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@@ -146,7 +146,7 @@ While the European Green Deal already recognizes that inequalities in income, en
 
 ## Income-stratified national household energy and carbon footprints
 
-We first used the EE-MRIO model EXIOBASE for 2015 (version3, industry-by-industry) [@stadler_exiobase_2018] and the European household budget survey (HBS) macro-data from EUROSTAT for 2015 [@eurostat_database_nodate] to calculate income-stratified national household energy and carbon footprints (together denoted as environmental footprints in this paper). The EUROSTAT HBS publishes mean household expenditure by income quintile, in purchasing power standard (PPS), by COICOP consumption category, country and year. We chose EXIOBASE as the EE-MRIO for this study because of its European focus, with nearly all countries in the EUROSTAT HBS also found as stand-alone countries in EXIOBASE (see SI, Table S5), its detailed environmental extension data, and its year coverage. 
+We first used the EE-MRIO model EXIOBASE for 2015 (version3, industry-by-industry) [@stadler_exiobase_2018] and the European household budget survey (HBS) macro-data from EUROSTAT for 2015 [@eurostat_database_nodate] to calculate income-stratified national household energy and carbon footprints (together denoted as environmental footprints in this paper). The EUROSTAT HBS publishes mean household expenditure by income quintile, in purchasing power standard (PPS), by COICOP consumption category, country and year. We chose EXIOBASE as the EE-MRIO for this study because of its European focus, with nearly all countries in the EUROSTAT HBS also found as stand-alone countries in EXIOBASE (see supplementary information (SI), Table S5), its detailed environmental extension data, and its year coverage. 
 
 To integrate HBS data into EXIOBASE we created correspondence tables between the EXIOBASE sectors and the matching COICOP consumption categories used in HBS (see SI, Table S4 for details). We then used the relative shares of the COICOP consumption categories of each income quintile in the HBS to decompose the matching EXIOBASE national household final demand expenditure per sector and per income quintile. Using standard input-output techniques (see SI) we calculated ‘total’ (i.e. direct and indirect supply chain) energy use and carbon intensities per EXIOBASE sector and multiplied them with the income-stratified EXIOBASE national household expenditure, to estimate the supply chain part of national household energy and carbon footprints by national income quintile. 
 
@@ -166,7 +166,7 @@ As inequality measure we use the 10:10 ratio, i.e. the expenditure or the enviro
 
 ## Computing maximum permissible inequality
 
-Based on an hypothetical current best technology distribution across European expenditure deciles, for each value combination of maximum energy supply from four scenarios [@riahi_shared_2017 @gea_gea_nodate] and minimum energy use requirements from Refs. [@grubler_low_2018 @millward-hopkins_providing_2020], the maximum permissible inequality was calculated as a 10:10 ratio using the formula [insert formula]. The remaining global emissions budget to achieve the 1.5 degree target from the scenarios was allocated in proportion to population (equal per capita allocation). All data and procedures are described in detail in the supplementary information (SI).
+Based on an hypothetical current best technology distribution across European expenditure deciles, for each value combination of maximum energy supply from four scenarios [@riahi_shared_2017 @gea_gea_nodate] and minimum energy use requirements from Refs. [@grubler_low_2018 @millward-hopkins_providing_2020], the maximum permissible inequality was calculated as a 10:10 ratio using the formula [insert formula]. All data and procedures are described in detail in the SI.
 
 # Results and discussion
 
@@ -515,7 +515,7 @@ exp_share_services_top_decile = round((pdat_basket %>% filter(eu_q_rank == 10, f
 
 Our results show that both of these factors play a role (Figure 2). The housing sector stands out with a carbon intensity of consumption more than 6 times higher in the bottom decile (`r int_co2eq_housing_bottom_decile` kgCO2eq/€) than in the top decile (`r int_co2eq_housing_top_decile` kgCO2eq/€). Housing has the highest variance in carbon intensity among expenditure deciles, and for the bottom deciles, it is the most carbon intensive sector. Overall, with increasing expenditure decile, the shares of mobility, services and housing expenditures increase and the shares of food and goods decrease. The bottom decile spent an average of `r exp_share_housing_bottom_decile`% of their household expenditure on housing, while the top decile spent `r exp_share_housing_top_decile`%. Households in the top decile spent about `r exp_share_services_top_decile`% in the services sector, which has the lowest carbon intensity of all consumption sectors, compared to `r exp_share_services_bottom_decile`% in the bottom decile. 
 
