Presented by T. Hanaoka during the 2nd Regional Consultation Meetin on the Economics of Climate Change and Low Carbon Growth Strategies in Northeast Asia, held on 11-12 October 2010 in Ulaanbaatar, Mongolia, hosted by the Asian Development Bank
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Assessment of Regional Marginal Assessment of Regional Marginal Abatement Cost Curves in 2020 Abatement Cost Curves in 2020 - comparison of Japan, China and Korea comparison of Japan, China and Korea - 2 nd Regional Consultation Meeting on Economics of Climate Change and Low Carbon Growth Strategies in Northeast Asia Ulaanbaatar, Mongolia 11-12 October 2010 Tatsuya Hanaoka Center for Global Environmental Research (CGER), National Institute for Environmental Studies(NIES), Japan
Transcript
Assessment of Regional Marginal Assessment of Regional Marginal Abatement Cost Curves in 2020Abatement Cost Curves in 2020
-- comparison of Japan, China and Korea comparison of Japan, China and Korea --
2nd Regional Consultation Meeting on Economics of Climate Change and Low Carbon Growth Strategies in Northeast Asia
Ulaanbaatar, Mongolia11-12 October 2010
Tatsuya HanaokaCenter for Global Environmental Research (CGER),National Institute for Environmental Studies(NIES),
Japan
Global Global scalescale
National National scalescaleTopTop--down approachdown approach
BottomBottom--upup approachapproach
Hybrid approachHybrid approach
AIM family for mitigation analysisAIM family for mitigation analysis
Output
Global emission paths to climate stabilization
AIM/Impact[Policy]
AIM/CGE[Global]
Mitigation potentials and costs curves
AIM/Enduse[Global]
model
AIM/CGE[Country]
Mitigation potentials and costs curves
AIM/Enduse[Country]AIM/Energy Snapshot
AIM/Extended Snapshot
Macro-economic driving forces
Macro-economic driving forces
Industrial production,transportation volume, etc
Element / transition(service demand)
Industrial production,transportation volume, etc
Element / transition(service demand)
AIM/Backcast
AIM/Material
Bottom-up models
Costs: definitions and determinantsCosts: definitions and determinants
1) The direct engineering and financial costs of specific technical measuresCost of switching from coal to gas in electric production, of improving energy efficiency of appliances, of planting trees in reforestation program. Technical costs can show negative net costs because a given technology may yield enough energy cost saving to more than offset the costs of adopting and using the technology. These costs depend on both technical-economic data and a given interest rate.
2) Economic costs for a given sectorCost by “partial equilibrium” analysis in sectroral models that do not capture the feedback effects between the behaviour of a sector and that of the overall economy.
3) Macroeconomic costsThe impact of a given strategy on the level of the GDP and its components (household consumption, investment,etc). This aggregated index measures the monetary value added of goods and services and provides an index of the scale of human activities including the feedback effects between the behaviour and economy.
4) Welfare costs
See in detail: IPCC Second Assessment Report, WGIII, Chapter 8, pp269-270
Bottom-up models
CGE modelsCGE models
MAC Curve by bottomMAC Curve by bottom--up modelsup models-- Implication, caution & limitation Implication, caution & limitation --
Implication:1) Technological mitigation potentials and technological implementation costs2) MAC curves can compare mitigation efforts across countries, because MAC considers
various factors such as the current level of energy efficiencies, difference of socio-economic characteristics by country, scope of renewable energies, etc.
Caution: MAC is a complicated index1) MAC curves differ widely depending on assumptions of technology data such as
technology costs, energy prices, payback periods, diffusion ratio of technology, etc.2) MAC curves differ widely depending on socio-economic assumptions and baseline
emissions.
Limitation:1) Difficult to discuss economic impacts (e.g. GDP loss) by using a bottom-up model.
