AIM activities for emissions of Long Lived GHGs and Short Lived Climate Pollutants by ... ·...
Transcript of AIM activities for emissions of Long Lived GHGs and Short Lived Climate Pollutants by ... ·...
AIM activities for assessing emissions of Long‐Lived GHGs
and Short‐Lived Climate Pollutantsby AIM/Enduse[Global] model
Tatsuya Hanaoka (on behalf of AIM team members)
Center for Social and Environmental SystemsNational Institute for Environmental Studies
TF‐HTAP/TFIAMWorkshop on Global Emissions Scenarios to 2050IIASA, Laxenburg, Austria
11‐13 February 2015
Topics
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1. Overview of AIM activities for assessing emissions of Short‐lived climate pollutants (SLCPs) and Long‐Lived GHGs (LLGHG)
2. Overview of AIM/Enduse[Global] and its scenarios
3. Comparison between GAINS & AIM/Enduse
4. Example results by AIM/Enduse – what we can analyze & what we cannot analyze
AIM models for mitigation analysis‐ role of the AIM/Enduse model ‐
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Global scale
National scaleTop-down approach
Bottom-up approach
Hybrid approach
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
MOEJ‐S12: Promotion of climate policies by assessing environmental impacts of SLCP and seeking LLGHG emissions pathways (FY2014‐FY2018)
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Goal: To develop an integrated evaluation system for LLGHG and SLCP mitigation policy, by interconnecting emission inventory, integrated assessment models, and climate models.
Theme 1: Air quality change event analysis・Analysis on regional AQ change・Development of emission inventory ・Inversion algorithms of emission estimation
Theme 2: Integrated model Theme 2: Integrated model and future scenarios・Global socio‐economic scenarios・National & regional emissions
scenarios・Urban & household emissions AQ
assessment
Theme 3: SLCP impacts on climate & environment・Impact assessment of aerosols & GHG・Assessment of health, agriculture,
water cycle, sea level rise
SLCP emissions scenariosImproved emission inventory
Feedback of impactsAssessment of activities/policies
Regional EmissionInventories and Chemical Transfer
Model
Integrated Assessment Model (AIM)
Climate and Environment
Model
Chemical transfer model and emission inventory in Asia
AIM/Enduse modelSocio‐economical & emissions scenario
Climate model, earth system model Climate change impact & adaptation
Theme 4: Integrated operation system (Toolkits, data archive)
MDG・SDG・Future Earth
StakeholdersPolicy makers Society Information
transmissionSystem utilization
CCAC, UNFCC, IPCC, EANET
air pollution policies
CCAC, UNFCC, IPCC, EANETProposal and assessment of climate and
air pollution policies
Regional
⇅
Regional strategy
⇅Global strategy
Science
Experiment setup
Metric definitions
Experiment setupDatabase development
Metric definitions
Model improvement
Challenges of S‐12 Theme 2led by NIES cooperating with MHIR and Kyoto Univ.
1. ‐ To indicate socio‐economic scenarios considering climate change and environmental impacts and
‐ To present emissions scenarios of Long‐lived GHG(LLGHG) and Short lived Climate Pollutant (SLCP).【global/national/local scales】
2. ‐ To evaluate co‐benefits of LLGHG mitigation measures and SLCP reduction measures and
‐ To analyze regional characteristics in Asia, in a manner consistent with long‐term global scenarios such as achieving 2℃ global temperature change limit target and halving global GHG emissions by 2050.【national/regional scales in Asia】
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S‐12 Theme2: Improvement of Integrated Assessment Model and Quantification of Future Scenarios
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Global model AIM/CGE
Global model AIM/Enduse
National modelAIM/Enduse
HouseholdModel
Local Air pollution model
Theme3Env. & Climate
ImpactsGlobal emissions scenarios onLLGHG・SLCP
Theme 1Emission inventory
Theme 4Synthesis system
Local emissionsscenarios onLLGHG・SLCP
National emissions Scenarios onLLGHG・SLCP
Air p
ollutio
n managem
ent
techno
logies
Air p
ollutio
n managem
ent
policies a
nd events
at national/local sc
ale
Information for negotiation on GHG reductions
Env. & climatePolicy in JapanAssessment of
Env. & climate policies in Asia
Green:Relation to otherThem
Orange:Relation to Env.policies
Improvement of Enduse(Local activities &
Pollution Management Technologies)
Assessment of actions & policies
Future scenarios
Improved
inventory
Assessment ofmitigation costs &
climate change impacts
Emissions scenarioson LLGHG & SLCP
Future socio‐economic scenarios
Env. & ClimateImpacts
Socio‐economic scenario considering climate & Env. Impact
AIM models
Future Scenarios
Research goals
Sub‐theme (2)
Sub‐theme (1)
Sub‐theme (3)
Overview of AIM/Enduse model
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Bottom-up type model with detailed technology selection framework with optimization
Recursive dynamic model
Assessing technological transition over time
Analyzing effect of policies such as carbon/energy tax, subsidy, regulation and so on.
