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nature energy
Analysis
https://doi.org/10.1038/s41560-023-01283-y
Emissions savings from equitable energy
demand reduction
Milena Büchs 1 , Noel Cass2, Caroline Mullen2, Karen Lucas3
& Diana Ivanova 1
Energy demand reduction (EDR) will be required to reach climate targets
in the Global North. To be compatible with just transitions principles, EDR
needs to be equitable. Equitable EDR may involve targeting high energy
users while ensuring the satisfaction of needs for all, which could require
increasing consumption of low users. Emissions impacts of equitable
EDR approaches have not yet been assessed. This Article nds that
capping energy use of the top quintile of consumers across 27 European
countries can achieve considerable greenhouse gas emissions reductions
of 11.4% from domestic energy, 16.8% from transport and 9.7% from total
energy consumption. Increasing consumption of low energy users in
poverty reduces these savings by only 1.2, 0.9 and 1.4 percentage points,
respectively. Additional high annual emissions cuts of 7.3–24.0% would be
required for Europe to meet globally equitable 2050 emissions budgets.
Equitable EDR could make an important contribution to increasing public
acceptance of such transformative action.
There is now wide recognition that energy demand reduction (EDR) in
the Global North will be required to meet climate targets as supply-side
measures that decarbonize energy use cannot be solely relied upon1–4.
For instance, the latest report by the Intergovernmental Panel on
Climate Change4 estimates that demand-side strategies could contribute
40–70% of emissions reductions globally by 2050. Concurrently, the
climate policy literature increasingly takes principles from energy and
climate justice research into account
5–7
, highlighting that EDR needs to
be equitable. This Article aligns with well-established equity principles
in the energy and climate justice literature that maintain that those
who have contributed most to climate change and who have greatest
capacity to act should carry the greatest responsibility for reducing
energy demand and emissions (polluter pays/historical responsibility
and capacity principles)5,8–13. At the same time, the energy and climate
justice literatures maintain that every human should have the right to
fulfil their basic needs and that those unable to meet their needs should
be supported to do so12,14–16.
Several concepts are relevant for conceptualizing equitable
EDR, including ‘consumption corridors’17,18, the ‘safe and just space of
humanity’19 and the ‘good life within planetary boundaries’20,21. These
approaches advocate reducing global energy use and associated emis-
sions and material use to a level compatible with planetary bounda-
ries
22,23
while ensuring that everyone’s human needs
24,25
are met. The
consumption corridor approach proposes to define minimum and
maximum thresholds between which consumption of goods and ser-
vices and related energy use and emissions can vary to achieve needs
satisfaction for all within ecological limits without harming other peo-
ple’s ability to fulfil their needs now and in the future17,18. The literature
stresses that consumption thresholds must be developed through
democratic and participatory decisionmaking18,26,27.
Equitable EDR would therefore target high energy users to bring
energy use and associated emissions within planetary limits and ensure
that everyone’s basic energy needs are met. In large parts of the world,
basic energy needs remain unfulfilled
28
. Because needs satisfaction
is relative, shaped by social context, high levels of fuel and transport
poverty, and hence unmet needs, continue to exist in countries of the
Global North
14,29,30
. In the long term, provisioning systems
31
will have to
be transformed to facilitate needs satisfaction at lower levels of energy
Received: 12 December 2022
Accepted: 24 May 2023
Published online: 17 July 2023
Check for updates
1Sustainability Research Institute, School of Earth and Environment, University of Leeds, Leeds, UK. 2Institute for Transport Studies, University
of Leeds, Leeds, UK. 3Department of Geography, School of Environment, Education and Development, University of Manchester, Manchester, UK.
e-mail: m.m.buchs@leeds.ac.uk
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Analysis https://doi.org/10.1038/s41560-023-01283-y
total of domestic energy, travel, food and all other consumption. Our
analysis therefore covers all direct and indirect household energy use
and emissions.
To conduct this analysis, energy use and emissions are estimated
for a representative sample of households in 27 European countries
based on European Household Budget Survey (HBS) data. For 23
countries, 2015 data are used; 2010 data are used for Malta, Portugal,
Slovenia and the United Kingdom, which were not included in the 2015
dataset at the time of data acquisition. The dataset has a total sample
size of 275,614 households. Household energy use and emissions are
estimated by combining HBS expenditure data with energy and emis-
sions conversion factors derived from the multi-regional input–output
database Exiobase so that all indirect energy use and emissions can be
accounted for39.
Energy use is very unequally distributed in the 27 European
countries (Fig. 1 and Supplementary Table 1). The distribution is most
unequal in the travel domain, where consumption by the top 10% and
20% of consumers accounts for 29.9% and 47.5% of total consumption,
respectively, while the bottom 50% of consumers are responsible
for only 20.4% of all consumption. Gini coefficients of 0.29 for total
energy, 0.41 for home energy, 0.32 for food-related energy, 0.47 for
travel-related energy and 0.35 for energy for ‘other’ consumption
confirm high levels of inequality, especially for travel. Supplementary
Fig. 1 and Supplementary Table 3 show Lorenz curves and Gini coef-
ficients per country.
Figure 2 shows considerable energy use and emissions reductions
from downscaling energy use of the top 10% or 20% of consumers to
the level of the 90th or 80th percentile, respectively. Reducing energy
use of the top 10% of consumers to the 90th percentile level leads to a
fall of ~2.50 EJ or 4.4% of total emissions, ~0.81 EJ or 6.0% of domestic
energy emissions and ~1.14 EJ or 8.3% of travel-related emissions across
all 27 countries. Reducing energy use of the top 20% of consumers to
the 80th percentile level has greater impact, resulting in a reduction
of ~5.4 EJ or 9.7% of total emissions, 1.6 EJ or 11.4% of home energy
emissions and ~2.3 EJ or 16.8% of travel emissions. In relative terms,
reductions are therefore particularly high in the travel sector because
energy and emissions intensities per unit of expenditure and inequality
use, but in the short term, facilitating needs satisfaction may require
an increase in energy use by those whose needs are not currently met.
Previous research has estimated energy requirements that are
compatible with climate targets while meeting people’s basic needs or
achieving certain wellbeing outcomes
3,32–35
. One previous study con-
cluded that while eradicating energy poverty globally would increase
global energy use by 7%, this could be counterbalanced by reducing
energy use of individuals who consume more than the European aver-
age by 15% (ref. 36). However, the emissions reduction potential of
equitable EDR, that is, cutting high-end energy consumption while
ensuring sufficient energy resources to ensure basic needs satisfaction,
has not previously been assessed.