Aba
tem
ent c
ost
($/tC
O2
eq)
0Cumulative GHG reductions (tCO2 eq)
MAC by energy-engineering models with bottom-up data
Key factors for MAC curvesKey factors for MAC curves
Data assumptions1) Population2) GDP and service demands 3) Energy price4) Discount rate5) Payback period6) Composition of power sources7) Baseline scenario
Definition1) Definition of “potential” 2) Definition of “cost”3) Definition of “drivers”4) Definition of any specific terms…
Detail information (which reflects key uncertainties)
1) The rate of technology development and diffusion
2) The cost of future technology 3) Climate and non-climate policy
drivers…. and so on
It is not enough just comparing shape of MAC curves by different models. It is important to conduct decomposition analysis to clarify reasons of differences of mitigation potentials and costs.
Population
GDPSector-wise value added
Socio-economic macro frame model
Steel production and trade model
Cement production model
Transportation demand model
energy service demand model
Agricultural trade model
Waste generation
model
Crude steelproduction
Cement production
Value added of secondary
industry
Transportation volume
Energy service demand
(residential)
Agricultural production
Waste generation
Technology bottom-up model
（power generation sector）
GHG emission
Emission of fluorocarbon
Primary energyproduction
Model
Endogenousvariable
Technology database
Energy database
Technology bottom-up model
（energy mining sector）
Iron and steel sector Cement sector Other industries
sectorTransportation
sectorResidential
sector
Energy service demand
(commercial)
Commercialsector
Agriculturesector
Waste management
sector
Fluorocarbon emission sector
Database
Technology bottom-up model
Macroeconomic model
Service demand model
Technology bottom-up model
Electricity demand
Energy price
Emission factor
Initial cost Efficiency
lifetime Maximum diffusion rate
Exogenousvariable
Fluorocarbonemission model
Overview of AIM/Overview of AIM/EnduseEnduse[Global][Global]
Target gas and sectors Target gas and sectors considering mitigation optionsconsidering mitigation options
GHG Sector Services
CO2CH4N2O
Power generation Coal power plant, Oil power plant, Gas power plant, Renewable (Wind, Biomass, PV)
Industry Iron and steel，Cement Other industries （Boiler, motor etc）
Transportation Passenger vehicle, Truck，Bus，Ship, Aircraft，Passenger train，Freight train (except for pipeline transport and international transport)
Residential and & Commercial
Cooling, Heating, Hot-water，Cooking，Lighting，Refrigerator, TV
Note) Nuclear power, hydro power, and geothermal power generation are considered in the analysis
but included in the baseline because they are not considered as mitigation options in this study. There are some mitigation options which are not able to be considered in this study due to the
lack of data availability, for example, CO2 mitigation options in petrochemical, N2O mitigation options in waste water, CO2 mitigation options in agriculture etc.
Sector Category Technology options
Energy supply
Coal power plant
Efficient coal power plant(Super critical, Ultra super critical), IGCC (Integrated Gasification Combined Cycle), IGFC (Integrated Gasification Fuel-cell Combined Cycle), PFBC (Pressurized Fluidized Bed Combustion),
Gas power plant
Efficient gas power plant(Combined Cycle, Advanced Combined Cycle), LNGFC (LNG Fuel-cell Combined Cycle)
Renewables Wind power, Photovoltaics, Biomass power plant
Industry
Steel
Coke oven (Coke gas recovery, Automatic combustion, Coal wet adjustment , Coke dry type quenching, COG latent heat recovery, Next generation coke oven), Sinter furnace (Automatic igniter, Cooler waste heat recovery, Mainly waste heat recovery, Efficient igniter), Blast furnace (Large size blast furnace, Blast furnace gas recovery, Wet top pressure recovery turbine, Dry top pressure recovery turbine, Heat recovery of hot blast stove, Coal injection, Dry top pressure gas recovery), Basic oxygen furnace (LDG recovery, LDG latent heat recovery), Casting & rolling (Continuous caster, Hot charge rolling, Hot direct rolling, Efficient heating furnace, Heat furnace with regenerative burner, Continuous annealing lines), Electric furnace (DC electric furnace, Scrap pre-heat)
Boiler (Efficient boiler [coal, oil, gas], Boiler with combustion control [coal, oil, gas], Cogeneration [coal, oil, gas], Regenerative gas boiler), Process heat (Efficient industrial furnace [oil, gas]), Motors (Motor with Inverter control, Efficient motor)
This study is based on realistic and currently existing technologies, and future innovative technologies which are under development are not taken into account.
