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GoGreenNation news

Community Benefits

News Feed
Wednesday, November 19, 2025

Construction of a new stadium or solar farm can spark both alarm and promise for local residents, and for good reasons. Often, communities are sidelined in decision making about these projects, and the benefits of such large-scale developments are not always evenly distributed.  Historically, when these opportunities arrive, local officials have held public hearings where residents could voice concerns. However, this type of engagement has its drawbacks. It tends to favor vocal residents with the time and resources to attend. Moreover, research shows residents who attend these public hearings are disproportionately project opponents, rather than those who are pushing for more energy infrastructure or housing. And, ultimately, there is no guarantee that local electeds will take community feedback into consideration.Community Benefit Agreements (CBA) have emerged as one way to increase local control over development decisions and ensure that economic and other gains from new infrastructure are more widely shared.  What is a CBA? A Community Benefit Agreement is a legally binding contract between a developer and local governments or community groups such as labor unions, neighborhood associations, or environmental advocates.  In exchange for specific, tangible benefits, such as job training programs, affordable housing units, local hiring guarantees, parks, reduced electricity rates, or direct financial payments, local organizations agree to support a proposed project – or at least not oppose it. In this way, CBAs might be able to help speed up approval processes and accelerate development by navigating potential community opposition. CBAs to Support Clean Energy Development As California moves toward its goal of 100% renewable energy by 2045, communities are beginning to see many more wind and solar infrastructure projects — particularly those in the inland and rural counties of the state. As of November 2025, there are 282 planned utility-scale solar projects in California. Their total planned capacity is 59,721 megawatts (MW). Historically, Community Benefits Agreements have resulted from extensive advocacy and organizing by local community members. However, instead of pushing communities to self-organize for these benefits, California has begun to require clean energy developers to enter into legally-binding agreements with local community organizations in order to benefit from streamlined permitting at the state level.  CBAs for renewable energy are becoming increasingly prominent in policy and some jurisdictions both in California and other states have institutionalized community benefits:  Riverside County’s Policy B-29 requires large solar projects to pay approximately $150 per acre. Imperial County’s Public Benefit Program collects fees from solar projects to issue grants for infrastructure improvements and job creation.  California’s AB 205 now requires developers seeking state-level permits for large solar and wind facilities to execute a CBA Michigan’s recent legislation mandates that developers enter Host Community Agreements with minimum payments of $2,000 per megawatt. New York established a Host Community Benefits program with annual fees per megawatt issued as electric bill credits to residents of municipalities hosting renewable energy projects Read the Report: Rethinking Community Benefits: Industry-Specific Insights for a Transforming California  In order to help community groups who want to negotiate benefits agreements with developers, our team at the Possibility Lab – in partnership with CA FWD – built an Energy Project Benefits Agreement Database to identify common characteristics of successful agreements.  Explore our Energy Project Benefits Agreement Database  The Promise and Challenges of CBAs The promise of CBAs is that they give communities direct power to negotiate for their needs and preferences. However, it can be unclear who actually represents “the community.” Because CBAs are often negotiated by select community groups, they can lack democratic accountability. And just as the residents attending a public hearing may not be representative of the demographics of a community, with varying and unequal access to economic and political capital, the same could be true of the community groups who participate in negotiating CBAs.  As a result, some critics view CBAs as essentially allowing developers to “buy off” opposition in order to streamline approvals. The importance of timing in these agreements doesn’t improve optics: offered too early, benefits might feel like bribes; too late, they may seem like unjust compensation for negative impacts.  In the end, CBAs are private contracts and the details of many agreements stay hidden. As a result, despite many examples of CBAs in and outside California, surprisingly little is known about their actual structure, benefits, and outcomes. Many important questions remain unanswered, including whether CBAs speed up or slow down development. Which communities successfully negotiate CBAs, and which don’t? What happens when negotiations are unsuccessful? Who follows through to ensure commitments are fulfilled? CBAs are a promising vehicle to address the potential tensions between the need to quickly build more infrastructure and the desire to engage communities in decision-making. Nonetheless, more research is needed to understand their effectiveness in delivering real benefits to communities while enabling progress on housing, energy, and other new development. To learn more, visit the UC Berkeley Possibility Lab’s People-Centered Policymaking site

Across California, communities and developers are coming to the negotiating table in an effort to distribute prosperity. Community Benefits Agreements can help.

