Climate injustice persists because those who are least responsible for emissions often bear the greatest consequences, both between and within countries. Extreme events caused by climate change have led to an average annual cost of $143 billion over the past two decades. How these costs should and could be covered – whether between or within countries – is a matter of debate. Central to this debate is the vast disparity between those responsible for emissions and those affected by their consequences.

New research published online May 7, 2025 in the journal Nature Climate Change quantifies this disparity and shows how greenhouse gas emissions from consumption and investment attributable to the wealthiest groups of the population have disproportionately affected current climate changeThe study linked inequality in emissions from 1990-2020 to regional climate extremes using a simulator-based framework.

The authors found that Two-thirds of global warming between 1990 and 2020 can be attributed to the richest 10% of the world's population, while the richest 1% accounts for one-fifth of this warming.. This means that the individual contribution of the richest 10 % is 6.5 times higher than the global average per capita, and for the richest 1 % this factor is even 20 times higher. If the entire world population emitted the same as the richest 10 %, the increase in global average temperature since 1990 would be 2.9 °C. If they emitted like the richest 1 %, the increase would reach 6.7 °C, and if like the richest 0.1 %, it would be as high as 12.2 °C.

Inequality is also evident in extreme climate events. When it comes to extreme heat (defined as 1 time in 100 years in the pre-industrial era), The richest 10 % (1 %) contributed approximately 7 (26) times more to the increase in monthly 1-in-100-year heat extremes worldwide compared to the average. In heavily affected regions such as the Amazon, Southeast Asia or Central Africa, the areas face up to a 30-fold increase in the probability of extreme hot months. The intensity of these extremes has increased by 0.83°C since 1990, with 0.55°C (0.17°C) of this increase attributable to the richest 10 % (1 %), which is 6.7 times (21.1 times) more than the global average.

For extreme drought (meteorological drought), the study found that the richest 10 % (1 %) contributed approximately 6 (17) times more to drought in Amazonia compared to the average. The Amazon region faces a threefold increase in the probability of extreme drought compared to 1990. It should be noted that robust drought attribution is more complex and strongly depends on the region and month.

The study also highlights significant cross-border impacts of emissions from wealthy groupsFor example, emissions from the richest 10 %s in the United States and China have led to a two- to three-fold increase in extreme heat in vulnerable regions such as the Amazon, Southeast Asia, and Southeast Africa. These cross-border contributions by wealthy individuals to worsening local extremes arise primarily through investment, not consumption.

The study findings underline that Low-income regions bear the brunt of the damage caused by emissions concentrated among the world's wealthier populations. This insight can contribute to the debate on climate justice and adaptation financing and loss and damage. Recognizing unequal contributions to warming can inform policy measures, such as the discussion of a coordinated global wealth tax that could reduce the widening gap in responsibility for climate impacts. Policies based on the “polluter pays” principle, including at the domestic level, can be an important basis for increasing support for climate action.

The authors note that their analysis has some limitations, including its reliance on consumption-based emissions accounting and use of a “what if” attribution method, as well as its failure to account for site-specific vulnerability and exposure. Nevertheless, Progress on frameworks for attributing emissions to individual emitters can inform global climate action and strengthen climate justice at a time of growing economic and climate inequalities. Spring

Glossary of key terms:

• Attribution science: A scientific framework used to determine the extent to which human activity may have influenced the likelihood or intensity of specific extreme climate events.
• CIF (Climate Inequality Factors): Climate drivers of inequality. The ratio of a population group's actual contribution to global warming (or extremes) to the contribution it would have if its per capita contribution were the global average. A higher CIF indicates a greater disparity.
• Counterfactual emission pathways: Hypothetical emissions scenarios, which are created by removing the emissions of specific groups or sectors over a certain period, in order to analyze how the climate would be different "if it hadn't happened."
• Climate Model Emulator: A more computationally efficient model that mimics the behavior of more complex Earth system models to generate large climate datasets at a fraction of the computational cost.
• Emissions based on consumption: Greenhouse gas emissions that occur during the production of goods and services consumed by a particular person or group, regardless of where the production took place.
• GHG (Greenhouse Gases): Greenhouse gases. Gases in the atmosphere that absorb and emit radiation in the thermal infrared range, causing warming. The main ones are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
• GMT (Global Mean Temperature): Global average temperature. The average temperature on the Earth's surface. The increase in GMT is a key indicator of climate change.
• Losses and damages: It refers to the impacts of climate change that go beyond what can be adapted to, and often refers to the financial and non-financial costs caused by these impacts, especially in vulnerable regions.
• MAGICC (Model for the Assessment of the Greenhouse Gas Induced Climate Change): A simple climate model used to translate emission scenarios into global climate indicators such as GMT.
• MESMER-M-TP (Modular Earth System Model Emulator for Monthly Temperature and Precipitation): An Earth System Model emulator used to generate gridded monthly temperature and precipitation data that statistically resemble data from complex models.
• PET (Potential Evapotranspiration): Potential evapotranspiration. The maximum amount of water that can evaporate from the surface and transpired from plants under given climatic conditions if sufficient water is available.
• SPI-3 (Standardized Precipitation Index computed over 3-month periods): Standardized Precipitation Index (calculated over 3-month periods). An indicator of meteorological drought based solely on precipitation.
• The "but for" method: An attribution approach that seeks to quantify changes in climate variables that would not have occurred "if not for" the emissions of a particular group.