The energy requirements of providing universal decent living in a ‘fairly’ unequal world

Ecological breakdown and economic inequality are among the largest contemporary global challenges, and the issues are thoroughly entangled – as they have been throughout the history of civilisations. Yet, the global economy continues toward ecological crises, and inequalities remain far higher than citizens believe to be ‘fair’. Here, we explore the role of inequality, alongside traditional drivers of ecological impacts, in determining global energy requirements for providing universal decent living. We consider scenarios from ‘fair inequality’ – where inequalities mirror public ideals – through a ‘fairly unequal’ world, to one with a ‘super-rich’ global elite. The energy-costs of inequality appear far more signi�cant than population: even fair levels increase the energy required to provide universal decent living by 40%, and a super-rich global 1% could consume as much energy as would providing decent living to 1.7 billion. We �nish by arguing that total population remains important nonetheless, but for reasons beyond ecological impacts.


Introduction
The issues of ecological breakdown and economic inequality have become increasingly prominent in recent decades, forming the focus of multiple UN Sustainable Development Goals and social movements from Occupy Wall Street to Fridays for Future.If the warnings of researchers studying the evolution of civilisations are to be believed, this is a welcome development.Some researchers suggest that both ecological overshoot and extreme social inequality tend to accompany the collapse of civilisations' collapse 1 -as the material basis for meeting human needs is eroded, those at the bottom immediately feel the effects; in contrast, luxury consumption of elites continues until the bitter end, furthering overshoot 2 .
Anxiety that civilisation is entering a period of severe decline isn't only found on the margins of academic discourse, and for the rst time the scale is global.Concerns about global ecological breakdown are longstanding, but societies have yet to summon the capacity to substantially reduce anthropogenic impacts.We remain headed towards a climate emergency 3 , while many other ecological impacts are at potentially catastrophic levels 4 .Researchers of Existential Risk have begun to take climate change seriously, highlighting the potential for climate impacts to cascade through food, provisioning, and political systems in ways that fragment the global cooperation required to address emissions 5 and heighten other existential risks (e.g.nuclear catastrophes) 6 .
Inequality is thoroughly entangled with these dynamics.Climate change and other ecological impacts are driven by the Global North and a uent populations elsewhere 7,8 , whose luxury consumption can be more di cult to decarbonise than that of those living at su ciency 9 .And in highly unequal societies -where resentment and mistrust are widespread and the basic needs of many unmet -ecological shocks are more likely to translate into socioeconomic instabilities or violent con icts 10,11,12 .The growing trend for global elites to purchase 'apocalypse real estate' in the apparent safe haven of New Zealand puts into sharp focus people's unequal capacities to adapt to ecological and socioeconomic instabilities.
Clearly, interrelations between ecological breakdown and inequality are complex.However, the nexus between ecological limits, inequality and social stability remains understudied.Global ecological limits themselves are widely researched 13 , and the implications for sustainable development of scenarios abiding by such limits are gaining attention 14,15,16 .Other research has explored current relationships between ecological impacts, inequality 17 , and well-being 18 , with some projecting relationships forward to assess how reducing inequality may effect ecological impacts 9,19,20 or to examine 'inequality corridors' 21 .Some have looked into the energy requirements of providing good living standards universally 22,23 .Far removed from such research (with one exception 24 ) are the social scientists investigating inequality tolerance and public notions of fair inequality 25 .But no studies have brought these elds together to consider scenarios where good living standards are provided to all within ecological limits, with inequalities low enough to ensure social stability.
Recently, we estimated that 40% of current global energy use would be su cient to provide universal decent living standards in 2050 -standards assumed a prerequisite for high well-being 22 .But the Decent Living Energy (DLE) model considered a strictly egalitarian, high-population world with state-of-the-art technologies deployed everywhere.Here the model is extended to investigate the impacts of inequality.Various futures are explored, from one of fair inequality to a fairly unequal world with inequalities closer to those found today, alongside worlds of differing technological ambition and population growth.Major novelties are the integration of public notions of fairness 24 (and the limits to inequality that follow), and a bottom-up modelling approach that allows inequalities to be implemented directly in material terms.The ndings put into context the energy-costs of inequality alongside the traditional drivers of population and technology.Moreover, they show these costs to be considerable.

