2015, November 18

MILES (Modelling and Informing Low Emissions
Strategies) Project - Japan Policy Paper:

A joint analysis of Japan’s INDC

Authored by:
Research Institute of Innovative Technology for the Earth (RITE), Japan:
Keigo Akimoto, Bianka Shoai Tehrani, Fuminori Sano, Junichiro Oda
National Institute for Environmental Studies (NIES), Japan:
Mikiko Kainuma Toshihiko Masui, Ken Oshiro (MHIR).

The current report details the Japanese contribution to the report “Beyond the Numbers.
Understanding the Transformation Induced by INDCs” prepared by the MILES project
Consortium under contract to DG CLIMA (No. 21.0104/2014/684427/SER/CLIMA.A.4).
This project is funded by the European Union.

Disclaimer. This report was written by a group of independent experts who have not been
nominated by their governments. The contents of this publication are the sole responsibilityof RITE and NIES and can in no way be taken to reflect the views of the European Union or
any government and organisation.

In parallel with the publications of countries’ Intended Nationally Determined Contributions(INDCs) at 2030 horizon, the “Modelling and Informing Low-Emission Strategies” (MILES)
project is an international research project bringing together 16 leading research teams from
US, China, Japan, EU, Brazil and India in order to build capacity and knowledge on lowemissions development strategies (http://www.iddri.org/Projets/MILES-%28Modelling-andInforming-Low-Emission-Strategies%29). Under the coordination of French Institute IDDRI(http://www.iddri.org/), the project aims at providing informed and transparent narratives for
low-emission development strategies at national levels. Following the publication of the
MILES report “Beyond the Numbers. Understanding the Transformation Induced by INDCs”
aggregating all teams’ contributions in October 2015, the current report co-written by
Japanese teams RITE and NIES provides the detailed material for the analysis of Japan’ssituation on the eve of the COP21.

2

Table of Contents
1. Introduction .................................................................................................. 4
2. Qualitative Description of the INDC ............................................................ 4
3. Quantitative, detailed description of the INDC .......................................... 6
INDC and the energy mix ............................................................................................. 7
Sectoral disaggregation of INDC ................................................................................ 12
Contributions towards achieving the ultimate objective of the UNFCCC .............. 16

4. Critical analysis .......................................................................................... 17
4.a NIES Analysis............................................................................................................ 17
Methodology ................................................................................................................. 17
Scenarios ...................................................................................................................... 18
Assessing feasibility and robustness of Government’s INDC .................................. 20
Implications for the long-term decarbonization pathway......................................... 25
Technical uncertainty associated with nuclear power .............................................. 26
4.b RITE Analysis ............................................................................................................ 26
The economic impacts and feasibility of the emission reduction target .................. 26
International Context: Fairness and Ambition ......................................................... 29
Contribution towards achieving the 2 C target ....................................................... 34

5. Conclusions ................................................................................................ 38
Acknowledgements (NIES) ............................................................................ 39
References (NIES) .......................................................................................... 39
Appendix I: overview of NIES model ............................................................ 40
AIM/Enduse [Japan].................................................................................................... 40
References .................................................................................................................... 41

Appendix II: overview of RITE models.......................................................... 42
DNE21+ model ............................................................................................................. 42
References .................................................................................................................... 43
DEARS (Dynamic Energy–economic Analysis model with multi-Regions and multiSectors) model .............................................................................................................. 43
References .................................................................................................................... 44

Appendix III: INDC measures ........................................................................ 45

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1. Introduction
In the run up to COP21, the Japanese INDC was submitted to the secretariat of the UNFCCC
on July 17th, 2015. This paper analyses the potential impacts of the Japanese INDC on theJapanese energy system, including the energy mix and the changed induced in the final
energy consuming sectors. It offers quantitative analysis of Japan’s INDC from the different
perspectives of two Japanese research institutions (RITE (Research Institute of Innovative
Technology for the Earth) and NIES (National Institute for Environmental Studies)) anddiscusses policy implications and challenges to achieve the INDC from an economic point ofview.

2. Qualitative Description of the INDC
The Japanese government announced its INDC to be a 26% emission reduction by 2030
compared to 2013 levels which corresponds to a 25.4% reduction compared to 2005 (theemissions target in 2030 is 1.042 GtCO2eq.). The detailed breakdown by type of gas in thegovernment INDC is shown in Table 1. The targeted greenhouse gases are CO2, CH4, N2O,
HFCs, PFCs, SF6 and NF3. All sectors emitting these greenhouse gases are covered by theJapanese INDC.

Table 1: Japanese INDC for 2030
Compared to 2013（compared to 2005）
Energy-related CO2-21.9% (-20.9%)

Other GHGs (except energy -related
CO2)-1.5% (-1.8%)

Removal by LULUCF-2.6% (-2.6%)

Total GHG

-26.0% (-25.4%)

It can be seen from Table 1 that reductions in energy-related CO2 are the principal
component of the Japanese INDC. Given this link with energy policy and the INDC, the INDC
was decided in line with the Government’s strategic energy plan for 2030. The INDC wasconsidered through discussions open to the public at the Joint Experts’ Meeting of the Central
Environment Council (Subcommittee on Global Warming Measurement after 2020, Global
Environment Committee) and the Industrial Structure Council (INDC WG, Global
Environment Subcommittee, Committee on Industrial Science and Technology Policy andEnvironment). At the same time, energy policies and the energy mix were considered4through open discussions at the Advisory Committee for Natural Resources and Energy.
Based on the discussions, the Global Warming Prevention Headquarters (ministerial
decision-making on global warming countermeasures: the chair is the Prime Minister)developed a draft INDC on June 2, and public comments were received from June 3 to July
2. Finally, after going through public comment procedure, the Global Warming Prevention
Headquarters made a final decision on the INDC, and it was submitted to the UNFCCC on
July 17.
In the Japanese context, the Great East Japan Earthquake and the accident at the Tokyo
Electric Power Company’s Fukushima Dai-ichi Nuclear Power Station on March 11, 2011,
have obviously had a tremendous impact on Japan’s energy policies and thus on thedetermination of the INDC. After long discussions, the Strategic Energy Plan was decided in
April 2014, highlighting the basic principles known as the 3E+S: energy security, economic
efficiency, environment, and safety. Regarding specific numbers for the energy mix for 2030,
however, the Strategic Energy Plan only mentioned that the Japanese government would
make an announcement quickly regarding each energy source in the energy supply-demand
structure. A draft vision for the energy mix for 2030 with specific numbers (primary energy,
final energy, power supply) was proposed in June, 2015 just before the decision on the draft
INDC. The vision for the energy mix in primary energy was designed with these three major
objectives, and also a general objective of safety:. 1) The self-energy sufficiency ratio should
be higher than prior to the Great East Japan Earthquake (around 25% in primary energy). 2)
The electricity cost should be reduced compared to the current level. 3) Greenhouse gas
emissions should be reduced as to make Japan a leading example for the rest of the world
and with levels at least equivalent to those of the EU and the U.S. The INDC was in turn
determined based on the energy mix and possible measures for GHG emissions reduction.

5

3. Quantitative, detailed description of the INDC
This section describes the outlook for the energy mix and INDC officially shown by
the Japanese government; all figures and graphs in this section are from official
governmental sources. The government’s plan regarding the energy mix and INDC is basedon the macro-economic assumptions regarding population and GDP growth below. The
average annual growth rate of GDP is 1.7% between 2013 and 2030: this GDP outlook
corresponds to the ‘economic recovery’ case. Not only the INDC but also the most of thedomestic policies by the government are developed based on this GDP outlook.

Table 2: Demographic evolution assumption for Japan (Source: METI/ANRI, 2015;
National Institute of Population and Social Security Research, 2012)
Year

2013 (historical data)

Population

127 million

2030
117
millionFigure 1: Estimation of middle and long-term GDP evolution (economic recovery case)(Source: METI/ANRI, 2015; Cabinet Office, Government of Japan, Feb. 12, 2015)
Approximately 90% of Japanese GHG emissions are energy-related CO2. The
INDC implementation is closely linked therefore to the implementation of the 2030 vision for
the energy mix. The two following paragraphs detail the government’s proposition regarding
energy supply measures and end-use measures by sector in order to build a well-balanced

6

energy future based on the 3E+S objectives.

