Energy Innovation partners with the independent nonprofit Aspen Global Change Institute (AGCI) to provide climate and energy research updates. The research synopsis below comes from AGCI Executive Director James C. Arnott. A full list of AGCI’s updates is available online. 

For many climate advocates preparing for this year’s COP29 in Baku, it might be a surprise to learn that a different annual Conference of Parties (COP) just wrapped in Cali, Columbia. This recent COP, also a pillar of global progress on sustainability, focused not primarily on climate change but on biological diversity.

Unfortunately, the climate crisis and biodiversity loss are too often considered separately from one another. As a result, the science about and potential solutions for each are typically explored through distinct channels, sometimes even competing with one another for attention and resources rather than navigating toward a more holistic path to sustainability.

Climate change presents a growing threat to biodiversity. Yet healthy and diverse living systems can play an important role in reducing future climate impacts by drawing down carbon in the atmosphere or helping communities build resilience. Accordingly, it’s worth looking at recent research for fresh insights on climate change and biodiversity, which can demonstrate the value of more integrated solutions.

At the most basic level, greater awareness of climate change impacts on nature heightens the case for urgency on reducing emissions. Some long-considered policies for biodiversity protection, like land use protections, may be emboldened or tweaked to capture benefits for climate solutions. But moving in this direction will require a more integrated approach to both policy and research. Though this has been largely missing in recent decades, there are glimmers of hope on the horizon.

Pinning down the magnitude of climate impacts on biodiversity

Historically, humans have impacted biodiversity in myriad ways, from land use change (e.g., clearing natural habitats for cropland) and resource extraction (e.g., fishing or logging) to the spread of invasive species (e.g., Burmese pythons in Florida overconsuming local fauna) and the introduction of pollution and toxins (e.g., PFAS and other “forever chemicals”).

Climate change aside, the consequences of these impacts on biodiversity is profound: The rate of species extinctions in the 20th century alone has been estimated at 30 to 120 times the rate in the previous 66 million years (based on the fossil record), on par with past mass extinction events.

Climate change now presents an added threat to the diverse web of life. Rising temperatures can shrink suitable habitats, drought can spur tree mortality, imperiling forest health, and ocean acidification, driven by elevated ocean uptake of CO2 emissions, intensifies damage to coral reefs and other marine species around the globe.

Studies attempting to quantify how much climate change will affect species extinction –– just one aspect of biodiversity –– have a hard time finding agreement or high confidence owing to the underlying difficulties in monitoring, let alone predicting, the health and interactions between the estimated nine million species on Earth. However, a new review by John J. Wiens and Joseph Zelinka from the University of Arizona examined a range of studies over the past several decades that estimated the climate impacts on species loss for plant and animal species.

Considering a worst-case, high-end climate change scenario, Wiens and Zelinka estimate a potential 16 percent of species loss due to climate change (Figure 1). But even if the planet avoids worst case projections or if species manage to be more climate-resilient than current models anticipate, nearly any magnitude of species loss is sobering given the finality that accompanies extinction and the oftentimes unknown ripple effects that the removal of even a single species can have on the web of life.

Combining existing tools yields fresh insights

Thinking about climate change and biodiversity together can help us transcend the bleak tally of potential damages. Modeling tools developed to explore climate change and biodiversity loss can be combined and compared to assess the issues as a more dynamic problem set, thus illuminating the connections.

An important study led by Portuguese conservation biologist Henrique Pereira and published earlier this year in Science conducted an extensive comparison of climate and biodiversity models. This analysis covered the period from 1900 to 2050, allowing for both historical and future-oriented exploration.

To simplify matters, the authors compared biodiversity impacts solely due to land use change (a predominant historical driver of biodiversity loss) with the combined impacts of land use change and climate change. The comparison included three different emissions and socioeconomic scenarios representing different storylines of global progress on sustainability and climate action. Unlike the Wiens and Zelinka review, this study looked across multiple aspects of biodiversity, not just the total number of different species. Other metrics of biodiversity included the intactness of habitat and the extent of habitat per species, offering a more multidimensional picture of biodiversity.