Collage of bike paths and wind farms, set against California mountains and deserts, symbolizing community benefits agreements to balance development and community needs.

Construction of a new stadium or solar farm can spark both alarm and promise for local residents, and for good reasons. Often, communities are sidelined in decision making about these projects, and the benefits of such large-scale developments are not always evenly distributed. 

Historically, when these opportunities arrive, local officials have held public hearings where residents could voice concerns. However, this type of engagement has its drawbacks. It tends to favor vocal residents with the time and resources to attend. Moreover, research shows residents who attend these public hearings are disproportionately project opponents, rather than those who are pushing for more energy infrastructure or housing. And, ultimately, there is no guarantee that local electeds will take community feedback into consideration.

Community Benefit Agreements (CBA) have emerged as one way to increase local control over development decisions and ensure that economic and other gains from new infrastructure are more widely shared. 

What is a CBA?

A Community Benefit Agreement is a legally binding contract between a developer and local governments or community groups such as labor unions, neighborhood associations, or environmental advocates. 

In exchange for specific, tangible benefits, such as job training programs, affordable housing units, local hiring guarantees, parks, reduced electricity rates, or direct financial payments, local organizations agree to support a proposed project – or at least not oppose it. In this way, CBAs might be able to help speed up approval processes and accelerate development by navigating potential community opposition.

CBAs to Support Clean Energy Development

As California moves toward its goal of 100% renewable energy by 2045, communities are beginning to see many more wind and solar infrastructure projects — particularly those in the inland and rural counties of the state. As of November 2025, there are 282 planned utility-scale solar projects in California. Their total planned capacity is 59,721 megawatts (MW).

Historically, Community Benefits Agreements have resulted from extensive advocacy and organizing by local community members. However, instead of pushing communities to self-organize for these benefits, California has begun to require clean energy developers to enter into legally-binding agreements with local community organizations in order to benefit from streamlined permitting at the state level. 

CBAs for renewable energy are becoming increasingly prominent in policy and some jurisdictions both in California and other states have institutionalized community benefits: 

  • Riverside County’s Policy B-29 requires large solar projects to pay approximately $150 per acre.
  • Imperial County’s Public Benefit Program collects fees from solar projects to issue grants for infrastructure improvements and job creation. 
  • California’s AB 205 now requires developers seeking state-level permits for large solar and wind facilities to execute a CBA
  • Michigan’s recent legislation mandates that developers enter Host Community Agreements with minimum payments of $2,000 per megawatt.
  • New York established a Host Community Benefits program with annual fees per megawatt issued as electric bill credits to residents of municipalities hosting renewable energy projects

Read the Report: Rethinking Community Benefits: Industry-Specific Insights for a Transforming California 

In order to help community groups who want to negotiate benefits agreements with developers, our team at the Possibility Lab – in partnership with CA FWD – built an Energy Project Benefits Agreement Database to identify common characteristics of successful agreements. 

Explore our Energy Project Benefits Agreement Database 

The Promise and Challenges of CBAs

The promise of CBAs is that they give communities direct power to negotiate for their needs and preferences. However, it can be unclear who actually represents “the community.” Because CBAs are often negotiated by select community groups, they can lack democratic accountability. And just as the residents attending a public hearing may not be representative of the demographics of a community, with varying and unequal access to economic and political capital, the same could be true of the community groups who participate in negotiating CBAs. 

As a result, some critics view CBAs as essentially allowing developers to “buy off” opposition in order to streamline approvals. The importance of timing in these agreements doesn’t improve optics: offered too early, benefits might feel like bribes; too late, they may seem like unjust compensation for negative impacts. 

In the end, CBAs are private contracts and the details of many agreements stay hidden. As a result, despite many examples of CBAs in and outside California, surprisingly little is known about their actual structure, benefits, and outcomes. Many important questions remain unanswered, including whether CBAs speed up or slow down development. Which communities successfully negotiate CBAs, and which don’t? What happens when negotiations are unsuccessful? Who follows through to ensure commitments are fulfilled?

CBAs are a promising vehicle to address the potential tensions between the need to quickly build more infrastructure and the desire to engage communities in decision-making. Nonetheless, more research is needed to understand their effectiveness in delivering real benefits to communities while enabling progress on housing, energy, and other new development.