INDC and the energy mix
In order to ensure the achievability of the INDC, the government elaborated thebreakdown targets by bottom-up calculation based on the energy mix with concrete policies,
measures and individual technologies. Table 3 shows the estimated energy-related CO2
emissions in 2030 by sector.

Table 3: The expected energy-related CO2 emissions by sector for achieving the INDC
(Source: METI/ANRI, 2015)
2005

2013

2030

Industry

457

429

401

Commercial and other

239

279

168

Residential

180

201

122

Transport

240

225

163

Energy conversion

104

101

73

1219

1235

927

Energy-related CO2 Total[Value: million t-CO2]
Note: Emissions by sector include indirect emissions (e.g., electricity consumptions). Emissions
from energy conversion is those of own use and losses in energy conversion.

The primary energy supply and final demands, and electricity supply in the energy mix isshown respectively in Figures 1 and 2. In the estimation, the government assumed the
GDP growth of 1.7% per year between 2013 and 2030. A significant improvement of energy
efficiency is expected in the energy mix:-

A cut of 13% in energy consumption compared to baseline (50.3 million kL (crude oil
equivalent))-

A cut of 17% in electricity consumption compared to baseline (196.1 TWh)7

Figure 2: Final energy demand and primary energy mix in 2030 (Source: METI/ANRI,
2015)

Figure 3: Electricity mix in 2030 (Source: METI/ANRI, 2015)
The government intends to reduce the dependence on nuclear power compared withthe share of nuclear power before the accident. On the other hand, all of the nuclear

8

reactors are stopped as of the end of June 20151, and large amounts of CO2 are emitted
by fossil fuel power substituting nuclear power. The government introduced a feed-in tariff
after the nuclear power accident to strongly promote renewable energies, and has alreadyachieved a significant introduction of photovoltaics in particular. However, the electricity
costs are increasing. The government intends to reduce both CO2 emissions and electricity
costs. The well-balanced electricity mix was determined to include the restart of nuclear
power, renewable energy increases (well-balanced increases in energy sources withinrenewables), and increases in efficiency of fossil fuel power in order to achieve both areduction in CO2 emissions and electricity costs (see Figures 3 and 4). In this case, theself-sufficiency of energy is expected to be 24.3% which nearly corresponds to that before
the nuclear power accident.

Figure 4: Expected fossil fuel and expected expenses in 2030 (Source: METI/ANRI,2015)

The unit 1 of Sendai nuclear power station was restarted on August 11, 2015. In addition,
the evaluations by the Nuclear Regulation Authority under the new regulations after the
Fukushima Dai-ichi Nuclear Power accident for the unit 2 of Sendai nuclear power station,
the units 3 and 4 of Takahama nuclear power stations, and the unit 3 of Ikata nuclear
power station were finished as of August 11, and are prepared to be restarted. 20 reactors
are under the evaluation processes by the Nuclear Regulation Authority.
19Figure 5: Renewable expenses trends and expected expenses in 2030 (Source:
METI/ANRI, 2015)10

Figure 6: Structure of national expenses for electricity in 2013 and 2030 (Source:
METI/ANRI, 2015)11

Sectoral disaggregation of INDC
The government submitted a detailed plan for the measures to be implemented toreach the INDC: examples are listed inthe following tables, while the full tables are available
in appendixes.
Table 4: Examples of measures for energy-originated CO2 (source: Submission ofJapan's INDC)
Energy-originated CO2
Industry
sectorIron and steel industry
environmentally harmonized steelmaking process (COURSE50)
Chemical industry

processing with microbe catalysis
Cross-sectoral/Other

Commercial
and other
sectors
water heater, high-efficient boiler)

water businessResidential
sectorPromotion of compliance of energy saving standards for newly constructed housing

fuel cell, solar water heater)purchase of upgraded, Home CO2 advisor)

Transport
sectorImprovement of fuel efficiency

railway, ...)
Energyconversion
sectorCrosssectional
strategies

12Energy-originated CO2
Industry
sectorIron and steel industry

Chemical industry

slag crusher, air-beam cooler, separator improvement, vertical roller coal mills)

Cross-sectoral/Other

Commercial
and other
sectors
water heater, high-efficient boiler)

diagnosis

buildings)

heat island effectmeasures, etc.

13

Table 5: Measures for non-energy-originated CO2 (source: Submission of Japan's
INDC)
Non energy-originated CO2
CH4
paddy rice fields)

N2O
originated from fertilizer application)
Fluorinated gases
Management of Fluorocarbons, emission control through industries’ voluntary action plans, etc.)
LULUCF sector
Forest management
Cropland management/Grazing land management
Revegetation

management/forestry industry measures

Final energy consumption by sector is shown in Figure 7. The energy consumptionof the industry sector is expected to increase slightly compared to the current level due tothe expected economic growth and fewer opportunities for cost-efficient improvements inenergy efficiency. On the other hand, the energy consumption in transportation, residential
and commercial sectors is expected to reduce greatly. The structure of final energy
consumption is expected to shift as well, as electricity is expected to play a greater role infinal energy consumption in most sectors, including plug-in hybrid and electric vehicles in thetransportation sector.

Transport
Residential
Commercial
Industry

Figure 7: Trajectory of final energy consumption with sectoral disaggregation (-13%in energy consumption compared to baseline) (unit: million kL of oil equivalent peryear); source: METI/ANRI, 2015)
The emission outlook is determined not only by CO2 intensity improvements but
also by the production and service levels. The government assumes the production levels

14for major energy-intensive industries to be consistent with the assumption of macroeconomic
growth of 1.7% per year (Cabinet Office Outlook). Projections for several main energyintensive industrial products such as crude steel, ethylene, cement, and paper are shown in
Figure 8. Most of the production is assumed to be roughly stable or slightly decrease toward2030.
For example, for crude steel, the world’s economic growth is expected to becentered in Asia in the next decades, and the Japanese production will be driven by both thenational demand and the Asian demand2. Balancing the effect of growth and efforts towards
a low carbon society has lead the government to project stabilized production for several
main industrial products such as crude steel.
For cement, although the demand is expected to grow steadily until 2020 due to thepost-2011 disaster reconstruction and the 2020 Olympic Games preparation, it should thendecrease until 2030.
Crude steel production (MtCO2)

Ethylene production (MtCO2)

Cement production (MtCO2)

Paper production (MtCO2)

Figure 8: Projection outlook for crude steel, ethylene, cement, and paper
productions in 2030 (Source: METI/ANRI, 2015)
According to the 2014 statistics of the Japan Iron and Steel Federation, Japan
exports 43 % of their iron and steel products (in metric tons), 77% of which in Asia.
2

15

Contributions towards achieving the ultimate objective of the UNFCCC
In the Government’s INDC, it is described that Japan’s INDC is consistent with thelong-term emission pathways up to 2050 to achieve the 2 degrees Celsius goal as presented
in the IPCC AR5, and with the goal the country upholds, namely, “the goal of achieving atleast a 50% reduction of global GHG emissions by 2050, and as a part of this, the goal ofdeveloped countries reducing GHG emissions in aggregate by 80% or more by 2050”.

16

4. Critical analysis
This section presents the critical analysis presented by each institute, NIES and RITE.
The NIES analysis mainly focuses on feasibility and robustness of Government’s INDC by2030 and a consistency with the long-term emission pathways up to 2050 to achieve the 2
degrees Celsius goal. In addition, it assesses a possibility and impact of enhanced action by
2030 toward the 2050 target which is to reduce GHG emissions by 80%.
The RITE analysis evaluates the economic impacts of the government’s target on GDP andhousehold consumption, and compares them with scenarios previously developed with RITE
models; it assesses their fairness and ambition from an international perspective bycomparing indicators such as energy efficiency performances, GHG intensity of GDP,emissions per capita, emission reduction costs per GDP and marginal abatement costs.

