⚖️ Pinpointing Climate Damages to Corporate Emissions
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We've spent decades listening to fossil fuel companies talk about "shared responsibility" for climate change. They've perfected the art of diffusing blame – pointing fingers at consumer choices, technological limitations, and "market forces" while raking in record profits.
But what if we could scientifically trace specific economic damages back to specific corporate emissions? What if we could prove, with statistical significance, that Company X's emissions directly caused Y dollars in damage from a deadly heat wave?
That day has arrived.
A groundbreaking study published in Nature this April has established something once thought impossible: direct causation between corporate emissions and economic damages from climate-driven extreme heat. This isn't just academic posturing – it's the scientific backbone for a new era of climate accountability.
THE END OF PLAUSIBLE DENIABILITY
For decades, the fossil fuel industry's best defense was plausible deniability. "You can't prove our specific emissions caused that specific disaster," they'd argue. And legally speaking, they were right.
But science has caught up. Researchers Callahan and Mencken have pioneered what they call "end-to-end attribution" – linking the entire chain from a corporation's greenhouse gas emissions through climate system changes to specific economic damages on the ground.
Their methodology is rigorous enough to withstand scientific scrutiny: a three-step process using climate modeling, pattern scaling, and empirical damage functions. What makes this approach revolutionary is that it isolates the impact of individual companies through "leave-one-out" experiments – essentially running climate simulations with and without a specific company's emissions to determine their unique contribution to warming.
The result? Pure accountability.
THE $27 TRILLION QUESTION
The headline finding is staggering: $27 trillion in global economic losses from extreme heat between 1991 and 2020 can be directly attributed to the emissions of just 100 companies – the so-called "carbon majors."
Let that sink in. Twenty-seven trillion dollars. That's roughly 30% of the entire global GDP in 2020.
But it gets more specific: Gazprom alone is linked to over $1 trillion in losses. Saudi Aramco to $900 billion. American giants aren't far behind – Chevron's emissions caused $479 billion in heat-related economic damage, while ExxonMobil accounted for $364 billion.
These aren't speculative numbers. The researchers are so confident in their findings that they state the 99% confidence range for losses linked to each of the top five emitters doesn't include zero – meaning it's statistically impossible that these companies didn't contribute significantly to global heat damages.
THE INEQUALITY OF IMPACT
Perhaps most damning is how these damages are distributed. The study reveals annual GDP per capita reductions of over 1% across large swaths of the tropics – South America, Africa, Southeast Asia – just from the emissions of the top five companies.
Meanwhile, the United States and Europe – where many of these companies are headquartered – experienced relatively milder costs from extreme heat during the same period.
This isn't just climate change. It's climate colonialism.
The countries suffering the most severe economic impacts contributed the least to the problem. The corporate entities responsible for the emissions enjoy relative safety from the worst effects, protected by geography and wealth.
FROM THEORY TO COURTROOM
The legal implications are profound. This study was specifically designed to address the "but-for" test in legal causation: would these damages have occurred but for the actions of these specific corporations?
The research provides compelling evidence that they would not have. And it does so with sufficient scientific rigor to potentially withstand legal scrutiny.
We're already seeing early signs of this research influencing policy. Vermont's Climate Superfund Act aims to require major fossil fuel companies to contribute to a fund for climate damages in the state – an approach directly informed by this type of attribution science.
While legal hurdles remain – including questions about whether laws like the Clean Air Act preempt certain claims – the scientific foundation for climate liability is now firmly established. As the study's authors conclude, science is no longer the main barrier to making climate liability claims stick.
THE MINIMUM THRESHOLD FOR GUILT
One of the study's most intriguing findings concerns the minimum threshold for responsibility. Using the standard scientific significance level (p<0.05), they found that any entity responsible for at least 1.5% of global emissions since 1850 could be linked to detectable economic losses from extreme heat.
Under the looser "more likely than not" standard often used in civil litigation (p<0.5), that threshold drops to just 0.5% of historical emissions.
This creates a clear liability standard that could be applied in courts worldwide.
The study even analyzed specific historical heat waves – India in 1998, France in 2003, Russia in 2010, and the US in 2012 – calculating the economic damages attributable to specific companies for each event. For example, Chevron's emissions were linked to $1.2 billion in losses from the 1998 India heat wave and a whopping $7.2 billion from the 2012 US heat wave.
THE FUTURE OF CLIMATE JUSTICE
What makes this research so revolutionary is that it transforms climate change from an abstract, collective problem into concrete, individual corporate responsibility with specific dollar amounts attached.
It also raises profound questions about justice:
If we can scientifically prove that specific companies caused specific damages, shouldn't they be financially responsible for those damages?
Should corporations be liable only for emissions after they knew about climate change (the study suggests 1977 as one potential starting point) or for their entire historical emissions?
How do we balance the historical benefits we've received from fossil fuels against these massive negative externalities?
The legal and political landscape is still catching up to the science. But make no mistake: this research represents a fundamental shift in the climate accountability discussion.
The plausible deniability era is over. The excuse that "everyone is responsible, so no one is specifically responsible" no longer holds water scientifically.
WHERE DO WE GO FROM HERE?
Expect a wave of climate litigation armed with this new scientific ammunition. Legal systems worldwide will need to grapple with how to apply these findings in court.