An initial encouraging insight from the Pereira et al. study is that declines in biodiversity from land use change alone may be expected to diminish, or even reverse, in the remaining first half of the century in response to land protection efforts assumed in the global sustainability scenario (see red bars Figure 2a). However, when climate change is added to the equation, all climate change scenarios continue to exacerbate biodiversity losses, with greater losses on higher emissions trajectories (see all color bars, Figure 2b).

What we can also glean from this kind of analysis is how increasingly dependent society is on nature, not just for resource extraction but also for nature’s healthy functioning. In Figure 3, under all scenarios, models show increased human demand for material ecosystem services — the things we depend on practically from nature, like timber, food, and bioenergy (notably, bioenergy dependence greatly increases in the more global, sustainability-oriented scenario). By contrast, the functions nature relies on to provide those services (so-called “regulating ecosystem services”) are expected to decline in almost every area, including coastal resilience, a growing area of concern.

Pereira et al.’s study helps to showcase how scientists and policymakers can draw upon existing modeling tools to better assess the impacts of climate change on biodiversity as well as the co-benefits (and tradeoffs) of pursuing solutions to both in tandem. The researchers’ results show the diminishing effects of land use change under the Global Sustainability scenario (see red bars in both Figures 2 and 3) and are encouraging in that sustainability policies aimed at a specific challenge, like land use conversion, can meaningfully impact that goal on a global scale, with co-benefits for climate. At the same time, the models show how sustainability pathways that include aggressive cuts to greenhouse gas emissions are necessary to stave off further impacts to biodiversity.

A glimmer of hope

As with mitigating climate change, reversing biodiversity loss is a daunting social task requiring well-designed policies, strong governance, and the more diffuse elements of social transformation, such as changes in norms, mindsets, and individual behavior. It’s easy to be discouraged that humans may fall short of achieving such a monumental undertaking. But what if lessons from human history show us the key to unlock our innate potential to rise to this challenge?

In a new perspective piece in Philosophical Transactions of the Royal Society B, ecologist and scholar of the Anthropocene Erle Ellis argues we underestimate the power of human aspirations to change how people relate to nature. As evidence, Ellis looks to humanity’s long history of dramatic interactions with nature, both for better and for worse. He cites examples from irrigation and granaries to the development of social norms to the more recent formation of environmental protection agencies and international environmental agreements.

For Ellis, the entry point to understanding how we can better relate to nature is recognizing these past examples where humans have devised and implemented transformational solutions to problems of our own making. “When these transformative capabilities to shape environments are coupled with sociocultural adaptations enabling societies to more effectively shape and live in transformed environments, the social–ecological scales and intensities of these transformations can accelerate,” Ellis wrote.

The underlying driver of successful transformation, for Ellis, is the power of culture and social learning, which in his view undergirds technological innovation (and adoption), good policy, and governance. Culture, then, becomes pivotal for progress at speed and scale.

Entry points

If Ellis is even partly correct about our latent potential, where are the most promising areas to focus attention? A team of scientists led by Brazilian ecologist Cássio Cardoso Pereira (2024) suggests six synergistic focus areas that would help to mitigate climate warming emissions while enhancing biodiversity.

Conserve carbon stocks and sinks. Land and ocean systems have naturally sequestered over half of humans’ historical emissions. Priorities for protection are likely in the Amazon, Congo Basin, and Southeast Asia, which have high levels of carbon storage and biodiversity.
Restore degraded lands. Marginal lands, or lands degraded from historical practices, can be repaired to enhance their carbon sequestration capacity. Designing restorations to repair ecosystem connectivity and cultivate rich, diverse native species can enhance biodiversity and associated ecosystem services.
Integrate conservation with local fauna and flora. Ecosystems that help sequester carbon and provide resilience depend on healthy interactions between plants and animals. Thus, climate-oriented conservation strategies should take these interactions into account.
Use only existing areas of agriculture, pasture, and silviculture. Although this area is in tension with other goals around livelihoods and food security, a direct path to avoiding additional emissions and biodiversity loss from land conversion is to establish strong policies that confine agriculture to already converted land.
Incorporate biodiversity into business models. While many companies promote values and goals around the protection of nature and are increasingly attaching themselves to science-based targets for climate action, corporate plans tend to lack specificity about biodiversity. Corporations can reduce the net impact of their activities by quantifying the impact of corporate activities on biodiversity loss and committing to measurable and verifiable actions to mitigate those impacts.
Convene joint biodiversity-climate COPs. Although both link to the pathbreaking 1992 Rio Conference on Sustainable Development, separate “Conference of Parties” currently address climate change and biodiversity issues on the international stage. Bringing these conversations together could further harness the synergies between them.

