194
is known as the indirect rebound effect. Alternatively, he might decide, rather than
to spend the money, to save it and therefore he puts it on deposit in a bank. The
bank, however, then invests the money, and this investment, in turn, gives rise to
carbon emissions. This is another example of the indirect rebound effect.
Another type of rebound effect that commonly arises is the ‘embodied’ rebound
effect, and this is better illustrated through an example of loft insulation. In this
example a person who installs loft insulation can calculate how much energy (and
hence carbon emissions) will be saved through reduced fuel use. However, energy
is used in the manufacture of the loft insulation, and, following the consumption
accounting principle discussed in Sect. 1 , carbon emissions from this energy use are
the purchaser of the insulation material’s responsibility. Hence these emissions offset the expected savings, and this is known as the embodied rebound effect.
If a measure is expected to achieve a reduction of 100 kgCO 2 e then a rebound
effect of 30 % implies that only 70 kgCO 2 e was saved, and a rebound effect of
100 % implies that no carbon was saved. A rebound effect greater than 100 % means
that the measure resulted in more, not less, emissions, and, from this view, it would
have been better not to have done the action at all. This is known as ‘backfi re’.
Until relatively recently, although the rebound effect was a well-known phenomenon, there were few studies that had estimated to what extent it is a problem with
respect to households. In the last few years, however, studies have been carried out
to explore it focusing on various different countries. These include Lenzen and Dey
( 2002 ) and Murray ( 2013 ) for Australia; Alfredsson ( 2004 ) and Brännlund et al.
( 2007 ) for Sweden; Mizobuchi ( 2008 ) for Japan; Kratena and Wuger ( 2010 ) for
Austria; and Thomas and Azevedo ( 2013 ) for US and Druckman et al. ( 2011a ) and
Chitnis et al. ( 2013 , 2014 ) for the UK. These studies generally consider a variety of
measures such as abatement actions (for example, reducing the amount of food
wasted, reducing household room temperature thermostat settings and replacing
short car journeys by walking or cycling) and energy effi ciency measures (for example, installation of cavity wall insulation, loft insulation, condensing boiler, water
tank insulation, energy effi cient lighting and purchase of an effi cient car). Chitnis
et al. ( 2014 ), who estimated the rebound effect in terms of GHG emissions , found
rebound to be around 0–32 % for measures affecting domestic energy use and
around 25–65 % for measures affecting vehicle fuel. The possibility of backfi re was
found for measures that reduce food waste, with estimates being around 66–106 %
(Chitnis et al. 2014 ). In general, rebound was found to be larger for lower income
groups (with some exceptions) as they have a higher proportion of expenditure on
direct energy (as discussed in Sect. 3.1 ) and this expenditure has relatively high
income elasticities (Chitnis et al. 2014 ).
The conclusion from this rebound effect work is not that encouragement to carry
out the abatement and energy effi ciency actions should be abandoned: indeed, for
all except food waste under certain conditions, considerable carbon emissions can
be saved through these means and therefore it is imperative that such actions should
be supported. However, it is vital that governments take into account the rebound
effect when estimating reductions in carbon emissions that can be achieved, else
they stand in danger of systemically missing their carbon reduction targets.
A. Druckman and T. Jackson
is known as the indirect rebound effect. Alternatively, he might decide, rather than
to spend the money, to save it and therefore he puts it on deposit in a bank. The
bank, however, then invests the money, and this investment, in turn, gives rise to
carbon emissions. This is another example of the indirect rebound effect.
Another type of rebound effect that commonly arises is the ‘embodied’ rebound
effect, and this is better illustrated through an example of loft insulation. In this
example a person who installs loft insulation can calculate how much energy (and
hence carbon emissions) will be saved through reduced fuel use. However, energy
is used in the manufacture of the loft insulation, and, following the consumption
accounting principle discussed in Sect. 1 , carbon emissions from this energy use are
the purchaser of the insulation material’s responsibility. Hence these emissions offset the expected savings, and this is known as the embodied rebound effect.
If a measure is expected to achieve a reduction of 100 kgCO 2 e then a rebound
effect of 30 % implies that only 70 kgCO 2 e was saved, and a rebound effect of
100 % implies that no carbon was saved. A rebound effect greater than 100 % means
that the measure resulted in more, not less, emissions, and, from this view, it would
have been better not to have done the action at all. This is known as ‘backfi re’.
Until relatively recently, although the rebound effect was a well-known phenomenon, there were few studies that had estimated to what extent it is a problem with
respect to households. In the last few years, however, studies have been carried out
to explore it focusing on various different countries. These include Lenzen and Dey
( 2002 ) and Murray ( 2013 ) for Australia; Alfredsson ( 2004 ) and Brännlund et al.
( 2007 ) for Sweden; Mizobuchi ( 2008 ) for Japan; Kratena and Wuger ( 2010 ) for
Austria; and Thomas and Azevedo ( 2013 ) for US and Druckman et al. ( 2011a ) and
Chitnis et al. ( 2013 , 2014 ) for the UK. These studies generally consider a variety of
measures such as abatement actions (for example, reducing the amount of food
wasted, reducing household room temperature thermostat settings and replacing
short car journeys by walking or cycling) and energy effi ciency measures (for example, installation of cavity wall insulation, loft insulation, condensing boiler, water
tank insulation, energy effi cient lighting and purchase of an effi cient car). Chitnis
et al. ( 2014 ), who estimated the rebound effect in terms of GHG emissions , found
rebound to be around 0–32 % for measures affecting domestic energy use and
around 25–65 % for measures affecting vehicle fuel. The possibility of backfi re was
found for measures that reduce food waste, with estimates being around 66–106 %
(Chitnis et al. 2014 ). In general, rebound was found to be larger for lower income
groups (with some exceptions) as they have a higher proportion of expenditure on
direct energy (as discussed in Sect. 3.1 ) and this expenditure has relatively high
income elasticities (Chitnis et al. 2014 ).
The conclusion from this rebound effect work is not that encouragement to carry
out the abatement and energy effi ciency actions should be abandoned: indeed, for
all except food waste under certain conditions, considerable carbon emissions can
be saved through these means and therefore it is imperative that such actions should
be supported. However, it is vital that governments take into account the rebound
effect when estimating reductions in carbon emissions that can be achieved, else
they stand in danger of systemically missing their carbon reduction targets.
A. Druckman and T. Jackson