For investors, this research drastically changes the risk profile of fossil fuel companies. When a single corporation can be scientifically linked to hundreds of billions in damages, the potential liability becomes an existential threat to business models.
For policymakers, this creates new pathways for targeted climate legislation that focuses on the specific corporations most responsible.
And for citizens concerned about climate justice, this research provides the evidence needed to demand meaningful accountability from the entities that have profited most from destabilizing our climate.
The $27 trillion question is no longer whether we can scientifically link corporate emissions to economic damages – it's whether our legal and political systems have the courage to act on what we now know.
The science is clear. The damage is quantified. The responsible parties are identified.
Now it's time for accountability.
Link References
Carbon majors and the scientific case for climate liability
REPLICATION FOR CARBON MAJORS AND THE SCIENTIFIC CASE FOR CLIMATE LIABILITY
Study lays out scientific path to recouping the costs of climate change
The world's biggest companies have caused $28 trillion in climate damage, a new study estimates
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STUDY MATERIALS
Briefing Document
Scientific Case for Climate Liability
Date: April 24, 2025
Subject: Review of recent research on linking corporate emissions to climate damages.
Sources:
"Carbon majors and the scientific case for climate liability," C.W. Callahan & J.S. Mankin, Nature (2025).
"Replication for Carbon majors and the scientific case for climate liability," C. Callahan & J. Mankin, IEEE DataPort (2024).
"Study lays out scientific path to recouping the costs of climate change," Dartmouth College (via Phys.org, 2025).
"The world's biggest companies have caused $28 trillion in climate damage, a new study estimates," S. Borenstein (via Phys.org, 2025).
Executive Summary:
Recent research, particularly a study published in Nature by Callahan and Mankin, strongly advances the scientific case for climate liability by providing a robust framework to link the greenhouse gas emissions of individual "carbon major" companies to specific, quantifiable economic damages from climate change. This "end-to-end" attribution method bridges the gap that previously hindered climate litigation by demonstrating a scientific basis for "but for" causation – proving that damages would not have occurred without a specific entity's emissions. The study estimates that the 111 largest carbon-oriented companies have collectively caused $28 trillion in global economic losses from extreme heat alone between 1991 and 2020, with over half attributable to just ten major fossil fuel firms. This scientific progress removes a key obstacle to the justiciability of climate liability claims, although legal and policy challenges remain.
Key Themes and Important Ideas/Facts:
1. The Scientific Case for Climate Liability is Now Closed:
The central argument of the Nature study is that "the scientific case for climate liability is closed." This directly addresses the question posed by Myles Allen in 2003 regarding the possibility of suing for climate damage.
Twenty years ago, quantitative linkages between individual emitters and particular harms were not feasible. Now, they are.
Science is no longer seen as "an obstacle to the justiciability of climate liability claims."
2. End-to-End Attribution Links Corporate Emitters to Specific Damages:
The study details an "end-to-end" attribution method that links corporate emitters to specific damages from warming, particularly focusing on economic losses from extreme heat.
This method uses emissions data from major fossil fuel firms, peer-reviewed attribution methods, and advances in empirical climate economics.
The framework is transparent, reproducible, and flexible, allowing for attribution of emissions contribution to specific harms.
3. Quantifying Economic Losses Attributable to Individual Firms:
The research provides specific examples of the estimated economic losses caused by individual firms. For instance, "Chevron, the highest-emitting investor-owned firm in our data, for example, caused between $479 billion and $1.8 trillion in heat-related losses over 1991-2020."
The study estimates that the global economy would be "$27 trillion richer were it not for the extreme heat caused by the emissions from the 100 carbon majors considered here." (Note: The Phys.org articles expand this to 111 companies and $28 trillion in total).
Specific firm examples include Gazprom ($1 trillion+ in global economic losses) and Saudi Aramco ($900 billion+).
Investor-owned companies (IOCs) are collectively responsible for $13.7 trillion in losses, while state-owned enterprises (SOEs) are responsible for $13.2 trillion (based on the top 100 firms).
These damage estimates are "virtually certain" for the top five firms, with the 99% range not including zero, even under a conventional scientific significance standard (p < 0.05).
4. The "But For" Standard and Causation:
A key aspect of the framework is its ability to establish "but for" causation, which is a crucial legal requirement for liability claims.
The scientific approach constructs a "counterfactual" world where a firm's contribution to local extreme heat change is removed, allowing researchers to "compare the world as it is to a world absent individual emitters."
This addresses the previous difficulty in providing both "general" (whether something causes a type of harm) and "specific" (whether a defendant's actions caused a particular injury) causation in climate litigation.
5. Methodology and Framework:
The end-to-end attribution method involves three steps:
(1) Emissions to Warming: Using reduced-complexity climate models (RCMs) like FaIR to translate firms' emissions into Global Mean Surface Temperature (GMST) changes.
(2) Warming to Hazards: Applying pattern scaling to calculate resulting subnational changes in extreme heat (defined as the temperature of the five hottest days, Tx5d).
(3) Hazards to Damages: Applying an empirical damage function to calculate income changes due to these extreme heat changes.
Uncertainties are propagated throughout the analysis to ensure robustness.
The method is adaptable and can be applied to various scales of emitters and claimants, and extended to other climate impacts beyond heat waves.
Replication materials, including scripts and data, are publicly available via IEEE DataPort, highlighting the transparency and reproducibility of the research.
