Climate change and the resulting global warming are forcing humanity to carry out what has come to be known as the energy transition. In the coming decades, this transition must, among other things, drastically reduce greenhouse gas emissions (GHG) into the atmosphere.
According to the Intergovernmental Panel on Climate Change (IPCC), the remaining carbon budget (RCB) at the beginning of this decade (year 2020) to limit warming to 1.5 °C with an 83 % probability is estimated at 300 Gt CO2 (Lee & Romero, 2023) (see table 1, (IPCC, 2021)). Given that historical CO2 emissions into the atmosphere over the past 170 years were 2390 Gt CO2, modern civilization has depleted 89 % of its total carbon budget.
Table 1. (IPCC, 2021)
The IPCC estimated in its latest assessment report (AR6) that global net anthropogenic GHG emissions were 59 ± 6.6 Gt CO2e in 2019 (Lee & Romero, 2023). Excluding CO2 emissions due to land use, land-use change and forestry (LULUCF), GHG emissions would be 52.5 Gt CO2e per year, of which 71 % are strictly CO2 emissions (37 Gt CO2, or 71 % of GHG emissions without LULUCF). This implies that, at this rate, humanity would exhaust the carbon budget to not exceed 1.5 ºC in just over eight years, and certainly before year 2030. This calculation does not include the need for complementary reductions in emissions of other greenhouse gases, such as methane, or the future management of LULUCF, which could also lead to negative emissions (capture of CO2). Some authors, on the other hand, already point out that the need to reduce CO2 emissions could be greater, given that the emission of aerosols into the atmosphere in recent decades has partially offset the effect of the emissions of the rest of the GHGs. The significant reduction in aerosol emissions in recent years linked to the new regulation of international maritime transport and the environmental improvement in China represent an environmental improvement that, paradoxically, will bring with it an increase in global warming as a collateral effect (Hansen et al., 2023).
Civilization as a whole must make a colossal effort, but the responsibilities are not equally distributed among regions of the planet. The IPCC tells us that in 2019 the East Asia region (mainly China) was responsible for 27 % of all net GHG emissions, while North America was responsible for 12 %, Europe for 8 % and Africa for 9 %. East Asia, however, is responsible for only 12 % of historical emissions, while Europe is responsible for 16 %, and North America for 23 %. The difference is more significant if the data are compared in per capita terms, taking as a reference the estimate based on the final consumption of the population (consumption-based emissions). According to the IPCC, in 2018 annual per capita emissions were 6.7 t CO2e in East Asia, 7.8 tonnes in Europe and 17 tonnes in North America (see Figure SPM.2 from (Shukla et al., 2022)).
Therefore, it seems that large countries such as China must greatly reduce their total emissions, but in individual terms (per capita) it seems logical to demand greater efforts from the populations of Western countries, which are also the ones that historically accumulate the highest emissions. This diversity of demands of efforts ultimately translates into a supposedly equitable sharing of humanity’s remaining carbon budget, which, as noted above, is around 300 Gt CO2 if we are to limit global warming to 1.5 °C.
However, the granularity of the analysis should also be increased within each region and country, since working with average values of large populations can hide significant inequalities. This much more granular analysis is being carried out by the World Inequality Lab, a centre for international economic and social research from the Paris School of Economics, and promoted by the French economist Thomas Piketty, among other academics. This centre researches economic inequality. One of its most recent studies (WORLD INEQUALITY REPORT 2022 (wir2022), (Piketty et al., 2023)) focuses on income, wealth and carbon inequality both globally and within each of the world’s major countries. The World Inequality Lab performs its calculations based on the use of environmental input-output (IO) tables. These tables make it possible to calculate the carbon emission content (and other environmental indicators, such as energy consumption, water, etc.) associated with the production of an economic sector, taking into account all the emissions used in the intermediate processes involved in the production of this sector, both in the country of production itself, and in other economic sectors abroad. This makes it possible to calculate the volume of emissions associated with the final consumption of households, the government sector and public and private investment in the economy, which in turn allows an estimate in per capita terms of the population’s carbon footprint, that is, with a perspective that includes the indirect impacts associated with consumption, even in countries other than the country of residence. By cross-referencing this data with other available data in relation to the distribution of wealth and income, the World Inequality Lab provides information on the distribution of carbon footprints for different centiles of the population. From this point on, we will not talk in terms of CO2 emissions, but of carbon footprint, which computes CO2 and other GHG emissions from the point of view of the population’s final consumption, regardless of where they are physically produced.