This Article addresses this gap by first estimating emissions and
energy impacts from downscaling high-level energy consumption
across 27 European countries with and without increasing energy
use of low-end consumers with poverty-level incomes. Second, we
assess the contribution that such an equitable EDR strategy can
make to Europe staying within its globally equitable share of the
1.5 °C compatible global carbon budget of 500 Gt CO
2
equivalent
(GtCO
2
e; 2020–2050)
4
. Third, we discuss justice implications and
public acceptance of policies for equitable EDR. Our results show
that capping energy use of the top quintile of consumers across
27 European countries can achieve considerable GHG emissions
reductions of 11.4% from domestic energy, 16.8% from transport and
9.7% from total energy consumption. Increasing consumption of
low energy users in poverty only marginally reduces these savings
by 1.2, 0.9 and 1.4 percentage points, respectively. Additional high
annual emissions cuts of 7.3–24.0% would be required for Europe
to meet globally equitable 2050 emissions budgets. We argue that
equitable EDR could make an important contribution to increasing
public acceptance of such transformative action.
Emissions savings from equitable EDR
To illustrate emission reduction potentials of equitable EDR strate-
gies in Europe, we assess through microsimulation greenhouse gas
emissions reductions achievable by reducing high-level energy use in
27 European countries. Specifically, we model a reduction of energy
use of the top decile, quintile and above-mean energy consumers to
the level of energy consumption that is equivalent to the 90th / 80th
percentile of the household distribution or the mean of energy con-
sumption for different consumption domains (corresponding levels
of energy use in Supplementary Table 2). The 27 countries consist of
the pre-Brexit European Union except Austria, which was not included
in the dataset. This study focuses on Europe to understand the scale
of reduction required from countries with high current and historical
contribution to climate change13.
In addition, we assess whether overall emissions reductions can
still be achieved if energy use of the bottom 20% of consumers with
poverty-level incomes is raised to the 20th percentile of energy con-
sumption of the whole sample. Choosing this definition of ‘low energy
consumption’ is motivated by the assumption that low energy users in
poverty are more likely to have unmet needs due to involuntarily low
consumption compared to low energy users who are not in poverty.
On the basis of our dataset, the following percentages of households
in the bottom 20% of energy users are in poverty: 33% for home energy,
36% for transport and 49% for total energy.
The chosen thresholds of high and low energy use have only
illustrative purpose for assessing emissions savings from a more
equitable EDR approach. The thresholds of the top 10% / 20% and
bottom 20% of energy consumers have been chosen because they
represent typical thresholds in inequality research37,38. We acknowl-
edge that in practice, thresholds would need to be chosen through
democratic processes. Thresholds are defined separately for each
country. Reductions are assessed for total emissions and energy use
and for four separate consumption domains, which add up to the
0
0.2
0.4
0.6
0.8
1.0
Cumulative proportion of energy
0 0.2 0.4 0.6 0.8 1.0
Cumulative population share
Home energy Travel
Food Other
Total Equality
Fig. 1 | Inequality of energy use in 27 European countries. Lorenz curves for
energy use related to home energy, travel, food, all other and total consumption.
Lorenz curves depict cumulative shares of energy use compared to the
cumulative share of population. Data: EU HBS 2015, 2010; Exiobase 3.7. The
calculations include positive observations (across all consumption domains
combined) and exclude the top 1% of outliers to address the infrequency of
purchase problem. Sample size: 197,739 households.
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Analysis https://doi.org/10.1038/s41560-023-01283-y
in consumption are highest in this domain. Supplementary Fig. 2 pro-
vides energy reductions in percentages.
A more radical downscaling of energy use above the mean to
the mean (which applies to 42% of households in the sample) would
result in a reduction of 12.1 EJ or 22.1% of total emissions, 3.5 EJ or 24.2%
of home energy emissions and 5.6 EJ or 40.5% of travel emissions.
Figure 2 also presents reductions for food and other consumption
and reductions in all consumption sub-domains expressed as a percent-
age of total emissions.
Scaling up energy use of the bottom 20% of energy consumers who
have poverty-level incomes to the level of the 20th percentile of energy
consumption slightly increases emissions and energy use by ~0.13 EJ or
1.2% of home energy emissions, ~0.15 EJ or 0.9% of travel emissions and
~0.81 EJ or 1.4% of total emissions. Combining high-end reductions with
increases at the bottom end therefore still leads to an overall decrease
in emissions. For instance, reducing energy use by the top 20% of con-
sumers to the 80th percentile while raising energy use by the bottom
20% of consumers in poverty to the 20th percentile results in overall
cuts of 4.62 EJ or 8.3% of total emissions, ~1.44 EJ or 10.2% of domestic
energy emissions and 2.16 EJ or 15.8% of travel emissions (Fig. 2).
Equitable energy reduction scenarios
Equitable EDR needs to consider not only equitable reductions within
countries or regions but also globally equitable distributions of
energy use and emissions. We therefore present annual and cumu-
lative emissions scenarios from 2020 to 2050 to assess whether the
equitable energy reduction approaches described above fit within
the remaining carbon budget for the 27 European countries. The
Sixth Intergovernmental Panel on Climate Change (IPCC) Assessment
Report4 identified a remaining global carbon budget of 500 GtCO2e
that is compatible with a 50% chance of limiting global warming to
1.5 °C. We apply two definitions of the remaining carbon budget for
the 27 European countries. The first, equal per capita (EPC) budget
represents the 27 countries’ share of the global IPCC budget based on
their share of the global population (35 GtCO
2
e). The second, Green-
house Development Rights (GDR) budget, is based on GDR budgets
calculated by Robiou du Pont et al.
8
, which we adjusted to the updated
global IPCC budget (15.1 GtCO2e). Three cumulative emissions sce-
narios are examined to assess reductions from cutting energy use by
the top 10% and 20% of energy consumers and those above the mean
with and without increasing energy use by bottom-end consumers
in poverty (Fig. 3).
Scenario (1) assesses an initial energy use reduction of top-level
consumers in 2020 combined with an annual rate of emissions reduc-
tion of 1.4% for the whole population. This annual reduction rate is
equal to the average annual fall in emissions for the European Union
from 2010 to 201940. Scenario (2) also assumes an annual reduction rate
of 1.4% but reduces energy use by top-level consumers by an additional
10% every five years. Scenario (3) applies a set of different annual reduc-
tion rates that achieve the EPC and GDR budgets for Europe by 2050
with and without capping high-level energy use.