To learn more, visit the UC Berkeley Possibility Lab’s People-Centered Policymaking site

Read the full story here.
Photos courtesy of

Related News

Introducing the MIT-GE Vernova Climate and Energy Alliance

Five-year collaboration between MIT and GE Vernova aims to accelerate the energy transition and scale new innovations.

MIT and GE Vernova launched the MIT-GE Vernova Energy and Climate Alliance on Sept. 15, a collaboration to advance research and education focused on accelerating the global energy transition.Through the alliance — an industry-academia initiative conceived by MIT Provost Anantha Chandrakasan and GE Vernova CEO Scott Strazik — GE Vernova has committed $50 million over five years in the form of sponsored research projects and philanthropic funding for research, graduate student fellowships, internships, and experiential learning, as well as professional development programs for GE Vernova leaders.“MIT has a long history of impactful collaborations with industry, and the collaboration between MIT and GE Vernova is a shining example of that legacy,” said Chandrakasan in opening remarks at a launch event. “Together, we are working on energy and climate solutions through interdisciplinary research and diverse perspectives, while providing MIT students the benefit of real-world insights from an industry leader positioned to bring those ideas into the world at scale.”The energy of changeAn independent company since its spinoff from GE in April 2024, GE Vernova is focused on accelerating the global energy transition. The company generates approximately 25 percent of the world’s electricity — with the world’s largest installed base of over 7,000 gas turbines, about 57,000 wind turbines, and leading-edge electrification technology.GE Vernova’s slogan, “The Energy of Change,” is reflected in decisions such as locating its headquarters in Cambridge, Massachusetts — in close proximity to MIT. In pursuing transformative approaches to the energy transition, the company has identified MIT as a key collaborator.A key component of the mission to electrify and decarbonize the world is collaboration, according to CEO Scott Strazik. “We want to inspire, and be inspired by, students as we work together on our generation’s greatest challenge, climate change. We have great ambition for what we want the world to become, but we need collaborators. And we need folks that want to iterate with us on what the world should be from here.”Representing the Healey-Driscoll administration at the launch event were Massachusetts Secretary of Energy and Environmental Affairs Rebecca Tepper and Secretary of the Executive Office of Economic Development Eric Paley. Secretary Tepper highlighted the Mass Leads Act, a $1 billion climate tech and life sciences initiative enacted by Governor Maura Healey last November to strengthen Massachusetts’ leadership in climate tech and AI.“We're harnessing every part of the state, from hydropower manufacturing facilities to the blue-to-blue economy in our south coast, and right here at the center of our colleges and universities. We want to invent and scale the solutions to climate change in our own backyard,” said Tepper. “That’s been the Massachusetts way for decades.”Real-world problems, insights, and solutionsThe launch celebration featured interactive science displays and student presenters introducing the first round of 13 research projects led by MIT faculty. These projects focus on generating scalable solutions to our most pressing challenges in the areas of electrification, decarbonization, renewables acceleration, and digital solutions. Read more about the funded projects here.Collaborating with industry offers the opportunity for researchers and students to address real-world problems informed by practical insights. The diverse, interdisciplinary perspectives from both industry and academia will significantly strengthen the research supported through the GE Vernova Fellowships announced at the launch event.“I’m excited to talk to the industry experts at GE Vernova about the problems that they work on,” said GE Vernova Fellow Aaron Langham. “I’m looking forward to learning more about how real people and industries use electrical power.”Fellow Julia Estrin echoed a similar sentiment: “I see this as a chance to connect fundamental research with practical applications — using insights from industry to shape innovative solutions in the lab that can have a meaningful impact at scale.”GE Vernova’s commitment to research is also providing support and inspiration for fellows. “This level of substantive enthusiasm for new ideas and technology is what comes from a company that not only looks toward the future, but also has the resources and determination to innovate impactfully,” says Owen Mylotte, a GE Vernova Fellow.The inaugural cohort of eight