baseline emissions are highly uncertain.
4) marginal abatement costs, average costs, and additional costs per GDP: model based >>large uncertainties of cost estimations.

Expost evaluatione.g.,1) level of CO2 and energy intensity of GDP
2) improvement rate of CO2 and energy intensity of GDP3) relationship between energy intensity change and per-capita GDP change >> removing theinfluences of economic activity changes from the observed intensity improvements4) energy (and CO2) intensity level in major sectors5) secondary energy prices, and carbon prices6) emission reduction ratio from baseline emission7) marginal abatement costs, average costs, and additional costs per GDP: model based

Points to be Noted for the Indexes11 Marginal abatement cost is an important indicator to measure emission

reduction efforts and to consider domestic emission reductions
particularly among countries with close economic conditions.
 When emission reduction contributions overseas are included, perGDP emission reduction cost is also a good indicator. However, large
differences in MAC among countries will induce carbon leakage, anddifferences in MAC should be within a certain acceptable level .
 Equal per-capita emission indicator is apt to be considered to be
simple and clear. But this indicator cannot objectively decide the baseyear, the pathways to the convergence per-capita emission, theconvergence year etc. The allowable emissions for each country arevery different from the assumptions. In addition, potential emissions
are different due to different geographic and climate conditions,
population density etc.
 Cost-based indicators are sometimes criticized due to large
uncertainties. However, such indicators are also useful because
definite emission allocations are not required under a P&R typeframework.

Self explanations of the NDCs by each country
and the review principle
Pledge by country Ａ

Pledge by country B

Pledge by country X

Emissions
per GDPEmissionsper capita

Marginal
abatement
cost

Per-GDPemission
reduction
cost

Country A

X

Y

Z

XX

Country B

X’（X’<X）○Y’（Y’>Y）×

Z’（Z’>Z）○

XX’（XX’>XX）
○

・・・

・・・

Each country justifies her NDCs by using the multiple (but appropriate)
indicators. The reviews should be conducted also by using the multiple
indicators and will make a peer-pressure if necessary.

12

Decomposition Factors of CO2 Emission
Kaya identity

energy intensity

GDP per capita
population

CO2 intensity

CO2 emission＝CO2 emission
ＰＥ

ＰＥ

×

×

ＧＤＰ

ＧＤＰ

GDP

△CO2 emission＝△annual change inenergy intensity

CO2 emission＋△

ＰＥ
Major candidate indicators formeasuring emission reduction efforts

× ＰＯＰ

ＰＯＰ

Major candidate indicators formeasuring emission reduction
efforts, which exclude different
economic conditions

annual change in CO2 intensity

13

ＰＥ

annual change in GDP＋ △ＧＤＰ

ＧＤＰ
Note the relationships between
the two factors

Comparison of Energy Intensity of GDP(MER)
14

UK
NorwayItaly
Japan
Germany
Spain
FranceEU28
Australia
US
MexicoCanadaHungary
PolandKorea
World
Czech Republic
Saudi Arabia
South Af rica
Indonesia
India
China
RussiaUkraine2012

The intensity will be
important forcomparability of theefforts but otherindicators are also
necessary.

2005
1990

The energy intensity
of GDP depends on
several factors, suchas the efforts forenergy saving,industrial structures,
market exchange rate
etc.

0

0.5

1

1.5

TPES/GDP (toe/thousands 2005 US$)

2

Comparison of Energy Intensity of GDP (PPP)
15

UK
Italy
Spain
Indonesia
GermanyJapan
EU28
MexicoNorwayFrancePolandHungary
India
Australia
US
Saudi Arabia
World
Czech Republic
Korea
CanadaChina
South Af rica
RussiaUkraine

2012
2005
1990

0

0.1
0.2
0.3
0.4
TPES/GDP PPP (toe/thousands 2005 US$)

0.5

Changes in GDP vs Energy Intensity of GDP
Between 2002 and 2012 (past 10 years)

160Change in primary energy of GDP (%/yr)

World
MexicoSaudi Arabia

-0.5

Korea

Italy
-1

South Af rica

Better???

China
France-1.5

Australia

Spain
EU28

-2

CanadaJapan

Increase in total primary energy

Germany

India

Russia

US

-2.5

UK
Decrease in total primary energy

Indonesia

-3
-2

0

2

4

6

8

10

12

Change in GDP (%/yr)

Not only the intensity level but also the intensity improvement rate is a candidate indicator tomeasure the emission reduction efforts. However, high economic growths usually induce highimprovement of energy intensity, and therefore, high improvement of intensity does notnecessarily mean large efforts for emission reductions.