Results confirm that targeting energy demand from high-end
consumers contributes to meeting climate targets over time, while
increasing energy use by low-end consumers in poverty has relatively
small impacts on this reduction. However, all pathways within cumula-
tive emissions scenarios (1) and (2) exhaust the remaining EPC and GDR
budgets before 2050 based on the recent average annual emissions
reductions rate for Europe of 1.4%. For instance, the EPC budget for
Europe would be exhausted by 2031 if energy use by the top quintile of
energy consumers decreases to the 80th percentile of energy use and
if their emissions fall by an additional 10% every five years. Even cut-
ting energy use by above-mean consumers to the mean and reducing
their emissions by 10% every five years would exhaust the EPC budget
for Europe by 2038. Both of these examples assume that energy use
by the bottom quintile of consumers in poverty is lifted to the 20th
percentile. Not increasing energy use by these bottom quintile con-
sumers would only delay the transgression of the EPC budget by one
year, respectively.
a
Home
Travel
Food
Other
Total
0 10 20
Emissions reductions (%)
Of domain Of domain + poverty uplift Of total Of total + poverty uplift
30 40
Home
Travel
Food
Other
Total
Home
Travel
Food
Other
Total
b c
0 10 20
Emissions reductions (%)
30 40 0 10 20
Emissions reductions (%)
30 40
Fig. 2 | Emissions reduction of capping high-level energy use. Emissions
reductions as a percentage of emissions in different domains (home energy,
travel, food, all other consumption) and as a percentage of total emissions, with
and without increasing energy use by low consumers in poverty to the 20th
percentile (‘poverty uplift’). a, Emissions reductions of limiting energy use by
the top 10% of energy users to the 90th percentile. b, Emissions reductions of
limiting energy use by the top 20% of energy users to the 80th percentile.
c, Emissions reductions of limiting energy use by above-mean energy consumers
to the mean. Data: EU HBS 2015, 2010; Exiobase 3.7. Calculations exclude the
top and bottom 1% of emissions and income outliers and values at or below zero
to address the infrequency of purchase problem. Sample sizes: home energy
n = 259,921; travel n = 207,875, food n = 264,154, other consumption n = 266,222,
total n = 266,252 households.
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Scenario (3) presents pathways with annual reduction rates that
enable Europe to stay within globally equitable budgets. If energy
use by high energy consumers remains unchanged, annual emissions
reduction rates of 9.9% and 24.0%, respectively, would be required
to stay within the EPC and GDR budgets. Cutting energy use by the
top quintile of consumers to the 80th percentile would lower these
annual reduction rates by 1.2 and 2.3 percentage points, respectively,
and cutting energy use by above-mean consumers to the mean would
reduce them by 2.6 and 5.4 percentage points, respectively. Addition-
ally reducing emissions from above-mean users by 20% by 2025 would
lower the required annual reduction rate for achieving the GDR budget
by 11.5 percentage points (to a required annual emissions reduction of
12.5%). To put this into context, the average emissions reduction rate
for the European Union during the first year of the global COVID-19
pandemic was equivalent to 10.7% (ref. 40). Lifting energy use of low
consumers in poverty up to the 20th percentile would have only a rela-
tively small impact on these annual reduction rates of between 0.1 and
0.3 percentage points (Supplementary Table 4). These results suggest
that while targeting high energy use can help Europe to stay within
its globally equitable carbon budget, it is not a sufficient measure on
its own. However, targeting high energy users could be an important
step in increasing the willingness of closer-to-average energy con-
sumers to reduce their energy use and emissions, as it would demon-
strate that efforts are differentiated by previous contributions to the
climate emergency.
Fairness and acceptance of equitable EDR
To assess which types of household would most likely be affected by
measures that limit energy use of high-end energy consumption, we
conduct logistic regressions to determine which household charac-
teristics are associated with belonging to the top 10% and top 20%
of energy consumers on a per capita basis in different consumption
domains. Results, expressed as average marginal effects
41
, show that
in the aggregate sample, high income and high education significantly
increase the probability of belonging to the group of high-end total
energy consumers. Larger household size, presence of children, old
age and living in an urban area significantly decrease this probability.
These findings are consistent with previous studies on determinants
of household energy use or emissions42–44.
For instance, belonging to the fourth income quintile increases
the probability of being among the top 20% of total energy users by 19
percentage points compared with being in the bottom income quintile.
Belonging to the top income quintile increases this probability by 41
percentage points. Living in a household in which at least one member
has higher education increases the probability of being among the
top 20% of energy users by 3 percentage points, the same as having a
household representative who is employed.
Having an additional adult in the household decreases the prob-
ability by 8 percentage points, and the presence of at least one child
decreases the probability by 18 percentage points. Living in an urban
area decreases the probability by 2 percentage points (Fig. 4 and Sup-
plementary Table 4). Results also show that people with older or retired
household representatives are more likely to be high domestic energy
users but less likely to be high travel energy users, compared to the base
groups (Supplementary Table 5). Figure 4 confirms that the associa-
tion is strongest with income, while the effect of additional household
members reveals the role of economies of scale for energy use within
households.
Supplementary Table 6 shows that results are reasonably con-
sistent across countries, especially for income, number of adults and
presence of children. The association between high income and high
energy use is particularly strong in several countries with relatively
high income inequality such as Bulgaria, Spain, Croatia, Hungary, Italy
and Romania.
Questions remain around which policies would be best suited to
targeting high energy demand and whether the public would support
such policies. Public acceptance is an important factor for policymak-
ers to adopt policies45. To better understand this, we conducted four
deliberative workshops in England with 31 participants to assess public
perceptions of policy options for targeting high energy consumption.
The method of deliberative workshops is informed by the idea of delib-
erative democracy
46
and is intended to provide space for deliberation
by participants with a broad range of energy-consuming practices and
related attitudes (see Methods). There are strong reasons for public
deliberation and participation in deciding what measures should be
taken to change energy consumption46. In part, this is because everyone
is affected by the nature of the measures taken to reduce energy con-
sumption and the consequences of failure to mitigate climate change.
Moreover, understanding the implications of policy measures is not
solely the preserve of policymakers, scientists or academics. People
across society have insights into how their lives would be affected by
policy interventions.
Results reveal common reasons for support of and objection
to policies that target high energy consumption (further details in
Methods and Supplementary Information). Some of the main avail-
able policy options
47
for targeting high energy consumption were dis-
cussed, including (financial) (dis)incentives to adopt energy efficient
or lower emitting behaviours such as taxes on frequent flights, energy
or travel quotas or regulation that targets businesses. The arguments
that participants made for or against such policies centred on several
key themes, especially freedom and needs.
Some participants argued that policies that target high energy
use, for example, through quotas for flights or car mileage, would not
be favoured by the public as they would restrict freedom and choice.