4.a NIES Analysis
Methodology
The Asia-Pacific Integrated Model (AIM) is a large-scale computer simulation model
developed by the National Institute for Environmental Studies, Kyoto University and Mizuho
Information & Research Institute in collaboration with several research institutes in the AsianPacific region (Kainuma et al., 2003).
The NIES analysis here uses the AIM/Enduse model which is a dynamic recursive andtechnology selection model for the mid- to long-term mitigation policy assessment. The model
covers both end-use sectors (transport, industrial, residential and commercial) and theenergy supply sector. Non-energy sectors (e.g. agriculture, industrial process, waste) arealso included and non-CO2 gases including CH4, N2O, hydrofluorocarbon (HFC),
perfluorocarbon (PFC) and SF6 (these emissions are converted into CO2-equivalents using
the GWP based on the IPCC SAR (GIO, 2014)) but NF3 emission and emission/carbon sinkfrom LULUCF are excluded. In each sector, service demands are given exogenously andtechnologies are selected in order to minimize total system costs (capital cost, energy costand carbon price).
The model used for this analysis is a multi-regional version of AIM/Enduse[Japan]. Thismodel explicitly distinguishes 10 regions to assess the regional differences in renewableenergy potentials and energy demand characteristics. These 10 regions coincide with thebusiness areas of 10 public power supply firms. For the details of AIM/Enduse[Japan], see
Appendix I.
AIM/Enduse[Japan] broadly takes into account the mitigation options of the Government’s
INDC by 2030. However, some options which contribute to cut service demands, such as

17

energy management in factories, promotion of Cool-Biz/Warm-Biz 3 , promotion of public
transport and modal shift to railways are not taken into account as mitigation options, since
it is difficult for technology selection model to consider the effect of these options. In addition,
as the technology selection is determined based on cost minimization, the levels of
introduction of each mitigation option are not precisely consistent with those of theGovernment’s INDC.

Scenarios
For NIES analysis, three different scenarios are developed in order to analyze feasibility androbustness of Japan’s INDC, and an opportunity for further emission reduction by 2030
toward the 2050 target. In NIES INDC Scenario, the level of GHG emissions is consistent
with Government’s INDC in 2030 and with long-term reduction target in 2050. In Enhanced
Action Scenario, an opportunity for further reduction in 2030 is assessed. In Low-Nuclear
Scenario, uncertainty of the availability of nuclear power is considered.
Regarding the long-term GHG emission reduction target, it is described in the Government’s
INDC that Japan’s INDC is consistent with the long-term emission pathways up to 2050 toachieve the 2 degrees Celsius goal and with the goal the country upholds, namely, “the goalof achieving at least a 50% reduction of global GHG emissions by 2050, and as a part of this,the goal of developed countries reducing GHG emissions in aggregate by 80% or more by2050”. In addition, in the Fourth Basic Environment Plan, the target in 2050 is set to reduce
GHG emission by 80%. Hence, NIES analysis sets the 2050 target to reduce GHG emission
by 80% compared to the 1990 level (Government of Japan, 2013).
For all scenarios, carbon prices are set as a driver for introduction of mitigation options,coupled with the energy efficiency standards for new buildings and houses which is alsomodelled in the Current Policies Scenario of WEO 2014 (IEA, 2014). However, other policies
such as feed-in-tariff for renewable energies, subsidies for low-carbon technologies and fueleconomy target for vehicles are not taken into account.
Followings are the detailed descriptions of each scenario.


NIES INDC Scenario – This scenario sets the target of reducing GHG emissions by 2030
by the same level with the Government’s INDC (25.4% reduction with respect to the2005 level, including reduction in LULUCF and NF3) and achieving the 80% reduction

3

The Cool-Biz and Warm-Biz are the public campaigns which encourage people in offices to wear
clothes that enable them to set the air conditioner to 28 degrees C in the summer and set the heating
to 20 degrees C in the winter, and live comfortably at these room temperatures (the Government ofJapan, 2013).

18

target by 2050 thereafter. Excluding emissions from LULUCF and NF3, the INDC targetof 25.4% reduction by 2030 corresponds to approximately 22.7% with respect to the2005 level.
In this scenario, availability of nuclear plant is given based on New Policies Scenario
developed by IEA’s World Energy Outlook 2014 (IEA, 2014); a lifetime of plants built
since the mid-1980s is extended to 60 years and limited to 40 years for all others.
Complying with this assumption, electricity generation from nuclear plant in 2030
accounts for approximately 232 TWh. It is broadly consistent with the description in theLong-term Energy Supply and Demand Outlook for 2030 which projects between 217
TWh and 232 TWh in 2030 (METI/ANRE, 2015). Extrapolating this assumption toward2050 without any new construction or replacement of nuclear plant, the electricity supply
from nuclear power will be approximately 184 TWh in 2050.
Enhanced Action Scenario – This scenario illustrates the opportunity for further
decarbonization by 2030 from the level of the Government’s INDC. In this scenario,
carbon prices are increased linearly from 2016 to 2050 in order to achieve 80% reduction
target by 2050. This means a carbon price in 2030 reaches roughly a half of the 2050
level. Assumptions on availability of nuclear power are the same as NIES INDC Scenario.

Low-Nuclear Scenario – Considering the uncertainty of availability of nuclear power
plants, all nuclear plants are not assumed to operate more than 40 years in Low-Nuclear
Scenario. In this scenario, new constructions and replacements of existing nuclear
plants are not considered as well and capacity factor of nuclear plant is fixed up to 70%.
In this scenario, the electricity supply from nuclear power will be zero in 2050.
Assumptions on GHG emissions constraint are the same as NIES INDC Scenario.

Assumptions on population and economic growth by 2030 is consistent with theGovernment’s INDC and the Long-term Energy Supply and Demand Outlook. From 2030 to2050, economic growth is estimated using GDP growth per capita of SSP5, conventional
development scenario of Shared Socioeconomic Pathways (IIASA, 2015). Population
prospects are taken from the perspectives by National Institute of Population and Social
Security Research (IPSS, 2012). Assumptions on socio-economic indicators up to 2050 are
summarized in Table 6.

19

Table 6: Assumptions on population and economic growth for NIES analysis 4
2005

2030

2050

Population (Million)

128

117

97

Real GDP (billion US$2005)

4,572

6,406

8,285

Assessing feasibility and robustness of Government’s INDC
The purpose of this section is to assess feasibility and robustness of Japan’s INDC based on
the developed three scenarios by 2030 with AIM/Enduse model.
In NIES INDC Scenario and Low-Nuclear Scenario, carbon prices in 2030 are estimatedapproximately as 187 US$/t-CO2 and 236 US$/t-CO2 respectively in order to cut GHG
emissions by approximately 22.7% with respect to the 2005 level. In Enhanced Action
Scenario, GHG emissions are reduced furthermore; 25.3% with respect to the 2005 level andthe carbon price in 2030 rises to approximately 220 US$/t-CO2 (Figure 9, Table 7). The
carbon price in this analysis is directly linked to the marginal cost to achieve the INDC target.
However, it should be noted that additional policy tools such as mandatory standards andrecycle of carbon tax revenue could help to lower the actual carbon prices.

