The side-event at the Japan pavilion for the COP27−
Industrial Decarbonization, Border Measures and Climate Clubs
November 11, 2022

The Emissions Reduction Efforts and Effects,and the Impacts on Competitiveness andBorder Carbon Adjustment

Keigo Akimoto
Systems Analysis Group
Research Institute of Innovative Technology for the Earth (RITE)

Key issues
2 How to measure the comparable emission reduction efforts, andhow mechanisms will achieve the global emissions reductions
effectively.
 Estimations of CO2 marginal abatement costs for the emissions

reduction targets of NDCs, and the expected economic impacts(Model estimations) The expected effects of BCA for avoiding carbon leakage (Modelestimation)
 How to measure carbon prices for the BCA: explicit carbon prices

vs implicit carbon prices• Explicit carbon prices: is relatively easy to estimate.
• Implicit carbon prices: is not easy to estimate, but the globalemissions reduction effects are determined by the embodied CO2
intensity of products which are induced by the implicit prices
including baseline final energy prices.
 How to measure sectoral energy or CO2 intensity, which has

impacts on emissions more directly rather than carbon prices

The estimated baseline emissions in the IPCC AR5 (2007)
and AR6 (2014) v.s. the actual emissions in 20193AR5 (2007): baseline CO2 emissions

2019 CO2 emissions：45 GtCO2/yr

AR6 (2014): all pathways
including baseline emissions✓ The actual emission in 2019 was nearly theupper range of all of the baseline
emissions estimated by IAMs in the IPCC
AR5 and AR6, while large efforts foremissions reduction have been conducted.
✓ It can be afraid that CO2 intensive
industries had moved from developed
countries to developing countries morethan those that IAMs had estimated.

2019 CO2 emissions：
45 GtCO2/yrComparisons in CO2 marginal abatement costs
for achieving NDCs in 2030 across countries

4Source) ALPS Int’l Symposium (2022)

Estimations by using a bottom-up energy systems model, DNE21+452438Japan
United Kingdom
EU27
United States
Switzerland
CanadaSaudi Arabia
Korea
Thailand
MexicoAustralia
South Africa
Malaysia + Singapore
China
Kazakhstan
RussiaIndia
Pakistan + Afghanistan
TurkeyUkraine412
359341
301
187
179

12062

CO2 marginal
abatement[$/tCOcost [$/tCO
CO2限界削減費用
2eq] 2eq]
060

200

400

600

800

EU276053

Germany
ドイツ

37France
フランス

2619

イタリア
Italy

0

スペイン、
Spain, Portugal
ポルトガル

0000

The least cost (equal marginal
abatement costs)：47$/tCO2
50

100

150

200

Poland,Hungary,
ポーランド、
Czechoslovakia
ハンガリー、チェコ

250

300

350

400

450

500

CO2 marginal abatement cost [$/tCO2eq]
Note) The estimations were not conducted for Brazil and Indonesia that have large potentials in emission reductions in LULUCF, due
to high uncertainties in costs for LULUCF; and for Iran, due to high uncertainties in the definition of BAU emissions of the NDC.

• Large differences in MAC for NDCs among countries, and they have potential risks ofcarbon leakages.

Sectoral Impacts on Production in Japan due to NDCs
50.0%

0%

Production changes(relative to the baseline)

-2%

0.0%

-0.5%

-0.7%

-1.2%
-2.7%

-4%

-2.8%

-3.0%

-3.5%

-3.7%

-4.2%

-6%

26% emissions
reduction with theenergy mix of the
5th strategicenergy plan

-6.6%

-8%

46% emissions
reduction with theenergy mix of the
6th strategicenergy plan

-10%-12%-11.7%-14%-14.0%-16%

GDP

Iron &steel

Chemical Metalic Paper & Machinery Serviceminerals
pulp• For the 46% reduction of the Japan’s NDC, the economic impacts on the CO2
intensive sectors, such as iron & steel and chemical sectors, will be muchhigher than the average impacts, including the impacts of emissions
reduction in international competitiveness and the resulting net export.