Such policies were also deemed unpopular given that certain lifestyles
have become ‘part and parcel of what people are able to do these days’
(workshop 4). At the same time, many participants supported measures
that would discourage or even ban energy consumption beyond a par-
ticular level, for instance, extensive business travel or family flights for
holidays beyond one or two per year. Here participants argued that the
climate emergency needs to be tackled urgently and that this is not pos-
sible if no restrictions are imposed. Several participants acknowledged
that regulations that limit ‘luxury’ energy use would treat everyone
equally and therefore fairly, which can be conducive to acceptance if
Fig. 3 | Equitable energy reduction scenarios in 27 European countries.
a,c,e, Annual total consumption-based household emissions in GtCO2e
2020–2050 in 27 European countries. BAU, business as usual. b,d,f, Cumulative
total consumption-based household emissions in GtCO2e 2020–2050 in
27 European countries. The orange line represents the carbon budget for the
27 European countries based on their EPC share of the 500 GtCO2e global carbon
budget defined by the IPCC4. The dashed orange line represents the GDR carbon
budget for the 27 countries based on Robiou du Pont et al.8 a,b, Scenario (1):
annual and cumulative emissions based on a one-off reduction of the top 10% and
top 20% of energy consumers down to the 90th and 80th percentile of energy
use, respectively, and reducing energy use above the mean to the mean, on top of
an annual emissions reduction rate of 1.4% (average reduction for the European
Union from 2010 to 2019). The top-end energy reduction scenarios without
‘poverty uplift’ (dotted and dashed lines) are compared with those that increase
energy use of the bottom 20% of consumers in poverty up to the 20th percentile
of energy use (solid lines and dashed-dotted line). c,d, Scenario (2): annual
and cumulative emissions based on the same parameters as scenario (1) but
with an additional emissions reduction of top-level energy consumers by 10%
every five years. e,f, Scenario (3): annual and cumulative emissions based on
annual emissions reduction rates (a.r.) that achieve the EPC and GDR budgets
for Europe with and without top-level reductions. The dashed line in e refers
to reducing above-mean consumption to the mean and an additional 20%
emissions reduction by this group in the first five years. Data: EU HBS 2015, 2010;
Exiobase 3.7. n = 271,277 households.
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good reasons are provided, as travel and other restrictions during the
COVID-19 pandemic have demonstrated.
Several participants stated that businesses should be regulated
to reduce emissions of the products and services they provide. While
regulation also restricts choice, it was considered fair and beneficial
for the environment to require everyone in society to purchase low
carbon products instead of leaving it to the market, so long as prices
were affordable or subsidized.
Participants supported policies that restrict high energy use when
low carbon alternatives are available. For instance, several participants
argued it would be fair to tax or even restrict frequent flights if train con-
nections are available or if people can holiday in their home country.
Much of the discussion on restricting high energy use through
quotas focused on differential needs. Many participants argued it
would be unfair to issue blanket energy rations, especially for neces-
sities such as domestic energy, because some people have higher
2020 2025 2030 2035 2040 2045 2050 2020 2025 2030 2035 2040 2045 2050
2020 2025 2030 2035 2040 2045 2050 2020 2025 2030 2035 2040 2045 2050
2020 2025 2030 2035 2040 2045 2050 2020 2025 2030 2035 2040 2045 2050
4.0
a
3.5
3.0
2.5
2.0
Household emissions (GtCO2e)
Household emissions (GtCO2e)
1.5
1.0
0.5
0
4.0
3.5
3.0
2.5
2.0
Household emissions (GtCO2e)
1.5
1.0
0.5
0
4.0
3.5
3.0
2.5
2.0
Household emissions (GtCO2e)
1.5
1.0
0.5
0
Household emissions (GtCO2e)Household emissions (GtCO2e)
100
EPC budget for Europe
YearYear
YearYear
YearYear
GDR budget for Europe
80
60
40
20
0
100
80
60
40
20
0
100
80
60
40
20
0
b
c d
e f
Equal per capita budget for Europe
Legend in a
No top-level reduction, 9.93% a.r., EPC
No top-level reduction, 24.00% a.r., GDR
Top 20% reduction, 8.78% a.r., EPC
Top 20% reduction, 21.70% a.r., GDR
Above mean reduction, 7.29% a.r., EPC
Above mean reduction, 18.6% a.r., GDR
Above mean reduction, 12.5% a.r. + 20% 2020–2025,
GDR
GDR budget for Europe
BAU
Top 10% reduction and 20% poverty uplift
Top 10% reduction, no poverty uplift
Top 20% reduction and 20% poverty uplift
Top 20% reduction, no poverty uplift
Reduction to mean
Reduction to mean and 20% poverty uplift
No top-level reduction, 9.93% a.r.
No top-level reduction, 24.00% a.r.
Top 20% reduction, 8.78% a.r.
Top 20% reduction, 21.70% a.r.
Above mean reduction, 7.29% a.r.
Above mean reduction, 18.6% a.r.
Above mean reduction, 12.5% a.r. + 20% 2020–2025
Equal per capita budget for Europe
GDR budget for Europe
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Analysis https://doi.org/10.1038/s41560-023-01283-y
energy consumption requirements than others due to age or health
issues. Conversely, energy quotas were considered fair if allowances
for extra needs are available.
Discussion and Conclusion
Our results demonstrate that targeting high-level energy consumers
can achieve considerable emissions reductions in Europe. This finding
holds true even when the energy use of low energy consumers in poverty
is increased to aid needs satisfaction. Results show that equitable EDR
strategies in Europe would be defensible from a social justice perspec-
tive: targeting high-level energy consumers would mostly affect those
with high household incomes and higher education, while reducing
the risk of additional deprivation for the most vulnerable people in
society. Even though some potentially less-advantaged groups such
as people with older, retired or female household representatives are
likely to be affected by measures in specific consumption domains such
as domestic energy use, Supplementary Fig. 3 shows that low income
reduces the likelihood for these groups to fall into the top energy
use category.
Equitable EDR needs to consider not only equitable reductions
within countries or regions but also globally equitable distributions
of energy use and emissions. The scenario analysis in Fig. 3 dem-
onstrates that targeting top-end consumers can make a contribu-
tion towards meeting globally equitable carbon budgets but that
high annual reduction rates are required for Europe to meet these
targets. Decreasing energy use by above-mean consumers to the
mean, with an additional 10% fall in their energy use every five years
on top of an annual reduction rate of 1.4% for the whole population,
transgresses Europe’s per capita budget by 2039 (without ‘poverty
uplift’). If energy use of low consumers in poverty is increased to the
20th percentile, the budget would be transgressed one year earlier
by 2038. If energy use of high energy consumers is not targeted,
annual emissions reduction rates of 9.93% and 24.00%, respectively,
would be required to achieve the EPC and GDR budgets. Limiting
energy use of above-mean consumers to the mean and reducing
their emissions by an additional 20% in the first five years can reduce
the annual emissions reduction rate required for achieving the GDR
budget by 11.5 percentage points (to 12.5%). The scale of the required
additional demand reduction across the whole population, alongside
technological change, is evident if one recalls that emissions fell by
an average of 10.7% across the European Union in the first year of the
global COVID-19 pandemic40.
Achieving globally fair energy demand and emissions reduc-
tions in Europe therefore presents a major policy challenge. Delib-
erative workshops discussed the main available policy options for
targeting high energy use: taxation, quotas and structural change
through regulation or infrastructure improvements. While support
was expressed for regulations that create a level playing field and for
financial incentives and caps if low carbon options are available, res-
ervations were expressed that measures that target high energy use
would limit personal freedom. However, the deliberative workshop
results generally indicate support for a more equal distribution of
energy use. While targeting high energy users may not in itself be
sufficient for Europe to meet globally equitable carbon budgets,
targeting high energy users while supporting needs satisfaction
for all, thus creating greater equality in energy use, could increase
public acceptance of the need for additional rapid annual energy
demand reduction and technological change required for meeting
these targets.