fellows will continue their research at MIT with tuition support from GE Vernova. Find the full list of fellows and their research topics here.Pipeline of future energy leadersHighlighting the alliance’s emphasis on cultivating student talent and leadership, GE Vernova CEO Scott Strazik introduced four MIT alumni who are now leaders at GE Vernova: Dhanush Mariappan SM ’03, PhD ’19, senior engineering manager in the GE Vernova Advanced Research Center; Brent Brunell SM ’00, technology director in the Advanced Research Center; Paolo Marone MBA ’21, CFO of wind; and Grace Caza MAP ’22, chief of staff in supply chain and operations.The four shared their experiences of working with MIT as students and their hopes for the future of this alliance in the realm of “people development,” as Mariappan highlighted. “Energy transition means leaders. And every one of the innovative research and professional education programs that will come out of this alliance is going to produce the leaders of the energy transition industry.”The alliance is underscoring its commitment to developing future energy leaders by supporting the New Engineering Education Transformation program (NEET) and expanding opportunities for student internships. With 100 new internships for MIT students announced in the days following the launch, GE Vernova is opening broad opportunities for MIT students at all levels to contribute to a sustainable future.“GE Vernova has been a tremendous collaborator every step of the way, with a clear vision of the technical breakthroughs we need to affect change at scale and a deep respect for MIT’s strengths and culture, as well as a hunger to listen and learn from us as well,” said Betar Gallant, alliance director who is also the Kendall Rohsenow Associate Professor of Mechanical Engineering at MIT. “Students, take this opportunity to learn, connect, and appreciate how much you’re valued, and how bright your futures are in this area of decarbonizing our energy systems. Your ideas and insight are going to help us determine and drive what’s next.”Daring to create the future we wantThe launch event transformed MIT’s Lobby 13 with green lighting and animated conversation around the posters and hardware demos on display, reflecting the sense of optimism for the future and the type of change the alliance — and the Commonwealth of Massachusetts — seeks to advance.“Because of this collaboration and the commitment to the work that needs doing, many things will be created,” said Secretary Paley. “People in this room will work together on all kinds of projects that will do incredible things for our economy, for our innovation, for our country, and for our climate.”The alliance builds on MIT’s growing portfolio of initiatives around sustainable energy systems, including the Climate Project at MIT, a presidential initiative focused on developing solutions to some of the toughest barriers to an effective global climate response. “This new alliance is a significant opportunity to move the needle of energy and climate research as we dare to create the future that we want, with the promise of impactful solutions for the world,” said Evelyn Wang, MIT vice president for energy and climate, who attended the launch.To that end, the alliance is supporting critical cross-institution efforts in energy and climate policy, including funding three master’s students in MIT Technology and Policy Program and hosting an annual symposium in February 2026 to advance interdisciplinary research. GE Vernova is also providing philanthropic support to the MIT Human Insight Collaborative. For 2025-26, this support will contribute to addressing global energy poverty by supporting the MIT Abdul Latif Jameel Poverty Action Lab (J-PAL) in its work to expand access to affordable electricity in South Africa.“Our hope to our fellows, our hope to our students is this: While the stakes are high and the urgency has never been higher, the impact that you are going to have over the decades to come has never been greater,” said Roger Martella, chief corporate and sustainability officer at GE Vernova. “You have so much opportunity to move the world in a better direction. We need you to succeed. And our mission is to serve you and enable your success.”With the alliance’s launch — and GE Vernova’s new membership in several other MIT consortium programs related to sustainability, automation and robotics, and AI, including the Initiative for New Manufacturing, MIT Energy Initiative, MIT Climate and Sustainability Consortium, and Center for Transportation and Logistics — it’s evident why Betar Gallant says the company is “all-in at MIT.”The potential for tremendous impact on the energy industry is clear to those involved in the alliance. As GE Vernova Fellow Jack Morris said at the launch, “This is the beginning of something big.”