Examples of Index in Expost
Evaluations(historical data and its analyses)

Explanation of energy intensity improvement by economic
growth (R2) between 2002 and 2012: for expost review 18
Eenergy intensity change (2002-2012, %/yr)0MexicoWorld-0.5

Saudi Arabia
Italy

Korea

-1
South Africa

-1.5

China

FranceAustralia

Spain
Canada

-2

Japan

-2.5

US

EU28

Better???
Energy intensity improvement ishighly explained by GDP growth.

Germany

India Russia

UK

Indonesia

-3
0

0.1

0.2

0.3

0.4

Explanation of energy intensity change by GDP (R2) between 2002 and 2012

0.5

50% of changes
in energy
intensity can be
explained bychanges in GDP.

The high rate of energy intensity improvement does not necessarily indicate the efforts ofenergy efficiency improvements or CO2 emission reductions. Some countries whose energy
intensity changes are well explained by changes of per-capita GDP. Thus, it will be also
important to analyze the relationship between per-capita GDP and energy intensity changes.

Energy efficiency comparison for major energyintensive sectors (1/2): for expost review
43

Japan

41

Germany

39

Coal powerUS

37

Efficiency(%)

19

Source) RITE, 2014
based on IEA, 2013

China

35

Korea

33

Russia

31

India

29
EU (27)
27
World
25
1990

1995

2000

2005

2010
60

Gas power

Spain
55

Source) RITE, 2014
based on IEA, 2013

Mexico50

Efficiency (%)

The level of energy intensity of
GDP is affected by differences inindustrial structure. Measuring
energy efficiency individually for
major energy-intensive sectors
or production processes isimportant.

UK

Italy
45

US
Japan

40

Iran
35

RussiaEU (27)

30

World
25
1990

1995

2000

2005

2010

Energy efficiency comparison for major energyintensive sectors (2/2): for expost review
Primary energy consumption of BOF steel(GJ/ton of crude steel)

35

2010

30

28.3
25.9 25.7

25

34.5

33.1

2005

23.1

22.9

26.8

27.7 27.7

28.1 28.2

28.9

28.3

29.1

20

33.2
31.1

30.0 30.3

Iron & steel(BOF steel)

28.3

23.5 23.8

20

15
Source) Oda et al. 2012;
RITE, 2012

10
Japan

Korea

Germany

China

FranceUK

India

BrazilUS

RussiaUkraineCementRef ） RITE estimates
based on WBCSD/CSI,
etc

Heat consumption of clinker production(GJ/t-clinker)

6

2005

5.4

2010

5.2

5
3.7 3.84
3.1 3.3

3.3 3.3

Japan

India

4.0

4.2

3.9

3.8

4.0

4.2

4.0

3.5

3
2

1
0
Germany

UK

FranceUS

China

RussiaSecondary energy prices  retail prices ofgasoline and diesel in 2012: for expost review
2.5

DieselGasoline

Nominal price (US$/L)

2

1.5

1

0.5

0

Source) RITE, 2014 based on IEA, 2013 and GIZ, 2013

Gasoline and diesel prices in some countries, esp. the Middle East, are low.
Those prices in Europe, Korea, and Japan are high.

21Secondary energy prices  electricity prices
in 2009-11: for expost review
30

22

Note: MERs in 2005 were used.
Ref: RITE (2014), Oda et al., (2014)

Electricity prices for Industry werehigher than those for Household.

CyprusItaly

25

Industry (US¢/kWh)

Malta

20
EU (27)

BrazilJapan

15

Mexico10Germany

India

Pakistan

Korea
SwedenChina
Indonesia

California, US

5
Kazakhstan

US (Ave.)
Washington State, US005Denmark

NZ

10

New York State, US
Electricity prices for Household werehigher than those for Industry.

Kansas, US

15

France

20

25

30

35

40

Household (US¢/kWh)

Although electricity prices depend on generation mix, they could imply levels of mitigation
efforts. Electricity prices were relatively high in Europe, and Japan, but relatively low in
US, China, and Korea.