Target Gas : Multiple gasesCO2, CH4, N2O, HFCs, PFCs, SF6, SO2, NOx, CFCs, HCFCs, etc
Target Sectors : multiple sectorspower generation sector, industry sector, residential sector, commercial sector, transport sector, agriculture sector, municipal solid waste sector, fugitive emissions sector, F-gas emissions sector(each of these can be further disaggregated into sub-sectors)
AIM/Enduse[Global]‐ Regional Classification ‐
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JPN (Japan)
AUS (Australia)
NZL (New Zealand)
RUS (Russia)
CHN (China)
IND (India)
IDN (Indonesia)
THA (Thailand)
USA (United States)
XE15 (Western EU‐15)
XE10 (Eastern EU‐10)
XE2 (Other EU‐2)
XSA (Other South Asia)
XEA (Other East Asia)
XSE (Other South‐East Asia)
MYS (Malaysia)
CAN (Canada)
TUR (Turkey)
XEWI (Other Western EU in Annex I)
XEEI (Other Eastern EU in Annex I)
XENI (Other EU)
XCS (Central Asia)
XOC (Other Oceania)
VNM (Viet Nam)
KOR (Korea)
MEX (Mexico)
BRA (Brazil)
ARG (Argentine)
XLM (Other Latin America)
ZAF (South Africa)
XAF (Other Africa)
XME (Middle East)
Annex I(exact)
OECD(approx)
ASEAN(exact)
World 32 regions
E.g.) Comparison to GAINS 25 RegionsAIM/Enduse GAINS
ASIA JPN, CHN, IND, IDN, KOR, THA, MYS, VNM, XSE, XSA, XEA, XCS
Japan, China+, India, Indonesia+, Korea, SE Asia, Rest S Asia, Asia‐STAN
ASEAN IDN, THA, MYS, VNM, XSE Indonesia, SE Asia
Annex I JPN, AUS, NZL, USA, CAN,XE15, XE10, XE2, TUR, XEWI, XEEI, RUS
Japan, Oceania, USA, Canada, Western EU, Central EU, Turky, Ukraina+, Russia +
AIM/Enduse[Global]‐ Target Gases and Sectors ‐
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GHG Sector Sub sectors whose mitigation actions are considered in Enduse model(other subsectors are treated as scenario)
CO2CH4N2OSO2 NOxBCPM
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
CH4N2O
Agriculture Livestock rumination, Manure management, Paddy field, Cropland
MSW Municipal solid waste
CH4 Fugitive Fugitive emission from fuel
ODSs, HFCs,PFCs,SF6
Fgas emissions By‐product of HCFC‐22, Refrigerant,Aerosol, Foams,Solvent, Etching,Aluminum production, Insulation gas, others.
