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)