Table 6.5 of the aforementioned report presents details on the global distribution of the carbon footprint in the world. The average annual global carbon footprint per capita is 6.6 tonnes, but with an unequal distribution. While half of the population with the smallest footprint has an average of less than 2 tonnes per year (1.6 tonnes), the 10 % with the largest footprint exceeds 30 tonnes per year per capita, which is 4.5 times the world average. According to the calculations of the World Inequality Lab, the poorest 20 % of the world’s population (1,500 million people) have a footprint of less than 1.8 tonnes per capita per year, and about one billion people have a footprint of less than one ton per capita per year.
The WORLD INEQUALITY REPORT 2022 also collects estimates of the average annual footprints in per capita terms for different sections of the population according to their emission level for 26 relevant countries in the world (the results are shown in a table below). These sections are the bottom 50 %, the middle 40 % –this “middle” section is very upwards, since it goes from the 50 % centile to the 90 % centile– the top 10 % and within it, the top 1 %. These results show, for example, that while the average annual carbon footprint in Spain is 7.7 tonnes, the bottom 50 % of the population has a footprint of 4.6 tonnes and the top 1 % of 64.7 tonnes on average. The top 10 % have a total footprint as large as that of the entire bottom 50 %.
What has been explained so far would be enough to close this post at this point, concluding it with the following idea: the great inequalities that exist today in the world in terms of carbon footprint, not only among the different large regions and countries, but also, and especially, within each country, require that policies to carry out the energy transition start from the obvious fact of this inequality of responsibilities. Those whose consumption results in a larger carbon footprint are the ones that must make the greatest efforts in the transition. Otherwise, the transition will not be fair.
In this post, however, I will try to go a little further, supported by the work already done by the World Inequality Lab. Specifically, 1) I will provide information with greater granularity (greater detail) on the distribution of footprints within each country; and 2) I will contrast these footprints with the demand for emission reductions that humanity must face over the coming decades, in the energy transition.
1. In search of greater detail in the distribution of the carbon footprint within each country
The wir2022 provides, for Spain, the following carbon footprints according to the segments of the population: the average for the population of the whole country is 7.7 t CO2e; half of the population with the smallest footprint has an average of 4.6 tonnes; the next 40 % have an average of 8.3 t; and the last 10 % –the decile with the largest footprint– an average of 20.8 t. But within that last 10 %, the 1 % with the largest footprint has an average of 64.7 tonnes. It is observed, therefore, that each section considered presents a certain degree of inequality in the distribution of the footprint. If the 100 % centile has a footprint of 64.7 t, the 90 % centile has to have a footprint well below 20.8 t (we will see later that it does not reach 10 t), since that is the average of the decile that includes the 100th centile, with a much higher footprint. Similarly, it could be concluded that the footprint of the bottom decile, the 10 % of the population with the smallest footprint, must be lower than the average of the lower half, which is 4.6 t (we will see later that it is less than 3 t).
Can the carbon footprint of each centile be calculated, based on the available data? We will make an attempt, assuming that the carbon footprint as a function of the centile behaves reasonably, and then we will try to obtain that mathematical expression.
The carbon footprint should increase as the centile increases, but that increase tends to be faster and faster as we approach the last centiles. This behaviour could be modelled by the sum of three terms: a constant term, a linear term, and an exponential term. Mathematically, we put it like this:
Carbon Footprint = a0 + a1·x + a2·exp((x-a4)/a3)
The ai coefficients are in principle unknown, but they can be obtained by means of an optimization algorithm that I have developed for this purpose, applying as boundary conditions the five carbon footprints provided in WIR2022. This optimization algorithm is available through this link. In the case of Spain, the five coefficients obtained are, respectively, 2.5044, 8.2182, 3.0705, 0.01377 and 0.9605. The average error obtained when recalculating the footprints for each of the sections whose footprint is the starting data turns out to be practically negligible, so the distribution obtained could be a good approximation to the one sought. The following figure shows the curve of the distribution obtained, for Spain.
