EC4MACSEuropean Consortium for Modelling of Air Pollution and Climate Strategies
GAINSGreenhouse Gas – Air Pollution Interactions and Synergies
DG ECFIN Workshop on Energy and Climate Change ModellingBrussels, September 15, 2008
Markus AmannInternational Institute for Applied Systems Analysis (IIASA)
The EC4MACS activities are supported by the EU-LIFE programme (www.ec4macs.eu)
EC4MACSEuropean Consortium for Modelling of Air Pollution and Climate Strategies
• Providing scientific and economic analyses for the revision of the EU Thematic Strategy on Air and European Climate Change Programme (ECCP)
• Improvement of existing models by including recent scientific findings
• Update of input data
• Acceptance of modelling tools and input data by stakeholders
• Make modelling tools available to the public over the Internet
E4MACS Partners
• IIASA (AT) – Coordinator, integrated assessment
• MNP/RIVM (NL) - Modelling of environmental impacts
• NTUA Athens (GR) – Energy projections, macro-economics
• Uni Bonn, EuroCare (DE) – Agricultural projections
• LUATh Thessaloniki (GR) – Transport modelling
• Mike Holland, AEAT, Metroeconomica (UK) – Economic benefit analysis
• JRC-Ispra – Global chemistry/climate models
• JRC-Sevilla – Global energy modelling
E4MACS Modelling tools
• GAINS integrated assessment model (IIASA)• PRIMES energy model (NTUA)• CAPRI agricultural model (UniBonn, EuroCare)• EUFASOM landuse emissions model (IIASA)• CCE ecosystems impact assessment (MNP)• GEM-E3 general equilibrium macro-economic impacts
(NTUA)• TREMOVE transport model (LAUTh)• Benefit assessment (MH, AEAT, MetroEconomica)
• TM5 Hemispheric chemical transport model (JRC-IES)• POLES global energy model (JRC-IPTS)
The EC4MACS model system
GAINSPOLES PRIMES
CAPRI
TM5 EMEP
CCE-CL
TREMOVE
BENEFITS
Global/hemisphericboundary conditions
European policy drivers
Energy
Transport
Atmosphere
Agriculture
Ecosystems
GEM-E3
Cost-effectiveness
(Macro-)economic Impacts
EU-FASOM, DNDCLand use
GAINS: GHG-Air pollution Interactions and SynergiesObjectives
Integrated assessment of international emission control strategies:
• Quantification of national emission control potentials and costs
• For exogenous (national) projections of activities
• Balancing of efforts across countries/economic sectors for
– different objective functions (e.g., cost effectiveness or other principles), and
– different exogenous constraints (environmental objectives/total costs/carbon prices, etc.)
• Considering interactions between gases (GHGs and air pollutants)
• Taking into account co-benefits between air pollution control and GHG mitigation (for health and cost savings in air pollution control costs)
• For 2020/2030.