Non-energy CO2& other GHGs

1,400

CO2- Energy
conversion

1,200
1,000

CO2- Transport

800

CO2- Residential

600
400

CO2- Commercial

2005 20102030

Low-Nuclear

Enhanced
ActionNIES INDC

NIES INDC

0

Low-Nuclear

200

Enhanced
ActionGHG emissions (Mt-CO2eq)

1,600

CO2- Industrial

2050

Figure 9: GHG emissions for the different scenarios developed by NIES54The Government of Japan (2015), IIASA (2015), IPSS(2012), METI (2015)
Both direct and indirect emissions are included. The data for FY2005 and FY2010 is taken from
historical GHG emission which is based on GWP subjected to IPCC SAR. As the authorized historical
data has been changed to the GHG based on GWP100 subjected to IPCC AR4 since 2013, the data for
FY2013 is not appeared in the figure.
520

Table 7: Carbon prices for the different scenarios developed by NIES
Scenario

2030

2050

NIES INDC Scenario

187

523

Enhanced Action Scenario

220

514

Low-Nuclear Scenario

236

631

(Unit: US$/t-CO2)
The further reduction in Enhanced Action Scenario by 2030 compared to NIES INDC
Scenario is due to a switch from coal to natural gas and an additional deployment of
renewable energies mainly in the power sector. As shown in Figure 10, in the Enhanced
Action Scenario, power generation from gas fired plants and renewable energies, such as
solar PV and biomass, is increased and a share of coal fired plant falls approximately 13%,
while it accounts for 17% and 18% in NIES INDC Scenario and Low-Nuclear Scenario,
respectively. However, a share of coal fired plants falls to lower level compared to the 2010
level even in NIES INDC Scenario because of high carbon prices, while Government’s INDC
requires a share of coal at, where it approximately 26% in 2030 in consideration of its stabilityof supply and economic competitiveness.
In NIES INDC Scenario, a share of renewable energies rises to around 20% in 2030 whichis slightly lower than the Government’s INDC (22%-24%). The share of renewable energies
accounts for approximately 23% and 29% in Enhanced Action Scenario and Low-Nuclear
Scenario respectively where the coal fired plants and nuclear power plants are replaced byrenewable energies. A share of renewable energies stays below 30% in 2030 even in LowNuclear Scenario despite the high carbon prices due mainly to the fragmented potential ofrenewable energies with narrow interconnection capacity between the 10 regions in Japan(As shown in Appendix I, AIM/Enduse considers the constraints on regional renewablepotential and interconnection capacity). Additionally, it should be noted that the additional
policies, such as feed in tariff and subsidies for renewable energies, are considered, a shareof renewable energies could be increased.
With respect to the 2013 level, total electricity generation in 2030 is almost the same level
because of economic growth and electrification in the demand side. This trend is roughly
consistent with the Government’s INDC.

21

Renewable (Total)
Ocean
Biomass
Geothermal
Wind
Solar PV
OilNatural Gas w/CCS
Natural Gas
Coal w/CCS
Coal
Hydro
Nuclear

1,200
1,000
800
600

400

2005 2010 2013

2030

Low-Nuclear

Enhanced
ActionNIES INDC

NIES INDC

0

Low-Nuclear

200
Enhanced
ActionElectricity generation (TWh)

1,400

2050

Figure 10: Electricity generation for the different scenarios developed by NIES6
Final energy consumption in NIES INDC Scenario is decreased by around 9% with respect
to the 2010 level. The level of energy efficiency in the model used for NIES analysis ismoderate compared to the Government’s INDC which accounts for 14% due mainly toabsence of some mitigation options which cut service demand, as it is difficult for technology
selection model to take into account the effect of these abatement options.
Even in Enhanced Scenario and Low-Nuclear Scenario, which applies higher carbon prices,
final energy consumption in 2030 stays the same level as NIES INDC Scenario. It implies
most of cost-effective energy efficiency option is introduced even in NIES INDC Scenario andremaining potential to additional reduction of energy use is insufficient excluding the options
which cut service demand. Therefore, it seems that the level of reduction of final energy
demand in Government’s INDC is appeared to be reasonable considering its high economic
growth.

The data for FY2005, FY2010 and FY2013 is taken from historical electricity generation. Electricity
generation by autoproducers are excluded in this figure.
622

Hydrogen

16.0

Heat

14.0

Renewable

12.0

Biomass

10.0

4.0

Coal

2.0

Electricity
NIES INDC

0.0

2005 20102030

Low-Nuclear

Oil

Enhanced
Action6.0

NIES INDC

Gas

Low-Nuclear

8.0

Enhanced
ActionFinal energy consumption (EJ)

18.0

2050

Figure 11: Final energy consumption for the different scenarios developed by NIES7
Figure 11 summarizes import bills of fossil fuels in the different scenarios which is estimatedbased on the perspectives of fossil fuel import prices taken from IEA’s Energy Technology
Perspectives 2015 (IEA, 2015). In 2030, it falls to approximately 220 billion US$ despite of arise of crude oil prices. However, import bills in Enhanced Action Scenario stays at the samelevel as NIES INDC Scenario because the impact on energy costs of a switch from coal togas nearly compensates that of improvement in energy efficiency and additional deploymentof renewable energies. Hence, promotion of early actions especially on gasification by 2030
entails challenges associated with energy security issue and impacts on end-use energy
price such as electricity.

The data for FY2005 and FY2010 is taken from historical energy consumption from the energybalance statistics in Japan. As the structure of the statistics has been updated since 2013 in Japan,
the data for FY2013 is not appeared in the figure. It should be noted that energy unit is described in
HHV complying with the manner of the Energy Balance Statistics.
7

23

100%

94%

75%

90%

79%

80%
70%

200

60%
150

41%

41%

46%

50%
40%

100

30%
20%

50

Import dependency (%)

75%

250

Natural gas
Coal
Oil
Importdependency

2013

2030

Low-Nuclear

Enhanced
ActionNIES INDC

NIES INDC

0

Low-Nuclear

10%

Enhanced
ActionFuel import bills (billion US$2013)

300

0%

2050

Figure 12: Fuel import bills for the different scenarios developed by NIES
Figure 13 shows the improvements of energy and carbon intensity in the final energy sectors
under the NIES INDC scenario. It can be seen that the industry, buildings and passenger
transport sectors require significant improvements in energy intensity by 2030 with respect
to the 2010 level of approximately 27%, 18% and 27% respectively, while those in freighttransport sector stay at around 7% in 2030. Likewise the carbon intensity (including direct
and indirect emissions) of energy demand in the industry and buildings sectors improve by
12% and 16% between 2010 and 2030, thanks notably to electrification and gasification. In
buildings sector, it can be seen that carbon intensity by 2020 increased by 3% with respect
to the 2010 level because of a temporal rise of carbon intensity of electricity due mainly to
reduction of nuclear power. By contrast, the carbon intensity of transport fuel declines only
by 1% by 2030, reflecting limited electrification and biofuel penetration.

24

Carbon intensity improvement0%

Industry(MJ/US$)

Buildings(GJ/m2)

Freighttransport(GJ/tkm)

-5%
-10%
-15%
-20%
-25%
-30%

Passenger
transport(GJ/pkm)

Industry

Buildings

Transport

5%

Carbon efficiency improvement (wrt. 2010)

Energy efficiency improvement (wrt. 2010)

Energy intensity improvement

0%

-5%

-10%

-15%

-20%

2020

2030

2020

2030

Figure 13: Improvement of energy and carbon intensity by sector in NIES INDC
Scenario

Implications for the long-term decarbonization pathway
This section mainly focuses on the implications for the long-term target by 2050 which is to
reduce GHG emission by 80% with respect to the 1990 level.
In NIES INDC Scenario, GHG emission reductions in 2050 reach80% due mainly to
improvement in energy efficiency, electrification and decarbonization of electricity. Finalenergy consumption in 2050 is nearly halved compared to the 2005 level and electrificationin demand side rises to more than 40% from 22% in 2005 (Figure 11). In addition, electricity
is almost decarbonized because of both a large scale deployment of solar PV and wind power
and a substitution from unabated coal/ gas fired plant to CCS equipped plant (Figure 10).
By 2050, a carbon price in NIES INDC Scenario rises to approximately 523 US$/t-CO2. As it
is not so far from the level of Enhanced Action Scenario, in which a carbon price in 2050
accounts for approximately 514 US$/t-CO2, it is implied that the 80% reduction target is stilltechnically feasible even if GHG emissions reduction in 2030 stays the same level as theGovernment’s INDC.
In all scenarios assessed in NIES analysis, power generation from unabated coal fired plantis almost substituted by low carbon sources while unabated gas fired plants plays still
important role as flexible resources in order to integrate variable renewable energies (VREs)
in the long-term. Though, the switch from coal to gas in early stage entail the challenge
associated with energy security, it could contribute to effective mitigation in the long run
because they avoid lock-in of high carbon intensity plant.