Human well-being, decent living and energy use
A multiplicity of approaches have been used to explore the relationship between well-being and ecological impacts.One way these differ is in the concept of well-being employed.Some take broadly hedonic approaches, focusing upon happiness and subjective well-being (typically self-reported) 26 .Others take eudemonic approaches, considering multidimensional indicators of well-being informed by theories of human need 27 .Approaches vary further in their quantitative methods, which can be top-down or bottom-up.Top-down approaches use empirical data to investigate relationships between average national ecological impacts (e.g.energy use 28 ) and social outcomes (life expectancy 29 , Human Development Index 30 ).A key nding is that while some countries manage to achieve good social outcomes with low ecological-impacts, none do so within planetary boundaries 18,31 .
But an issue with top-down approaches is they inevitably start from observed relationships between social outcomes and ecological impacts, which emerge from current socio-political organisation with uneven global trade relations, high economic inequalities and the redundancies of consumer culture 32 .
This limits their ability to explore transformative futures 33,34 , where high social outcomes are secured universally with minimum impact.Bottom-up models can probe precisely such futures.They start from inventories of material consumption across key dimensions of human life -e.g.shelter, mobility, healthwhich together are assumed to meet human needs through providing decent living standards 35,36 .By estimating the energy-intensity of provisioning each aspect of these inventories, total energy requirements for a given population can be estimated.
Following pioneering work by Goldemberg et al. 37 , recent research has estimated the energy required to secure decent living standards in key regions 23 and globally 22,38

Modelling inequality (fair or otherwise)
An advantage of bottom-up models is that to study inequality, it must be explicitly incorporated.The DLE model included only need-based inequalities -colder climates were permitted higher energy use for heating; more sparsely populated regions more mobility.This work develops three less idealised scenarios (key features are summarised in Table 2) to compare with this strict equality: Table 1 Inventory of material consumption assumed to underpin decent living from Rao and Min 35 .Activity levels listed are those assumed for decent living standards (DLS) in the DLE model 22 , but in the three inequality scenarios developed here levels are varied for the categories indicated by triangles (note that for food, kcal/day are xed and GJ/kcal modi ed instead; see Supplementary Information).*** Large range as this varies with regional population density

DLS dimension Material requirements
The fair inequality scenario modi es the activity levels of Table 1 to mirror the fair levels of income inequality emerging from public value surveys 39 , expanding upon an approach recently developed for carbon-footprint models 24 (see Methods).Inequalities are applied only to private luxuries (indicated by red in Table 1) and within countries (between-country inequalities remain need-based).The decent living standards provide a oor on consumption for the lowest consumers.High-consumers aren't assumed to consume different goods, only more of what's in the inventory, making the results conservative.(It should also be noted that any notion of 'fair' inequality typically relies upon meritocratic values 25 , which are easily contested 40 ).
The super-rich scenario is identical to the fair inequality scenario, except for the top 1% in each country whose consumption of private luxuries is increased to that reported in a study of the carbon-footprints of the super-rich (see Supplementary Information).Essentially, this is a world of fair inequality for all but a small elite.Note, however, that the direct ecological impacts of the super-rich's lifestyles are a narrow conception of their in uence, which plays out more fully through political power and investments in destructive industries 41,42 .

Population and technology
To compare the energy-costs of inequality with those of other drivers of consumption, scenarios of differing population and technological ambition are also developed: For 2050 population, projections from the Shared Socioeconomic Pathways (SSPs) of the IPCC are used 44 .Putting aside massive catastrophes and global 1-child policies, the SSPs span the range of projections in the literature, which vary from ~8.4-10.1 billion depending upon compliance with educational & gender-equality related SDGs and how much the unmet-need for contraception remains unmet 45,46 .Here, the high population scenario uses SSP3 (10 billion in 2050) while for other scenarios SSP1 is used (8.5 billion in 2050).Estimates for global energy use scale almost linearly with population, but also vary with age composition and urbanisation.
For technology, the previous DLE model assumed universal provision of highly-energy-e cient, state-ofthe-art technologies that are either currently available or will likely become so before 2050.The same assumptions are made for this work across except in the current technology scenario, where ambition is reduced so energy-e ciencies re ect current best-practice.For example, while the DLE scenario assumes extremely e cient electric cars with a degree of automation for further e ciency bene ts, the current technology scenario assumes electric cars equivalent to the most e cient of those widely available now.This scenario thus remains highly ambitious, considering these technologies are deployed globally to all.