CO2 CH4 N2O HFCs PFCs SF6 CFCs HCFCs SO2 NOx BC OC PM10 PM2.5 CO NH3 NMV HgFuel
combustion ✔ ✔ ✔ ✔ ✔ ✔ ✻ ✔ ✔ ✻ ✻ ✻
Industrial process ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✻ ✔ ✔ ✻ ✻ ✻
Agriculture ✔ ✔ ✻Waste ✔
Fuel mining ✔Others ✔ ✔ ✔ ✻ ✻
✔: Updated & elaborating ✻:On‐going updatingEmission factors can be set by energy, by sector and by region over time. Settings on technology options are the same, too
AIM/Enduse[Global] and element models
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2005 2010 2015 2020 2025 2030 2035 2040 2045 2050GHG emission
s in Asia (G
t CO2eq)
Cement production
Value added of 2nd industry
Agricultural production
Fluorocarbon emission
Transport volume (Freight)
Energy service (Residential)
Municipal solid waste generation
Energy service (Commercial)
Transportation Demand Model
Household Lifestyle Model
Municipal Solid Waste Model
Cement Production Model
Building sector(Residential)
Energy Supply sector
Socio-economicscenario
Agricultural Prod & Trade model
FluorocarbonEmission Model
Agriculture sector
Model DatabaseVariable
Solid waste management sector
Transport volume (Passenger)
Crude steelproduction
Steel Production & Trade Model
Gas fuel
Heat
Liquid fuel
Solid fuel
Hydrogen
Energy balance
Primaryenergy
Energy price
Emission factor
EnergyDB
Nuclear Hydro Geothermal
Solar Wind Biomass
Emissions
Energy mining sector
GasCoal Oil
Bottom-up model (i.e. AIM/Enduse)
Macro Economic
frame Model
Population & Household number
GDP & Sector value added
Macro-economic model
Iron and steelsector
Cementsector
Other industries sector
Transport sector(Passenger)
Fluorocarbon sector
Energy Resource DB
Cost
Lifetime
Technology DB
Efficiency
Diffusion rate
Service demand models
Electricity
Freight sector(Freight)
Building sector(Commercial)
Future Socio‐economic settings
Socio-economicscenario
Energy mining sector
Macro Economic
frame Model
Population & Household number
GDP & Sector value added
Energy Resource DB
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1980 2000 2020 2040 2060 2080 2100
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GDP pe
r cap
ita
(100
0 US$2005/person)
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GDP pe
r cap
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0 US$2005/person)
Historical trend
SSP1 scenario
SSP2 scenario
SSP3 scenario
SSP4 scenario
SSP5 scenario
This study
Considering various features of different socio‐economic scenarios 1111
e.g.) GDP growth per capita in each country
Macro-economic model
Modeling future service demands
Cement production
Value added of 2nd industry
Agricultural production
Fluorocarbon emission
Transport volume (Freight)
Energy service (Residential)
Municipal solid waste generation
Energy service (Commercial)
Transportation Demand Model
Household Lifestyle Model
Municipal Solid Waste Model
Cement Production Model
Socio-economicscenario
Agricultural Prod & Trade model
FluorocarbonEmission Model
Model DatabaseVariable
Transport volume (Passenger)
Crude steelproduction
Steel Production & Trade Model
Macro Economic
frame Model
Population & Household number
GDP & Sector value added
Total transportation volume PKTOTi,t
Total transportation volume per capita
PKTOTPi,t
PopulationPOPi,t
GDP per capitaGDPPi,t
Transportation volume of each mode
PKm,i,t
Modal shareSHm,i,t
Endogenousvariable
Exogenousvariable
Estimationequation
Definitionalequation
i: regiont: yearm: mode
E.g.) Passenger transport volume estimation mode
Considering socie‐economic features to future service demand estimations in each sector and country (i.e. POP, GDP, are consistent across sectors and countries) 12
02000400060008000100001200014000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
Pass
enge
r tra
nspo
rt (b
illion
pkm
)
JapanChinaIndiaKorea
Macro-economic model Service demand models
Modeling on technology selections
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Selecting technologies to satisfy future service demands and to balance supply and demand, by sector, by country
under various constraints& under minimizing total system costs
By energy, sector and country, we can set various constraints such as Technology settings in the base year Energy balance in the base year Technology diffusion rate Speed of technology diffusion rate Technology constraints Energy constraints Speed of energy efficiency improvement Technology cost Technology costs improvement etc
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2005 2010 2015 2020 2025 2030 2035 2040 2045 2050GHG emission
s in Asia (G
t CO2eq)
Building sector(Residential)
Energy Supply sector
Agriculture sector
Solid waste management sector
Gas fuel
Heat
Liquid fuel
Solid fuel
Hydrogen
Energy balance
Primaryenergy
Energy price
Emission factor
EnergyDB
Nuclear Hydro Geothermal
Solar Wind Biomass
Emissions
Energy mining sector
GasCoal Oil
Bottom-up model (i.e. AIM/Enduse)
Iron and steelsector
Cementsector
Other industries sector
Transport sector(Passenger)
Fluorocarbon sector
Energy Resource DB
Cost
Lifetime
Technology DB
Efficiency
Diffusion rate
Electricity
Freight sector(Freight)
Building sector(Commercial)
Future Scenario settings
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Case 1) Reference scenario (GHG mitigations under BaU & no pollution control measures)Case 2) Technological mitigation measures under emissions pathways constraints at 2 ℃,
2.5℃, and 3℃ reported by UNEP Emission Gap ReportCase 3)Technological mitigation measures under carbon pricing scenarios, considering the
current useful references of carbon pricing such as EU‐ETS carbon prices fluctuated due to global economic change, and varied around
15‐30 EURO/tCO2. The price of CER for CDM projects also fluctuated around 10‐20 EURO/tCO2. Due to the economic recession, the carbon price decreased, around 1 ‐ 5 EURO/tCO2. Upper limits of carbon price of EU‐ETS penalty price is 100 EURO/tCO2 IEA (2010) reported carbon price is at 175 US$/tCO2 in the 450 ppmv scenario.