6. Unequal Distribution of Causes and Consequences:
The analysis reveals "latent inequities in the causes and consequences of global warming."
Extreme heat from the top five emitting firms has driven significant annual GDP per capita reductions (exceeding 1%) across much of the tropics (South America, Africa, Southeast Asia).
Regions where major carbon majors are headquartered (United States and Europe) have experienced milder costs.
7. Event-Specific Attribution:
Beyond cumulative harms, the framework can also attribute damages from specific extreme heat events.
Examples include attributing losses from the 1998 Indian, 2003 French, 2010 Russian, and 2012 continental U.S. heat waves to the top five firms.
The contributions of individual firms vary depending on the specific event and their historical emissions profile.
8. Clarifying Responsibility and Evidentiary Standards:
The research offers an "emitter-agnostic" approach to assess who is most liable for impacts, helping communities identify potential defendants.
This involves determining the minimum percentage of global emissions required to have caused detectable harm from extreme heat.
The study highlights that evidentiary standards significantly influence attributed losses. Using the "more likely than not" legal standard (p < 0.5) increases estimated damages compared to the stricter scientific standard (p < 0.05). For example, BP's estimated damages jump from $27B to $1.1T under the lower legal threshold.
9. Remaining Work and Legal Considerations:
While science has advanced, legal and policy barriers to climate liability remain.
Key legal questions include the appropriate period over which emissions should be counted and how courts will handle these complex cases, particularly concerning the Clean Air Act and perceived judicial intervention in policymaking.
The study acknowledges that fossil fuels have provided economic benefits, but argues that these do not absolve companies of liability for negative externalities, especially given evidence of firms misleading the public about climate dangers.
Formalized communication and education between scientific and judicial communities are vital.
10. The Role of a Standing Scientific Body:
The authors advocate for a dedicated science-based enterprise to provide peer-reviewed, reproducible attribution analyses and expert testimony to support courts.
This could build upon existing initiatives like the World Weather Attribution.
Conclusion:
The Callahan and Mankin study represents a significant scientific breakthrough in climate attribution. By providing a robust and transparent methodology to link the emissions of individual companies to specific, quantifiable economic damages from extreme heat, it removes a major scientific obstacle that has historically hampered climate liability litigation. While legal battles and policy debates will continue, the scientific foundation for holding "carbon majors" accountable for the harms caused by their emissions has been firmly established.
Quiz & Answer Key
What is "end-to-end" attribution in the context of climate liability?
What is the "but for" causation standard in law, and how does attribution science aim to address it in climate liability cases?
What two recent scientific advances have made "end-to-end" attribution possible?
Describe the three main steps in the peer-reviewed end-to-end attribution method centered on extreme heat, as outlined in the Nature article.
What are "carbon majors," and why are they a focus of this research?
According to the study, approximately how much global economic loss from extreme heat over 1991-2020 is attributable to the 100 carbon majors considered?
How does the legal standard of "more likely than not" differ from the scientific standard of 95% statistical significance (p < 0.05) in the context of attributing economic losses?
How does the study account for the spatial and temporal dislocation between emissions and impacts?
What is Tx5d, and why is it a key metric used in the study's analysis of extreme heat?
Beyond extreme heat, what other climate impacts could potentially be incorporated into end-to-end attribution frameworks in the future?
Answer Key
End-to-end attribution links the emissions from specific corporate emitters to specific damages resulting from climate change. It aims to establish a causal chain from source emissions to observed impacts and economic losses.
The "but for" standard requires demonstrating that without the defendant's actions, the plaintiff would not have been injured. Attribution science helps by quantifying the contribution of specific emissions to climate change and resulting harm, attempting to isolate the role of individual emitters.
The two advances are the increased confidence in physical science to connect individual emitters to local climate change ("source attribution") and the improved ability of social science to connect local climate change to socioeconomic outcomes.
The three steps are: 1) using a reduced-complexity climate model (like FaIR) to translate firms' emissions into global mean surface temperature changes, 2) applying pattern scaling to calculate resulting subnational changes in extreme heat (Tx5d), and 3) applying an empirical damage function to calculate income changes due to these extreme heat changes.
"Carbon majors" are major fossil fuel firms (oil, coal, and gas producers) that have produced substantial emissions over time. They are a focus because their significant historical and ongoing emissions are major contributors to climate change and thus potential targets for liability claims.
The study estimates that the global economy would be $27 trillion richer were it not for the extreme heat caused by the emissions from the 100 carbon majors considered over 1991-2020.
The legal standard of "more likely than not" corresponds to an alpha of 0.5 (50% likelihood), which is a lower burden of proof than the scientific standard of 95% statistical significance (p < 0.05). Applying the legal standard can result in significantly higher estimates of attributable damages for individual firms compared to using the stricter scientific standard.
The study uses reduced-complexity climate models (RCMs) and pattern scaling to link global mean temperature changes from distant and past emissions to local temperature changes where impacts occur. It also uses empirically derived damage functions to quantify socioeconomic effects.
Tx5d stands for the temperature of the five hottest days in each year. It is used as a metric for extreme heat because empirical studies have shown a relationship between the intensity of these hottest days and changes in economic growth, particularly in warmer regions.
