João Cleto, Sofia Simões, Patrícia Fortes, Júlia Seixas

The role of cost-effective measures in Portugal for The role of cost-effective measures in Portugal for compliance with the EU climate-energy targets compliance with the EU climate-energy targets

Research work funded by the FCT/MCES and POCI 2010, supported by FEDER

Quantifying the Synergies and Antagonisms Between Energy and Environment Policy Instruments in Place – feed-in tariffs, EU ETS and on-budget aids to gas infrastructures;Energy and GHG Emissions – Evaluation of Long Term Scenarios for Portugal;Renewable Energy Sources Availability under Climate Change Scenarios – Impacts on the Portuguese Energy System;Evaluation of the Energy Savings Potential of the Portuguese Households;Competitiveness of Portuguese Industry in Post-Kyoto EUTS: Sector CO2 MAC;Portugal Climate 2020: GHG Emission Scenarios in the Post-Kyoto regimeH2 technologies roadmap for Portugal for 2050

European Projects

Portuguese Project and Policy Support

Energy demand: • based on 2008 macro-economic and demographic scenarios – industry

(validated)• bottom-up approach to compute residential, commercial and transport energy

service demand

Technology database: • validation of the industry, transport, solar thermal and electricity production

technologies by the Portuguese stakeholders

Delivery Costs EU-ETS

• emissions disaggregated and possibility to model acquisition of allowances at different price and allocation scenarios

What is the contribution of “ cost-effective measures” in the residential and commercial sectors for GHG emission targets?

What are the hidden gains if changes in behaviour and technologies follow a perfect knowledge pattern?

The role of cost-effective measures in Portugal for The role of cost-effective measures in Portugal for compliance with the EU climate-energy targets compliance with the EU climate-energy targets

– 5% biofuels beyond 2010– 31% of renewable electricity in 2010

– 10% biofuels beyond 2010– 45% of renewable electricity in 2010

BAU

BAUeff

PQ

PQeff

Baseline

Insulation, renewable heat, fuel shifts

Evolution based on 2000- 2005 trends (e.g. diesel lessons from past)

“zero cost measures”

- Renew. and biofuels

+ Renew. and biofuels

Analyzed:

Non-trend “zero cost”

Not analyzed:

Trend “zero cost”(e.g. Lighting, refrigeration)

Final energy demand in 2020

-30 -20 -10 0 10 20 30

Oil

Gas

Coal

Electricity

Biomass

Heath

Other ren.

Biofuels

Total

Variation in final energy demand with zero cost measures (PJ)

PQBAU

-1%

+15 to +20%

<1%+14 to +7%

0 to +2%

-3%

-18 to 14%-14 to -17%

Sector% variation in sector final energy

demand

BAU PQ

Commercial -15 -11

Residential +10 +8

Fuel and Technology change 2005 – 2020 Residential – heating, cooling, water heating

-20

0

20

40

60

80

100

120

2000 BAU BAUeff PK PKeff

PJ

RSD - renewables

RSD - Insulation

RSD - fossils

RSD - Electricity

2020

31%

21%

37%

20%

43%

49%

Biomass heat

Natural gas

Solar thermal

31%

25%

37%

17%

38%

51%

Fuel and Technology change 2005 – 2020Comercial – heating, cooling, water heating

2020

-20

0

20

40

60

80

100

120

140

160

2000 BAU BAUeff PK PKeff

PJ

COM - Renewables

COM - Insulation

COM Fossil

COM - Electricity

31%

21%

74%

47%

31%

21%

74%

47% Oil

Heat Pumps

Solar thermal

GHG Emissions in 2020

-2500 -2000 -1500 -1000 -500 0 500 1000

Energy Supply

Industry

Transport

Commercial

Residential

Agriculture

National total

Variation in GHG Emissions with zero cost measures (Gg CO2e)

PQ

BAU

-2 %

-63 to -71%

-3 to 0%+2%

-3 to -0%

% variation from 2005

GHG emissions

BAU BAUeff PQ PQeff

EU ETS 5 4 7 8

Non EU ETS 1 -2 -5 -9

National Total 3 0 0 -2

EU proposal for Portugal

EU ETS ?

Non-EU ETS +1

Renewables

EU proposal for Portugal

+31%

PJ2020

BAU BAUeff PQ PQeff

Renewable electricity 111 110 143 142

Renewable heating & cooling 83 114 69 96

Residential 24 51 20 42

Commercial 12 19 12 17

Industry 48 44 37 36

Renewables in transport 16 16 27 27

Total renewable (a) 210 240 238 265

Total final energy (b) 849 848 850 849

% Renewables (a/b) 25 28 28 31

Conclusions & remarks Savings of roughly 3 M€ (0.1% of GDP) Possible bias in results

• Biomass statistical info on biomass may be biasing results for residential sector

• Diesel in commercial sector – trend evolution possible?

Policy implications • Current policies for implementation of these measures are not ambitious enough and do not

realize the full low hanging fruits potential

Next steps• fully evaluate cost-effective options on remaining sectors