Download References

Global technical potentials for energy-efficiency improvement
[Wina Graus, Ecofys Netherlands bv, +31306623324, [email protected]]
[Eliane Blomen, Ecofys Netherlands bv, [email protected]]
[Corinna Kleßmann, Ecofys Germany, [email protected]]
[Caroline Capone, Ecofys Germany, [email protected]]
[Eva Stricker, Ecofys Germany, [email protected]]
Overview
In this study the technical potentials and costs are calculated for energy-efficiency improvement in 10 world regions in 2030
and 2050. The regions considered in the study are the regions as defined by the International Energy Agency: OECD Europe,
OECD North America, OECD Pacific, Transition Economies, China, India, Latin America, Africa, Middle East, and Rest of
Developing Asia.
The reference scenario is based on the World Energy Outlook (WEO) of the International Energy Agency edition 2007 (IEA,
2007) and assumptions regarding GDP development per region after 2030. The technical potentials for energy-efficiency
improvement are based on literature sources and own calculations. Cost calculations for global energy-efficiency improvement
are based on two case studies for the regions, OECD Europe and China.
The results of this study show that on a business-as-usual trajectory, worldwide final energy demand is expected to grow by
95% from 290 EJ in 2005 to 570 EJ in 2050. By exploiting the technical potential for energy efficiency improvement in that
period the increase can be limited to 8% or 317 EJ in 2050. It is estimated that to implement the global technical potential,
annual costs equivalent to 0.4% of GDP in 2050 are needed. It was found that there is a large potential for cost-effective
measures, equivalent to around 55-60% of energy savings of the efficiency measures.
Methods
The reference scenario is based on the World Energy Outlook (WEO) of the International Energy Agency edition 2007 (IEA,
2007), for the period 2005-2030. For the period 2030-2050 the WEO scenario is extended by assumptions regarding GDP
(based on Simon et al., 2008) and energy intensity developments per region. Under the reference scenario global GDP grows
by 440% from 63720 bln US$ (in 2006 dollars, ppp) in 2005 to 279100 bln US$ in 2050. Population increases from 6.5 billion
in 2005 to 9.2 billion in 2050. The energy intensity in this period decreases from 4.6 MJ/US$ to 2.0 MJ/US$ (with 1.8% per
year).
The technical potentials for energy-efficiency improvement are based on literature sources and own calculations. Energy use is
split up into three sectors: transport, industry and others (mainly buildings and agriculture).
For the transport sector calculations are based on the WBCSD transport model (IEA/SMP, 2004). Technical potentials are
based on literature sources indicating potential improvement in 2050 for energy-efficiency per transport mode. The main
sources used are Blok (2005), Akerman (2005), Fulton & Eads (2004), DeCicco et al. (2004) and Lensink and De Wilde
(2007).
For the industry sector, technical potentials for energy-efficiency improvement are calculated specifically for the four largest
energy consuming sectors: chemical and petrochemical industry, iron and steel, non-metallic minerals and aluminum
production. Potentials are based on implementing best practice technolgy. Literature sources that are used are e.g. Kim and
Worrell (2002), IISI (1998), IEA (2006), Fruehan et. al (2000), Keulenaer et al (2004), ENCI (2002), Sinton et al (2002) and
Phylipsen et al. (1998).
For the other sectors (buildings and agriculture), the potential for energy-efficiency improvement is calculated per type of
energy use: space heating, cooking, hot water use, lighting, standby power, cold appliances, other appliances and air
conditioning. Main literature sources used are: US DOE/EIA (2007), Bertoldi & Atanasiu (2006), WBCSD (2005), Koomey
(2007), EuroTopten (2008), IEA (2006), Meier (2001), UNECE (2008).
The cost estimates for energy-efficiency improvement measures are based on additional investment costs, expected energy
savings, lifetime of measure and current energy prices. The costs are expressed in EUR 2005 values and a discount rate of 6%
is used. The main literature sources used for investment costs and energy savings data per measure are TNO et. al (2006), JRC
(2008), EESI (2006), US EPA (2008), IPCC (2007), Boermans and Petersdorff (2007), Harmelink (2005), European
Commission (2007), LBNL (1999) and De Beer and Phylipsen (2001).
Results
On a business-as-usual trajectory, worldwide final energy demand is expected to grow by 95% from 290 EJ in 2005 to 570 EJ
in 2050. By exploiting the technical potential for energy efficiency improvement in that period the increase can be limited to
8% or 317 EJ in 2050.
Based on case studies done for OECD Europe and China it is estimated that to implement the global technical potential, annual
costs equivalent to 0.4% of GDP in 2050 are needed. It was found that there is a large potential for cost-effective measures,
equivalent to around 55-60% of energy savings of all included efficiency measures.
The table below gives the increase or decrease of energy demand in 2050 in comparison to 2005 per sector for the world.
Table 1 Change of energy demand in 2050 in comparison to 2005 level
Sector
Reference scenario
Technical scenario
2005 (EJ)
2050 (EJ)
Change 2050/ 2005
2050 (EJ)
Change 2050/
2005
Industry
88
178
+101%
103
+17%
Transport
84
183
+119%
75
-11%
Buildings and Agriculture
121
210
+74%
139
+16%
Total
292
571
+95%
317
+8%
Figure 1 shows the global final energy demand in 2005, 2020, 2030 and 2050 in the reference scenario and the technical
potential scenario.
Total final energy demand
Buildings
250
600
500
Technical potential scenario
Final energy demand (EJ)
Final energy demand (EJ)
Reference scenario
400
300
200
100
0
200
150
100
50
0
2005
2020
2030
2050
2005
2020
2050
2030
2050
Industry
200
200
160
160
Final energy demand (EJ)
Final energy demand (EJ)
Transport
2030
120
80
40
0
120
80
40
0
2005
2020
2030
2050
2005
2020
Figure 1 Global final energy demand in reference scenario and technical potentials scenario for 2020, 2030 and 2050
Conclusions
The potential for energy-efficiency improvement is large. Results show that by implementing the technical potential for energyefficiency improvement the expected growth of final energy demand can be limited to 8% instead of 95%.
The costs for implementing the energy-efficiency measures are estimated to be around 0.4% of GDP in 2050. 55-60% of the
measures are estimated to be cost-effective. It is found however that cost estimates for efficiency measures are very sensitive to
fuel price assumptions. Also the discount rate used influences costs significantly as well as assumptions regarding incremental
investment costs of energy efficiency measures and estimated fuel savings. Further research is therefore needed in this field.
3
Intelligent Well Technology: Status and Opportunities for Developing Marginal Reserves
SPE
References