GAINS model features (1)
• Bottom-up analysis of 300+ mitigation options for GHGs, country-specific mitigation potentials and costs
• For exogenous baseline activity projections (PRIMES/POLES/national projections/IEA World Energy Outlook)
• Mitigation costs: International technology costs, modified by local factors
• For different interest rates and oil prices
• Least-cost optimization of mitigation measures to achieve environmental constraints
• Flexibility to modify energy supply structure within bounds derived from other energy models
• Macro-economic feedbacks of pollution control strategies can be addressed via EC4MACS linkage with PRIMES/POLES/GEM-E3
GAINS model features (2)
• Spatial coverage: Country-specific implementations for – Annex 1 countries:
• 27 EU countries, Belarus, Croatia, Norway, Switzerland, Ukraine (completed)
• Australia, Canada, Iceland, Japan, New Zealand, Russia, US, Turkey (end 2008)
– China, India, Pakistan (completed)
• Includes CO2, CH4, N2O, F-gases; SO2, NOx, PM, NH3, VOC (LULUCF under development)
• Implemented by – IIASA (for Europe)– TERI (for India)– ERI and Tsinghua University (for China)
Policy applications
• GAINS/RAINS: – Thematic Strategy on Air Pollution 2005
– National Emission Ceilings Directive 1999, 2008
– Various protocols of LRTAP Convention (1994, 1999, 2007)
– Chinese national acid rain policy
• GAINS
– Non-CO2 cost curves for Climate and Energy Package
– Co-benefits on air pollution for C&E Package, CCS paper
Analytical capabilities of GAINSof potential interest to DG-ECFIN
• Revenue recycling:– No
• Carbon leakage:– Estimates of environmental impacts
• Costs of alternative policy proposals: – Direct mitigation costs and environmental benefits
• Efficiency gains from multiple instruments:– Least-cost strategies for multiple environmental targets
• Ex-post analysis: – For environmental impacts
• Endogenous energy prices:– No
Illustrative GAINS output(1) GHG cost curves for Sweden 2020 (beyond baseline)
-300
-200
-100
0
100
200
300
GHG emissions (Mt CO2eq)
Uni
t cos
t (€
/t C
O2e
q)
50 60 70 80
Marginal mitigation costs
-0.4%
-0.3%
-0.2%
-0.1%
0.0%
0.1%
0.2%
0.3%
0.4%
0.5%
0.6%
50 60 70 80
GHG emissions (Mt CO2eq)
To
tal c
osts
(%
of
GD
P)
Total mitigation costs
70%
75%
80%
85%
90%
95%
100%
60% 70% 80% 90% 100%
GHG emissions relative to baseline
AP
em
issi
ons
rela
tive
to b
asel
ine
SO2 NOX PM
Air pollutant emissions
Illustrative GAINS output(2) Mitigation measures for Sweden 2020 beyond baseline
Measure Mitigation potential
Mt CO2-eq
Marginal costs
€/tCO2eq
Resulting emission level
relative to 1990
Total costs
[% GDP in 2020]
Baseline emissions in 2020 +13% CO2 Solarthermal heating in domestic sector, replacing oil 0.27 -240 +12% -0.30% CO2 substitute fuel oil, gas and diesel with wind and hydro 1.66 -125 +9% CO2 improve efficiency of buses 0.03 -74 9% CO2 switch from boilers and power plants to CHP 1.34 -57 7% CO2 improve efficiency of diesel cars 0.28 -19 7% CO2 improve efficiency of light duty diesel trucks 0.18 -11 7% CO2 improve efficiency of heavy duty diesel trucks 0.58 -3 6% N2O Side effect of switch to CHP (coal) 0.11 0 6% -0.30% N2O Side effect of solar thermal in domestic (less combustion) 0.03 0 6% N2O Optimization of waste water treatment 0.06 0 6% CH4 Side effect of efficiency improvement (less combustion) 0.02 0 6% CH4 Side effect of switch to CHP 0.00 0 6% CH4 side effect of switch to renewables 0.01 0 6% CH4 Rural or urban domestic wastewater -decentralized collection and none or