Simulation Cases for the impacts of BCA
6Club*Cases

NDC
CTAX0Emission
Club
reductionmembers
targets
Europe,US,JapanNDC targets

Non-Club

BCA**, ***ExportrebateMembers

No BCANo

othercountries(collaborativereductions withinClub)

CTAX0+BCA EITEBCA (EITE)

CTAX0+BCA I&S

BCA (I&S)

CTAX0+BCA EITE+ExpRebate

BCA (EITE)

Emission
reductiontargets
NDC targets
Zero carbon
pricesagainst non-clubagainst non-clubYesagainst non-club

Note:*Emission trading schemes (ETS) is assumed to be available within Club members. (i.e., same carbon prices within the club)**BCA on "all Energy intensive sectors (EITE)" or "Iron & Steel (I&S) alone " are assumed.
***The imposed import tariffs for BCA are estimated using the difference in carbon prices between club and non-clubs.
- Baseline GDP and CO2 emissions are calibrated to those of the current policy scenario of IEA-WEO 2018, in which COVID-19
impacts are not considered.
- “Europe” covers EU and non-EU European countries (UK, Norway, Switzerland, and Iceland).
- EITE={Iron & Steel, Chemical, Non- ferrous metals, Non-metallic minerals, Paper & pulp}.

Source) T. Homma et al., (2021)

Effects of the BCA on international competitiveness(Iron & Steel sector in 2030)
Estimations by using a CGE type, DEARS model

Changes in Net Import(%, from baseline)

3.5%

Source) T. Homma et al., (2021)

Effects of looser emission reduction efforts(carbon prices: 0 $/tCO2) in non-club regions

CTAX0

3.0%
2.5%

7NDC

Effects of BCA

2.0%

Ambitious NDCs of Club

CTAX0+BCA EITE

1.5%
1.0%
0.5%
0.0%
-7.0%

-6.0%

-5.0%

-4.0%

-3.0%

-2.0%

-1.0%

0.0%

Changes in production (%, from baseline)
Note: Changes % are normalizedusing baseline production.

• The international competitiveness of Club (Europe, US, and Japan) in iron andsteel sector (and EITE) will decrease (the productions decrease and net
imports increase) under ambitious NDCs of the Club.
• BCA will be able to mitigate a part of carbon leakage, but will be limited.

Effects of the BCA plus Export Rebate on international
competitiveness (Iron & Steel sector in 2030)

8

Estimations by using a CGE type, DEARS model

Changes in Net Import(%, from baseline)

3.5%

CTAX0

3.0%

NDC

2.5% Effects of BCA
2.0%
1.5%

Effects ofExport Rebate

CTAX0+BCA EITE

CTAX0+ BCA EITE
+ ExRebate EITE

1.0%
0.5%
0.0%
-7.0%

-6.0%

-5.0%

-4.0%

-3.0%

-2.0%

-1.0%

0.0%

Changes in production (%, from baseline)
Note: Changes % are normalized using baseline production.

• Adding export rebates can also alleviate losses of productions and exports. The
effects of export rebates in Iron & Steel sector have possibly much higher thanBCA limited to imports.
• But export rebates possibly have inconsistency with the WTO rule.

Energy intensity of iron and steel productions
through BF/BOF routeSource) RITE, J. Oda (2022)

35

2005

20102015

2019

30

Primary energy intensity(GJ/t-crude steel)

925

20

15

10

• It is very challenging to define and measure implicit carbon prices.
• Another method to measure the corresponding to the implicit carbon prices
is to measure energy and CO2 intensity embodying in products, which canbe considered to be outcomes from implicit carbon prices, and also will bedirectly the most important for the global emissions.

Energy intensity of steel sector (BOF+EAF)
10Year of 2015

Primary energy intensity (GJ/t crude steel)30

UkraineRussia

25

China
UK

WorldFrance
India

20Japan

Korea

U.S.

Mexico15Germany

TurkeySpain, Portugal

Italy

10500%

25%

50%

75%100%

EAF ratio (%)- Energy intensity by country depends on EAF ratio rather than the energy(in)efficient conditions.
- On the other hand, the availabilities of scrap steel vary widely across countries.