Energy
Climate
Education

Bigger datasets aren’t always better

MIT researchers developed a way to identify the smallest dataset that guarantees optimal solutions to complex problems.

Determining the least expensive path for a new subway line underneath a metropolis like New York City is a colossal planning challenge — involving thousands of potential routes through hundreds of city blocks, each with uncertain construction costs. Conventional wisdom suggests extensive field studies across many locations would be needed to determine the costs associated with digging below certain city blocks.Because these studies are costly to conduct, a city planner would want to perform as few as possible while still gathering the most useful data for making an optimal decision.With almost countless possibilities, how would they know where to start?A new algorithmic method developed by MIT researchers could help. Their mathematical framework provably identifies the smallest dataset that guarantees finding the optimal solution to a problem, often requiring fewer measurements than traditional approaches suggest.In the case of the subway route, this method considers the structure of the problem (the network of city blocks, construction constraints, and budget limits) and the uncertainty surrounding costs. The algorithm then identifies the minimum set of locations where field studies would guarantee finding the least expensive route. The method also identifies how to use this strategically collected data to find the optimal decision.This framework applies to a broad class of structured decision-making problems under uncertainty, such as supply chain management or electricity network optimization.“Data are one of the most important aspects of the AI economy. Models are trained on more and more data, consuming enormous computational resources. But most real-world problems have structure that can be exploited. We’ve shown that with careful selection, you can guarantee optimal solutions with a small dataset, and we provide a method to identify exactly which data you need,” says Asu Ozdaglar, Mathworks Professor and head of the MIT Department of Electrical Engineering and Computer Science (EECS), deputy dean of the MIT Schwarzman College of Computing, and a principal investigator in the Laboratory for Information and Decision Systems (LIDS).Ozdaglar, co-senior author of a paper on this research, is joined by co-lead authors Omar Bennouna, an EECS graduate student, and his brother Amine Bennouna, a former MIT postdoc who is now an assistant professor at Northwestern University; and co-senior author Saurabh Amin, co-director of Operations Research Center, a professor in the MIT Department of Civil and Environmental Engineering, and a principal investigator in LIDS. The research will be presented at the Conference on Neural Information Processing Systems.An optimality guaranteeMuch of the recent work in operations research focuses on how to best use data to make decisions, but this assumes these data already exist.The MIT researchers started by asking a different question — what are the minimum data needed to optimally solve a problem? With this knowledge, one could collect far fewer data to find the best solution, spending less time, money, and energy conducting experiments and training AI models.The researchers first developed a precise geometric and mathematical characterization of what it means for a dataset to be sufficient. Every possible set of costs (travel times, construction expenses, energy prices) makes some particular decision optimal. These “optimality regions” partition the decision space. A dataset is sufficient if it can determine which region contains the true cost.This characterization offers the foundation of the practical algorithm they developed that identifies datasets that guarantee finding the optimal solution.Their theoretical exploration revealed that a small, carefully selected dataset is often all one needs.“When we say a dataset is sufficient, we mean that it contains exactly the information needed to solve the problem. You don’t need to estimate all the parameters accurately; you just need data that can discriminate between competing optimal solutions,” says Amine Bennouna.Building on these mathematical foundations, the researchers developed an algorithm that finds the smallest sufficient dataset.Capturing the right dataTo use this tool, one inputs the structure of the task, such as the objective and constraints, along with the information they know about the problem.For instance, in supply chain management, the task might be to reduce operational costs across a network of dozens of potential routes. The company may already know that some shipment routes are especially costly, but lack complete information on others.The researchers’ iterative algorithm works by repeatedly asking, “Is there any scenario that would change the optimal decision in a way my current data can't detect?” If yes, it adds a measurement that captures that difference. If no, the dataset is provably sufficient.This algorithm pinpoints the subset of locations that need to be explored to guarantee finding the minimum-cost solution.Then, after collecting those data, the user can feed them to another algorithm the researchers developed which finds that optimal solution. In this case, that would be the shipment routes to include in a cost-optimal supply chain.“The algorithm guarantees that, for whatever scenario could occur within your uncertainty, you’ll identify the best decision,” Omar Bennouna says.The researchers’ evaluations revealed that, using this method, it is possible to guarantee an optimal decision with a much smaller dataset than would typically be collected.“We challenge this misconception that small data means approximate solutions. These are exact sufficiency results with mathematical proofs. We’ve identified when you’re guaranteed to get the optimal solution with very little data — not probably, but with certainty,” Amin says.In the future, the researchers want to extend their framework to other types of problems and more complex situations. They also want to study how noisy observations could affect dataset optimality.“I was impressed by the work’s originality, clarity, and elegant geometric characterization. Their framework offers a fresh optimization perspective on data efficiency in decision-making,” says Yao Xie, the Coca-Cola Foundation Chair and Professor at Georgia Tech, who was not involved with this work.

Energy
Science

The world’s carbon emissions continue to rise. But 35 countries show progress in cutting carbon

In 2025 the world has fallen short, again, of peaking and reducing its fossil fuel use. But there are many countries on a path to greener energy.