A range of policy options are available for supporting those who
do not currently have the means to fulfil their basic energy needs. For
instance, the energy poverty and energy justice literatures propose
measures such as the provision of energy efficient social housing,
targeted subsidies for energy efficiency home retrofitting and public
transport, additional cash support through the social security sys-
tem, reduced energy or public transport tariffs for people on specific
benefits or the provision of Universal Basic Services for energy and
transport, which could include an allocation of a free basic amount of
renewable domestic electricity or public transport
14,48,49
. Allocating
equal per capita energy quotas as discussed in the deliberative work-
shops could also address energy poverty, especially if the allocation
accounts for special needs.
The deliberative workshop results indicate that policy framing
and communication are likely to be important vehicles to increase
public acceptance of EDR policies. For instance, common objections
against equitable EDR can be addressed by highlighting justice, health
and other co-benefits of reducing high energy consumption
50
and
the urgent need to act collectively while expressing sensitivity to dif-
ferentiated needs. However, the workshops did not discuss the scale
of change required for rich regions such as Europe to reduce energy
use and emissions in ways that are compatible with globally equitable
emissions budgets. Future research is required to examine how public
and political acceptance of reductions outlined in scenario (3) for
above-mean energy consumers can be supported.
Methods
Concepts
Debates about equitable energy demand reduction (EDR) are informed
by concepts such as ‘consumption corridors’17,18, the ‘safe and just
space of humanity’
19
and the ‘good life within planetary boundaries’
20
.
The proposal to reduce global energy use and associated emissions
to a level compatible with planetary boundaries
22,23
while ensuring
that everyone’s basic needs24,25 are met responds to a situation where,
globally and nationally, overconsumption is paired with undercon-
sumption. On the one hand, humanity as a whole, and countries in the
Equivalized income
quintiles = 2
Equivalized income
quintiles = 3
Equivalized income
quintiles = 4
Equivalized income
quintiles = 5
Number of adults
Children present
35−64
65+
Female
Not working
Retired or long-
term sick
Higher education
Household characteristics
Urban
0 0.1 0.2 0.3 0.4
Top 10% Top 20%
Top total energy consumption
Average marginal eects
Fig. 4 | Relationship between household characteristics and high per capita
energy use. Average marginal effects from logistic regressions on belonging to
the top 10% and top 20% of total energy consumers. Coefficients represent the
change in probability of belonging to the top 10% / 20% of energy users compared
to the base category. Base categories are: bottom income quintile; age group
35–64; male household representative; household representative not employed;
no one in household has higher education; rural location. The significance of
coefficients is assessed with the z statistic, and the significance of the overall
model with the Wald Chi-square statistic. Data: EU HBS 2015, 2010; Exiobase 3.7.
The calculations exclude the top and bottom 1% energy consumption and income
outliers and countries for which information in education and employment
status is missing (Supplementary Table 5). n = 208,539 observations.
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Global North in particular, are exceeding planetary boundaries
20,21
.
On the other hand, basic needs of disadvantaged people within rich
countries, and of large proportions of people within countries in the
Global South, fail to be met28,51.
Defining minimum levels of consumption has a history, building
on theories of human needs
24,25
. These theories distinguish needs from
wants or desires and identify a set of universal needs and culturally
and historically variable needs satisfiers that must be met to enable
adequate participation in society
24,25
. Examples of approaches that
define minimum standards of consumption are the Minimum Income
Standard that has been applied since 2008 in the United Kingdom and
the Reference Budget Framework that has informed work on minimum
consumption budgets in the European Union since 201052.
Setting upper limits for consumption is a more recent idea, and
more controversial because it seems to conflict with individual free-
dom. Conceptually, the proposal draws on conceptions of positive
freedom, which maintains that everyone has the right to have their
basic needs fulfilled and a duty not to harm others’ rights to needs
satisfaction, now and in the future17,18. Consumption that contributes
to exceeding planetary boundaries can thus be regarded as infring-
ing on other people’s rights to needs satisfaction, especially those of
future generations. Some justifications for upper consumption limits
rest on research that finds energy consumption above certain levels no
longer contributes to substantial increases in human wellbeing
35
. The
consumption corridor and needs satisfaction literatures stress that
lower and upper limits of consumption would need to be democrati-
cally negotiated and adjusted over time18,26,27.
Previous research has proposed a range of estimates for global
energy requirements related to satisfying basic human needs in the
future supported by advanced technological development and/or
reduced energy demand through behaviour change, for instance of
15.3 GJ per capita (2050)
32
, 26.1 GJ per capita (2050)
2
or 42.4 GJ per
capita (2040)
53
. (Note that per capita figures for 2050 are calculated
from total global energy use estimates of 245 EJ in Grubler
2
and an
assumed global population of 9.7 billion; figures for 2040 are based on
an estimate of 390 EJ of total global energy use in International Energy
Agency (IEA)53 and a global population of 9.2 billion). Other research
assesses minimum energy requirements for needs satisfaction for
specific countries or regions
33,34
and/or for achieving specific wellbeing
outcomes such as life expectancy33,35.
It is currently unclear how much ‘room’ will be available between
minimum and maximum energy requirements where upper limits
should be compatible with planetary boundaries and not harm any-
one’s right to satisfy their needs, including for future generations.
Millward-Hopkins et al.
32
estimated that energy use could be minimized
to 15.3 GJ per capita per year by 2050 if current state-of-the-art low
carbon technologies replaced high carbon technologies and if energy
use were reduced to levels of basic needs satisfaction.
At current emissions intensity per GJ, maximum per capita energy
use equivalent to global per capita emissions compatible with 1.5 °C
equate to 25.3–29.1 GJ per capita per year (based on estimated annual
global per capita emissions within a 1.5 °C budget of 1.4 t per capita
per year and of 1.6 t per capita per year for a 2 °C budget
20,54,55
and an
emissions intensity of ~0.06 tonnes of CO
2
per GJ, using data from
the International Energy Agency56). This would not leave much room
between minimum and maximum thresholds, demonstrating the
urgent need for further decarbonization of energy supply and trans-
formation of provisioning systems31,57 to increase the available ‘room’
between minimum and maximum levels of energy use. The available
corridor may also depend on the level of inequality of energy use; Jac-
card et al.
58
found that near equality of energy consumption and rapid
improvements in the emissions intensity of energy could facilitate
higher levels of per capita energy use, and thus greater needs satisfac-
tion, at the same level of decarbonization, compared to more unequal
patterns of energy use.
For comparison, mean per capita total energy consumption across
the 27 countries included in this study was 122.5 GJ per year. Even energy
use at the tenth percentile of the energy consumption distribution
already stood at 52.7 GJ per capita per year (Supplementary Table 2).