25

Technical uncertainty associated with nuclear power
In Low-Nuclear Scenario, the 2030 target which reduces GHG emission to the level of INDC
is still feasible with additional deployment of natural gas and renewable energies, which
substitute nuclear power with low-carbon resources (Figure 9). However, a carbon price rises
to 236 US$/t-CO2 up to 2030 and import bills of fossil fuels become approximately 221 billion
US$, which are 1.5 billion US$ higher than NIES INDC Scenario. The 80% reduction target
in 2050 is also technically feasible with the entire phase out of nuclear power, with the
deployment of CCS equipped as well as renewable energies, though carbon price reaches
approximately 631 US$/t-CO2 in 2050 in order to promote additional deployment of
renewables, particularly VREs, and CCS-equipped natural gas plant as alternative lowcarbon energies.

4.b RITE Analysis
The economic impacts and feasibility of the emission reduction target
Before the government provided the draft of INDC, RITE analyzed several scenarios ofdifferent electricity mix and CO2 emission reduction levels with RITE’s economic models (atechnology-rich energy systems model DNE21+ and a CGE-type energy-economic model
DEARS: see Appendices for a detailed overview of each model). Compared with theanalyses for the assumed scenarios by RITE, the GDP loss and consumption loss for thesubmitted INDC is expected to be substantial. The electricity mix (relative share by primaryenergy) proposed by the government is well-balanced enough not to trigger importanteconomic losses. However, as to the absolute amount, substantial energy savings are
expected, and therefore a relatively high economic impact is estimated to meet these goals.
According to DNE21+ model, the marginal abatement cost for the INDC is about
380$/tCO2eq for the 26% reduction of GHGs compared to 2013 and about 260$/tCO2eq for
the 21.9% reduction of energy-related CO2 compared to 2013.
According to DEARS model, achieving these targets will require considerable costs on
GDP and households consumption as shown in Figure 14.

26

+2.6 trillion
yen+2.6兆円+0.2
trillionyen+0.2兆円+3.5 trillion
yen+3.5兆円+3.3 trillion
yen+3.3兆円+0.6
trillionyen+0.6兆円-0.6兆円-0.6 trillion
yen+4.0 trillion
yen+4.0兆円+3.0 trillion
yen+3.0兆円+1.8
trillion yen+1.8兆円+1.0
trillion yen+1.0兆円+0.3

IEA WEO2014 新政策シナリオレベル
New Policies Scenario levels of carbon prices
450 Scenario levels of carbon prices
IEA WEO2014 450シナリオレベル

60%

-1.0%
-2.0%
-2.5%

Part of baseload generation

0.0%

0.7%

0.6%
0.3%

0.2%

0.4%

0.0%
-0.5%
-1.0%
-1.5%
-2.0%
-2.5%
-3.0%
-3.5%

原子力30%
Nuclear 30% +Coal 20% ++石炭20%
Renewables
20%+再エネ20%

Nuclear 20% +原子力20%
Coal 20% ++石炭20%
Renewables
25%+再エネ25%

原子力20%
Nuclear 20% +Coal 30% ++石炭30%
Renewables
20%+再エネ20%IEA WEO2014 新政策シナリオレベル
New Policies Scenario levels of carbon prices
450 Scenario levels of carbon prices
IEA WEO2014 450シナリオレベル

-0.2%

-0.5%
Nuclear 15% +原子力15％
Coal 15% ++石炭15%
Renewables
30%+再エネ30%

0.5%

0.7%

Nuclear 25% +原子力25%
Coal 25% ++石炭25%
Renewables
20%+再エネ20%0.1%

Nuclear 25% +原子力25%
Coal 25% ++石炭25%
Renewables
15%+再エネ15%

0.5%

0.6%
0.2%

< Government’s
proposition *>-2.8%

原子力20-22%
Nuclear 20-22% +
26% +
Coal
+石炭26%
Renewables 22+再エネ22-24%
24%

0.9%

1.0%

現状放置
2013
electricity
ケース
composition

consumption
Households
家計消費の変化variation (in % compared to(%,基準ケース比)
the reference case)appr. 56%

(nuclear, coal, hydro and geothermal)

1.5%

-1.0%

-17.9
trillion yen-17.9兆円-3.0%Households consumption-0.5%*The impact
of carbon
price of
380$/tCO2
which wasestimatedby DNE21+-0.5%

原子力30%
Nuclear 30%+ Coal 20% ++石炭20%
Renewables
20%+再エネ20%

Nuclear 20%
原子力20%+ Coal 30% ++石炭30%
Renewables
20%+再エネ20%

Nuclear 25%
原子力25%+ Coal 25% ++石炭25%
Renewables
20%+再エネ20%50%

Nuclear 25% +原子力25%
Coal 25% ++石炭25%
Renewables
15%+再エネ15%

Nuclear 20% +原子力20%
Coal 20% ++石炭20%
Renewables
25%+再エネ25%40%< Government’s
proposition *>-1.5%

trillion yen+0.3兆円-3.6兆円-3.6 trillion yen

Note
The reference case is the2013 composition ofelectricity mix and IEA WEO
New Policies Scenario (forcarbon intensity)

0.0%

原子力20-22%
Nuclear 20-22% +Coal 26% ++石炭26%
Renewables 2224%+再エネ22-24%+1.9 trillion
yen+1.9兆円

原子力15％
Nuclear 15% +Coal 15% ++石炭15%
Renewables
30%+再エネ30%

0.8%
0.6%
0.4%
0.2%
0.0%
-0.2%
-0.4%
-0.6%

現状放置
Business
2013
Business
electricity
usual
asケース
usual
as
composition

GDPの変化(in % comparedGDP variation
to the (%,基準ケース比)
reference case)GDP

Figure 14: GDP and households consumption losses for the different scenarios
assumed by RITE and for the INDC
As described in Section 3, in the government’s proposition, despite a high GDP
growth rate (1.7%/year) projection, the power generation after GHG reduction measures isanticipated to be almost constant. The GDP elasticity of electricity after the reduction
measures is 0.05 between 2013 and 2030. The elasticity between 2000 and 2010 is nearly
1.0 in Japan. The elasticity will decrease gradually toward 2030 due to population decrease
and industry structure changes (our estimates of the elasticity for 2013-2020 and 2020-2030
are respectively 0.8 and 0.6; the elasticity of IEA WEO2014 Current policy scenario for 20122030 is 0.7). However, the expected electricity generation in 2030 in the government’s
proposition is too small compared to the GDP outlook. In addition, the price elasticity isrelatively small according to the historical records not only in Japan but also in EU countries.
Japanese government has a priority to reduce electricity costs compared to the current level(around 30% increase compared to that before the nuclear power accident). Such large
electricity savings should be achieved under a high GDP growth and reductions of electricity
cost. Such a challenge should have important economic impacts as shown above.

27

Figure 15 and Figure 16 show the energy mix and electricity mix for the different
scenarios developed by DNE21+ model and for the INDC. For primary as well as electricity,
the disparity between the government’s proposed energy amount and the total amount in allother scenarios estimated by RITE shows how ambitious the government’s objectives interms of energy savings are.

Figure 15: Primary energy mix for the different scenarios developed by RITE and forthe INDC. The carbon prices for the RITE scenarios are assumed to be the same level of theCurrent Policies Scenario of IEA WEO2014 (37$/tCO2 in 2013 price which corresponds to
23$/tCO2 in 2000 price).

28

Figure 16: Electricity mix for the different scenarios developed by RITE and for the
INDC. The carbon prices for the RITE scenarios are assumed to be the same level of theCurrent Policies Scenario of IEA WEO2014 (37$/tCO2 in 2013 price which corresponds to
23$/tCO2 in 2000 price). Also, the analysis with DNE21+ includes autoproducers in total
power generation (unlike NIES analysis).

International Context: Fairness and Ambition
Japan’s submitted INDC aims at achieving fairness and ambition regarding levels amongworld countries. This paragraph discusses quantative analyses on fairness and ambition in
the international context.