Such areas of attention require actionable science to inform good decisions where the details matter. One upcoming effort along these lines in North America is the Biodiversity and Climate Chang­­e Assessment. This report, with participation from Canada, the U.S., and Mexico, will be released sometime next year. Importantly, it will help to bridge communities of researchers who have previously contributed to either climate change-specific or biodiversity-specific assessment processes.

Ultimately, the systems that regulate both climate and life on Earth are deeply interwoven, and it’s impossible to consider the sustainability of either without looking at them together.

Featured research

Pereira, H. M., Martins, I. S., Rosa, I. M. D., Kim, H. J., Leadley, P., Popp, A., … Alkemade, R. (2024). Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050. Science, 384(6694), 458–465. https://doi.org/10.1126/science.adn3441

Wiens, J. J., & Zelinka, J. (2024). How many species will Earth lose to climate change? Global Change Biology, 30(1). https://doi.org/10.1111/gcb.17125

Ellis, E. C. (2024). The Anthropocene condition: Evolving through social-ecological transformations. Philosophical Transactions of the Royal Society B: Biological Sciences, 379(1893). https://doi.org/10.1098/rstb.2022.0255

Pereira, C. C., Kenedy-Siqueira, W., Negreiros, D., Fernandes, S., Barbosa, M., Goulart, F. F., … Fernandes, G. W. (2024). Scientists’ warning: six key points where biodiversity can improve climate change mitigation. BioScience, 74(5), 315–318. https://doi.org/10.1093/biosci/biae035

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Energy Innovation partners with the independent nonprofit Aspen Global Change Institute (AGCI) to provide climate and energy research updates. The research synopsis below comes from AGCI Executive Director James C. Arnott. A full list of AGCI’s updates is available online.  For many…
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This post is part of an ongoing “What Is” series from Energy Innovation that answers some of today’s most pressing climate policy questions. The first in this series answered the question–What is Net-Zero?, and the second answered the question What is The Inflation Reduction Act?.

What is Clean Energy?

Fighting climate change is the challenge of our time—cutting emissions at the speed and scale science deems necessary will determine the future of nearly all living things on the planet for generations. It’s an overarching problem that impacts every corner of our society and economy, and it requires.

However, as complicated as the problem seems, the solution to cleaning up climate pollution is straightforward: Use clean energy to make electricity and use that clean electricity to power equipment like vehicles, factories, and appliances that currently burn fossil fuels.

But what counts as clean energy?

The answer to that question varies depending on who is responding, muddying the landscape, diverting resources from the best solutions, and costing precious time in the effort to cut climate pollution. But the bottom line is clear – energy isn’t clean if it generates greenhouse gas emissions or air pollution.

To set the record straight, here’s a guide that walks through the clearly clean energy technologies and those requiring more nuance.

The obvious candidates: Renewable energy

 Renewables—wind, solar, geothermal, and hydropower—are universally recognized as clean energy. To generate electricity, they harness natural processes like wind, the sun’s rays, the earth’s heat, and the flow of water. And because they don’t burn any feedstock like coal or natural gas, they emit no air or climate pollution, qualifying them as clean energy. These sources currently generate about 20 percent of U.S. electricity.

Renewables are a bedrock climate solution, they’re the cheapest form of power today and will keep getting cheaper over time, and we know how to reliably manage an electric grid with a high share of renewable energy.