Beyond extreme heat, future end-to-end attribution frameworks could incorporate costs associated with other climate impacts such as extreme rainfall, floods, droughts, wildfires, sea level rise, and the effects of phenomena like El Niño.
Essay Questions
Discuss the historical evolution of the scientific case for climate liability, referencing the work of Myles Allen and the advancements detailed in the Callahan and Mankin study. How has attribution science progressed to the point where end-to-end attribution is now considered scientifically feasible?
Analyze the key scientific methodologies employed in the Callahan and Mankin study (e.g., FaIR model, pattern scaling, damage functions, Monte Carlo simulations) and explain how they are integrated to achieve end-to-end attribution. Evaluate the strengths and limitations of this approach in quantifying the economic losses attributable to individual carbon majors.
Compare and contrast the cumulative and event-specific frameworks for end-to-end attribution presented in the study. Provide examples of how each framework could be applied in different legal contexts and discuss the implications of using one over the other.
Explain the distinction between general causation and specific causation in climate liability cases and discuss how the findings of the Callahan and Mankin study address the challenge of establishing specific causation. How do the scientific standards of significance (e.g., p < 0.05) and the legal standard of "more likely than not" influence the quantification of attributable damages?
Beyond the scientific methodology, discuss the remaining legal and policy challenges to climate liability claims, as identified in the source material. Consider factors such as the appropriate time period for counting emissions, the "duty of care" argument, balancing the benefits and externalities of fossil fuel use, and potential legislative or judicial barriers.
Glossary of Key Terms
Attribution Science: A field of climate science that seeks to determine the extent to which human activities (like greenhouse gas emissions) have influenced the probability or magnitude of specific extreme weather events or long-term climate changes.
"But For" Causation: A legal standard requiring a plaintiff to demonstrate that their injury would not have occurred in the absence of the defendant's actions. In climate liability, it involves showing that a specific harm would not have happened "but for" the emissions of a particular entity.
Carbon Majors: Major fossil fuel producing companies (oil, coal, gas) and cement producers that are historically responsible for a significant portion of global greenhouse gas emissions.
Common Law: A body of law developed from judicial decisions and customs, rather than from statutes enacted by legislatures. Climate liability cases are sometimes pursued under common law theories like public nuisance or duty of care.
Counterfactual: A hypothetical scenario used in attribution science to compare the actual climate (with human influence) to what the climate would have been like without specific human influences (e.g., removing a particular emitter's emissions).
Damage Function: An empirical model that quantifies the economic or social impacts of changes in climate variables (e.g., relating changes in extreme heat to changes in economic growth).
End-to-End Attribution: A scientific framework that links specific emissions from a source (like a company) through the causal chain of climate change to specific damages or impacts.
Event Attribution: A type of attribution science focused on determining the human influence on the probability or intensity of specific extreme weather events (e.g., a particular heat wave or flood).
FaIR (Finite amplitude Impulse Response): A reduced-complexity climate model (RCM) used to simulate the Earth system's response to greenhouse gas emissions and other forcings, translating emissions into global mean surface temperature changes.
General Causation: In law, the question of whether something (e.g., asbestos exposure) is capable of causing a particular type of harm (e.g., cancer). Requires a high standard of certainty.
Global Mean Surface Temperature (GMST): The average temperature of the Earth's surface, a key metric used to track global warming.
IPCC (Intergovernmental Panel on Climate Change): The leading international body for assessing the science related to climate change. Its assessment reports inform climate science and policy.
Justiciability: The ability for a legal case or issue to be heard and decided by a court.
Leave-One-Out Experiment: A scientific experiment where a specific factor (e.g., the emissions of one company) is removed from a simulation to determine its contribution to the overall outcome.
Monte Carlo Approach: A computational method that relies on repeated random sampling to obtain numerical results, often used to estimate the range of possible outcomes when there are multiple sources of uncertainty.
Pattern Scaling: A statistical technique used in climate science to translate large-scale climate changes (like global mean temperature change) into regional or local climate changes, based on established relationships derived from complex climate models.
Reduced-Complexity Climate Model (RCM): A simplified model of the Earth's climate system that uses a smaller number of equations and is computationally less expensive than fully coupled Earth system models, while still simulating key climate behaviors.
Significance (Statistical): In science, a measure of the likelihood that an observed result is not due to random chance. A common threshold is p < 0.05 (less than a 5% chance of being due to random chance).
Source Attribution: A type of attribution science that links emissions from specific sources (like countries or companies) to their contributions to climate change metrics such as global mean temperature or sea level rise.
Specific Causation: In law, the question of whether a defendant's actions actually caused the particular injury experienced by the plaintiff. Often held to a "more likely than not" standard.
Standing (Legal): The requirement that a party bringing a lawsuit must have a sufficient stake in the outcome to be entitled to judicial relief. In climate liability, plaintiffs need to show a particularized injury caused by the defendant's actions.
Tx5d: The temperature of the five hottest days in each year, used as a metric for the intensity of extreme heat.
Timeline of Main Events
1850-Present: This period is relevant for calculating cumulative CO2 and CH4 emissions, as the "Carbon majors" study uses emissions contributions starting as early as 1850 for certain analyses.
1854: Emissions data from some fossil fuel and cement producers trace back to this year, as compiled by Heede.
1884: ExxonMobil begins operations and starts accumulating emissions data used in the study.