This demonstrates the scale of necessary action for rich countries to
move energy use and emissions into the bounds of a globally equitable
consumption corridor.
Data
Quantitative analysis in this article utilizes data from the latest avail-
able 2015 European Household Budget Surveys (HBS) and Exiobase
3.7. The HBS provides detailed household expenditures in Euros for
23 European countries, harmonized and disseminated by Eurostat.
We add to the analysis four countries from the 2010 HBS dataset that
were not included in the 2015 version at the time of data acquisition
(Malta, Portugal, Slovenia and the United Kingdom). The total sam-
ple size for the 27 countries, which comprise the pre-Brexit EU-28
countries except Austria, is 275,614 households. The focus on Euro-
pean countries is useful for gaining insights into the scale of required
action within rich world regions with high historical responsibility for
climate change59.
We aggregate detailed expenditure variables into broader catego-
ries for home energy (including electricity, gas, other fuels such as coal,
coke and bottled gas), travel (including motor fuels, public transport,
air and sea travel), food and all other goods and services. Household
characteristics such as number of adults and children, age, gender,
education and employment status of the household representative are
created from the HBS member files. Household weights provided in the
HBS are applied throughout to account for sampling and response bias.
The multi-regional input–output analysis Exiobase dataset (ver-
sion 3.7) is utilized to estimate annual energy use (in GJ) and greenhouse
gas emissions (in tonnes of CO
2
equivalents) per household and per
person in the HBS39. Net energy estimates are used, which avoids dou-
ble counting from the conversion of primary into secondary energy
sources. To estimate emissions, we apply the Global Warming Potential
(GWP100) metric
60
to convert different greenhouse gases (carbon
dioxide, methane, nitrous oxide and sulphur hexafluoride) to CO2
equivalents for 2015 (2010 for the United Kingdom, Malta, Portugal
and Slovenia). Exiobase covers high sectoral detail (200 products), 49
countries (including all EU countries) and rest-of-the-world regions
and a wide range of environmental accounts39.
We use these data to estimate energy and greenhouse gas emis
-
sions for home energy, travel, food and all other consumption for each
country in 2015/2010 in Exiobase, based on 2015/2010 purchasers’
prices and accounting for global trade. We then divide energy and
emissions from Exiobase by HBS expenditure per category and country
to generate energy and emissions factors in GJ per Euro and kg CO2e
per Euro (Supplementary Table 7). Household expenditure is then
multiplied by these factors to estimate household energy consump-
tion and greenhouse gas emissions. Because expenditure in the HBS is
provided in Euros, this method corrects for differences in price levels
between countries. Lorenz curves and regression analysis are based
on per capita, not household values to account for household size;
per capita values are created by dividing household-level estimates
by household size. Person-based weights are applied in the analysis of
per capita figures where household weights provided by the HBS are
multiplied by household size.
Qualitative analysis draws on data
61
collected for the ‘high energy
consumers’ project of the United Kingdom Research and Innovation
(UKRI) funded Centre for Research into Energy Demand Solutions.
In this project, interviews were conducted with 31 high energy users in
England in 2021, followed by four deliberative workshops to explore
which energy-consuming activities exceed reasonable expectations
and which, if any, interventions might fairly reduce excessive energy
consumption. This paper utilizes the workshop data.
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Analysis https://doi.org/10.1038/s41560-023-01283-y
The method of deliberative workshops gave space for dis-
cussion by participants with a broad range of energy-consuming
activities and practices. This method begins from the idea of delib-
erative democracy, which holds that policies or other measures
can be considered fair on the basis of ‘justifiability to all affected’46.
A number of deliberative and participatory methods already aim to
inform climate change mitigation
62
. These include citizens’ juries
and assemblies such as the European Citizens’ Panels organized by
the European Commission and citizen climate assemblies in various
countries, including France, Ireland, Poland and the United King
-
dom
63
. However, deliberative events considering energy reduction
are, to date, limited in number and location and there is uncertainty
about whether they lead to more radical policy than would otherwise
be expected64. Yet, participation matters for legitimacy and prospects
of effective action. Despite their limitations, deliberative events
already held offer insights into the role that deliberative democ-
racy can take in setting boundaries for sustainable and fair energy
consumption.
As detailed in Table 1, deliberative workshop participants were
recruited such that each workshop represented one combination
of high/low consumption of domestic and travel-related energy.
The aim was to examine whether the views of reasonableness of
energy use and reduction policies varied across the groups. Each
workshop lasted for three hours, with seven to eight participants
in each and 31 participants in total. Two additional facilitators ran
smaller breakout sessions for most of the duration to facilitate
a better exchange of views. The participants were provided with
pre-workshop information on energy demand, the need for climate
mitigation and the four broad policy approaches of economic (dis)
incentives, rationing, structural change (for example, infrastructure
improvements and regulation) and behaviour change, including
the video at this link (https://mymedia.leeds.ac.uk/Mediasite/Play/
f6e8043b3b4241b39c1e0f968e3e54cf1d).
In recruiting the sample for the high mobility and domestic con-
sumption workshops, we used the 31 interviewees as a recruitment
pool who had been sampled by professional recruiter, QA Research.
These interviewees had been recruited as fitting the following criteria:
• Twenty high domestic and mobility energy-using households:
that is, monthly bills over £120 per month and car mileage
>10,000 miles per year, with additional sub-samples:
• Five super high domestic energy consumers (monthly energy
bills over £160 per month) and
• Five super high mobility households:
• One recruit with more than two personal vehicles,
• One household with three plus vehicles,
• One recruit driving >15,000 miles per year and
• Two recruits who take four plus annual return ights.
All recruitment factors applied to a ‘normal’ (that is,
pre-COVID-19) year.
Participants for the other three workshop groups were also
recruited by QA Research to reflect a mixture of levels of domestic
and transport-related household consumption.
Analysis
To assess inequality of energy use, we apply common procedures of
inequality analysis
65
. Lorenz curves, and our definitions of bottom
and top 10% / 20%, are generated by first sorting observations by their
energy use from the lowest to the highest and then dividing observa-
tions into ten (deciles) or five (quintiles) equally sized groups (for
example, in a sample of 1,000 households, each quintile group would
have 200 households). The lowest decile/quintile corresponds to the
bottom, and the highest decile/quintile to the top 10% / 20% of energy
consumers. This is done for each country separately.
Expenditure data that are collected through diaries are affected
by the ‘infrequency of purchase’ problem where some recorded expen-
ditures over-represent actual consumption during the observation
period and where zero expenditures are recorded even though the
household consumes these items using up stocks (these represent
‘false zero’ observations as virtually no household can live without
using home energy, food or transport). The top 1% of energy users per
country and observations at or below zero are, therefore, excluded
from the distributional analysis as including them would skew results
(the Methodological limitations section provides more details).