Examples of Exante
Evaluations for Tentative INDCs
Including Comparisons with
Historical Data

Tentative INDCs
Cancun pledge for 202024

Tentative INDCs for post-2020Japan-3.8% relative to 2005*

Just example simulations for -15 to-20% relative to 2005

U.S.

around -17% relative to 2005

-26 to -28% in 2025 relative to 2005

EU

-20% relative to 1990-40% in 2030 relative to 1990

Russia-15 to -25% relative to 1990

-25 to -30% in 2030 relative to 1990

Korea

-30% relative to BAU

China-40 to -45% of per-GDP CO2
emission relative to 2005

India

-20 to -25% of per-GDP CO2
emission relative to 2005

* Excluding of GHG emission reduction effects of nuclear power―
The peaking of CO2 emissions
around 2030 and to make best
efforts to peak early―Comparison of GHG Emission Intensity of GDP(MER)
in 2010 and Evaluations of the Preliminary Pledged Targets 25

GHG emission per GDP(MER)(kgCO2eq. per US$ 2005 price)

3
2.5
2
1.5

1
0.5
0
US

EU28

Japan

Russia2010
2010
2025 Pledged target (bottom range)
2030 Pledged target (bottom range)

Korea

China

India

2025 Pledged target (upper range)
2030 Pledged target (upper range)

The GHG emissions per capita of temporal INDCs for US, EU28, China, Russia, and that in
the case of 10 to 15% reductions relative to 2005 for Japan are estimated as shown here.

Changes in GDP vs CO2 Intensity of GDP
Between 2002 and 2012 (past 10 years)
World

0

Japan

Change in CO2 per GDP (%/yr)

Saudi Arabia

Korea

Mexico-1

Decreasein CO2intensity

26

India
South Africa

Italy

China

CanadaGermany
Germany-2
EU28
FranceSpain

Indonesia

Australia
EU28Japan(2010-30)

UKUS
EU28(2010-30)-3Better???

-4

RussiaUS(2010-25)

Increase in CO2 emission compared to the level in 2002

Russia(2010-30)-5China(2010-30)
Decrease in CO2 emission

-6
-2

0

2

4

6

8

10

12

Change in GDP (%/yr)
Note: The CO2 intensity of Japan in 2012 was strongly affected by nuclear power plant stops.

The CO2 intensity of GDP of tentative INDCs for US, EU28, China, Russia
between 2010 and 2025/2030 can be mapped here.

GHG emission per capita (tCO2eq./cap.)

Comparison of GHG Emission per Capita in 2010

27

25

20

15

10

5

0
US

EU28

Japan

Russia20102025 Pledged target (bottom range)
2030 Pledged target (bottom range)

Korea

China

India

2025 Pledged target (upper range)
2030 Pledged target (upper range)

The GHG emissions per capita of temporal INDCs for US, EU28, China, Russia, and that in
the case of 10 to 15% reductions relative to 2005 for Japan are estimated as shown here.

Baseline Emissions and Pledged Targets
28

200%

Relative to 2005

200%

150%

150%

100%

100%

50%

50%

0%

0%

-50%

-50%

US

EU28

Japan Russia China

USYear 2020

EU28

Japan Russia China
Year 2025

US

EU28

Japan Russia China
Year 2030

Baseline(extrapolation of CO2 per GDP)

Baseline(extrapolation of intensity by sector and by fuel)Baseline (BaU of RITE model)

Baseline (Current policy of RITE model)

Pledged target (Upper range)

Pledged target (Bottom range)

Note1: The pledged target of Japan for 2020 is the emission when emission reduction effects of nuclear power are excluded.
Note2: The emission targets of China are estimated by RITE to meet the peak-out of CO2 emissions in 2030.
Note3: All the emission targets after 2020 are preliminarily.

Future baseline emissions have large uncertainties, and further studies are needed. However, the difference between
the baseline and pledged emissions is also an important information for measuring emission reduction efforts.

Evaluations of Emission Reductions of
Pledged Targets from BaselineYear 2025
US

29

Year 2030
EU28

RussiaChina

Pledged emission target: upper range
Relative to Baseline (extrapolation of CO2 per GDP)

-7%

-18%

-41%

-26%

Relative to Baseline (extrapolation of intensity by
sector and by fuel)

-10%

-4%

-24%

-28%

Relative to Baseline (BaU of RITE model)

-32%

-51%

-4%

2%

Relative to Baseline (Current policy of RITE model)

-23%

-34%

0%

17%

Relative to Baseline (extrapolation of CO2 per GDP)

-9%

-18%

-49%

-51%

Relative to Baseline (extrapolation of intensity by
sector and by fuel)

-12%

-4%

-32%

-53%

Relative to Baseline (BaU of RITE model)

-34%

-51%

-12%

-23%

Relative to Baseline (Current policy of RITE model)

-25%

-34%

-8%

-7%

Pledged emission target: bottom range

Note: percent point change (relative to 2005)

The emission reduction ratios of tentative INDCs of US, EU, Russia, and China from theirbaseline emissions are shown here. The emission reduction ratios are very different
according to the baseline definitions.