In the distribution obtained, the 1 % centile (the population with the smallest footprint) has a footprint of 2.6 t; the 10 % centile of 3.3 t; and the 50 % centile of 6.6 t. In fact, you have to climb to the 63 % centile to find a footprint equivalent to the average footprint of the entire population (7.7 t). In other words, 63 % of the population has a footprint below the total average. You have to climb to the 98 % centile to reach the carbon footprint corresponding to the average of the highest decile (≥ 90 %). The Gini index of this distribution is 31 %.
All these data are shown in the following table (also collected, with other calculations, in this spreadsheet), for the 26 countries included in the WIR2022 report. The first six columns of the table are the input data for our calculation algorithm. The following five columns collect the results provided by our algorithm: the Gini index calculated according to the distribution obtained; the carbon footprint of the 50 % centile (the median); the percentage of the total population that has a footprint below the national average; the lower percentage of the total population needed to accumulate half of the total national footprint; and the ratio between the top and bottom decile footprints.
Internal inequality, within each country, from the point of view of carbon footprint is remarkable. The percentage of the population whose footprint is below the national average is always above 60 % (only Italy has a lower percentage, 59 %). European countries are around 62-63 %; and quite a few countries exceed 75 % (Brazil, Chile, India, South Africa). The data suggest that two thirds of the population has a footprint lower than the corresponding national average. And to accumulate at least half of each country’s footprint, we must add the footprints of around three-quarters of the population with the smallest footprint. The footprint of the other quarter of the population accounts for the other half of the total footprint. The inequality is also evident when looking at the ratio between the footprints of the top and bottom deciles (last column of the table). Even leaving aside countries with internal differences in the degree of development (China, India, Indonesia, Mexico, South Africa), with ratios that exceed 20 and even 30, the ratios in Europe are around 8; in Japan it is 10.5 and in the USA it is almost 18.
These data can only lead us to confirm what has already been said above: the carbon footprint is very unevenly distributed among segments of the population of all countries in the world, and therefore policies to carry out the energy transition must assume this obvious inequality of responsibilities and demand the greatest effort from those segments of the population with the largest carbon footprint.
It should also be noted that this estimate of the distribution of the carbon footprint within each country is surely conservative, if we look at the calculation procedure by the World Inequality Lab. The carbon footprint is calculated using environmental IO tables that provide the footprint of households, the government sector and the footprint associated with capital investment. The footprint is distributed among the population according to different criteria. The share associated with households is distributed according to income and consumption statistics; the part associated with private investment, depending on the distribution of wealth; but the part associated with the footprint of the government sector and public investment is distributed equally, for simplicity’s sake (Chancel, 2021). However, it seems clear that the sectors of the population with the greatest footprint, as they are also those with the highest consumption, income and wealth, will also benefit the most, in general terms, from public services and public infrastructures. The figure below shows the evolution of the footprints of these institutional sectors globally (Figure 4 of (Burq & Chancel, 2021)).
Therefore, it seems reasonable to assume that the degree of real inequality existing in the distribution of the carbon footprint within each country is at least slightly higher than estimated.
After these calculations, we are now in a better position to try to understand how efforts to reduce the carbon footprint in the energy transition should be distributed.
2. The distribution of the effort of the energy transition
As noted above, the IPCC estimates a surplus of the carbon budget in 2020 of 300 Gt CO2 to limit warming to 1.5 °C with an 83 % probability. In our spreadsheet (“Carbon_Budget_IPCC_2020-” tab) we have made the following calculation: we have calculated the percentage of annual reduction of the per capita carbon footprint in the world, so that the cumulative emissions since 2020 do not exceed that carbon budget of 300 Gt. To this end, we have assumed an evolution of the world population in accordance with the forecasts of the United Nations. The resulting evolution of the per capita carbon footprint in the world is shown in the figure below.