Current energy efficiency performances in JapanAs discussed in Section 3 and in the previous paragraph, the government proposition
has high targets in terms of energy savings. The government proposition especially counts
on energy efficiency equipments to achieve these targets. A close look on energy
performances in electricity generation and industrial sectors is given below. The energy
efficiency for coal and gas power generation is shown in Figure 17 and Figure 18, respectively.
Energy efficiency for coal power generation in Japan has been the highest among majorcountries for more than 20 years. The room of efficiency improvements is not large in Japanfor this reason. According to Figure 18, energy efficiency for gas power generation is not thehighest although it is very high compared to world levels. Replacements of existing old gas
power stations to state-of-art gas combined power plants will be expected, and in the29

government’s proposition, the efficiency improvements and the emission reduction effects
are considered.

43

Japan

41

Germany

39

US

Efficiency(%)

37

China

35

Korea

33

Russia

31

India

29
EU (27)
27
World
25
1990

1995

2000

2005

2010

Figure 17: Efficiency of coal power generation. Source: RITE, 2014 (estimation based
IEA data, 2013)
60
Spain
55

UK
MexicoEfficiency (%)

50

Italy
45

US
Japan

40

Iran
35

RussiaEU (27)

30

World
25
1990

1995

2000

2005

2010

Figure 18: Efficiency of gas power generation. Source: RITE, 2014 (estimation based
IEA data, 2013)
Figure 19 and Figure 20 show energy efficiencies for crude steel productions in the ironand steel sector and for clinker productions in the cement sector, respectively. According toboth figures, Japan has the best performances among many countries. In these energyintensive sectors, the room for efficiency improvements is not large in Japan.
Since electricity consumption is expected to decrease in the residential and comercial

30

sectors rather than in the industry, the energy effiency will thus need apply to home
appliances and optimizing individual consumption. Such a conclusion is however pretty
consistent with the fact the government did not project a decrease in energy consumption for
the industry sector. Innovative technology developments are required for further efficiency
improvements in the power and industry sectors.

Figure 19: Energy consumption in the iron and steel sector (BOF steel). Source: Oda
et al. 2012; RITE, 2012. Note: The efficiency in some countries in 2010 worsen compared
to in 2005 mainly due to the decrease in the operation ratios.

Figure 20: Heat consumption in the cement sector (clinker). Source: RITE estimatebased on WBCSD/CSI data. Note: The efficiency in some countries in 2010 worsencompared to in 2005. Main reasons are increases in waste energy use and the decrease in
the operation ratios.

Comparison of the level of ambition of Japan’s INDC with other countries
Comparing the Japanese INDC to other submitted INDCs can be one way of putting
them into perspective and assessing their relative ambition. The comparison in particular

31

allows to explain why the Japanese government estimated their proposition to be appropriate
given the already submitted INDC.
Table 8 shows the INDC for Japan, US, and EU, with the reduction rate from 1990, 2005,
and 2013. The underlined figure represents the official announcement by the country.

Table 8: INDC for Japan and major economies
Emissions reduction ratio from base year

Japan: in 2030, -26%
from 2013 levels
US: in 2025, about -26 to -28%
from 2005 levels
EU28: in 2030, -40%
from 1990 levels

From 1990

From 2005

From 2013-18.0%-25.4%-26.0%-14 to -16%

-26 to -28%

-18 to -21%

-40%

-35%

-24%

According to the chosen base year, the apparent value of INDC changes; for instance,with 2013 as a base year, EU28 and Japan have relatively close INDC. Japan will need large
emission reduction efforts toward 2030 to achieve the INDC. However, the existing energy
efficiency is different among countries as shown in the previous paragraph, different expectedeconomic growth rates etc., and therefore it is difficult to make a relevant comparison
between INDC in terms of ambition from the emission reduction rates from a base year.
Several indicators are required for measuring the ambition. This report shows the Japanese
INDC in the international context by assessing them through a few significant indicators: theGHG intensity of GDP, the emissions per capita, the marginal abatement cost, and theemission reduction cost per GDP. Cost indicators have large uncertainties but also help tohave a global view of the effort implied by the INDC.
Figure 21 shows the GHG intensity of GDP trajectories induced by the announced
INDC in Japan, EU28, United States, Korea, China and Russia. We can see that developed
countries aim at levels that are rather close, EU28 and Japan in particular. Japan is thelowest-carbon economy among the considered countries and remains so with the announced
INDC.

32

Figure 21: Evolution of GHG intensity of GDPMER (kgCO2eq/US2005$)
Figure 22 shows the emissions per capita trajectories induced by the submitted INDC in
Japan, EU28, United States, Korea, China and Russia. Again, Japanese and European
trends are the most alike: the INDC projects a progressive reduction of per capita emissions.
EU28 has the lowest per capita emission objective. The INDC for the United States implies
a more aggressive decrease given the current levels of emissions per capita. Population ofJapan is expected to decrease toward 2030. Under the population reduction, the reduction
rate of emission per capita is smaller than that of emission.

33

Figure 22: Emissions per capita (tCO2eq/capita)
According to DNE21+ model, the marginal abatement costs induced by the INDC are
strikingly higher for Japan than for other countries. Japan’s marginal abatements costs are
estimated about 380 $/tCO2eq, while around 166 $/tCO2eq for EU28 and between 60$/tCO2eq (low case) and 69 $/tCO2eq (high case) for the US. The main cause would be thathigh energy savings are expected in the INDC despite good performances in energy
efficiency in Japan. To limit such costs, innovation, whether purely technological or not(related to lifestyle), would be highly needed.
The emission reduction cost per GDP induced by the INDC for Japan is 0.7% in 2030,
and that for EU is 0.77%, and almost same level. The cost for the U.S. is 0.34-0.40% in 2025.
In total, the Japanese INDC is evaluated from several possible appropriate indicators tohave fairness and ambition in the international context.

Contribution towards achieving the 2 C target
The Japan’s INDC describes “The Japan’s INDC is consistent with the long-term emission
pathways up to 2050 to achieve the 2 degrees Celsius goal”. This paragraph discusses theanalyses on the consistency of the 2C target, including both Japanese INDC and other INDC
submitted so far – since achieving the 2C target can only be the result of a collective longterm effort.

34

Consistency achieving the 2C target
Actually, as shown in Figure 23, it turns out that there are large gaps between the expected
global emission under current INDC and the emission pathway to 2C target under climate
sensitivity to a doubling of CO2 estimated at 3.0C, However, the INDC are consistent with2C target if climate sensitivity is 2.5C. Even if we assume to stay within a 2C warming
compared to preindustrial levels, there is great uncertainty regarding the actual outcome due
to climate sensitivity; based on the latest expertise of the IPCC Fifth Assessment Report, theemissions pathways for the “+2C” target present a high flexibility (The climate sensitivity
was changed from 2.0-4.5C in the IPCC AR4 to 1.5-4.5C in the IPCC WG1 AR5.). The
INDC submitted so far, including the Japanese ones, are within the pathway range to meetthe 2C target as long as the expected value is used (under a climate sensitivity of 2.5C).
However, the consistency of 2C target depends strongly on the requirement of the
expectation probability achieving the target and the climate sensitivity knowledge.
The framework of the processes to induce future emission reductions is more important
than the levels of INDC decided in COP21. In a long-term perspective, we should keepenhancing the INDC through the enforcement of PCDA (Plan-Check-Do-Act) cycles anddevelopment of innovative technologies.

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

80

GHG emissions (GtCO2-eq./yr)70Larger emission reductions
should be realized throughpeer-reviews in the PDCA cycle.

60+2℃ with around
50% probability

50AR5
530-580 ppm(+7 -47%)

40

30
Actual emissions20

AR5
480-530 ppm(-25 -57%)

Global emission pathway under current policies and measures
Global emission pathway under current INDCs*

10

Below +2.0 ºC through 2100 under climate sensitivity of 2.5 ºC; temporary overshoot of 580 ppm

The probability
achieving below+2℃ increases.
On the other hand,measures withunrealisticallyhigh costs have tobe adopted.