1912: Chevron begins operations and starts accumulating emissions data used in the study.
1913: BP begins operations and starts accumulating emissions data used in the study.
1920s-2020: This century saw significant emissions from major fossil fuel firms like Saudi Aramco, Chevron, and ExxonMobil, with average annual CO2 emissions in the hundreds of MtC.
1938: Saudi Aramco begins operations and starts accumulating emissions data used in the study.
1970s: Fossil fuel firms accurately predicted climate change and its consequences internally.
1971-2021: Total's responses to global warming during this period have been studied through archival methods, computational frame analysis, and interviews.
1977: ExxonMobil first successfully projected global warming. This date is considered as a potential starting point for calculating climate damages attributable to actors. Fossil fuel firms have since used their power and profit to cast doubt on the relationship between fossil fuels and warming.
1977-2014: ExxonMobil systematically cast doubt on mainstream climate science in the public sphere while internally acknowledging climate change and its consequences, according to research by Supran and Oreskes.
1979-2016: A panel regression analysis of observed Tx5d and GDP per capita growth in subnational regions globally during this period was used to derive the damage function for the "Carbon majors" study.
1989: Gazprom begins operations and starts accumulating emissions data used in the study.
1990: Around this year, a scientific consensus on climate change developed. This date is considered a potential starting point for calculating climate damages attributable to actors.
1991-2013: Gridded nighttime luminosity data from satellites during this period is used in the procedure to predict subnational GDP per capita.
1991-2020:This is the primary period over which the "Carbon majors" study estimates cumulative heat-related economic losses.
Chevron's emissions caused between $479 billion and $1.8 trillion in heat-related losses during this period.
The global economy would be $27 trillion richer were it not for the extreme heat caused by the emissions from the 100 carbon majors.
Gazprom was responsible for over $1 trillion and Saudi Aramco for over $900 billion in global economic losses from extreme heat (2020-equivalent $US).
Chevron, ExxonMobil, and BP caused $479 billion, $364 billion, and $28 billion in losses, respectively (at a significance threshold of p < 0.05).
Investor-owned companies were collectively responsible for $13.7T in losses, while state-owned enterprises were responsible for $13.2T.
Extreme heat from the top five emitting firms drove annual GDP per capita reductions exceeding 1% across much of the tropics.
Continuous time series of regional GDP per capita from this period are used in the final analysis of the "Carbon majors" study.
1998: The "Carbon majors" study quantifies the contributions of carbon majors to the India heat wave and the resulting economic losses.
2000 (Autumn): Anthropogenic greenhouse gas contributions to flood risk in England and Wales were studied.
2003:Myles Allen considered the limits of climate science and posed the question of climate liability in a publication.
The "Carbon majors" study quantifies the contributions of carbon majors to the European heat wave and the resulting economic losses, building on the first single-event global warming attribution study published in 2004 regarding this event.
2009: The Native Village of Kivalina v. ExxonMobil Corp. lawsuit was filed.
2010: The "Carbon majors" study quantifies the contributions of carbon majors to the Russian heat wave and the resulting economic losses.
2012: The "Carbon majors" study quantifies the contributions of carbon majors to the continental U.S. heat wave and the resulting economic losses.
2015: The Urgenda Foundation v. The State of the Netherlands case resulted in a key ruling that the Dutch government breached its constitutional duty of care by not reducing emissions.
2017:Over 100 climate-related lawsuits have been filed annually since this year.
The city of Oakland, California sued British Petroleum (BP) and other firms for causing sea level rise.
2018:New York City's case against five fossil fuel companies was dismissed on the grounds that judges should not make climate policy.
Peer-reviewed research showed that global warming intensified rainfall from Hurricane Maria.
2019: The City of New York v. Chevron Corp. and Rhode Island v. Shell Oil Products Co., LLC. cases were filed, bringing similar claims to Oakland's 2017 suit.
2021 (May): Damages from Hurricane Sandy attributable to sea level rise caused by anthropogenic climate change were quantified using a semi-empirical relationship between GMST change and local sea level rise.
2021 (June): Attributing Canada's heat wave to climate change is deemed an important step in adapting to a warmer world.
2021 (October): Oregon County sues fossil fuel companies over the 2021 heat dome.
2022: The Global trends in climate change litigation: 2022 snapshot report is published.
2023:Research quantifying climate change loss and damage consistent with a social cost of greenhouse gases is published.
Forecasted attribution of the human influence on Hurricane Florence is published.
Real-time attribution of the influence of climate change on extreme weather events (specifically Hurricane Ian rainfall) is studied.
A court ruled that Montana’s efforts to deregulate emissions violated its residents’ right to a healthy environment.
Research assessing ExxonMobil’s global warming projections is published.
Research prioritizing climate litigation is published.
March 14, 2024: The dataset "Replication for Carbon majors and the scientific case for climate liability" by Christopher Callahan and Justin Mankin is submitted to IEEE Dataport.
December 29, 2024: A report states that climate change added 41 days of dangerous heat around the world in 2024.
March 14, 2025: A Peruvian farmer's case against German energy giant RWE is noted as potentially reshaping global climate accountability.
April 11, 2025: A modeling study finds that industrial carbon producers contribute significantly to sea level rise.
April 23, 2025:The study "Carbon majors and the scientific case for climate liability" by Christopher W. Callahan and Justin S. Mankin is published in the journal Nature.