Estimates of global nal energy use
Global nal energy use in the new Decent Living Energy scenario is 125 EJ (Figure 1); ~70% lower than current levels.In the high population scenario this increases 18% to 148 EJ, due to the 16.7% increase in 2050 population from SSP1 to SSP3 and marginal ~1% increase in average per-capita energy use (largely due to less urbanisation).Energy use in the current technology scenario is higher still, increasing 47% to 183 EJ -a substantial change considering the conceptually small difference between this and the DLE scenario, but still under 50% of current global consumption.
Moving from the need-based inequalities of the DLE scenario to fair levels increases energy use by 40% (to 175 EJ); over twice the increase incurred by the high population scenario (Figure 1).Adding a superrich 1% of consumers increases energy use by a further 22 EJ, matching the increase of the high population scenario relative to DLE.This implies that the additional luxury consumption of the super-rich top 1% -above and beyond their consumption under fair inequality -uses as much energy as would providing decent living standards to the extra ~1.4 billion people in the high population scenario.Finally, energy use in the fairly large Inequality scenario reaches 269 EJ; over double the DLE estimate, even though global inequality remains small compared to today.
Despite the signi cant energy costs of inequality, 2050 energy use in all scenarios remains far lower than many projections.Even in their most ambitious scenarios, the International Energy agency project 2050 nal energy consumption of ~340-400 EJ, while some IPCC scenarios consistent with 1.5°C warming approach 500 EJ 15 .And hovering over such projections are feasibility issues and trade-offs relating to negative emissions 47 , systematic underestimations of rebound effects 48 , and, consequently, questions regarding the ability to decouple ecological impacts from economic growth 34 .The present results match these mainstream projections when scenarios are combined into a worst-case run -the fairly large Inequality, current technology and high population scenarios combined give 2050 energy use of ~460 EJ (Figure 1, right).