-The tendency for energy and carbon intensity to decrease with increasing affluence has been reported for the global level [@hubacek_global_2017] between countries and also within Europe [@sommer_carbon_2017 @bianco_understanding_2019]. Our results show that the four lowest European expenditure deciles make up 80% to 100% of the population in Poland, Romania, Bulgaria and the Czech Republic, while less than 20% of the population in the higher-income European countries (Scandinavia, Germany, France, Austria, the Netherlands, Belgium, the UK, and Ireland) are in the lowest European expenditure deciles. Note here that this does not imply that there are no high-income households in Eastern Europe. Our analysis is based on average expenditure data from national income quintiles. This aggregation cuts off the lower and higher tails of the respective national expenditure distributions (see SI - Supplementary Note and Map). 
+The tendency for energy and carbon intensity to decrease with increasing affluence has been reported for the global level between countries [@hubacek_global_2017 @berthe_mechanisms_2015 @scruggs_political_1998] and also within Europe [@sommer_carbon_2017 @bianco_understanding_2019]. Our results show that the four lowest European expenditure deciles make up 80% to 100% of the population in Poland, Romania, Bulgaria and the Czech Republic, while less than 20% of the population in the higher-income European countries (Scandinavia, Germany, France, Austria, the Netherlands, Belgium, the UK, and Ireland) are in the lowest European expenditure deciles. Note here that this does not imply that there are no high-income households in Eastern Europe. Our analysis is based on average expenditure data from national income quintiles. This aggregation cuts off the lower and higher tails of the respective national expenditure distributions (see SI - Supplementary Note and Map). 
 
 The high intensities in the bottom four European expenditure deciles can be attributed in large part to more inefficient and dirtier domestic energy supply and demand technologies for heating and electricity generation in Poland, Bulgaria, the Czech Republic, and Romania. Poland alone was responsible for about 40% of total coal combustion for heat production in Europe in 2015 [@eurostat_eurostat_nodate-2], and had a higher average intensity of carbon per MJ of heat delivered than both Europe and the world [@werner_international_2017]. We did not account here for subsidies which could also have attributed to high energy and carbon intensities (see SI limitations, pp xx). 
 
@@ -1004,11 +1004,14 @@ The colored curves in Figure 5 represent constant average household energy footp
 
 # Conclusions
 
-Estimates of energy and carbon footprint inequality are increasingly being used to assign responsibility for climate change. At a global, regional, and within-country level, energy use and carbon emissions are often highly unequal [@piketty_carbon_2015 @kartha_carbon_2020 @gore_extreme_2015 @hubacek_global_2017 @ivanova_unequal_2020 @gore_t._confronting_2020 @wiedenhofer_unequal_2017 @golley_income_2012 @steenolsen_carbon_2016 @weber_quantifying_2008 @hardadi_implications_2020 @oswald_large_2020]. The proposed solution is often a call to reduce the carbon or energy inequality by reducing over-consumption, especially by the richest at the top of the economic distribution, which would then also reduce the energy and carbon footprints, everything else held equal. Complicating this picture, however, is the fact that energy and carbon intensities of consumption usually differ between economic groups. This is due to different consumption baskets and different access to technology. That lower-income groups tend to have higher energy and carbon intensities is an important finding from the environmental Kuznet's curve literature [@berthe_mechanisms_2015 @scruggs_political_1998]. This finding has not yet been well integrated with the current carbon and energy footprint inequality literature, that focuses more on assigning responsibility based on aggregate energy and carbon footprint inequality. 
+To achieve the aggregated energy use targeted in the different 1.5°C compatible scenarios, the energy footprint needs to be reduced in all European countries, as well as almost all expenditure groups. The total energy footprint of households in the studied region must be reduced by 40% from 300 TJ (2015) to 200 TJ (2050). The GHG intensity of energy services needs to be reduced across all expenditure groups. The focus in the lower deciles should be on efficiency improvements and on absolute reductions in energy consumption in the upper deciles. Even under our bold assumption that the energy and emission efficiencies of the ten expenditure quantiles converge and demand develops as in the 1.5°C scenarios, our results show that a drastic reduction in the inequality of energy footprints is needed to secure decent living standards for all Europeans.
 