Akerman, J. (2005) Sustainable air transport–on track in 2050. Transportation Research Part D 10, pp. 111-125.

Blok, K. (2005). Improving energy efficiency by five percent and more per year? Journal of Industrial Ecology.
Volume 8, Number 4. Massachusetts Institute of Technology and Yale University.

Boermans, T. and C. Petersdorff (2007). U-values for better energy performance of buildings.

De Beer, J. and D. Phylipsen (2001). Economic evaluation of Carbon Dioxide and Nitrous Oxide emission reduction
in the EU. Ecofys, Netherlands.

DeCicco, J., F. An, and M. Ross. Duffield, W.A., and J.H. Sass (2004). Geothermal Energy - Clean Power From the
Earth's Heat: U.S. Geological Survey Circular 1249, 43 p. http://pubs.usgs.gov/circ/2004/c1249/c1249.pdf

EESI (2006)

ENCI (2002). Energy data for cement production, ENCI, Maastricht

European Commission (2007). Preparatory studies for Eco-design Requirements of EuPs. Lot 3: Personal Computers
(desktops and laptops) and Computer Monitors. Final Report (Task 1-8); Study for the European Commission DG
TREN, August 2007.

Fruehan, R.J., O. Fortini, H.W. Paxton and R, Brindle (2000). Theoretical minimum energies to produce steel for

Fulton, L. and G. Eads (2004). IEA/SMP Model Documentation and Reference Case Projection. July 2004.

Harmelink M., K. Blok, M. Chang, W. Graus, S. Joosen (2005). Options to speed up energy savings in the
selected conditions. Carnegie Mellon University, Pittsburgh. United States.
Netherlands (Mogelijkheden voor versnelling van energiebesparing in Nederland). Ecofys, Utrecht, June 2005

IEA (2007). World Energy Outlook 2007. International Energy Agency. Paris, France.

IEA (2006). Energy Technology Perspectives – Scenarios and strategies to 2050. OECD/IEA, 2006.

IEA/SMP (2004). IEA/SMP Model Documentation and Reference Case Projection. L. Fulton (IEA) and G. Eads
(CRA) for WBCSD’s Sustainable Mobility Project (SMP), July 2004.

International Iron and Steel Institute (IIISI) (1998). Energy use in the Steel Industry, 1998. Brussels, Belgium: IISI.

IPCC (2007): Special Report on Emission Scenarios. A Special Report of Working Group IV of the Intergovernmental
Panel on Climate Change. Cambridge University Press, 2007

JRC (2008). Environmental Improvement Potential of Cars (IMPRO-Car), JRC Scientific and Technical report, EUR

Keulenaar et al. (2004). Energy efficiency motor systems. European Copper Institute.

Kim, Y. and E. Worrell (2002). An International Comparison of CO2 Emission Trends in the Cement Industry.
23038 En, April 2008, available at: http://www.jrc.es/publications/pub.cfm?id=1564
Economic Analysis Team Electronics and Telecommunications Research Institute, Lawrence Berkeley National
Laboratory.

LBNL (1999). Energy Efficiency and Carbon Dioxide Emissions Reduction Opportunities in the U.S. Iron and Steel
Sector. Ernst Worrell, Nathan Martin, Lynn Price. Energy Analysis Department. Environmental Energy Technologies
Division Ernest Orlando Lawrence Berkeley National Laboratory. LBNL-41724.

Lensink, S.M and H. de Wilde (2007). Kostenefficientie van (technische) opties voor zuiniger vrachtverkeer. Energy
research Centre of The Netherlands (ECN). http://www.ecn.nl/docs/library/report/2007/e07003.pdf

Phylipsen, G.J.M. K. Blok and E. Worrell (1998). “Benchmarking the energy efficiency of the Dutch energy-intensive
industry”, A preliminary as-sessment of the effect on energy consumption and CO2 emissions, Depart-ment of
Science, Technology and Society, Utrecht University. Utrecht, The Netherlands.

Simon, S., W. Krewitt, and T. Pregger (2008). Energy [R]evolution scenario 2008. Working Paper on specification of
world regions, population development and GDP development. DLR, Institute of Technical Thermodynamics Systems
Analysis and Technology AssessmentStuttgart.Sinton, J.E., J.I. Lewis, L.K. Price and E. Worrell (2002). China’s
sustainable energy future scenarios and carbon emissions analysis. Subreport 11: international trends in energy
efficiency technologies and policies. LBNL, Berkeley, US.

TNO et al. (2006). Review and analysis of the reduction potential and costs of technological and other measures to
reduce CO2-emissions from passenger cars, TNO, IEEP, LAT, 2006.

U.S.
Environmental
Protection
http://www.epa.gov/smartway/
Agency
(EPA)
(2008).
under
the
SmartWay
Transport
Partnership.