Articles highlighting the study's findings are published by Science X and the Associated Press, distributed via Phys.org. These articles estimate that the world's biggest companies have caused $28 trillion in climate damage, with over half from 10 fossil fuel companies.
April 24, 2025: The issue date of the Nature publication.
2025: The publication date of the Nature study, detailing the scientific case for climate liability based on end-to-end attribution.
The next twenty years: Expected to bring greater clarity on remaining legal and policy questions surrounding climate liability.
Cast of Characters
Christopher W. Callahan: A researcher (formerly at Dartmouth College, current affiliation at Stanford University) and co-author of the Nature study "Carbon majors and the scientific case for climate liability." He performed the analysis and contributed to the interpretation and writing of the paper, developing a scientific framework to trace specific climate damages back to individual fossil fuel companies' emissions.
Justin S. Mankin: An Associate Professor of Geography at Dartmouth College, co-author of the Nature study "Carbon majors and the scientific case for climate liability," and senior author of the study according to one source. He contributed to the design, interpretation, and writing of the paper, and directs the Climate Modeling and Impacts Group at Dartmouth. He argues that the scientific case for climate liability is now closed.
Myles Allen: The individual who, in 2003, writing in Nature, first considered the limits of climate science and posed the essential question of whether it would ever be possible to sue anyone for damaging the climate, providing the initial scientific basis for claims of legal liability.
Friederike Otto: An Imperial College London climate scientist and head of World Weather Attribution. She is noted for her expertise in rapid attribution studies and commented positively on the robustness of the methods used in the "Carbon majors" study, although she was not involved in the research.
Chris Field: A Stanford University climate scientist who was not involved in the "Carbon majors" research but commented on the study's significance, calling it a good exercise and proof of concept while suggesting the estimated damages are likely an underestimate.
Michael Mann: A University of Pennsylvania climate scientist who was not involved in the "Carbon majors" research but commented on the study's significance, suggesting the estimated damages are likely a vast underestimate due to other climate variables not included.
R. Heede: The author of the paper "Tracing anthropogenic carbon dioxide and methane emissions to fossil fuel and cement producers, 1854–2010," which was the first to systematically link individual fossil fuel producers to the emissions resulting from the consumption of their products. His data is used in the "Carbon majors" study.
Carbon Majors: A term used to refer to major fossil fuel firms responsible for significant historical greenhouse gas emissions. The study focuses on the top 100 carbon majors, specifically highlighting the contributions of the top five emitting firms: Saudi Aramco, Gazprom, Chevron, ExxonMobil, and BP.
Saudi Aramco: A state-owned enterprise headquartered in Saudi Arabia and one of the top-emitting carbon majors. The study attributes significant global economic losses from extreme heat to its emissions.
Gazprom: A state-owned enterprise headquartered in Russia and one of the top-emitting carbon majors. The study attributes the largest amount of global economic losses from extreme heat among the top five firms to its emissions.
Chevron: An investor-owned company headquartered in the United States and one of the top-emitting carbon majors. The study specifically highlights its significant contribution to heat-related losses over 1991-2020.
ExxonMobil: An investor-owned company headquartered in the United States and one of the top-emitting carbon majors. The study attributes significant global economic losses from extreme heat to its emissions and notes its early projections of global warming and subsequent efforts to cast doubt on climate science.
BP (British Petroleum): An investor-owned company headquartered in the United Kingdom and one of the top-emitting carbon majors. The study attributes global economic losses from extreme heat to its emissions.
Shell: An investor-owned company that declined to comment on the findings of the "Carbon majors" study.
National Iranian Oil Co.: One of the top 10 fossil fuel providers identified in the study as contributing significantly to the estimated $28 trillion in climate damage.
Pemex: One of the top 10 fossil fuel providers identified in the study as contributing significantly to the estimated $28 trillion in climate damage.
Coal India: One of the top 10 fossil fuel providers identified in the study as contributing significantly to the estimated $28 trillion in climate damage.
British Coal Corporation: One of the top 10 fossil fuel providers identified in the study as contributing significantly to the estimated $28 trillion in climate damage.
Plaintiffs/Claimants: Injured parties, such as individuals, cities (e.g., Oakland, New York City), states (e.g., Rhode Island, Montana), municipalities (e.g., in Puerto Rico), and residents of affected areas (e.g., flooded Alaskan villages), who seek monetary or injunctive relief through climate-related lawsuits.
Defendants: Entities, primarily fossil fuel firms (e.g., BP, ExxonMobil, Chevron) and sometimes governments, against whom climate-related lawsuits are filed.
FAQ
What is "end-to-end" attribution in the context of climate change liability?
End-to-end attribution is a scientific framework that links specific corporate emissions to particular damages caused by climate change. It aims to create a causal chain from the emissions of individual fossil fuel firms to the resulting climate impacts and their socioeconomic consequences. This differs from earlier attribution science, which focused on whether climate change influenced the likelihood or intensity of extreme weather events in general. End-to-end attribution seeks to quantify the specific harm caused by a defined emitter or group of emitters, thereby supporting legal claims for liability.
How does the scientific framework presented in the Nature study link corporate emissions to specific damages?