Example of technology optionsExample of technology options
Abatement Cost Curves Abatement Cost Curves -- magnitude of technology implementation magnitude of technology implementation --
Marginal abatement cost curves show the lines connecting the plot of a certain carbon price
(i.e. marginal cost)
Mitigation potentials compared to baseline
Marginal cost
Marginal cost
Marginal cost
Marginal cost
Marginal cost
Marginal cost
Marginal cost
Marginal cost
Marginal cost
Logic of technology selectionLogic of technology selection
ReplacementReplacement
New demandsNew demands
X X+1
RecruitmentRecruitmentin in year X+1year X+1
Service demand
Year
(1) Recruitment of technology to satisfy new demand and demand of replacement
ExistingExisting
• Total cost = investment cost + O&M cost + energy cost + carbon tax + subsidies
Thus ,it is important to pay attention to the following setting:How to annualize the initial cost ? how to set discount rate for investment (hurdle rate) ?
how to set payback period ?
Initial cost Annual cost→ annualized costs are compared under technology selection framework
Annualizedinitial cost O&M and energy cost
Technology A < Technology B
Conventional Technology A
High-efficient Technology B
Technology A > Technology B
Annualizedinitial cost O&M and energy cost Carbon tax
Conventional Technology A
High-efficient Technology B
How to annualize initial costHow to annualize initial cost
Initial costC
Annualized initial cost
Technology lifetime T
・・・
C Ca Ca Ca= + + + ・・・CCaT
11 1
T
TCa C
α: Discount rate for investment
C 21
Ca 1 T
Ca
= + + +・・・
Ca Ca Ca Ca
+Ca
31Ca
+
Capital recoveryfactor
Payback period is set as a technology lifetime
Inverse value becomes payback period
1Ca
Scenarios :Discount rate for investment Scenarios :Discount rate for investment (hurdle rate, or internal rate of return)(hurdle rate, or internal rate of return)
Scenario Sector Discount rate(hurdle rate)
Example of assumed payback period（Numbers in bracket show technology lifetime）
LDR All sectors 5％
Residential equipments：7-10 year (10-15 year）Car, Truck, Bus：6-9 year (8-12 year）Large plant：14-15 year (30 year）Train, Ship, Aircraft：12-13 year (20 year）Insulation housing：15-16 year（30 year）
MDREnergy related sectors 10％
Residential equipments：6-8 year (10-15 year）Car, Truck, Bus：5-7 year (8-12 year）Boiler：9-10 year （30 year）※ other things are same as the setting in HDR
Non-energy sectors 5％ ※ same as the setting in HDR
HDR
Residential and commercialTransport（automobile）Industry （cross-cuttings）
33％Residential equipments：3 year (10-15 year）Car, Truck, Bus：3 year (8-12 year）Boiler：3 year （30 year）
Power plantIndustry plant（steel, cement）Transport（train, ship, aircraft）Insulation housing
10％Large plant：9-10 year (30 year）Train, Ship, Aircraft：8-9 year (20 year）Insulation housing： 9-10 year （30 year）
5％Agriculture： 1-11 year (1-15 year）MSW：10-16 year (15-30 year）Fluorocarbons ： 1-13 year (1-20 year）
Abatement Cost Curves: JapanAbatement Cost Curves: Japan-- under different discount rate for investment under different discount rate for investment --
-50
-25
0
25
50
75
100
0 50 100 150 200 250 300 350 400 450
Aba
tem
ent c
osts
(US$
/tCO
2eq)
Reduction quantity (tCO2eq)
JPN(HDR) JPN(MDR) JPN(LDR)
Settings of discount rate have a large impact on mitigation potentials
because of high energy prices in Japan
Large impact on the demand side.