Evaluations of Emission Reduction Costs(MAC) for Achieving the Tentative INDCs

30

The following marginal abatement costs were estimated preliminary by using atechnology-oriented energy systems model, DNE21+ developed by RITE.
Marginal abatement cost ($/tCO2eq)
US: -26 to -28% in 2025 relative
to 2005

For upper range

For bottom range

5776

EU28: -40% in 2030 relative to
1990

168

Russia: -25 to -30% in 2030
relative to 1990

012

China: peak-out in 2030 (RITE
outlook emissions)

09Note: The cost ranges include not only the rage of target but also the model assumptions for LULUCF.

The estimates of mitigation costs accompany large uncertainties, but the mitigation costs
are very important to measure emission reduction efforts under different conditions
across countries. Marginal abatement costs are important particularly for similar economy
levels of countries to keep international competitiveness.

Toward COP21

Toward COP21 in Paris: INDCs

32

 Past discussions on fair and equitable indicators under the KP-like

top-down framework tended to seek emission allocations among
countries. However, this approach falls into a zero-sum game. Thereexists no single indicator that is capable of measuring fair andequitable allocations does not exist. The post-2020 framework will
be pledge and review (P&R) type, and a new method and processes
should be developed.
 These indicators which we showed here are NOT for emission
allocations, but do intend to be used just for evaluating INDCs andinducing deeper emission reductions after COP21 through peerreviews in the PDCA cycle.
 For the indicators intended for emission allocations with legalbindings, use of only certain statistic data will be justified. On theother hand, such data cannot measure fair and equitable emission
reduction efforts. The indicators with smaller certainty can be
adopted for the review under a P&R type emission reduction
framework, as long as they meet logicality and validity
requirements.

ACE: Action for Cool EarthJapan’s Aggressive Diplomatic Strategy for Climate Change Responses 33

The relationship between climate sensitivity and global
emission pathways for 2C target, and outlook of INDCs
80000

GHG emissions (MtCO2eq./yr)

Deeper emission
reductions should be
realized throughtechnology
innovations although
they are uncertain.

Larger emission reductions
should be realized throughpeer-reviews in the PDCA cycle.

70000

34

60000

+2 C with around
50% probability

50000
AR5
530-580 ppm

40000

30000

20000

Current climate policy scenario
Temporal INDCs (high emission reduction case)(only U.S., China,
EU, and Russia)AR5480-530 ppm

The probability
achieving below+2C increases.
On the other
hand, unrealistic
measures withhigh costs haveto be expected.

AR5 430-480 ppm

2.0℃ stabilization; climate sensitivity of 3.0℃ (below 500 ppm)
10000

2.0℃ in 2100; climate sensitivity of 3.0℃ (exceedance of 530 ppm)
2.0℃ stabilization; climate sensitivity of 2.5℃ (no exceedance of 580 ppm)
2.0℃ in 2100; climate sensitivity of 2.5℃ (exceedance of 580 ppm)

0
1990

2000

Estimated by RITE

2010

2020

2030

2040

The framework of theprocesses to induce
Future emission reductions
2050 are more important thanthe levels of INDCs decided
in COP21.

Conclusion

35

 Achievable post-2020 targets should be decided in the realworld, while ambitious targets are desirable. The 25%
reduction target of Japan by 2020 relative to 1990 rather led tostagnant climate change response measures in Japan. The 450
ppm CO2eq stabilization target may also lead to stagnant
climate change response measures if we have the adherenceof the target. The long-term target should also be treated withflexibility considering uncertainties in climate sensitivity etc.
 A specific number of emission reduction rate is not necessarily
important. The establishment of review processes for inducing
sustainable emission reduction efforts are more important.
 Deeper emission reductions should be realized in long-term
through wide deployments and diffusions of high energy
efficiency and low-carbon technologies, and technology
innovations and their deployments.

Appendix

Comparison of CO2 Emission per Capita
India
Indonesia
MexicoHungary
World
France
Spain
China
Italy
Ukraine
EU28
UK
South Africa
NorwayPolandGermanyJapan
Czech Republic
Russia
Korea
CanadaUS
Saudi Arabia
Australia

2012
2005
1990

0

5
10
15
CO2 per capita (tCO2 per capita)

2037