Global fossil fuel emissions are projected to rise in 2025 to a new all-time high, with all sources – coal, gas, and oil – contributing to the increase. At the same time, our new global snapshot of carbon dioxide emissions and carbon sinks shows at least 35 countries have a plan to decarbonise. Australia, Germany, New Zealand and many others have shown statistically significant declines in fossil carbon emissions during the past decade, while their economies have continued to grow. China’s emissions have also been been growing at a much slower pace than recent trends and might even be flat by year’s end. As world leaders and delegates meet in Brazil for the United Nations’ global climate summit, COP30, many countries that have submitted new emissions commitments to 2035 have shown increased ambition. But unless these efforts are scaled up substantially, current global temperature trends are projected to significantly exceed the Paris Agreement target that aims to keep warming well below 2°C. These 35 countries are now emitting less carbon dioxide even as their economies grow. Global Carbon Project 2025, CC BY-NC-ND Fossil fuel emissions up again in 2025 Together with colleagues from 102 research institutions worldwide, the Global Carbon Project today releases the Global Carbon Budget 2025. This is an annual stocktake of the sources and sinks of carbon dioxide worldwide. We also publish the major scientific advances enabling us to pinpoint the global human and natural sources and sinks of carbon dioxide with higher confidence. Carbon sinks are natural or artificial systems such as forests which absorb more carbon dioxide from the atmosphere than they release. Global CO₂ emissions from the use of fossil fuels continue to increase. They are set to rise by 1.1% in 2025, on top of a similar rise in 2024. All fossil fuels are contributing to the rise. Emissions from natural gas grew 1.3%, followed by oil (up 1.0%) and coal (up 0.8%). Altogether, fossil fuels produced 38.1 billion tonnes of CO₂ in 2025. Not all the news is bad. Our research finds emissions from the top emitter, China (32% of global CO₂ emissions) will increase significantly more slowly below its growth over the past decade, with a modest 0.4% increase. Emissions from India (8% of global) are projected to increase by 1.4%, also below recent trends. However, emissions from the United States (13% of global) and the European Union (6% of global) are expected to grow above recent trends. For the US, a projected growth of 1.9% is driven by a colder start to the year, increased liquefied natural gas (LNG) exports, increased coal use, and higher demand for electricity. EU emissions are expected to grow 0.4%, linked to lower hydropower and wind output due to weather. This led to increased electricity generation from LNG. Uncertainties in currently available data also include the possibility of no growth or a small decline. Fossil fuel emissions hit a new high in 2025, but the growth rate is slowing and there are encouraging signs from countries cutting emissions. Global Carbon Project 2025, CC BY-NC-ND Drop in land use emissions In positive news, net carbon emissions from changes to land use such as deforestation, degradation and reforestation have declined over the past decade. They are expected to produce 4.1 billion tonnes of carbon dioxide in 2025 down from the annual average of 5 billion tonnes over the past decade. Permanent deforestation remains the largest source of emissions. This figure also takes into account the 2.2 billion tonnes of carbon soaked up by human-driven reforestation annually. Three countries – Brazil, Indonesia and the Democratic Republic of the Congo – contribute 57% of global net land-use change CO₂ emissions. When we combine the net emissions from land-use change and fossil fuels, we find total global human-caused emissions will reach 42.2 billion tonnes of carbon dioxide in 2025. This total has grown 0.3% annually over the past decade, compared with 1.9% in the previous one (2005–14). Carbon sinks largely stagnant Natural carbon sinks in the ocean and terrestrial ecosystems remove about half of all human-caused carbon emissions. But our new data suggests these sinks are not growing as we would expect. The ocean carbon sink has