aerobic treatment with temporary overloads (MCF=0.1) 0.07 0 6%
CO2 switch from gas to fuel wood in boilers 2.88 <5 2% -0.30% N2O fertilizer reduction on arable land 0.39 <5 1% N2O fertilizer reduction on grassland 0.11 <5 1% CO2 Switch from hard coal and brown coal to gas and fuel wood in industrial boilers 0.99 <10 -1% -0.29% N2O side effect of fuel substitutions 0.01 <10 -1% CO2 Efficiency improvements in industry - other combustion 0.25 <20 -1% -0.29% CO2 Switch from hard coal and brown coal in existing power plants to gas and wind
and hydro 0.84 <20 -2%
CH4 CH4 recovery from coal mines 0.01 <20 -2% N2O side effect of fuel substitutions 0.02 <20 -2% CO2 Switch from hard coal and brown coal in existing power plants to gas and wind
and hydro 0.02 <25 -2% -0.29%
CO2 Higher efficiency diesel cars 0.52 <30 -3% -0.28% CO2 Efficiency improvements in industry - other combustion 0.25 <35 -3% -0.28% CO2 replace existing gas and oil electricity plants with new ones 0.01 <35 -3% CO2 Efficiency improvements in industry - other combustion 0.03 <45 -3% -0.28% CO2 Electricity savings in households 0.57 <50 -4% -0.27% CH4 Replacement of grey cast iron gas distribution network 0.00 <50 -4% CH4 Doubling of leak control frequency of gas distribution network 0.00 <50 -4% CO2 Efficiency improvements in industry - other combustion 0.05 <60 -4% -0.27% CO2 Efficiency improvements in refineries etc 0.00 <65 -4% -0.26% CO2 Efficiency improvements in industry - other combustion 0.25 <65 -4% CO2 Switch from coal to coal CHP, and to CCS 0.30 <65 -5% CO2 Switch from coal to coal CHP with CCS, and fuel wood CCS 3.76 <70 -10% -0.20% CO2 Efficiency improvements in refineries etc 0.00 <125 -10% -0.05% CO2 Efficiency improvements in industry - other combustion 0.53 <125 -11% CO2 Higher efficiency gasoline cars 2.40 <125 -14% CO2 Hybrid heavy duty trucks 2.01 <125 -17% CO2 from existing powerplants to new gas and fuel wook with CCS; electricity
savings in domestic and industry; 1.76 <125 -19%
CH4 Community anaerobic digestion plant 0.14 <125 -20% CH4 efficiency improvements in household combustion 0.00 <125 -20% CH4 Replacement of grey cast iron gas distribution network 0.01 <125 -20% CO2 Efficiency improvements in industry - other combustion and refineries etc 0.01 <150 -20% -0.05% CO2 Efficiency improvements in industry - other combustion 0.08 <175 -20% -0.05% CO2 Switch from oil to gas in industrial boilers 0.16 <200 -20% 0.06% CO2 Efficiency improvements in industry - other combustion 0.36 <200 -20% CO2 Efficiency improvements in households - reduce heating oil 1.20 <200 -22% CO2 Efficiency improvements in households - reduce heating oil; electricity savings
households 0.12 <225 -22% 0.06%
CO2 Efficiency improvements in refineries etc 0.00 <300 -22% 0.07% CH4 Municipal food waste treated in anaerobic digestion (biogasification) plants 0.07 <300 -22% CH4 Food industry waste incinerated 0.12 <300 -23% CO2 Efficiency improvements in households - reduce gas, LPG and oil 1.14 >300 -24% 0.56% CO2 Efficiency improvements in industry - other combustion 0.05 >00 -24% CO2 Hybrid gasoline cars 1.46 >300 -26% CH4 Food industry waste incinerated 0.04 >300 -26%
Illustrative GAINS output (3) Data sheets on GHG mitigation potentials (for all Annex1)
Sensitivity analysis for different interest ratesGHG cost curve for Sweden, 2020
-300
-200
-100
0
100
200
300
Uni
t cos
t (E
uro/
tCO
2eq.
)
50607080
GHG emissions (MtCO2eq.)
-300
-200
-100
0
100
200
300
Uni
t cos
t (E
uro/
tCO
2eq.
)
50607080
GHG emissions (MtCO2eq.)