Scenario name 2013 2020 2030 2040 2050Reference 0 0 0 0 0
50 US$/tCO2 3.75 12.5 25 37.5 50100 US$/tCO2 7.5 25 50 75 100200 US$/tCO2 15 50 100 150 200400 US$/tCO2 30 100 200 300 400
Future global economy‐wide carbon prices scenarios (US$/tCO2)
Increase from the range of current carbon price up to 50US$/tCO2
Increase from the carbon price before economic recession, up to IEA assumption
Increase from the range of current carbon price up to EUETS penalty price
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GtCO2
AIM/Enduse[Global] in global 32 regionsBaseline emissions from fuel combustion & industry in Asia
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ASEAN
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GtCO2
IndiaChinaAsia
EDGER4.2
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MtSO2
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1970 1990 2010 2030 2050
MtNOx
ASEAN ASEAN
020406080100120140160180200
1970 1990 2010 2030 2050
MtSO2
Asia
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120
1970 1990 2010 2030 2050
MtNOx
Asia
CO2
SO2 NOx
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1970 1990 2010 2030 2050
GtCO2 eq
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1970 1990 2010 2030 2050
GtCO2 eq
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1970 1990 2010 2030 2050
GtCO2 eq
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1970 1990 2010 2030 2050
GtCO2 eq
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1970 1990 2010 2030 2050
GtCO2 eq
Comparison with GAINS results ‐ Reference CH4 emissions ‐
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Annex I
Asia China
India
ASEAN
Major emission sources of CH4 are not from fuel combustion. Thus, we need to carefully see sectors such as agriculture, waste and fugitive emissions.
Another major difference is that AIM/Enduse includes “no regret” in this reference scenario.EDGER4.2AIM/Enduse (reference scenario)GAINS(NFC scenario)
Example of CH4 emission estimationHow to estimate MSW generation in Asia?
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Note )Data include Japan, China, Thailand, USA, EU27 & Chinese provinces
y = 184.4ln(x) ‐ 1243.3R² = 0.8302
Following US trend
y = 139.7ln(x) ‐ 904.65 R² = 0.7938
Following developedcountries average
y = 100.94ln(x) – 617.02R² = 0.7445
Following Japan trend
Outlier(Tibet)
China in provincial level
How to estimate future MSW generations in Asia?Asia will follow historical US trend? Japan trend or the average trend of developed countries?
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MtSO2
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MtSO2
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MtSO2
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MtSO2
Comparison with GAINS results ‐ Reference SO2 emissions ‐
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Asia China
India
ASEAN
Major differences are how to estimate future energy service demands, how to set emission factors by fuel and by country, and how to consider fuel policies and air pollution control policies in the future scenario.
The results in the AIM/Enduse[Global] model does include neither fuel policies nor air pollution control policies in the reference scenario
EDGER4.2AIM/Enduse (reference scenario)GAINS(NFC scenario)
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MtNOx
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MtNOx
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MtNOx
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MtNOx
Comparison with GAINS results ‐ Reference NOx emissions ‐
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Asia China
India
ASEAN
EDGER4.2AIM/Enduse (reference scenario)GAINS(NFC scenario)
Major differences are how to estimate future energy service demands, how to set emission factors by fuel and by country, and how to consider fuel policies and air pollution control policies in the future scenario.
The results in the AIM/Enduse[Global] model does include neither fuel policies nor air pollution control policies in the reference scenario
051015202530354045
1990 2010 2030 2050
MtPM
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MtPM
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MtBC
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MtBC
Comparison with GAINS results ‐ Reference PM & BC emissions ‐
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AIM/EnduseGAINS(NFC)
Asia China India ASEAN
Asia China India ASEAN
Large uncertainties & large gaps maybe due to settings of EF and pollution control measures?