Clean but not pollution-free: Nuclear power 

Nuclear power currently supplies 20 percent of the United States’s electricity, making it one of our largest sources of power free from climate pollution. Nuclear plants can provide around-the-clock zero-carbon power, meaning they’re an important part of a clean grid. While constructing new nuclear plants is a timely and expensive process, maintaining the operating nuclear fleet is critical to meeting climate goals, because if they aren’t online, fossil fuel power could fill that required generation capacity.

We consider nuclear power to be “clean” on the basis that it does not emit pollution, although it must be acknowledged nuclear plants do create nuclear waste, which has complicated storage requirements and can be hazardous. The lack of greenhouse gas emissions is the key distinction in this analysis.

Hydrogen: It’s complicated

 Hydrogen has long been discussed as a potential climate solution, and it has certain use cases where it will be needed to provide energy free from climate pollution in a way electrified processes cannot like steel production, aviation, and long-haul maritime shipping.

However, even though burning hydrogen only emits water vapor, it’s complicated from a climate perspective. Hydrogen on its own scarcely exists in nature—generally it must be separated from other molecules using energy-intensive equipment called electrolyzers. If electrolyzers are powered by fossil fuels, the hydrogen they produce isn’t considered clean, since pollution occurs during the creation of that hydrogen, even if it only water vapor is emitted when the hydrogen itself is subsequently burned.

To be considered clean, hydrogen must be produced by electrolyzers powered by another clean energy source, ideally wind or solar. This is called green hydrogen.

Carbon capture and storage (CCS): Theoretically clean, absent in the real world

 CCS entails burning fossil fuels at a facility like a coal power plant or steel mill, and then sequestering the resulting climate pollution in an underground geologic formation or substance like limestone. While theoretically possible, this process is not and has not been used anywhere in the world at scale. Failures and cost overruns have plagued CCS demonstration projects. And while CCS captures carbon dioxide, it doesn’t capture traditional air pollution like soot, NOx, or Sox, all of which harms human health.

Natural gas: A bridge to nowhere

 Many industry groups have worked for years to brand natural gas as clean with the narrative of gas as a “bridge fuel” to a clean energy future often pushed by fossil fuel interest groups. But this is resoundingly false. Although natural gas emits half the carbon dioxide of coal, it still generates substantial amounts of climate pollution when burned.

And natural gas wells, pipelines, and appliances often leak methane, a much more potent greenhouse gas in terms of trapping heat in the atmosphere than carbon dioxide and is responsible for an estimated 20-30 percent of global warming since the Industrial Revolution.

There is no credible scenario in which natural gas can be considered clean from a climate perspective.

How policy can bring more clean energy online, faster

Because of clean energy’s superior economics, state and federal policy, and corporate climate goals, nearly all new additions to the U.S. electric grid are now clean.

In 2024, 96 percent of the new capacity added in the U.S. will consist of wind, solar, storage, and nuclear, all free from climate pollution. While this is a hopeful development, we’re still not adding clean energy fast enough.

Headwinds such as high interest rates, local siting challenges, supply chain constraints, and long wait times to connect to the grid are among the factors adding sand to the gears of the clean transition. Instituting smart policy can help ease the friction, including:

Improving regional and interregional transmission planning.
Accelerating interconnection by reducing the requirements on interconnection studies to only those necessary to connect the project to the grid.
Upgrading transmission lines using affordable technology to get big capacity increases in short timelines.
Implementing state and national clean electricity standards to mandate the transition to clean energy.
Improving regional sharing of electricity to improve reliability and resiliency.
And enabling demand-side solutions to meet peak loads quickly and affordably.

Clean energy is foundational to the fight against climate change—other solutions like electrification of transportation, buildings, and industry will only reach their fullest potential if clean energy supplies the electricity those technologies run on, rather than coal and natural gas.

Therefore, it’s crucial that policymakers, regulators, advocates, and businesses understand what energy sources are truly clean and which are imposters. Otherwise, they risk offering incentives, investments, and support to the wrong technologies that might only make our climate progress worse.

The post What Is Clean Energy? appeared first on Energy Innovation: Policy and Technology.