Energy inequality and composition
Globally, energy inequality in these scenarios is much lower than currently existing (Figure 2).In the fair inequality scenario, energy use of the global top 1% (39.4 GJ/cap) is 2.7 times that of the bottom 10% (14.6 GJ/cap) who are at decent living standards.This ratio falls just within an inequality corridor suggested for Europe 21 .In the super-rich and fairly large inequality scenarios, the ratio climbs to ≈20 and ≈7, respectively, thus remaining considerably lower than the current ratio of ≈50 43 .In absolute terms, energy use of the top 1% in the fair inequality scenario remains below that of the bottom 20% in advanced economies such as Germany, Italy and Japan (ibid).Energy use of the top 1% in the fairly large Inequality scenario (~105 GJ/cap) matches national averages in these same countries and is well below the current USA average.For the super-rich 1% (~300 GJ/cap) it's just below that of the current top 20% in the USA 43 .Finally, modelled energy use of those at decent living standards is similar to current averages in low-consuming countries of the Global South such as India, Tanzania and Ethiopia (15-17 GJ/cap).Of course, this doesn't imply decent living standards are being met here -indeed, the gaps are substantial 38 .
Gini coe cients of energy consumption in the fair Inequality, super-rich and fairly large Inequality scenarios are also much lower than the current global level (>0.5), but vary substantially across sectors (Figure 3, left).Shelter, water and mobility are where the largest energy inequalities are found -mobilityenergy in the super-rich scenario is most unequally distributed -while nutrition-energy is most equally distributed in all scenarios.The overall sectoral composition of energy thus changes across scenarios, with the shares of nutrition and public services falling with increased inequality while those of shelter and mobility rise signi cantly (Figure 3, right).Recent empirically-grounded simulations also show a prominent shift in energy consumption towards mobility under increasing inequality 9 .Note that the present results follow directly from the assumptions made when implementing material inequalities, however, the assumptions are guided by literature -particularly saturation points for each category (see Supplementary Information).
planning services may be diminished 52 .Second, those arguing overconsumption, not overpopulation, dominates ecological impacts reference the very low per-capita impacts in high-fertility regions today.But current consumption is irrelevant unless one condemns these populations to remain at their current living standards, which are incompatible with human ourishing.The important question asks what would be the ecological impacts of providing these people with good living standards, while reducing overconsumption of wealthy global populations.If living standards of the Global North and South converge (as they should), the impacts of an additional 3.5 billion in Africa and India by 2100 -the difference between SSP1 & SSP3 -become highly signi cant.Finally, however, this focus on impacts in relation to population growth distracts from the potentially larger issue of exposure to harm.Lower population growth in Africa, for example, may make little difference to global carbon emissions, but it would substantially reduce the population at risk of hunger in a warming world 53 .Moreover, while it's likely that lower population growth in poorer regions of the Global South won't slow the momentum of the global economy as it continues toward ecological crises 45 , such growth will leave far more people in the regions suffering the worst effects -and perhaps unable to escape, given the emergence of antiimmigration populist movements in the Global North that are driven, in large part, by discontent with current inequalities.
This work has probed the relationship between global ecological impacts, living standards, inequality, and public notions of fairness using a highly idealised model with many limitations.A concurrent advantage has been not being constrained by empirical data emerging from existing global political and economic structures, which have so far proven unable to respond to the urgency of climate breakdown.However, this leaves enormous scope for further studies to explore both the real-world potential to reduce global ecological impacts by reducing inequalities, and practical means of realising such futures.

Declarations
Acknowledgements removed for review]

Modelling Decent Living Energy
The approach used to estimate global energy requirements is bottom-up, and involves combining activity levels for each material dimension of decent living with associated energy intensities, before summing across dimensions to obtain total nal energy consumption.For example, for residential buildings, we have direct energy intensities for heating and cooling and indirect intensities of construction, all in MJ/m 2 , which can be multiplied by the assumed activity-levels, in m 2 /capita, to obtain energy use.The estimates thus include both direct energy use and the indirect energy required to produce products and infrastructures; the latter is divided by product/infrastructure lifetimes to give annualised values of unequally, provisioned via ine cient technologies, or directed towards energy services that are at odds with human well-being.

Modelling 'fair' inequalities
Social and political scientists have studied public attitudes to inequality in various ways.We draw upon data reporting people's 'ideal' income ratios between the highest earners and unskilled workers for 40 countries 39 , of which 39 overlap with the 120 considered here (Iceland accounting for the difference).
These ratios are lowest in Scandinavia and some Eastern European countries (at 2-3), higher in Germany and the USA (~7) and highest in Taiwan and South Korea (>10).Other important conclusions from this eld of research are that notions of fair inequality are surprisingly consistent across countries, socioeconomic status, and political identities 39 , and that almost all data suggests people signi cantly underestimate the extent of current inequalities 55 .
We follow Millward-Hopkins and Oswald (2021) 24 to convert these maximum income ratios into idealised distributions considered to describe public notions of fair inequality.The rst stage involves simplifying the approach by categorising countries as egalitarians, moderates or meritocrats, depending upon the level of inequality considered fair: egalitarians are countries where the reported ideal income ratio is under 4, moderates where it's 4-6, and meritocrats where it exceeds 6.We then produce idealised (lognormal) distributions for each group, at a resolution of deciles up to the top decile, which is split into the 90-95 th , 95-99 th , and top 1%.Again following Millward-Hopkins and Oswald, for the three fair distributions, ratios between the top 1% and bottom 10% are set to 2.5, 5 and 8 for egalitarians, moderates and meritocrats, respectively, leading to the distributions shown in Supplementary Figure 1 (see Supplementary Information).For the Fairly-large inequality scenario, these distributions are widened until the GINI coe cients of the distributions become 0.25, 0.35 and 0.45, respectively (up from 0.12, 0.21 & 0.26 in the fair inequality scenario), which together roughly span the range of national income GINI coe cients currently observed (see data.worldbank.org/indicator/SI.POV.GINI).
Sensitivity analysis shows our main results to hold even when these idealised distributions are parameterised differently, consistent with Millward-Hopkins and Oswald (2021).This leaves the major limitation being the amount of missing data -for 81/120 counties, largely in Africa and Asia -and we simply categorise these countries as moderates.Note, however, that the 39 countries for which we have data cover all six continents and include the world's major economies (e.g.China, the USA & most of Europe).