been relatively stagnant since 2016, largely because of climate variability and impacts from ocean heatwaves. The land CO₂ sink has been relatively stagnant since 2000, with a significant decline in 2024 due to warmer El Niño conditions on top of record global warming. Preliminary estimates for 2025 show a recovery of this sink to pre-El Niño levels. Since 1960, the negative effects of climate change on the natural carbon sinks, particularly on the land sink, have suppressed a fraction of the full sink potential. This has left more CO₂ in the atmosphere, with an increase in the CO₂ concentration by an additional 8 parts per million. This year, atmospheric CO₂ levels are expected to reach just above 425 ppm. Tracking global progress Despite the continued global rise of carbon emissions, there are clear signs of progress towards lower-carbon energy and land use in our data. There are now 35 countries that have reduced their fossil carbon emissions over the past decade, while still growing their economy. Many more, including China, are shifting to cleaner energy production. This has led to a significant slowdown of emissions growth. Existing policies supporting national emissions cuts under the Paris Agreement are projected to lead to global warming of 2.8°C above preindustrial levels by the end of this century. This is an improvement over the previous assessment of 3.1°C, although methodological changes also contributed to the lower warming projection. New emissions cut commitments to 2035, for those countries that have submitted them, show increased mitigation ambition. This level of expected mitigation falls still far short of what is needed to meet the Paris Agreement goal of keeping warming well below 2°C. At current levels of emissions, we calculate that the remaining global carbon budget – the carbon dioxide still able to be emitted before reaching specific global temperatures (averaged over multiple years) – will be used up in four years for 1.5°C (170 gigatonnes remaining), 12 years for 1.7°C (525 Gt) and 25 years for 2°C (1,055 Gt). Falling short Our improved and updated global carbon budget shows the relentless global increase of fossil fuel CO₂ emissions. But it also shows detectable and measurable progress towards decarbonisation in many countries. The recovery of the natural CO₂ sinks is a positive finding. But large year-to-year variability shows the high sensitivity of these sinks to heat and drought. Overall, this year’s carbon report card shows we have fallen short, again, of reaching a global peak in fossil fuel use. We are yet to begin the rapid decline in carbon emissions needed to stabilise the climate. Pep Canadell receives funding from the Australian National Environmental Science Program - Climate Systems HubClemens Schwingshackl receives funding from the European Union's Horizon Europe research and innovation programme and Schmidt Sciences.Corinne Le Quéré receives funding from the UK Natural Environment Research Council, the UK Royal Society, and the UK Advanced Research + Invention Agency. She was granted a research donation by Schmidt Futures (project CALIPSO – Carbon Loss In Plants, Soils and Oceans). Corinne Le Quéré is a member of the UK Climate Change Committee. Her position here is her own and does not necessarily reflect that of the Committee. Corinne Le Quéré is a member of the Scientific Advisory Council of Societe Generale. Glen Peters receives funding from the European Union's Horizon Europe research and innovation programme.Judith Hauck receives funding from the European Union's Horizon Europe research and innovation programme, the European Research Council and Germany's Federal Ministry of Research, Technology and Space.Julia Pongratz receives funding from the European Horizon Europe research and innovation programme and Germany's Federal Ministry of Research, Technology and Space.Mike O'Sullivan receives funding from the European Union's Horizon Europe research and innovation programme, and the European Space Agency.Pierre Friedlingstein receives funding from the European Union's Horizon Europe research and innovation programmeRobbie Andrew receives funding from the European Union's Horizon Europe research and innovation programme and the Norwegian Environment Agency.