This post is part of an ongoing “What Is” series from Energy Innovation that answers some of today’s most pressing climate policy questions. The first in this series answered the question–What is Net-Zero?, and the second answered the question What is…
The post What Is Clean Energy? appeared first on Energy Innovation: Policy and Technology.[#item_full_content]

By Energy Innovation’s Modeling and Analysis Team

The free and open-source Energy Policy Simulator (EPS) computer model developed by Energy Innovation has become one of the most widely used tools to inform policymakers and regulators about which climate and energy policies will reduce greenhouse gas emissions most effectively while creating the largest economic and public health benefits.

With EPS models now available for dozens of countries and subnational areas, including 48 U.S. states, we’re often asked how the EPS works and what peer review it has undergone through its development.

The EPS is a System Dynamics computer model created in Vensim, a tool produced by Ventana Systems for the creation and simulation of System Dynamics models. The model can be run via the free Vensim Model Reader or through a web interface Energy Innovation developed. Directions on obtaining Vensim Model Reader and the EPS are available on the Download and Installation page and users can access the model online via the energypolicy.solutions website.

Users can access advanced features or modify input data by downloading the EPS and running it locally on their Mac or Windows PC. All input data is meticulously cited, publicly available, and freely accessible and editable. Users can run the model in Vensim Model Reader and instantly see how changes in input assumptions change the model’s outputs.

The EPS is an economy-wide, single region model that runs in annual time steps. It can be configured to run to 2100, though it is most often configured to run to 2050. The EPS includes bottom-up stock turnover tracking in several sectors and a profit-maximizing least-cost optimized electricity model, including 24 hours across six different time slices. It also has local cost minimization for certain sectors and technologies, for example it selects the lowest cost mix of new vehicles sold in a given year based on demand for new vehicles.

The EPS is designed to model dozens of policies affecting energy use and emissions. The model first builds a business-as-usual case based on input data and current policies. From there, the EPS allows users to model any combination of included policies and to customize the policy stringency and timelines of those policies. These policies include, for example:

Renewable portfolio standards or clean energy standards
Fuel economy standards for vehicles
Zero emissions vehicle standards and incentives
Industry methane standards
Incentives for clean energy technologies like those in the Inflation Reduction Act
Accelerated R&D advancement of various technologies

The EPS features an embedded downstream input-output model that translates changes in spending from policy to changes in economic outcomes, such as jobs, GDP, and worker wages. Changes in demand for services and goods that result from macroeconomic changes are fed back into the model on a one-year time delay, allowing the model to adjust energy demand and emissions based on the economy’s evolution.

The EPS also includes a simplified downstream health module that translates changes in health-damaging pollutants into changes in health outcomes. The health module relies on benefit-per-ton estimates from U.S. Environmental Protection Agency modeling and follows standard practices for converting changes in emissions to changes in health outcomes.

Thousands of outputs are available in the model, but some key metrics include:

Emissions of 12 different pollutants including carbon dioxide, methane, N2O, fluorinated gases, NOx, SOx, PM2.5, PM10, black carbon, organic carbon, carbon monoxide and volatile organic compounds.
Changes in spending on capital, fuel, maintenance, taxes and subsidies.
Direct, indirect, and induced impacts on jobs, GDP, and employee compensation as a whole or disaggregated into 42 sectors.
Premature mortality and 10 other avoided health-related outcomes from reduced primary and secondary particulate pollution.
Detailed electricity sector information including hourly demand and supply, generation, capacity, and retail electricity rates.
Sales and stock of different vehicles and vehicle technologies, such as battery electric, plug-in hybrid electric, hydrogen fuel cell, and gas-powered vehicles.
Energy used by different services and technologies across the economy, broken down by fuel type
Breakdowns of how each policy within a policy package contributes to total abatement and the cost-effectiveness of each policy (e.g., wedge diagrams and cost curves).
Fuel imports and exports, and associated expenditures or revenues.
Detailed accounting of energy used by 25 different industry sectors, including construction and agriculture, end use (e.g., boiler, low/medium/high temperature heat, machine drive) and fuel type.