Implementing inequalities in material consumption
In Millward-Hopkins and Oswald (2021), these idealised distributions were taken as income distributions, then translated into expenditure distributions and onto carbon and energy footprints using input-output data.For the present model, however, these distributions must instead be translated directly into material consumption.
To this end, the idealised distributions are taken as dimensionless descriptions of relative consumption.
The distributions are thus applied linearly to private luxuries -housing size, car travel, air travel, hot water for bathing, energy-intensive foods, etc. -while retaining decent living standards as a oor on consumption for the lowest consumers.For housing, for example, the bottom 10% have 15 m 2 /cap of oor space, while the top 1% have 37.5 m 2 and 120 m 2 in egalitarian and meritocratic countries, respectively (i.e.15×2.5 and 15×8).Mobility is more involved, as increases in private road transport are assumed to displace public surface transport before total mobility increases (see the Supplementary Information for details, and Supplementary Figure 2 for an example).To ensure this linear scaling didn't result in unrealistic values -there's only so many ights even the richest may take each year, for example -a sense check was done on the resulting consumption, and limits de ned based upon the maximum expected even for the wealthiest (see Supplementary Table 3).For hot water, for example, a limit of 300 L/cap/day was applied, based upon owrates of modern luxury showerheads.As mentioned above, for the super-rich scenario consumption of the top 1% was increased further for housing and mobility, to levels based upon those reported by Otto et al. 56 (also detailed in Supplementary Table 3).
The major assumption thus underpinning this process is that the income inequalities people believe to be fair can be taken to describe the inequalities in material consumption people think fair.Clearly this assumption can be challenged.However, for the present modelling approach -which is absent of monetary values -this is the only viable option, and it can be argued a reasonable approximation, as biases pull in both directions: On the one hand, applying inequalities only to a subset of the dimensions within the DLE consumption basket of Table 1, and not considering how wealthier classes will consume other luxury goods, biases the model towards underestimating the material inequalities that accompany income inequalities.Similarly, some of the things assumed to be equally distributed in the inequality scenarios are not so in reality -wealthier classes may draw more upon educational and healthcare services, for example, with children attending schools with smaller classes, and more frequent use of medical care, directed not just towards health issues but also improvements (e.g.cosmetic surgery).On the other hand, however, income inequalities frequently manifest in ways that don't require additional material consumption -for example, expensive houses are of course not more expensive merely because they're larger, but due also to more exclusive locations.Such factors bias the present model towards overestimates, as a proportion of income inequality will not manifest anywhere in the material consumption that the model considers.
Assuming 10 m 2 of living space/capita plus 20 m 2 of communal space per 4-person household *** Activity levels here are not straightforward to de ne.

Figures
Figures

Figure 1 Total
Figure 1

Figure 2 Final
Figure 2

Table 2
43mmary of the key features of the six scenarios, with red text indicating key differences.thefairlylarge inequality scenario, within-country inequalities in consumption are widened until they're closer to current levels for income inequality.Again, the lowest consumers are at decent living standards and between-country inequalities only need-based, leaving global inequalities far lower than today; the global GINI coe cient of energy use in this scenario is 0.28, compared to 0.13 in the fair inequality scenario and the current level of 0.5243.Inequalities in this fairly large inequality scenario are somewhat arbitrarily de ned (see methods for more details), but can be understood to be midway between what people deem fair and what currently exist.