Conclusions
11

 The Government of Japan revised the 2030 emissions reduction target to



46% reductions compared to the 2013 level. Many developed countriesalso revised their emissions reduction target to be more ambitious ones.
The assessments for the emissions reduction efforts of NDCs areimportant under a “pledge-and-review” process of the Paris Agreement.
In addition, the assessments of the expected economic impacts of theNDCs including the expected carbon leakages are important in order toobtain the global emissions reduction effects.
Large differences in MAC (carbon prices) for NDCs among countries are
estimated, and they have potential risks of carbon leakages.
Use of a BCA can mitigate leakage from the EITE sectors by a third(reducing leakage from 3% to 2%), if the export rebates are notintroduced.
Globally coordinated among emission reduction efforts should bepursued.
But the global benchmarking for the resulting CO2 intensity of
production processes of each sector or products, which will be achievedby retail prices of final energy etc. including additional efforts of carbon
prices, will be more important.

Appendix

Energy-related Technology Assessment Model: DNE21+(Dynamic New Earth 21+)13



Systemic cost evaluation on energy and CO2 reduction technologies is possible.

Linear programming model (minimizing world energy system cost; with 10mil. variables and10mil. constrained conditions)

Evaluation time period: 2000-2100
Representative time points: 2005, 2010, 2015, 2020, 2025, 2030, 2040, 2050, 2070 and 2100

World divided into 54 regions
Large area countries, e.g., US and China, are further disaggregated, totaling 77 world regions.

Interregional trade: coal, crude oil/oil products, natural gas/syn. methane, electricity, ethanol,hydrogen, ammonia, CO2



Bottom-up modeling for technologies on energy supply side (e.g., power sector) and CCUS

For energy demand side, bottom-up modeling conducted for the industry sector including steel,cement, paper, chemicals and aluminum, the transport sector, and a part of the residential &commercial sector, considering CGS for other industry and residential & commercial sectors.

Bottom-up modeling for international marine bunker and aviation.

Around 500 specific technologies are modeled, with lifetime of equipment considered.

Top-down modeling for others (energy saving effect is estimated using long-term price elasticity.)••

Regional and sectoral technological information provided in detail enough to analyze consistently.
Analyses on non-CO2 GHG possible with another model RITE has developed based on US EPA’s assumptions.
•Model based analyses and evaluation provide recommendation for major governmental policy making on
climate change, e.g., cap-and-trade system and Environmental Energy Technology Innovation Plan, andalso contribute to IPCC scenario analysis.

Energy-economic Model: DEARS

14

An energy-economic model, DEARS (Dynamic Energy-economic Analysis model with multi-Regions
and multi-Sectors)*
 Integration model of a top-down-typed economic module (of computational general equilibrium
approach based on international input-output tables) and bottom-up-typed energy systems module Intertemporal non-linear optimization model (Maximization of global consumption utility)
 Evaluation time period: up to the middle of this century (10 years steps)
 World divided into 18 regions (US, EU, Japan, China, India,...)
 Non-energy sectors: 16 sectors
 Energy: 8 types of primary energy and 4 types of secondary energy Economic module that represents international economic structures based on input-output
tables of GTAP (Global Trade Analysis Project) database. The baseline GDP by region/country
are calibrated to those of the IEA-WEO2018.
 Simplified energy systems module✓ Bottom-up modeling for technologies in energy supply (e.g. , power generation) and CCS (carboncapture and storage)✓ Primary energy (8 types): coal, crude oil, natural gas, hydro & geothermal, wind, PV, biomass andnuclear✓ Top-down modeling for energy demand (residential sector: price and income elasticities ofdemand for energy and income, industrial and transport sectors: price elasticity, linked to theeconomic module)✓ Final energy (4 types): solid, liquid and gaseous fuels and electricity* T. Homma & K. Akimoto,” Analysis of Japan's energy and environment strategy after the Fukushima nuclear plant accident “, Energy Policy 62 (2013)
1216–1225

Employed indicators for measuring emissions
reduction efforts (1/2)
Emissions reduction
efforts evaluation method

Framework

Notes

Emissions
reduction ratio
from base year(only for OECDcountries orAnnex I countries)

When baseline emissions are expected
to stagnate, it is more relevant to simply
compare the projected reduction rates(all the more since there areuncertainties regarding the BAU). This
is why we use the reduction ratio
compared to BAU for OECD countries
only - on the other hand, such an
approach would be irrelevant for
countries where emissions are
expected to grow substantially.