To assess inequality of consumption, mean energy use is calcu-
lated for each group and the whole sample (country-level values are
weighted by population shares), and multiples are calculated of energy
use of the top 10% and 20% of consumers compared to the bottom
50%. Energy use is also totalled up for each of these groups to calcu-
late shares of total energy use (Supplementary Table 1). On the basis
of per capita values per household, Gini coefficients are calculated
for total energy use and each energy domain, and Lorenz curves are
generated, depicting the cumulative share of energy use compared to
the cumulative share of the population (Fig. 1, Supplementary Table 1
and Supplementary Fig. 1).
Impacts of equitable EDR options are assessed through micro-
simulation and emissions scenarios from 2020 to 2050. High energy
users are defined as the top 10% and top 20% of household consum-
ers per country and consumption domain. Defining two thresholds
for ‘high energy’ use is useful for comparison. Our approach bears
similarity to common definitions of high and low income and wealth
groups, where official statistics customarily use the top and bottom
10% and 20% of the distribution as comparators37,38. However, choos-
ing an approach based on the distribution of consumption is only
one option for defining high energy users66. Therefore, the thresh-
olds of the top 10% and 20% of energy consumption adopted in this
article have only illustrative purpose; they are not intended to rep-
resent policy recommendations as, in practice, thresholds would
need to be negotiated through democratic processes. High energy
use could alternatively be defined with reference to remaining emis-
sions budgets and other planetary boundaries
66
. However, the diffi-
culty with this approach is that energy and emissions are not fixed as
Table 1 | Deliberative workshop participant recruitment
criteria
Workshop 1: Workshop 2:
High mobility, high domestic energy
consumption Low mobility, high domestic
energy consumption
Ten highest-consuming interviewees
targeted for re-booking in workshop 1. Min: 1×no car AND less than one
return light a year, on average
Min: 1×<5,000 miles per year AND
less than one return light a year, on
average.
Min 1×any mileage per year AND no
lights in last ive years, on average.
All: energy bills >£120 per month
Workshop 3: Workshop 4:
High mobility, low domestic energy
consumption Low mobility, low domestic energy
consumption
Every recruit its at least one of: Min: 1×no car AND less than one
return light a year, on average
3+ cars in household, 2+ cars
personally, 15,000+ miles car travelled
annually or 2+ return lights
Min: 1×<5,000 miles per year AND
less than one return light a year, on
average.
All: energy bills <£80 per month Min 1×any mileage per year AND no
lights in last ive years, on average.
All: energy bills < £80 per month
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the emissions intensity per unit of energy depends on technological
development.
This study defines low energy users who are at risk of having
unmet energy needs as the bottom quintile of consumers with equiv-
alized household incomes below the relative poverty line of 60%
of median equivalized income (based on the Organisation for Eco-
nomic Co-operation and Development (OECD) equivalization scale)
for each country. This group makes up 33% of the bottom quintile of
energy consumers for home energy, 36% for transport and 49% for
total energy. Focusing on this group was based on the assumption
that low energy use by those in poverty is more likely to be involuntary
compared to low energy use by wealthier people and thus likely to rep-
resent unmet needs. Alternatively, ‘low energy users’ could have been
defined as households in fuel or transport poverty based on the ‘low
income high cost’ approach
67,68
. This approach was deemed unsuitable
for the analysis of equitable EDR approaches because households in
‘low income high cost’ energy or transport poverty have mean energy
consumption above the sample average. In addition, it would have been
difficult to define equivalent groups for food, other consumption and
total energy use poverty. Observations at or below zero and the top
1% of the distribution are excluded in the definition of groups of high
and low energy consumers to address the infrequency of purchase
problem and avoid skewed results (Methodological limitations section
provides more details).
Equitable EDR options are then assessed through microsimula
-
tion by replacing, within each country and energy domain separately,
energy use by the top 10% and 20% of consumers with energy use at
the 90th and 80th percentiles, respectively, and by the bottom 20%
of energy consumers in poverty with energy use at the 20th percentile
(where, for example, the 90th percentile equates to the energy use of
the 900th household in a sample of 1,000 households). For the ‘mean’
model, energy use above the mean is replaced with mean energy use;
this applies to 42% of households in the sample.
Emissions reductions from capping high-level energy use are
assessed by allocating emissions of the household at the 90th or 80th
percentile to households in the top decile or quintile of emitters,
respectively, separately for each country and consumption category.
Because the households at the 80th and 90th percentiles of the energy
and emissions distribution are the same, this approach is equivalent
to calculating the emissions savings from reducing energy use by the
high-end consumers down to the 90th and 80th percentiles. Emissions
are then totalled up for each country and energy domain for (1) original
energy use, (2) energy use with capped top-level consumption and (3)
energy use with capped top-level energy consumption and increased
energy use of low consumers in poverty. Differences in emissions
(Fig. 2) and energy use (Supplementary Fig. 2) are then calculated
between (1) and (2) and (1) and (3) and expressed as a percentage of
original emissions and energy use.
Three emissions scenarios (Fig. 3) plot annual and cumulative
emissions from 2020 to 2050. All three scenarios assume a reduction in
top energy consumption in 2020, with and without increasing energy
use of low consumers in poverty, alongside an annual emissions reduc-
tion for the whole population of 1.4% in scenarios (1) and (2). Variable
annual reduction rates through which globally equitable emissions
budgets are achieved are applied in scenario (3). In scenario (2), emis-
sions of top-level energy consumers are reduced by an additional
10% every five years. The annual emissions reduction rate of 1.4% in
scenarios (1) and (2) equates to the average annual reduction rate for
the European Union between 2010 and 2019 (based on Eurostat data
40
).
The extent to which the energy demand reduction scenarios are com-
patible with globally equitable targets is then assessed based on two
different budgets for Europe. Each of these budgets assumes a global
carbon budget of 500 GtCO
2
e from 2020 until 2050 that the latest IPCC
report4 estimated to provide a 50% chance of not exceeding 1.5 °C of
global heating. The first equal per capita (EPC) budget calculates the
27-country share of the global IPCC budget based on these countries’
proportion of the world population in 2020, which was 7%. This results
in an EPC budget of 35 GtCO
2
e. The Greenhouse Development Right
(GDR) budget is based on Robiou du Pont et al.’s
8
GDR budgets. The
GDR approach, which was developed by Baer et al.
9
, is designed to
allocate carbon budgets equitably across countries in the world based
on capacity (wealth), responsibility (past emissions and projected
business-as-usual emissions) and need (population size). We adjust
Robiou du Pont’s GDR budgets to the updated global IPCC budget and
the period from 2020 to 2050 by calculating what proportion of their
EPC budget for the 27 European countries is represented by the GDR
budget (0.43). Our EPC budget of 35 GtCO2e is then multiplied by that
proportion, generating a GDR budget of 15.1 GtCO2e. For scenario (3),
annual reduction rates are calculated through which both of these
European carbon budgets can be achieved under different assump-
tions of energy use reductions among high-level energy consumers.