6 GHGs emissions pathways in Asiaand comparison with 2 ℃ target pathways
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2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
GHG emission
s in Asia(Gt C
O2e
q)
Reference T50 T100 T200 T400 2 ℃ 2.5 ℃ 3 ℃
‐100%
‐90%
‐80%
‐70%
‐60%
‐50%
‐40%
‐30%
‐20%
‐10%
0%2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
GHG re
ductions ratio in
Asia
(% from
reference)
Source) modified from Hanaoka et al, Environmental Pollution (2014)
Reference 50US$/tCO2 100US$/tCO2 200US$/tCO2 400US$/tCO2
2℃ scenario 2.5 ℃ scenario 3 ℃ scenario
Scenario name 2013 2020 2030 2040 2050Reference 0 0 0 0 0
50 US$/tCO2 3.75 12.5 25 37.5 50100 US$/tCO2 7.5 25 50 75 100200 US$/tCO2 15 50 100 150 200400 US$/tCO2 30 100 200 300 400
Emissions constraints of achieving 2℃‐3℃ were calculated based on UNEP Gap Report Future global economy‐wide carbon prices scenarios (US$/tCO2)
45% reductions from the 2005 levels
0
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2005 2010 2015 2020 2025 2030 2035 2040 20452050
SO2em
ission
s in Asia(M
t SO2)
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120
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
NOxem
ission
s in Asia(M
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Reference T50 T100 T200 T400 2 ℃ 2.5 ℃ 3 ℃
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BCem
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t BC)
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PMem
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Reference T50 T100 T200 T400 2 ℃ 2.5 ℃ 3 ℃
SLCP & Air pollutants emissions in Asia‐ Cobenefits of implementing CO2 mitigation policies‐
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Reference
50US$/tCO2
100US$/tCO2
200US$/tCO2
400US$/tCO2
2℃ scenario
2.5℃ scenario
3℃ scenario
Source) modified from Hanaoka et al, Environmental Pollution (2014)
There are large reduction potentials of air pollutants and SLCPs, due to GHG mitigation actions such as drastic fuel sifts and energy efficiency improvement.(e.g. 60~90% reductions compared to baseline in 2050
SLCP & Air pollutants reduction potentials in Asia‐ Cobenefits of implementing CO2 mitigation policies‐
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Energy supply
Residential & Commercial
Transport
Industry
Reference scenario
2℃ scenario
Emissions pathway & reduction potentials Reduction potentials in 2050
Source) modified from Hanaoka et al, Environmental Pollution (2014)
Features of reduction potentials are different by energy type, by gas typeand by sector, e.g.)Sox: Power & industry Nox: transport and powerBC: power and transport
There is a limitation of large reductions only by fuel sifts and energy efficiency improvements
What AIM/Enduse can & cannot dofor Global Emissions Scenarios Comparison
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AIM/Enduse can discuss Estimating future emissions scenarios both LLGHGs, SLCPs and air pollutants,
quantitatively up to 2050. Analysing abatement actions by technology, by sector and by country under
carbon tax, energy tax, subsidies, etc Analysing technology selections under various constraints such as emissions
pathways constraint, energy supply constraint, technology diffusions, etc Discussing mitigation costs and required initial investments
AIM/Enduse cannot discuss Considering “spill‐over effects” and “rebound effects” such as changes in the
industrial structure, changes of service demands and changes in technology and energy price.
Considering GDP losses due to GHG mitigation actions and pollutants abetment actions
Considering land use change and its corresponding open biomass burnings
Conclusion
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Mitigation measures of energy efficiency improvement on the demand side and the shift to less‐or non‐carbon energies on the supply side play important roles in reducing CO2 emissions as well as increasing cobenefits of SO2 and NOx emissions reductions.
Energy shift in energy supply sector largely contribute to reducing GHGs as well as SO2 in Asia. However, NOx are derived from transport as well as energy supply, and there are limitations to shifting from fuel vehicles to Hybrid, plug‐in Hybrid, electric vehicles in developing countries.
One caveat in this study is that, to focus on cobenefits of reducing air pollutants by introducing GHG mitigation measures, air pollutant control policies and fuel policies are not considered in this study. It is also possible to include these impacts into the Enduse model analysis in the further study.
There is a limitation of reducing SLCPs and air pollutants only by fuel sifts and energy efficiency improvements from the viewpoint of low carbon measures, thus it is also required to consider policies such as air pollutant control measures and low sulfur content fuel policies.
Contact: [email protected]