AR5 430-480 ppm(-41 -72%)

Below +2.0 ºC in 2100 under climate sensitivity of 3.0 ºC; temporary overshoot of 530 ppm
Below +2.0 ºC through 2100 under climate sensitivity of 3.0 ºC; below 500 ppm through 2100

0
1990

2000

2010

2020

2030

2040

2050

* INDCs of US, Canada, EU28, Norway, Switzerland, Japan, Russia, China, Mexico, and South Korea are considered.
For other countries, emission pathways under current policies and measures are adopted.

Figure 23: Relationship between climate sensitivity and global emission pathwaysfor 2C target, and outlook on INDC

35

Equity of emission reduction cost burden between 2030 and 2050
Emission reduction costs in 2030 and 2050 were compared, applying INDC emissions
reduction for 2030 and assuming a cut by half of world total energy-related CO2 emissions
in 2050 compared to 2005 levels as a long-term goal (Marginal abatement costs are assumed
to be equal across countries in 2050.).The expected marginal abatement cost is 431$/tCO2
in 2050 for the long-term goal. At that time, the Japanese emissions are assessed to be about
half of 2005 emissions levels under the equal marginal abatement costs, and the ratio ofemissions reductions costs compared to GDP to be 0.74%. In other words, the economic
burden of Japanese INDC for 2030 is about the same level as the cut by half of emissions
worldwide in 2050.

36

Table 9: GHG emission, marginal abatement costs, ratio of emissions reduction costs
compared to GDP for Japan
2050
2030

(Reduction by half of world total energyrelated CO2 emissions after equalizationof marginal abatement costs)

GHG emissions (compared
to 2005 levels)-25.4%-50%

Marginal abatement cost($/tCO2)

381

431

Ratio of emissions reduction
costs compared to GDP (%)

0.72

0.74

Note 1: In the case of below +2C through 2100 under climate sensitivity of 2.5C, the required
GHG emission for Japan in 2050 is -32% compared to 2005, and the marginal abatement cost is
40$/tCO2; the emissions reduction costs per GDP is 0.22%.
Note 2: In the case of below +2C in 2100 (overshoot of temperature) under climate sensitivity of
3.0C, the required GHG emission for Japan in 2050 is -48% compared to 2005, and the marginal
abatement cost is 360$/tCO2; the emissions reduction costs per GDP is 0.65%.

37

5. Conclusions
The Japanese INDC was submitted to the secretariat of UNFCCC on July 17th, 2015. The
GHG emission target for 2030 is 26% reduction compared to 2013, which corresponds to
25.4% compared to 2005. This target is consistent with the energy mix planned for 2030
given the conditions after the accident at the Tokyo Electric Power Company’s Fukushima
Dai-ichi Nuclear Power Station, and was developed by bottom-up calculation with concrete
policies and measures. The energy mix was developed based on the basic principles known
as the 3E+S, namely: controlling electricity costs, reducing CO2 emissions, ensuring energy
security and stability of supply, while ensuring safety at all levels.
As described in Section 3, in the government’s proposition, despite a high GDP growthrate (1.7%/year) projection, the power generation after GHG reduction measures isanticipated to remain almost unchanged. The GDP elasticity of electricity after the reduction
measures is 0.05 between 2013 and 2030, while the elasticity between 2000 and 2010 was
nearly 1.0 in Japan. A high energy efficiency improvement is assumed in the INDC.
As for GHG emissions reduction targets, the estimated marginal abatement costs (carbon
prices) are about 187 US$/tCO2 and about 260 US$/tCO2 by the NIES and RITE models,
respectively, to achieve the 22% reduction of energy-related CO2 emissions in 2030 (whichcorresponds to the 26% reduction of GHGs according to the government outlook). However,since these ambitious targets are based on high expectations from the energy savings policy(corresponding marginal abatement costs in Japan are exceedingly high compared to othercountries) and on great efforts of restarting of nuclear power with extensions to sixty years
operation for some nuclear power stations, it will not be easy to achieve such ambitious target.
For example, the marginal abatement cost increases by about 26% in 2030 under the nuclear
power limitation scenario according to the NIES model. Further reductions in emissions, fuelswitch from coal to natural gas and an additional deployment of renewable energies are costeffective under such high carbon price measures. The high costs for society could be limited
by breakthrough innovation, whether purely technological or not (related to lifestyle).
More concrete policies and measures are desired to achieve such an ambitious target atthe domestic level, and the further contributions of emission reductions all over the world
including the Joint Crediting Mechanism (JCM) which has been proposed by the Japanese
government are expected. For that, high energy efficiency technologies from Japanese firms
are to be helpful to the world.

38

Acknowledgements (NIES)
NIES analysis is supported by the Environment Research and Technology Development
Fund 2-1402 of the Ministry of Environment Japan.

References (NIES)
Government of Japan, Japan’s Sixth National Communication under the United Nations
Framework Convention on Climate Change,
http://unfccc.int/files/national_reports/annex_i_natcom/submitted_natcom/application/pdf/nc
6_jpn_resubmission.pdf, 2013
Government of Japan, Submission of Japan’s Intended Nationally Determined Contribution(INDC),
http://www4.unfccc.int/submissions/INDC/Published%20Documents/Japan/1/20150717_Ja
pan's%20INDC.pdf, 2015.
Greenhouse Gas Inventory Office of Japan (GIO). National GHGs Inventory Report of JAPAN,
2014
IEA, Energy Technology Perspectives 2015, OECD/IEA, Paris, 2015
IEA, World Energy Outlook 2014, OECD/IEA, Paris, 2014
IIASA, SSP database – Version 1.0, 2015
IPSS. Population Projections for Japan (January 2012) -2011 to 2060-, 2012
Kainuma M., Y. Matsuoka and T. Morita, 2003. Climate policy assessment: Asia-Pacificintegrated modeling. Springer, Tokyo; New York.
Ministry of Economy, Trade and Industry / Agency of Natural Resources and Energy(METI/ANRE),

Long-term

EnergySupplyand

DemandOutlook,

http://www.meti.go.jp/press/2015/07/20150716004/20150716004_2.pdf (in Japanese), 201539

Appendix I: overview of NIES model
AIM/Enduse [Japan]
AIM/Enduse [Japan] model is a partial equilibrium, dynamic recursive technology selection
model for the mid- to long-term mitigation policy assessment (Kainuma et al., 2003). The
model covers both end-use sectors (industrial, residential, commercial and transport) andenergy supply sector. In addition, non-energy sectors (e.g. agriculture, industrial process,waste) are also included.
Technology selection is formulated by linear programming algorithms that minimize the total
system cost subject to several constraints, such as satisfying service demands which are
specified exogenously, maximum/minimum shares of technologies and constraint of GHG
emissions or explicit carbon prices. A detailed formulations and data of the model can befound in Kainuma et al. (2003). As end-use and power generation sectors are mutuallyinterlinked, technology selection in power generation sector is implemented subject toelectricity demand derived from end-use sectors. Technology selection is implemented year
by year time step, over a time horizon from 2010 (base year) to 2050.
The model explicitly distinguishes 10 regions in Japan with their regional differences inrenewable energy potential and energy demand characteristics (Oshiro and Masui, 2015).
These 10 regions are coincide with the business areas of 10 public power supply firms.
A wide range of low carbon technologies are taken into account in AIM/Enduse [Japan].
Shares in electricity, such as coal, natural gas, oil and renewable energies, are endogenously
determined based on cost minimization, though maximum potentials are set for renewableenergies. Electricity generation from nuclear plant is exogenously given based on different
assumptions on their lifetime, capacity factor and possibility of new construction. CCS
technologies are also included in power sector and industrial sector, though they are
assumed to be available after 2030 in NIES analysis.
For end-use sectors, technology selection is also implemented based on cost minimization.
However, considering their pace of replacement, maximum share of introduction of energy
efficient technologies particularly in industrial sector are exogenously fixed complying with
the Long-term Energy Supply and Demand Outlook (METI/ANRE, 2015a). In addition, costsof electricity generation is updated for MILES Project and consistent with the report publishedby Power Generation Cost Verification Working Group under the Subcommittee on Longterm Energy Supply-demand Outlook which was held in 2015 (METI/ANRE, 2015b).