Abatement cost curves at a carbon price of 100 US$/tCO2-eq
Abatement Cost Curves: ChinaAbatement Cost Curves: China-- under different discount rate for investment under different discount rate for investment --
-50
-25
0
25
50
75
100
0 1,000 2,000 3,000 4,000 5,000 6,000
Aba
tem
ent c
osts
(US$
/tCO
2eq)
Reduction quantity (tCO2eq)
CHN(HDR) CHN(MDR) CHN(LDR)
Settings of discount rate have a relatively less impact
on mitigation potentials because of low energy
prices in China
Abatement cost curves at a carbon price of 100 US$/tCO2-eq
Abatement Cost Curves: KoreaAbatement Cost Curves: Korea-- under different discount rate for investment under different discount rate for investment --
-50
-25
0
25
50
75
100
0 20 40 60 80 100 120 140 160 180 200
Aba
tem
ent c
osts
(US$
/tCO
2eq)
Reduction quantity (tCO2eq)
KOR(HDR) KOR(MDR) KOR(LDR)
Settings of discount rate have a certain impact on
mitigation potentials because of energy prices in between Japan and China
Abatement cost curves at a carbon price of 100 US$/tCO2-eq
Logic of technology selectionLogic of technology selection
X X+1
Service demand
Year
it is important to pay attention to a case if substitution of existing technology is allowed.e.g. ) if a new gas power plant is more cost effective than a existing coal or oil power plant,
the coal or oil power plant is immediately stopped and replaced with a gas power plant.
Annualizedinitial cost
O&M and energy cost
Technology A < Technology B
ExistingConventional Technology A
High-efficient Technology B
ExistingExisting SubstitutionSubstitutionin year X+1in year X+1
→ annualized costs are compared under technology selection framework
Additional investment cost ≦ energy savings ×（energy price ＋ emission factor × carbon price ）× payback period
Under the logic of technology selection, energy efficient technology options are selected if energy saving cost benefits exceeds additional investment costs.
Scenarios: energy price & energy shiftScenarios: energy price & energy shift
Based on HDR scenarios, following two additional scenarios are assessed.
1. HDR scenario: high discount rate scenario at international energy prices based on IEA forecast, under cost optimization without considering energy security restrictions (i.e. substitution of existing coal and oil power plants are allowed.)
2．HDR-EP2 scenario： supposing a double energy prices in each country due to rising the international energy prices more rapidly than the IEA’s forecast.
3．HDR-ws scenario：considering composition of power sources with energy security, and social barriers restrict to a certain extent of any drastic energy shift from coal and oil power plants to efficient gas powers or renewables. (i.e. substitution of existing coal and oil power plants are not allowed.)
Abatement Cost Curves: JapanAbatement Cost Curves: Japan-- under different scenarios under different scenarios --
-50
0
50
100
150
200
0 50 100 150 200 250 300 350 400 450
Aba
tem
ent c
osts
(US$
/tCO
2eq)
Reduction quantity (tCO2eq)
JPN(HDR) JPN(HDR-ws) JPN(HDR-EP2)
Large impact on the demand side at low
carbon priceif energy prices are double.
This is because of high energy prices in Japan.
Large impact on the supply side at high carbon price
if composition of power sources are restricted with
considering energy security.
Stop an existing coal power plant and build a new efficient gas power plant
Abatement Cost Curves: ChinaAbatement Cost Curves: China-- under different scenarios under different scenarios --
-50
0
50
100
150
200
0 1,000 2,000 3,000 4,000 5,000 6,000 7,000
Aba
tem
ent c
osts
(US$
/tCO
2eq)
Reduction quantity (tCO2eq)
CHN(HDR) CHN(HDR-ws) CHN(HDR-EP2)
Relatively less impact on the demand side even though energy prices are double. This is because
of low energy prices in China.
Large impact on the supply side at high carbon priceif composition of power
sources are restricted with considering energy security.
Stop an existing coal power plant and build a new efficient gas power plant
Abatement Cost Curves: KoreaAbatement Cost Curves: Korea-- under different scenarios under different scenarios --
-50
0
50
100
150
200
0 50 100 150 200 250
Aba
tem
ent c
osts
(US$
/tCO
2eq)
Reduction quantity (tCO2eq)
KOR(HDR) KOR(HDR-ws) KOR(HDR-EP2)
A certain impact on the demand side at
low carbon priceif energy prices are
double. Large impact on the supply side at high carbon priceif composition of power
sources are restricted with considering energy security.