-In this study, we have found that, for Europe as a whole, lower-economic groups have higher energy and carbon intensities of consumption (although this is not necessarily true within each European country) [@sommer_carbon_2017 @kerkhof_determinants_2009]. These higher intensities come almost entirely from domestic electricity production and heating/cooling for housing, in a handful of Central and Eastern European countries. This is already an important focus of European climate policy, but reducing these intensities should be a major priority for investment fund allocation going forward, especially within a framework such as the EU's European Green Deal [@bianco_understanding_2019]. Efforts to break consumer lock-in to these high intensities must be occurring alongside policies that seek to reduce aggregate consumption and intensities higher up in the economic distribution [@royston_invisible_2018]. Bringing intensities of consumption for all economic groups in line with those of higher-economic groups in Europe with access to the cleanest and most efficient available technologies, would substantially reduce the European household energy and carbon footprints, everything else held equal. The unequal intensity structure hinders clear conclusions on footprint inequality. We have shown that in an important sector such as housing, lower-economic groups have almost the same level of footprint as higher-economic groups despite a fraction of the expenditure, because of their higher intensities. This can then be misleading in terms of assigning responsibility for climate change. Bringing energy and carbon intensities of all economic groups in line with the top group, and thus removing the inequality in intensity structure, would reduce the footprint, all else held equal, but *increase* energy and carbon inequality. The reduction of energy and carbon inequality is not a meaningful goal by itself. 
+This illustrates an immense political challenge: ensuring a decent life for all at the targeted energy level of the minimum consumption scenarios (X GJ per adult equivalent, down from an average of X GJ) requires a fundamental reorganization of almost all areas of life and economy. It seems hard to imagine how, for example, the living space per capita can be reduced from about 40m² to 15m², or the number of private cars can be reduced from X to X which are the assumption behind the [xxx] scenario. However, each increase in the minimum energy consumption for a decent life also increases the need to redistribute the energy footprint between countries and expenditure groups, i.e. to reduce energy inequality ever more drastically. Achieving this seems at least as difficult politically. This shows that, in addition to measures to reduce average energy consumption and emissions, instruments to reduce inequality in energy consumption must be developed to ensure a just transition that "leaves no body behind", as the European Green Deal promises. 
 
-Current consumption inequality, however, is a barrier to achieving both scenario targets *and* providing minimum energy use (and minimum carbon in the short-term) for decent living to every European. At a global level, there is concern that achieving extreme poverty eradication may put global climate targets at risk [@hubacek_poverty_2017 @woodward_incrementum_2015 @alfredsson_why_2018]. In the European context, although less unequal than the globe as a whole, if/as lower-consumption groups increase their income and consumption, energy use and carbon emissions will increase if more efficient and cleaner technology is not adopted at a fast enough rate [@gough_recomposing_2017]. Achieving an average per capita/adult equivalent energy and carbon footprint in Europe, in scenarios that reach the Paris agreement goals, means either doing so at current consumption inequality levels and keeping lower-economic groups near or below minimum energy use levels for decent living, or reducing consumption inequality. 
+Particularly in the coming phase of necessary restructuring of the European economy, a social protection mechanism of whatever kind assuring a decent life will play a central role. However, the current organization of the euro zone offers little monetary or fiscal leeway to member states, especially the less wealthy where this would be particularly important, to strengthen or introduce such measures. At the European level, implementation fails due to the lack of a common economic policy, as well as the fact that the ECB (unlike other central banks) only has a mandate to stabilize prices, but not to provide full employment or other effective means of social protection for European citizens. At least in the Eurozone, there is a great need for action to increase the scope for national and/or EU-wide policy making; both to ensure the social protection of citizens and to enable the necessary investments to restructure infrastructure and the economy.
+
+Strong progressive carbon pricing could have a positive distributional effect besides its effect on absolute emission reduction (MCC/Edenhofer). In addition, other distribution instruments such as a wealth tax, income tax or inheritance tax will have to be discussed in order to reduce the large differences in purchasing power within and between the countries of the EU, at least as long as expenditure remains coupled to environmental footprints. 
+Our study highlights the challenges largely implicit in the 1.5°C scenarios with respect to securing a decent standard of living for all, and provides further evidence that achieving this dual objective likely requires a shift in the current policy focus on growth in favor of decreasing environmental impacts and increasing social equity (Haberl, 2020, D’Alessandro 2020). Although our empirical investigation is limited to countries in Europe, we contend that our main conclusions apply in a similar or stronger form to the global achievement of climate and equity goals as articulated in the SDGs.
 
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