Most countries use 2005 as theirbase year (as a matter of fact, 1990
seems too far in the past to be used
as a base year to evaluate theemissions reduction effort forupcoming emissions)Compared to2005Compared to2012 (or 2010)

15

This seems a relatively good choice
to evaluate future efforts as it allows
assessing reduction ratios incomparison with recentcircumstances.

Emissions per
capita (only fornon-OECDcountries or nonAnnex I countries)

Absolute value

For OECD countries, we adopt thereduction ratio from base year insteadof the absolute value of emissions per
capita.

As it is highly dependent on thecountry’s level of economic activity
and situation in general, it can bedifficult to assess emissions reduction
efforts through this indicator.

CO2 intensity(GHG emissions
per GDP)

Absolute value

Reveals what level of CO2 emissions
corresponds to what degree of
economic activity

It can easily reach bad values forcountries with a low GDP; it is also
highly dependent on the country’s
industry structure.

Improvement
rate(compared to2012 or 2010)

As it removes the bias due to the factthat economic growth has changed
compared to the base year, it reveals
the real effort in emission reduction.

For countries with a low GDP, carbon
intensity can improve greatly just due
to high economic growth.

Employed indicators for measuring emissions
reduction efforts (2/2)

16

Emissions reduction efforts
evaluation method

Framework

Notes

Emissions
reduction ratio
compared to BAU

It allows taking into account thedifference of economic growths, etc.

It puts aside past efforts inenergy savings and abatement
potential of renewables.

CO2 marginal
abatement cost(carbon price)

This is a particularly relevant
indicator to assess reduction efforts
as it contains countries’ differences interms of economic growth, energy
savings efforts, abatement potentialof renewables.

Past measures such as taxes onenergy are out of the scope(however, one must keep in mind
that, as energy savings efforts
have already been made in thepast, this may lead to higher
estimates of marginal abatement
costs.)

While marginal abatement costs
show the additional effort to be made,this indicator also includes the efforts
made in the baseline.

Market data is available for expost evaluation, but for ex-anteevaluation, only model-based
estimates are available whichmakes uncertainties rather high.

As marginal abatement costs do nottake into account the economy’s
ability to bear such an effort, thisindicator does.

Uncertainties are high as this is amodel-based estimation.

Retail prices ofenergy(electricity, citygas, gasoline,diesel)
Emission
reduction costs
per GDP

Weighted
average ofhistorical datafrom 2012 or2010

Comparison in GHG emission per capita (2015, 2030)
172015 historical values
Pakistan
India
Indonesia
Switzerland
MexicoBrazillThailandUkraineUnited Kingdom
EU27
ChinaJapan
RussiaMalaysia
South Africa
Korea
United States
Kazakhstan
CanadaAustralia
Saudi Arabia

This indicator is highly dependent
on the country’s level of economic
activity and situation in general.

NDCs for 2030
BrazilSwitzerland
United KingdomIndia
EU27
MexicoPakistanJapan
ThailandSouth Africa
Indonesia
Ukraine
Korea
United States
Saudi Arabia
Malaysia
CanadaChina
RussiaAustralia
Kazakhstan

2.9
2.9
3.7
4.1
4.8
5.6
5.6
6.1
6.2
6.7
7.1
7.6

2.2
2.5
3.7
5.5
5.9
5.9
6.0
7.0
7.9
8.0
9.5
10.0
10.1
10.4
10.4
13.8
18.4
19.2
20.2
22.3
22.3
0

5

1015

2025

GHG emission per capita (tCO2eq./capita)

8.7
9.1
9.7
10.5
10.6
10.7

Yellow: GHG emission per capita decreased from 2015;
Gray: GHG emission per capita increased from 2015

16.1
16.4
17.005

10

GHG emission per capita (tCO2eq./capita)

1520* Average values are shown for countries having upper/lower targets.