Stop an existing coal power plant and build a new efficient gas power plant
Marginal Abatement Cost curves Marginal Abatement Cost curves compared to 1990 emissions level compared to 1990 emissions level
Baseline emissions based on baseline scenarios such as GDP growth rate, increase of service demands will affect a lot on the results when comparing to 1990 emissions level
GHG emissions in 2020GHG emissions in 2020compared to 1990 emissions level compared to 1990 emissions level
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
Fixed 0$ 200$
1990 1995 2000 2005 2020
GH
G e
mis
sion
s (M
tCO
2 eq
)
JPN_HDR
CHN_HDR
KOR_HDR
0
200
400
600
800
1,000
1,200
1,400
1,600
Fixed 0$ 200$
1990 1995 2000 2005 2020
GH
G e
mis
sion
s (M
tCO
2 eq
)
JPN_HDR
KOR_HDR
-50%
0%
50%
100%
150%
200%
250%
300%
Fixed 0$ 200$
1990 1995 2000 2005 2020
Redu
ctio
n ra
tio
(com
pare
d to
199
0 le
vel)
JPN_HDR
CHN_HDR
KOR_HDR
Key factors for MAC curvesKey factors for MAC curves
Data assumptions1) Population2) GDP and service demands 3) Energy price4) Discount rate5) Payback period6) Composition of power sources7) Baseline scenario
Definition1) Definition of “potential” 2) Definition of “cost”3) Definition of “drivers”4) Definition of any specific terms…
Detail information (which reflects key uncertainties)
1) The rate of technology development and diffusion
2) The cost of future technology 3) Climate and non-climate policy
drivers…. and so on
It is not enough just comparing shape of MAC curves by different models. It is important to conduct decomposition analysis to clarify reasons of differences of mitigation potentials and costs.
For a bottom-up analysis, mitigation potentials and their costs vary depending on the baseline settings
as well as key data settings, such as technology data and future energy prices.
For finalizing results, these key factors should be carefully assessed.
SocioSocio--economic settings (POP and GDP)economic settings (POP and GDP)
・Population (POP)： the prospects at medium variant by UN World Population Prospects ・GDP：GDP by region are estimated by the Socio-economic Macro Frame model．
Japan USA EU25 Russia China India Developed Developing Global
POP -0.2% 0.9% 0.1% -0.6% 0.5% 1.3% 0.3% 1.2% 1.1%
Service demands are estimated by Steel production and trade model, Cement production model, Socio-economic macro frame model, Passenger transportation demand model, Freight transportation demand model, Agricultural trade model and so on. Data settings of GDP and population are the same across all sectors.
service demands in each service and sector are estimated by these models based on various kinds of international and national statistics
Service Demand SettingsService Demand Settings
＜Example of service demands in 2020 by major region＞Japan USA EU25 Russia
Example of composition of power sourcesExample of composition of power sources
CaseA
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
2005
Base
line
≤ 0
≤ 2
0
≤ 5
0
≤ 1
00
≤ 2
00
Elec
tric
ity o
utpu
t (TW
h)
PV
WIN
BMS
GEO/HYD
NUC
GAS
OIL
COL
Japan USA EU25
A drastic energy shift from coal and oil to gas is allowed if it is cost effective.
Social barriers restrict any drastic energy shift considering realistic state.
CaseB
CaveatsCaveatsThe following points must be kept in mind while interpreting the results of this study:
This study is based on realistic and currently existing technologies, and future innovative technologies expected in 2020 are not taken into account. Therefore, it may be possible to reduce more if innovative technologies become available in the future.
The baseline emissions in 2020 are estimated under the technology-frozen case which does not take into account changes in the industrial structure. Moreover, future service demands are exogenous parameters, thus changes in the industrial structure and service demands due to the effects of mitigation measures are not taken into account. Thus baseline emissions and reduction potentials may be overestimated.