Core methodologies and structures in the EPS have undergone extensive peer review as they were developed, and we continually seek input from outside experts to modify the methodologies and address concerns that are raised. Components of the model have been reviewed by individuals from prestigious institutions including:

American Council for an Energy-Efficient Economy
Argonne National Laboratory
Lawrence Berkeley National Laboratory
Massachusetts Institute of Technology
National Renewable Energy Laboratory
RMI
Stanford University
Tufts University
University of Chicago
U.S. Environmental Protection Agency
World Resources Institute

The post How Energy Innovation’s Energy Policy Simulators Work And Are Developed appeared first on Energy Innovation: Policy and Technology.

An overview of how the Energy Policy Simulator works and what peer review it undergoes during model development.
The post How Energy Innovation’s Energy Policy Simulators Work And Are Developed appeared first on Energy Innovation: Policy and Technology.[#item_full_content]

Energy Innovation partners with the independent nonprofit Aspen Global Change Institute (AGCI) to provide climate and energy research updates. The research synopsis below comes from AGCI Climate Social Scientist Rebecca Rasch. A full list of AGCI’s updates is available online. 

In the year 2050, we may look back on the events of December 5, 2022, as game-changing for the clean energy landscape. This was the day that scientists at the Lawrence Livermore National Laboratory (LLNL) produced using nuclear fusion technology. Unlike nuclear fission, which splits atoms to generate energy, nuclear fusion combines, or “fuses,” atoms to generate energy.

Fusion technology likely won’t be readily available for commercialization until mid-century, and even then, some argue it may prove too expensive to ever become commercially viable. Nevertheless, the milestone at LLNL is significant given the technology’s long-recognized potential. According to the International Atomic Energy Agency, fusion, the same process that powers the sun and other stars, could produce “four million times more energy than burning oil or coal” (Barbarino 2023).

Beyond the hurdles of technological readiness and financial viability, there is a looming question of whether fusion technology would face similar hurdles as nuclear fission technology in the court of public opinion given the tumultuous history of support for nuclear energy development in the United States (Gupta et al. 2019).

What is the state of public support for nuclear power and fusion energy?

New social science research by Gupta and colleagues published in the journal Fusion Science and Technology utilizes a unique empirical lens to answer this question. The team surveyed a representative sample of U.S. households to understand current perceptions of and attitudes toward nuclear technologies, including feelings about the balance of risks and benefits, and support for or opposition to the construction of new nuclear energy power plants in the United States. They use an experimental design, randomly assigning respondents to reflect on three terms: “fusion energy,” “nuclear energy,” and “nuclear fusion.” While “fusion energy” and “nuclear fusion” are terms describing the same technology, “nuclear energy” refers to current nuclear fission technology.

By gathering public sentiment on each term, the researchers can distinguish how sentiment varies based on both the technology itself (i.e., fusion vs. fission energy technology) and feelings around the term “nuclear,” in general. The authors focus on understanding people’s emotional response by asking respondents to list three words or phrases that come to mind when they think about the given term (Figure 1). Next, they ask respondents how each word or phrase makes them feel, on a five-point scale ranging from very negative to very positive (Figure 2).

The most common terms people associated with “nuclear energy” were “dangerous,” “clean,” and “scary.” The mean response score to “nuclear energy” was 2.92 out of 5, where 3 is the midpoint, indicating neutral feelings. This result suggests that, on average, people tended to attach neutral or even slightly negative feelings to the term “nuclear.” Similarly, the most common terms associated with “nuclear fusion” were “dangerous,” “energy,” and “clean.”

The mean favorability score for “nuclear fusion” was 2.97, only slightly higher than the score for “nuclear energy.” Conversely, “fusion energy” tended to evoke more positive feelings, with a mean response score of 3.36. The terms associated with “fusion energy” were more benign, with only 2.5 percent associating fusion energy with “dangerous.”

The authors highlight the clear bias that respondents tended to hold against the term “nuclear,” especially given their lack of familiarity with fusion energy. According to this research, more than half of Americans (63 percent of respondents) are not familiar with fusion energy technology. Yet once presented with the concept of fusion energy, 58 percent of respondents said they would support the “construction and use of fusion reactors to generate electricity in the United States.” This is in contrast to the amount of support for current nuclear fission technology, which only 48 percent of those surveyed support. The researchers find that support for construction of fusion reactors is higher among those aged 18 to 34, those more familiar with the technology, and those concerned about the environment.