Logistic regressions are conducted to examine which types of
household might be most affected by policies that target top-end
energy consumers. Binary variables are created for belonging to the top
10% and top 20% of per capita energy users for each domain. Predictor
variables are: equivalized income quintiles (using the modified OECD
scale for equivalization and quintiles by country); number of adults;
presence of children (binary variable); age categories of 15–34, 35–64
and 65 and over; having a female household representative; employ-
ment status (working, not working but of working age, retired); having
at least one member in the household with a higher education degree
(binary variable); and urban vs rural area (binary variable). All models
control for country variables and exclude the top 1% of energy users,
and weights are applied throughout. Supplementary Table 4 presents
average marginal effects, which show the change in probability of
belonging to the top 20% of energy users in each domain compared to
the base category. Average marginal effects are based on computing
probabilities for each observation in the dataset for each characteristic
and then averaging these probabilities.
The data from the workshop deliberations were transcribed ver-
batim for analysis. The data were analysed through thematic analy-
sis, which identifies key themes in the text and interprets participant
statements
69
. Qualitative thematic analysis was conducted based on
thematic coding with NVivo software, with a focus on examining dis-
cussions about policy options for energy demand reduction. Initially,
a list of codes was developed deductively. Workshop headline codes
included ‘policy approaches’, ‘type of consumption’ and ‘views’. Addi-
tional codes were then generated through inductive analysis. A full list
of codes can be found in the documentation of the archived dataset.61
Study design, data collection and analysis methods for the qualita-
tive part of this study followed all relevant research ethics regulations
and guidelines. Ethics approval was granted by the Research Ethics
Committee for the Faculties of Business, Environment and Social Sci-
ences at the University of Leeds (application AREA 19-160). All of the
research participants provided informed consent for their participa-
tion, use of anonymized data in publications and data archiving.
Methodological limitations
The analysis in this article has several limitations related to data issues
and approaches to scenario assessments.
The analysis is limited by the quality of data provided by the HBS.
The HBS consists of country-level surveys on household expenditure
without full harmonization of data collection approaches across coun-
tries. Expenditure data are often collected through individual and
household-level expenditure diaries that are kept for short periods
of time, for example, one or two weeks (the period of data collection
varies by country). Short collection periods lead to the ‘infrequency of
purchase problem’
70
; some households may not record an expenditure
on certain items during the observation period, even though they
continue to consume these items using stocks.
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Analysis https://doi.org/10.1038/s41560-023-01283-y
Equally, some expenditures recorded during the observation
period are higher than the actual amounts consumed when purchased
stocks outlast the observation period (for example, a full tank of petrol)
or when items are purchased infrequently (such as flights, furniture or
appliances). While mean expenditure for the whole sample is assumed
to be balanced, distributional analysis is problematic because high
and zero values are inflated, over- and under-representing actual con-
sumption, respectively70. Measures of inequality are therefore highly
likely to be overestimated based on unadjusted expenditure data. To
address the infrequency of purchase problem, we use a more aggregate
approach in estimating energy and emissions intensities (for four
consumption categories instead of more disaggregate categories)
and values of zero and below zero expenditure (which arise when, for
instance, a household is in credit with an energy company) and the
top 1% of expenditure values per country and consumption domain
are excluded from the analysis. As a result, the measures of inequal-
ity and the assessment of potential emissions reductions that result
from capping the top 10% and 20% of energy consumption might be
underestimated in this paper.
Additional limitations arise from the fact that household carbon
and energy footprints are based on monetary expenditure instead of
actual physical consumption data
71
. For instance, products within the
same product category can have different energy and carbon foot-
prints that are not reflected in the price (for example, more expensive
local and organic food items might have a lower carbon footprint
than cheaper products). Energy and carbon footprints are therefore
probably overestimated for some expensive products (and hence for
wealthier households that are more able to purchase these products)
and underestimated for cheaper products (and less wealthy house-
holds). Existing literature discusses and assesses limitations associated
with expenditure-based approaches44,71.
It also needs to be noted that while the scenario data cover 27
European countries, the deliberative workshop data have been col-
lected only in England. It is likely that public attitudes to equitable
EDR policies vary across European countries, influenced by political,
economic and socio-cultural contexts. England, and the United King-
dom more widely, is often regarded as having a strong liberal orienta-
tion that emphasizes individualism and freedom but is also shaped
by a universal welfare approach as represented in the National Health
Service, which puts greater emphasis on equality and solidarity
72
. Both
of these traditions are likely to shape public opinion on EDR policies
in England in specific ways. Deliberative workshop results therefore
cannot be claimed to be representative of other countries. The work-
shop discussions focused on public attitudes and acceptance, but it is
acknowledged that policymakers will also have to consider efficiency
and effectiveness of policies in their decisionmaking. Because climate
change needs to be tackled globally, this type of analysis would very
much benefit from the inclusion of middle- and low-income countries.
This is currently not possible because there are no comparable data-
sets with household-level expenditures that cover a larger number of
countries. Creating harmonized household-level expenditure (or, even
better, consumption) datasets for a larger number of countries would
be an important first step for future research.
Reporting summary
Further information on research design is available in the Nature Port-
folio Reporting Summary linked to this article.
Data availability
Data used for this analysis are available from Eurostat (Household
Budget Survey microdata 2015 https://ec.europa.eu/eurostat/web/
microdata/household-budget-survey) and Exiobase (version 3.7) for
energy and emissions data (https://www.exiobase.eu/). Qualitative
workshop data have been archived with the UK Data Service and are
available from https://doi.org/10.5255/UKDA-SN-855789.
Code availability
MATLAB code for extracting energy and emissions data from Exiobase
and STATA code for the HBS analysis is available from the Research Data
Leeds Repository https://doi.org/10.5518/1352.
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Acknowledgements
We received funding from UK Research and Innovation, Centre for
Research on Energy Demand Solutions (project EP/R035288/1).
We would like to thank J. Anable who acted as research lead of the
transport and mobilities theme in the centre.
Author contributions
M.B. conceived the idea for the manuscript and designed the study.
M.B. analysed the quantitative and qualitative data. M.B. wrote and
revised the article. N.C., C.M. and K.L. designed the qualitative data
collection. N.C. and C.M. collected and archived the data. N.C.
and C.M. provided access to the working paper that describes the
qualitative collection for this study. D.I. and M.B. extracted energy
and emissions data from Exiobase. N.C., C.M., D.I. and K.L. provided
comments on the manuscript.
Competing interests
The authors declare no competing interests.
Additional information
Supplementary information The online version
contains supplementary material available at
https://doi.org/10.1038/s41560-023-01283-y.
Correspondence and requests for materials should be addressed to
Milena Büchs.
Peer review information Nature Energy thanks Marine Cornelis,
Dirk-Jan van de Ven and the other, anonymous, reviewer(s) for their
contribution to the peer review of this work.
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