40

Figure 24: Outline of AIM/Enduse[Japan]

References
Kainuma M., Y. Matsuoka and T. Morita, 2003. Climate policy assessment: Asia-Pacificintegrated modeling. Springer, Tokyo; New York.
Oshiro, K. and T. Masui, 2015, Diffusion of low emission vehicles and their impact on CO2emission reduction in Japan, Energy Policy, Vol. 81,pp. 215–225.
Ministry of Economy, Trade and Industry / Agency of Natural Resources and Energy(METI/ANRE),

Long-term

EnergySupplyand

DemandOutlook,

http://www.meti.go.jp/press/2015/07/20150716004/20150716004_2.pdf (in Japanese), 2015
Ministry of Economy, Trade and Industry / Agency of Natural Resources and Energy(METI/ANRE), The report of Power Generation Cost Verification Working Group,
http://www.enecho.meti.go.jp/committee/council/basic_policy_subcommittee/mitoshi/cost_w
g/pdf/cost_wg_01.pdf (in Japanese), 201541

Appendix II: overview of RITE models
DNE21+ model
The DNE21+ model (Akimoto et al. 2010) is an inter-temporal linear programming model forassessing global energy systems and global warming mitigation. In this model, the sum of
the discounted world total energy systems costs is minimized. The model covers the first halfof the 21st century as a time range, with 2000, 2005, 2010, 2015, 2020, 2025 2030, 2040,
and 2050 as representative time points.
The energy supply sectors are connected to the energy end-use sectors, so thatassessments are made while maintaining complete consistency across energy supply anddemand levels. For the energy supply sectors and several groups of the energy end-use
sectors (energy intensive industries, road transportation, and several kinds of appliances inresidential and commercial sector), various technology options are explicitly modeled withassumptions of costs, energy efficiencies, and life times of facilities. Activity amounts of theenergy end-use sectors (e.g., crude steel production in iron and steel sector, passenger or
freight transport service in road transportation) are exogenously assumed as a scenario.
Other sectors in the energy end-use sectors are modeled in a top-down fashion; final energy
demands are exogenously assumed as a scenario by energy carrier. Energy-saving effects
in these sectors are evaluated using long-term price elasticity. The model specifies energy
systems whose costs are minimized and which meet the assumed scenarios and otherrequirements (e.g, carbon taxes).
The world is divided into 54 regions. To take into consideration the transportation of energy
and CO2, large countries such as the United States, Canada, Australia, China, India, andRussia are further disaggregated into several regions. This detailed regional segregation
enables us to perform our analysis while taking regional differences into consideration.
About 300 specific technologies, including carbon dioxide capture and storage (CCS)
technologies and CO2 fixation by afforestation, are explicitly modeled as the technology
options. This enables us to assess CO2 emission reduction measures in detail.
The model has been developed based on the study by Hyman et al. (2003), and with somemodifications considering new insights for non-CO2 GHGs, it is used for assessment of nonCO2 GHGs emissions and reductions. The non-CO2 GHGs assessment model calibrates
the recent historical emissions of non-CO2 GHGs (Akimoto et al. 2010).
In this evaluation on the Japan’s INDC, electricity generation mix is exogenously assumed
to be same with that in Japan’s INDC (Oil: 3%, Coal: 26%, LNG: 27%, Nuclear: 20-22%,
Renewables: 22-24%). However, shares in renewable electricity are endogenously evaluatedthrough cost optimization.

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Figure 25: Outline of energy flows in DNE21+

References
RITE

Systems

Analysisgroup,

www.rite.or.jp/English/lab/syslab/about-global-

warming/download-data/E-RITE_GHGMitigationAssessmentModel_20090529.pdf
K. Akimoto, F. Sano, J. Oda, T. Homma, U.K. Rout, T. Tomoda (2008) “Global Emission
Reductions through a Sectoral Intensity Target Scheme”, Climate Policy, Vol.8, S46-S59.
K. Akimoto, F. Sano, T. Homma, J. Oda, M. Nagashima, M. Kii (2010) “Estimates of GHG
emission reduction potential by country, sector, and cost”, Energy Policy, Vol. 38, Issue 7,(2010) 3384-3393.

DEARS (Dynamic Energy–economic Analysis model with multi-Regions
and multi-Sectors) model
The DEARS (Homma and Akimoto 2013) is an intertemporal optimization model, which
maximizes global discounted consumption utilities up to the middle of this century with 10year time steps and a computable general equilibrium (CGE) model. The model evaluates
the impacts of energy and CO2 emissions reduction policies on economic systems withconsideration of international industrial relationships.
The DEARS model has two modules. One is the economic module, which represents
explicitly industrial structures of production, consumption, and trade by region and by sector
in terms of monetary units, which are required for sectoral analysis on climate policies. The
other is the simpliﬁed energy systems module, which represents explicitly energy ﬂows in43

terms of physical units. The two modules are completely linked. The model includes 18
regions and 18 non-energy sectors. The model has nested model structures in the nonenergy sectors. The macro production functions for the regional whole economies are basedon the Cobb–Douglas function. The summations of GDP and energy inputs in a region areformulated as a Cobb–Douglas function consisting of capital, labor and energy. The threefactors are substituted to each other in the function. On the other hand, each sectoral
production function for the non-energy sector is based on the Leontief function. The
production function for the energy sectors are also based on the Leontief function as primaryenergy is inputted to the relevant secondary energy.
The model also includes twelve energy sources with eight types of primary energy (coal,crude oil, natural gas, biomass, hydro power, wind power, nuclear power, and photovoltaics)
and four types of secondary energy (solid, liquid and gaseous fuels, and electricity). Thesevarious types of electricity generation and carbon dioxide capture and storage (CCS)
technology are modeled. The energy-saving effects are evaluated using long-term priceelasticity. The main economic datasets of DEARS are based on the GTAP database (Hertel,
1997) for economic systems. The input–output tables of the model starting time for 1997 arebased on GTAP version 5 and the input–output tables for 2007 are based on the otherversions. The energy-related datasets are based on IEA energy balances and datasets ofother models (Akimoto et al., 2010) for energy systems. Since the information on the energy
supply and the power generation sector is not sufﬁcient in the input–output table, we conduct
bottom-up modeling taking relevant technologies into account and make adjustments toachieve consistency with IEA statistics and others, which allows consistent analyses andassessments of energy and the economy. Such bottom-up modeling is able to analyze
economic impacts with full consideration of differences in electricity generation shares andtheir costs.

References
K. Akimoto, F. Sano, T. Homma, J. Oda, M. Nagashima, M. Kii (2010). Estimates of GHG
emission reduction potential by country, sector, and cost. Energy Policy 38 (7), 3384–
3393.
T. Homma and K. Akimoto (2013) “Analysis of Japan's energy and environment strategy after
the Fukushima nuclear plant accident,” Energy Policy 62 (2013) 1216–1225
T. Hertel (1997). Global Trade Analysis: Modeling and Applications. Cambridge University
Press, New York.

44

Appendix III: INDC measures
Table 10: Measures for energy-originated CO2 (source: Submission of Japan's INDC)
Energy-originated CO2
Industry
sectorIron and steel industry

Chemical industry

slag crusher, air-beam cooler, separator improvement, vertical roller coal mills)

Cross-sectoral/Other

Commercial
and other
sectors
water heater, high-efficient boiler)

diagnosis

buildings)

heat island effectmeasures, etc.

45

Table 11: Measures for non-energy-originated CO2 (source: Submission of Japan's
INDC)
Non energy-originated CO2
CH4
paddy rice fields)

N2O
originated from fertilizer application)
Fluorinated gases
Management of Fluorocarbons, emission control through industries’ voluntary action plans, etc.)
LULUCF sector
Forest management
Cropland management/Grazing land management
Revegetation

management/forestry industry measures46