This generational difference in support for fusion energy is not surprising, considering the history of public support for nuclear energy development in the U.S. In the 1970s and 1980s, public support for nuclear power was significantly eroded due to accidents related to nuclear waste disposal and explosions at nuclear fission facilities, most notably the Three Mile Island nuclear plant explosion in Pennsylvania in 1979 (Gupta et al. 2019). A new generation has come of age since that time, and Gupta et al. (2024) find that those born in the 1990s and later are less likely to attach negative feelings to or oppose nuclear energy.

What drives public sentiment around nuclear power in the United States?

In a separate study published in Renewable and Sustainable Energy Reviews, Kwon and colleagues (2024) at the University of Michigan used large language models (LLMs) to classify the sentiment of approximately 1.26 million English-language nuclear power-related tweets posted from 2008 through 2023. The LLMs categorized both key themes of the tweets as well as which tweets were most associated with positive, neutral, and negative sentiment. This novel approach allowed the authors to go beyond simply identifying sentiment to provide visibility into the drivers of those emotions.

The authors chose to use Twitter/X as a data source for public sentiment over alternatives like Instagram, Facebook, or LinkedIn for several reasons, including “the platform’s concise text format and its widespread use for discussing both scientific and non-scientific topics.” The team further segmented the data by city and state for 300,000 of the 400,000 tweets originating in the U.S. to understand geographic variance in support for nuclear power.

The authors found that nuclear power-related tweets tended to fall into two distinct categories: those pertaining to nuclear energy and those pertaining to nuclear policy. Nuclear energy-related tweets referenced nuclear power generation and related processes (including nuclear waste). Below are examples of tweets that typify negative, positive, and neutral nuclear energy tweets, respectively.

“Nuclear power generates dangerous radioactive wastes, and the U.S. should stay away from this energy source.’’
“The U.S. should build more small modular reactors to ensure a clean energy transition.’’
“There are 440 nuclear power plants operating in the world.’’

Tweets classified as nuclear policy referred to geopolitics, world leaders, and/or nuclear weapons. Words and phrases in tweets classified as policy tweets included references to nuclear warheads, nuclear deal, North Korea, Iran, Benjamin Netanyahu, and Hillary Clinton.

The researchers utilized GPT-3.5 to determine that a majority of tweets (68 percent) were policy-related, and 26 percent were energy-related (Figure 3). Favorability sentiment varied considerably by topic, with most policy-related tweets classified as negative and energy-related tweets as mainly neutral. Where energy-related posts were not neutral, there was a roughly even split between positive and negative sentiments associated with energy tweets, with slightly more positive tweets. This suggests that the bulk of negative-sentiment tweets related to nuclear power is associated with geopolitical concerns, not energy development.

To understand the themes driving the sentiments associated with energy-related tweets, the authors used LLM topic models to identify frequent keywords. Based on keyword frequencies, the authors grouped tweets into six main themes: Nuclear Science, Other Energy Sources, Environment and Health, Nuclear Technology, Errors and Misuse, and General.

The authors grouped tweets that mention “fusion” and “fission” into the Nuclear Science theme. Figure 4 shows the distribution of sentiments of energy-related tweets by keyword for the Nuclear Science theme. The bulk of positive tweets in this theme contain the keywords fusion or reactor, suggesting fusion technology is partially responsible for the positive-sentiment tweets associated with nuclear energy-related tweets overall. Additionally, tweets in the Nuclear Technology theme skewed positive, further suggesting that advances in technology are driving positive sentiment tweets.

Interestingly, the distribution of sentiments of tweets mentioning fusion and fission aligns well with Gupta and colleagues’ (2024) survey results, which show similar distributions of sentiments for fusion and nuclear (i.e., fission) energy (see Figure 2). Both studies show a majority of neutral or positive sentiment for fusion, and a larger proportion of negative sentiment for fission, compared to fusion.