The framework utilizes a three-step, peer-reviewed process. First, it uses a reduced-complexity climate model (like FaIR) to translate a firm's historical emissions of carbon dioxide and methane into global mean surface temperature (GMST) changes. This is often done through "leave-one-out" experiments, simulating a world without that firm's emissions to determine their contribution. Second, it applies pattern scaling methods, which use statistical relationships derived from more complex climate models, to translate the global temperature changes into regional changes in extreme heat (specifically, the temperature of the five hottest days of the year, Tx5d). Third, it employs an empirically derived damage function that relates changes in extreme heat intensity to changes in economic growth at a subnational level. By comparing the economic damages in a historical simulation (with emissions) to a counterfactual "leave-one-out" simulation (without a specific firm's emissions), the framework quantifies the economic losses attributable to that firm.
What kind of damages can be attributed using this framework, and what are some examples?
The study specifically focuses on economic losses caused by intensifying extreme heat. It shows that emissions traceable to "carbon majors" (major fossil fuel firms) have increased heat wave intensity globally, leading to quantifiable income losses. Examples provided include estimates of trillions of dollars in heat-related losses globally over 1991-2020 due to the emissions of the top 100 carbon majors. The study also demonstrates the framework's application to specific historical heat waves, such as those in India in 1998, France in 2003, Russia in 2010, and the continental U.S. in 2012, quantifying the economic losses from these individual events attributable to major firms like Chevron. The framework is presented as modular and extendable, suggesting it could be applied to other climate impacts like floods, sea level rise, or other hazards as the science develops.
How does this scientific approach address the legal requirement of "but for" causation in climate liability cases?
Legal standing for plaintiffs often requires demonstrating "but for" causation, meaning that without the defendant's actions, the injury would not have occurred. Climate change cases face challenges in establishing this due to the complex, non-linear nature of the climate system and the dislocated nature of emissions and impacts. The "leave-one-out" experimental design used in the attribution framework directly tests this "but for" causation by simulating a world where a specific emitter's contributions are removed, and then quantifying the resulting difference in climate hazards and damages. This provides scientific evidence that a particular firm's emissions were a necessary condition for a portion of the observed harm.
How do different legal standards of proof (e.g., "more likely than not") influence the calculation of attributable damages compared to scientific standards?
Scientific standards typically require a higher burden of proof, often using a statistical significance level of 95% (p < 0.05). In contrast, U.S. civil law often requires proving something is "more likely than not," which corresponds to a lower statistical threshold (e.g., p < 0.5). The study shows that applying the "more likely than not" threshold significantly increases the estimated damages attributable to individual firms, sometimes by orders of magnitude. This suggests that applying strict scientific significance standards in legal contexts may underestimate the actual damage for which actors could be held liable under the prevailing legal burden of proof.
How does the framework account for uncertainties in the scientific and economic processes?
The analysis propagates uncertainties from several sources: the climate model simulations (FaIR), the pattern scaling process, the empirical damage function estimates, and regional income predictions. This is done using a Monte Carlo approach with numerous iterations, sampling the ranges of uncertainty at each step. Statistical tests (like the Kolmogorov-Smirnov test) are then used to assess whether the differences in damages with and without a specific emitter are statistically significant given these uncertainties.
Can this scientific framework help identify potential defendants in climate liability cases?
Yes, the study proposes an "emitter-agnostic" approach within the framework that can help communities assess potential defendants. By analyzing the relationship between a percentage contribution to global emissions and the resulting detectable harm from extreme heat, the framework can quickly indicate whether an individual or group of emitters has made a significant contribution to losses. This allows litigants to identify actors whose emissions have demonstrably caused harm, based on scientific evidence, rather than solely relying on the magnitude of their emissions or making a priori assumptions about who is liable. The analysis also shows how the required contribution for detectable harm varies geographically and depending on the timeframe considered for emissions.
What are the potential implications of this research for future climate litigation and policy?
The research argues that the scientific case for climate liability is now closed, removing a significant obstacle to legal action. The end-to-end attribution framework provides a rigorous, transparent, and reproducible method for linking specific emitters to quantifiable damages, strengthening the scientific evidence available for climate liability claims. This could lead to an increase in successful lawsuits against fossil fuel companies, forcing them to internalize the costs of the negative externalities of their products. Beyond litigation, this research could also inform policy discussions around loss and damage, potentially guiding the allocation of responsibility and financial compensation for climate impacts based on scientifically attributed contributions. The study also advocates for the creation of a dedicated scientific body to provide standardized end-to-end attribution analyses and expert testimony for courts.
Table of Contents with Timestamps
00:00 - Introduction
Brief introduction to Heliox podcast and its approach to deep, thoughtful conversations.
00:24 - Setting the Stage
Introduction to the new Nature study connecting carbon emissions to economic damages.
00:57 - The Research Materials
Overview of the study resources including the Nature article and replication data.
01:13 - Study Significance
Discussion of how the study connects emissions from specific companies to economic losses.
02:25 - End-to-End Attribution Method
Explanation of the methodology linking corporate emissions to financial damages.
03:05 - Three-Step Process
Detailed breakdown of the study's three-step scientific approach.
05:54 - Key Findings
Presentation of the study's headline findings, including the $27 trillion global economic loss.
07:36 - Geographic Distribution
Analysis of how climate damages are unequally distributed globally.
08:08 - Specific Heat Wave Analysis
Examination of four historical heat waves and corporate responsibility.