With an annual reduction of 11.7 %, cumulative emissions from 2020 would be 295.1 Gt in 2050, and 300 Gt in 2100. To limit these cumulative emissions, it would be necessary to reduce the carbon footprint from the level of 7.5 t CO2e/cap in 2020 (including LULUCF) to 2.2 t/cap in 2030, 0.6 t/cap in 2040 and 0.2 t/cap in 2050.
If cumulative emissions are higher, the chances of staying below 1.5 ºC are lower. The IPCC estimates a 50 % probability if the cumulative emissions amount to 500 Gt. It can be seen in the spreadsheet that this would require a reduction of 7.5 % per year. If the reduction is limited to 4.4 % per year, then cumulative emissions would reach 900 Gt, implying only a 17 % chance of staying below 1.5 °C, and the same chance of exceeding 2 °C (or 83 % of staying below 2 °C; see Table 1 above).
These calculations assume that emissions begin to fall in 2021, which we already know has not happened. If we delay the start of the reductions to 2025 by maintaining the 2020 emissions level (37.1 Gt CO2) until 2024, then the annual reduction needed from 2024 onwards would amount to 20.3 %, year after year (“Carbon_Budget_IPCC_2025-” tab). This highlights the need to start reducing emissions as soon as possible; the longer they are delayed, the greater the reduction effort must be. We could also see that the effort would have been significantly less if the reductions had started a decade ago.
How should this demand to reduce emissions affect the different sectors of the world’s population, given the enormous inequality of their carbon footprints? The table below can help us get an idea. It shows our calculation of the carbon footprint of the centiles of the 26 countries included in the wir2022 report. The values on a white background correspond to a carbon footprint higher than the world average in 2020 (7.52 t/cap, including LULUCF); The values on a red background correspond to a carbon footprint between the values expected for 2020 and 2030 (7.52-2.17 t/cap); the values in yellow with carbon footprints expected between 2030 and 2040 (2.17-0.62 t/cap); the values in green with carbon footprints lower than that expected for 2040.
It can be seen that a small part of the population of some countries such as Nigeria, Mexico, India and Indonesia already met the carbon footprint targets for 2040 in 2020. Much more of the population of these countries is already meeting the 2030 targets (in yellow), to which are added the lower sectors of countries such as Chile, China, South Africa, Turkey, Argentina, Brazil, Morocco, Algeria.
What is happening in the rest of the countries? Let’s take as a reference what would be the carbon footprint target for the year 2025, of 4 t/cap. It can be seen that 15 % of the population in France, 12 % in Germany and Great Britain and 18 % in Spain already met this target in 2020. However, most of the populations in these countries exceeded the global average footprint in 2020 (7.7 t/cap, values on a white background in the table). This sector of the world’s population –the one that in 2020 had a carbon footprint higher than the world average– should be the one that should assume emission reductions as a priority in the coming years. And the rest of the sectors should gradually join the reductions. If the transition is not implemented in this way, then it will not be fair; moreover, with the carbon footprints of the highest decile being so important in almost all countries, it would not be possible to meet the carbon budgets estimated by the IPCC either.
Our calculations tell that a transoceanic Berlin-New York journey by plane (round trip, 2×6400 km) generates a carbon footprint of 1.4 t CO2e. Every 10 thousand km travelled in a petrol vehicle generates a footprint of 3.3 t CO2e (if the car is electric and the electricity is renewable, 0.87 t CO2e; we cannot forget the manufacture of the car and the entire electricity generation infrastructure, or the construction and maintenance of the road). The carbon footprint of manufacturing a laptop can reach 200 kg CO2e, and that of a smartphone can exceed 40 kg. The consumption of 1 MWh of electricity that is only partly renewable can have a footprint that exceeds 300 kg. These data show that consumption levels (in transport, energy, consumer products) that are not very moderate will very quickly lead us to exceed our personal share of the remaining carbon budget. The energy transition must focus, above all, on those sectors of society whose lifestyles are above the carbon budget. In fact, even the European Union assumes that certain changes in lifestyles are inevitable in order to achieve transition scenarios compatible with 1.5 ºC of global warming (European Commission, 2018).
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