Concern for the environment is driving public support for nuclear power

Tweets grouped into the Environment and Health theme and that contain the keywords clean and renewable also skew positive, suggesting that positive-sentiment tweets around nuclear power are also driven by concern for the environment and an interest in clean energy development. This finding aligns well with Gupta and colleagues’ (2024) finding that those concerned about the environment are more likely to support nuclear energy development.

The notion that nuclear power is more appealing to those concerned about the environment is a distinct shift in public motivation for nuclear power generation, which historically was driven by industrialists interested in lower energy costs. This suggests an evolution of environmental concern in the past decade, where climate change mitigation efforts are taking precedence over more traditional environmental interests of biodiversity loss, environmental contamination, and degradation.

In a recent perspective piece for WIREs Energy and Environment, “Nuclear power and environmental injustice,” Höffken and Ramana (2024) argue that nuclear power is wholly incompatible with environmental justice, pointing to a legacy of nuclear reactor siting and waste disposal in socially marginalized communities. Fusion energy, which theoretically would not produce the type of radioactive waste that the fission process generates (as it does not rely on uranium or plutonium), could help address this perception of incompatibility. As fusion technology advances, it will be important to include the environmental justice community in planning and implementation to ensure transparency, procedural justice, and a more equitable distribution of environmental benefits, risks, and impacts than we have seen historically with nuclear energy development.

LLM-based analysis tracks with survey data, demonstrating the power of AI to categorize sentiment 

Gupta et al. (2024) and Kwon et al. (2024) both focus on understanding U.S. public sentiment around nuclear power. Although their methods for gathering public sentiment differ substantially, their findings converge. Based on both a representative sample of the American public and 300,000 U.S.-based tweets, the research suggests a lack of majority opposition to nuclear power, in general, and fusion technology, in particular. In the case of fusion energy, the data indicate a slight majority of support.

Featured research and references

Barbarino, Matteo. 2023. “What is Nuclear Fusion?” International Atomic Energy Agency. Retrieved July 29, 2024. https://www.iaea.org/newscenter/news/what-is-nuclear-fusion.

Cooke, Stephanie. 2024. “The Fantasy of Reviving Nuclear Energy.” The New York

Times Opinion. The New York Times. Retrieved July 24, 2004. https://www.nytimes.com/2024/04/18/opinion/nuclear-power-fantasy-climate.html.

Gupta, Kuhika, Hank Jenkins-Smith, Joseph Ripberger, Carol Silva, Andrew Fox, and Will Livingston. 2024. “Americans’ Views of Fusion Energy: Implications for Sustainable Public Support.” Fusion Science and Technology 1–17. doi: 10.1080/15361055.2024.2328457.

Gupta, Kuhika, Matthew C. Nowlin, Joseph T. Ripberger, Hank C. Jenkins-Smith, and Carol L. Silva. 2019. “Tracking the Nuclear ‘Mood’ in the United States: Introducing a Long Term Measure of Public Opinion about Nuclear Energy Using Aggregate Survey Data.” Energy Policy 133:110888. doi: 10.1016/j.enpol.2019.110888.

Höffken, Johanna, and M. V. Ramana. 2024. “Nuclear Power and Environmental Injustice.” WIREs Energy and Environment 13(1):e498. doi: 10.1002/wene.498.

Kwon, O. Hwang, Katie Vu, Naman Bhargava, Mohammed I. Radaideh, Jacob Cooper, Veda Joynt, and Majdi I. Radaideh. 2024. “Sentiment Analysis of the United States Public Support of Nuclear Power on Social Media Using Large Language Models.” Renewable and Sustainable Energy Reviews 200:114570. doi: 10.1016/j.rser.2024.114570.

Lawrence Livermore National Laboratory. “Ignition.” Lawrence Livermore National Laboratory. Retrieved August 1, 2024. https://www.llnl.gov/news/ignition.

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Energy Innovation partners with the independent nonprofit Aspen Global Change Institute (AGCI) to provide climate and energy research updates. The research synopsis below comes from AGCI Climate Social Scientist Rebecca Rasch. A full list of AGCI’s updates is available online.  In the…
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