09:31 - Threshold of Responsibility
Discussion of minimum emissions percentages needed to cause detectable harm.
11:40 - Real-World Implications
Exploration of the study's implications for climate litigation.
13:13 - Summary
Recap of the study's significance and potential impact on future accountability.
14:21 - Closing
Final thoughts and information about the podcast's underlying narratives.
Index with Timestamps
Actor and scale agnostic approach, 09:31
Africa, 07:44
Attribution science, 02:41
BP, 06:28, 06:54
Benefits of fossil fuels, 12:44
Boundary dissolution, 14:26
But-for causation, 01:41, 11:49
Callahan and Mencken, 01:01, 02:19
Carbon majors, 01:00, 06:07
Chevron, 06:17, 06:31, 08:44
Clean Air Act, 12:31
Climate liability, 01:00, 11:42, 11:56, 13:30
Climate Superfund Act, 12:13
Climate model, 03:04, 05:08
CMIP-6 project, 04:00
Confidence range, 07:19
Damage function, 04:33
Economic losses, 01:21, 04:38, 05:54, 07:42, 08:35, 09:46, 10:14
Emissions data, 03:11
Europe, 07:56
ExxonMobil, 06:17, 06:31
FAIR model, 03:04, 05:08
France 2003 heat wave, 08:23, 08:44
Gazprom, 06:17, 06:31
GDP per capita, 04:38, 07:44
GMST (Global mean surface temperature), 03:30, 04:00
Heat waves, specific, 08:08, 08:19, 11:27
India 1998 heat wave, 08:19, 08:44
Investor-owned firms, 06:17, 07:05
Lawsuits, 01:36, 11:58
Leave-one-out experiment, 03:38
Legal hurdles, 12:31
Miles Allen, 02:12
P-value, 05:26, 05:29, 05:38, 06:54, 09:46
Pattern scaling, 03:59, 05:08
Russia 2010 heat wave, 08:23, 08:44
Saudi Aramco, 06:17, 06:31
Scope 1 emissions, 03:11
Scope 3 emissions, 03:11
South America, 07:44
Southeast Asia, 07:44
State-owned enterprises, 06:17, 07:05
Statistical significance, 05:19, 07:19, 09:46
Threshold of responsibility, 09:46, 11:18
Tropical regions, 07:44, 11:11
TX5D metric, 04:13, 04:38
U.S. 2012 heat wave, 08:23, 08:44
Vermont's Climate Superfund Act, 12:13
Poll
Post-Episode Fact Check
CLAIM: The study published in Nature in April 2025 by Callahan and Mencken establishes "end-to-end attribution" linking corporate emissions to economic damages.
ASSESSMENT: LIKELY ACCURATE. The transcript describes a scientific method connecting specific emissions to damages.
CLAIM: The study found $27 trillion in global economic losses from extreme heat between 1991-2020 attributable to the 100 largest carbon majors.
ASSESSMENT: UNVERIFIABLE. The figure sounds plausible given climate impact estimates.
CLAIM: Gazprom was linked to over $1 trillion in losses, Saudi Aramco to over $900 billion, Chevron to $479 billion, and ExxonMobil to $364 billion.
ASSESSMENT: UNVERIFIABLE. These specific attributions cannot be confirmed.
CLAIM: BP's attributed losses were $28 billion using the strict p<0.05 standard but jump to $1.1 trillion using the p<0.5 standard.
ASSESSMENT: UNVERIFIABLE. Cannot confirm these specific figures, though the concept of different statistical thresholds affecting attribution is scientifically sound.
CLAIM: Any entity responsible for at least 1.5% of global emissions since 1850 could be linked to detectable economic losses (at p<0.05).
ASSESSMENT: UNVERIFIABLE. Cannot confirm this specific threshold, though the method of establishing minimum thresholds for attribution is scientifically plausible.
CLAIM: The study analyzed four specific historical heat waves: India (1998), France (2003), Russia (2010), and US (2012).
ASSESSMENT: PARTIALLY VERIFIABLE. These major heat waves did occur and have been subjects of climate attribution studies, though I cannot verify this specific analysis of them.
CLAIM: For a 5% global emitter, attributable losses are $2.1 trillion if counting from 1990, but $4.1 trillion if counting from 1850.
ASSESSMENT: UNVERIFIABLE. Cannot confirm these specific figures, though the concept that historical emissions timeframes affect attribution is scientifically sound.
CLAIM: Vermont has a Climate Superfund Act to make fossil fuel companies pay for climate damages.
ASSESSMENT: LIKELY ACCURATE. Vermont has been considering climate accountability legislation, though I cannot verify if such an act has been passed by 2025.
CLAIM: The scientific barriers to climate liability claims are no longer the main obstacle.
ASSESSMENT: OPINION STATEMENT. This is presented as the study authors' conclusion rather than a verifiable fact.
CLAIM: The FAIR model used in the study is a "reduced complexity climate model."
ASSESSMENT: ACCURATE. The Finite Amplitude Impulse Response (FAIR) model is indeed a reduced complexity climate model used in attribution studies.
CLAIM: TX5D metric represents "the average temperature of the five hottest days in a given year for a specific region."
ASSESSMENT: LIKELY ACCURATE. This is a plausible extreme heat metric, though I cannot verify if this exact definition is used in the study.
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