9%/year4%/year
-45%
-40%
-35%
-30%
-25%
-20%
-15%
-10%
-5%
0%
-30% -20% -10% 0%
Change in CO2 emissions compared to baseline
Cha
nge
in a
ir po
llutio
n em
issi
ons
com
pare
d to
bas
elin
e
-45%
-40%
-35%
-30%
-25%
-20%
-15%
-10%
-5%
0%
-30% -20% -10% 0%
Change in CO2 emissions compared to baseline
Cha
nge
in a
ir po
llutio
n em
issi
ons
com
pare
d to
bas
elin
e
-45%
-40%
-35%
-30%
-25%
-20%
-15%
-10%
-5%
0%
-30% -20% -10% 0%
Change in CO2 emissions compared to baseline
Cha
nge
in S
O2
emis
sion
s co
mpa
red
to b
asel
ine
Co-control of air pollution with CO2 mitigationassuming current legislation on air pollution
SO2 NOx PM2.5
● EU-27 ● China ● India
Health impacts from air pollution2005
0
1
2
3
4
5
EU China India
Loss
in s
tatis
tical
life
exp
ecta
ncy
attr
ibut
able
to P
M2.
5 (y
ears
)
2005 2030 Baseline 2030 CO2 mitigation case
Health impacts from air pollution 2030 baseline
0
1
2
3
4
5
EU China India
Loss
in s
tatis
tical
life
exp
ecta
ncy
attr
ibut
able
to P
M2.
5 (y
ears
)
2005 2030 Baseline 2030 CO2 mitigation case
Health impacts from reduced air pollutiondue to CO2 mitigation 2030
0
1
2
3
4
5
EU China India
Loss
in s
tatis
tical
life
exp
ecta
ncy
attr
ibut
able
to P
M2.
5 (y
ears
)
2005 2030 Baseline 2030 CO2 mitigation case
-45%
-40%
-35%
-30%
-25%
-20%
-15%
-10%
-5%
0%
-30% -20% -10% 0%
Change in CO2 emissions compared to baseline
Cha
nge
in lo
ss in
sta
tistic
al li
fe e
xpec
tanc
y co
mpa
red
to b
asel
ine
● EU-27 ● China ● India
Air pollution control costs for implementation of current legislation in 2020/2030
0
20
40
60
80
100
120
EU-27 China India EU-27 China India
Abolute emission control costs Costs as share of GDP(PPP)
Bil
lio
n €
/yr
0.0%
0.1%
0.2%
0.3%
0.4%
0.5%
0.6%
% o
f G
DP
(PP
P)
Baseline CO2 mitigation case
+ health benefits as shown before!
0
25
50
75
100
125
National energy projections (+3% CO2 in 2020) Illustrative projections meeting the EU climatetarget (-20% CO2 in 2020)
Bill
ion
€/y
r
Indicative costs for changes in the energy system to meet climate and energy targets Costs for further measures to achieve the targets of the EU Thematic Strategy on Air PollutionCosts for implementing current air pollution legislation
0
25
50
75
100
125
National energy projections (+3% CO2 in 2020) Illustrative projections meeting the EU climatetarget (-20% CO2 in 2020)
Bill
ion
€/y
r
Indicative costs for changes in the energy system to meet climate and energy targets Costs for further measures to achieve the targets of the EU Thematic Strategy on Air PollutionCosts for implementing current air pollution legislation
Emission control costs to meet the EU air quality and climate targetsEU-27, 2020 (Source: IIASA’s GAINS model)
0
25
50
75
100
125
National energy projections (+3% CO2 in 2020) Illustrative projections meeting the EU climatetarget (-20% CO2 in 2020)
Bill
ion
€/y
r
Indicative costs for changes in the energy system to meet climate and energy targets Costs for further measures to achieve the targets of the EU Thematic Strategy on Air PollutionCosts for implementing current air pollution legislation
Business as usualNational energy projections
(+3% CO2 in 2020)
PRIMES energy scenario with climate measures
(-20% CO2 in 2020)
€20 bn/yr
ConclusionsOutlook for use by DG ECFIN
• EC4MACS: – Consortium of model developers,
aiming at model linkages, maintenance and stakeholder acceptance– Case studies need to be run by modelling teams
• GAINS– Focus on international comparability of GHG mitigation strategies– Addresses multi-pollutant, multi-effects and co-benefits– But limited focus on macro-economic feedbacks– Free and open access via the Internet (gains.iiasa.ac.at)