Comparison in GHG emission per GDP (MER) in 2030
18

GHG emission per GDP (MER) change ratio
2019-2030 (or 2015-2030)

GHG emission per GDP (MER)
Switzerland
United Kingdom
EU27
United StatesJapan
CanadaKorea
Australia
BrazilSaudi Arabia
MexicoThailandChina
Malaysia
South Africa
Kazakhstan
RussiaIndia
Indonesia
UkrainePakistan

0.03
0.07
0.13
0.13
0.13
0.21
0.21
0.26
0.27
0.45
0.50
0.64
0.67
0.71
0.77

United States
Saudi Arabia
CanadaUnited Kingdom
Switzerland
BrazilJapan
South Africa
EU27
Korea
China
Australia
Kazakhstan
Thailand
Malaysia
MexicoIndia
UkraineRussiaIndonesia
Pakistan

-7.3
-7.1
-6.7
-6.2
-6.2
-6.2
-5.9
-5.6-5.4
-5.3
-3.8
-3.4
-3.3
-3.1-2.6-1.6-1.2
-1.0
1.1
1.5
5.3
64

20-2-4-6

CO2 intensity (GHG emission per GDP) (%/yr)

1.20
1.24
1.30
1.38

This indicator is determined by thecountry’s industrial structure etc.
2.93
3.35

012GHG emission per GDP (kgCO2eq./$2015)34* Average values are shown for countries having upper/lower targets.

-8

Comparisons in emission reduction costs per GDPin 2030 across countries

19Emission reduction costs per GDP [%]108

Net costs of reduced imports and exports of fossil fuels, oil products and gas products
Other costs including those through changes in fossil fuel priceNet costs

6420-2-4-6-8✓ In developed countries, while the MACs are high, the emission reduction costs per GDP are around0.5-1.5% since their GDP values are high.
✓ In oil/gas export countries, the net emission reduction costs are expected to increase (due to salesdecrease) as fossil fuels export will decrease along with emission reduction by NDCs. Japan’s net costof imports and exports of fossil fuels will increase driven by the transition from coal to gas, etc.
✓ Also, the oil/gas export will be shifted from higher MAC countries to lower MAC countries.

International comparison ofretail prices of energy (electricity)

20

Estimations by using a bottom-up energy systems model, DNE21+Japan
United KingdomEU27
Switzerland
Australia
United States
South Africa
Thailand
MexicoKorea
India
CanadaChina
Saudi Arabia
UkraineRussiaPakistan, Afghanistan
Malaysia, Singapore
TurkeyKazakhstan

35.7
35.6
34.7
32.7
25.4
23.8
23.3

21.4
18.1
17.5
14.1
14.0
12.3
11.9
10.2

7.0
6.3
5.5
3.9
1.8
05

1015

20

25

30

3540

Electricity prices for households [UScent/kWh]• Final energy prices including retail prices of electricity will induce low energy
consumptions for products and services directly, while carbon prices and emissions
reduction costs will induce tha additional effects.

Carbon Prices of NDCs in 2030
21This and the following estimations are conducted by using an energy-economic model,DEARS.
2030 NDCs

CO2 marginal abatement cost(carbon prices) [$/tCO2]

350

Club2 (217 $/tCO2)

300
250

Club1

EU

-55% relative to 1990

UK

-68% relative to 1990

US-50 to -52% relative to 2005

Japan

-46% relative to 2013 (challenging to -50%)Canada-40 to -45% relative to 2005

Australia -26 to -28% relative to 2005

200

China

-65% of CO2 intensity relative to 2005

India-33 to -35% of CO2 intensity relative to 2005
The analysis assumes the lowest targets of emission reductions.

150
100

500Europe

USJapanCanadaANZ

China

India

Estimated carbon prices to achieve the NDCs differ greatly among countries.