Buildings Scenarios

BAU G2

Emission intensity – CO2 emissions per US$ GDP - -57.0% Carbon intensity – CO2 -3.2% -45.0% emissions per unit of energy consumption

Reduction between 2005 and 2050 Reduction relative to BAU in 2050 Reduction between 2005 and 2050 Reduction relative to BAU in 2050 -45% -76%

- -42.8% Table 6: Emissions intensity in the GER model simulations

reduction in this intensity under G2 will be 36 per cent compared with 9 per cent in the BAU. In 2050, the G2 scenario would deliver a 64 per cent reduction in the intensity of power demand relative to BAU.

Power demand, however, only accounts for approximately 30 per cent of energy use by all buildings in 2010 (21 per cent for residential buildings and 51 per cent for commercial buildings). Efficiency improvements in the use of other energy sources in buildings were not simulated, due to lack of data. In these partial results of the simulation, therefore, total energy use in the building sector, which is influenced in the model primarily by economic growth, continues to rise. It turns out that the increased energy use from non-power sources, such as fuel for heating, driven by additional economic growth in the green investment scenarios, approximately offsets the savings in power demand. Thus, total energy-use rises similarly under all scenarios. This is, in part, an example of the rebound effect (see Box 6). It should be emphasised, however, that improvements in the efficiency of energy use from non-power sources, which are not captured by the model and its simulations, should entail lower energy use under any potential green investment scenario.

As mentioned, the green investment scenario modelled includes an integrated package of investments in multiple sectors, which affect each other, sometimes indirectly, through inter-sectoral linkages and economy- wide effects. For this reason, the results in one sector, such as the buildings, need to be seen as a result of both direct effects from the specific investments in the sector, in this case energy-efficiency, as well as indirect effects, such as those that affect GDP growth.

The multi-sector G2 scenario also entails substantial investment in the supply of energy from renewable sources. In the G2 scenario, 0.5 per cent of GDP is committed to renewables with the aim of reaching the targets set in IEA’s Blue Map scenario (IEA 2008). Although total energy use in buildings may still continue to rise under any scenario due to continued economic growth, the level of emissions would be much lower due to the increased share of renewables.

The simulations (see Figure 6) reveal that by 2050 the green scenario leads to levels of emissions that are 4.7 GtCO2

below the BAU and approximately 27 per cent

lower than current emissions. In G2, the absolute level of CO2

emissions increases slightly during the first years

Box 6: The rebound effect

The phenomenon known as the “rebound effect” describes the limits to energy savings achievable by increasing the energy efficiency of a given technology. Financial savings incurred owing to greater efficiency may lead to increased use of the same product or to the consumption of other energy- consuming goods and services. This highlights the Jevons paradox, where efficiency gains from a new technology are undermined by increase in consumption of the resource involved. Examples are leaving lights on because they are energy-saving bulbs and driving a more efficient car further or using the money saved on petrol to buy another car. It highlights the importance of accompanying new technologies with appropriate behavioural and institutional change. This rebound effect is widely

recognised, but its estimated magnitude varies by activity, as shown by the following estimates (WBCSD 2007a):

■ Space heating: 10-30 per cent ■ Space cooling: 0-50 per cent ■ Lighting: 5-20 per cent ■ Water heating: 10-40 per cent ■ Automobile: 10-30 per cent.

The rebound effect has to be viewed differently in low-income countries, where consumption increases from a low status quo. Here energy efficiency can contribute to development as reduced expenditure on energy enables poor families to invest in other necessities of daily life.

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