Energy
Climate
Forests

AI power use forecast finds the industry far off track to net zero

Several large tech firms that are active in AI have set goals to hit net zero by 2030, but a new forecast of the energy and water required to run large data centres shows they’re unlikely to meet those targets

A data centre in Ashburn, VirginiaJIM LO SCALZO/EPA/Shutterstock As the AI industry rapidly expands, questions about the environmental impact of data centres are coming to the forefront – and a new forecast warns the industry is unlikely to meet net zero targets by 2030. Fengqi You at Cornell University in New York and his colleagues modelled how much energy, water and carbon today’s leading AI servers could use by 2030, taking into account different growth scenarios and possible data centre locations within the United States. They combined projected chip supply, server power usage and cooling efficiency with state-by-state electrical grid data to conduct their analysis. While not every AI company has set a net zero target, some larger tech firms that are active in AI, such as Google, Microsoft and Meta have set goals with a deadline of 2030. “The rapid growth of AI computing is basically reshaping everything,” says You. “We’re trying to understand how, as a sector grows, what’s going to be the impact?” Their estimates suggest US AI server buildout will require between 731 million and 1.125 billion additional cubic metres of water by 2030, while emitting the equivalent of between 24 and 44 million tonnes of carbon dioxide a year. The forecast depends on how fast AI demand grows, how many high-end servers can actually be built and where new US data centres are located. The researchers modelled five scenarios based on the speed of growth, and identified various ways to reduce the impact. “Number one is location, location, location,” says You. Placing data centres in Midwestern states, where water is more available and the energy grid is powered by a higher proportion of renewables, can reduce the impact. The team also pinpoints decarbonising energy supplies and improving the efficiency of data centre computing and cooling processes as major ways to limit the impact. Collectively, those three approaches could cut the industry’s emissions by 73 per cent and its water footprint by 86 per cent. But the group’s projections could also be scuppered by public opposition to data centre installations because of their potentially extractive impact on the environment. In Virginia, which hosts about one-eighth of global data centre capacity, residents have begun lodging opposition to further planned construction, citing the impact on their water reserves and the wider environment. Similar petitions against data centres have been lodged in Pennsylvania, Texas, Arizona, California and Oregon. Figures from Data Center Watch, a research firm tracking data centre development, suggests local opposition has stymied $64 billion worth of projects. However, it is unclear, even in places that have successfully rejected data centres, just how much power and water they may use. That is why the new findings have been welcomed – albeit cautiously – by those who have attempted to study and quantify AI’s environmental impact. “AI is such a fast-moving field that it’s really hard to make any kind of meaningful future projections,” says Sasha Luccioni at AI company Hugging Face. “As the authors themselves say, the breakthroughs in the industry could fundamentally alter computing and energy requirements, like what we’ve seen with DeepSeek”, which used different techniques to reduce brute-force computation. Chris Preist at the University of Bristol in the UK says, “the authors are right to point out the need to invest in additional renewable energy capacity”, and adds data centre location matters. “I think their assumptions regarding water use to directly cool AI data centres are pretty pessimistic,” he says, suggesting the model’s “best case” scenario is more like “business as usual” for data centres these days. Luccioni believes the paper highlights what is missing in the AI world: “more transparency”. She explains that could be fixed by “requiring model developers to track and report their compute and energy use, and to provide this information to users and policymakers and to make firm commitments to reduce their overall environmental impacts, including emissions”.

Energy
Water
CO2

Having children plays a complicated role in the rate we age

The effort of reproducing may divert energy away from repairing DNA or fighting illness, which could drive ageing, but a new study suggests that is only the case when environmental conditions are tough

Some say children keep you young, but it’s complicatedJavier Zayas/Getty Images For millennia, we have tried to understand why we age, with the ancient Greek philosopher Aristotle proposing it occurs alongside the gradual drying up of the internal moisture necessary for life. In modern times, a leading idea known as the disposable soma hypothesis suggests that ageing is the price we pay for reproduction, with evolution prioritising the passing on of genes above all else. This creates a fundamental trade-off: the immense energy devoted to having and raising offspring comes at the cost of repairing DNA, fighting off illness and keeping organs in good shape. This may particularly apply to women, who invest more in reproduction than men via pregnancy and breastfeeding. However, when scientists have tested this hypothesis by checking if women with more children live shorter lives, the results have been mixed: some studies support the idea, while others have found no effect. “It is very difficult to disentangle what is just correlation [between having more children and a shorter life] and what is the underlying causation, unless you have a good, big dataset that covers several generations,” says Elisabeth Bolund at the Swedish University of Agricultural Sciences, who wasn’t involved in the study. Euan Young at the University of Groningen in the Netherlands and his colleagues hypothesised that the inconsistency between studies exists because the cost of reproduction isn’t fixed – it depends on a mother’s environment. “In good times, this trade-off isn’t really visible. The trade-off only becomes apparent when times are tough,” says Young. To investigate this idea, the researchers analysed the parish records of more than 4500 Finnish women, spanning 250 years. These included the period of the Great Finnish Famine from 1866 to 1868, providing a means to gauge how hard times affect reproduction and longevity, says Young. They found that among the women who lived before or after the famine or who didn’t have children during it, there was no significant association between the number of children they had and their lifespan. However, for the women who did have children during the famine, their life expectancy decreased by six months for every child they had. The study builds on research published last year that used a dataset from a pre-industrial population in Quebec, Canda, monitored over two centuries, which showed this trade-off in mothers who were probably in poor health or under great stress, but didn’t explore how this was affected by specific environmental conditions. In contrast, Young’s team points to a specific, catastrophic event as the driver that exposes the trade-off for mothers. “This very large dataset makes it feasible to account for confounding factors [such as genetics and lifestyle factors],” says Bolund. “The study gets us as close as we can to identifying causation without running a controlled experiment in the lab.” The study also confirms the energetic demands of pregnancy and breastfeeding, which require hundreds of extra calories per day. During a famine, women can’t get this energy from food, so their bodies pay the price, “lowering basal metabolism [the minimum number of calories your body needs to function at a basic level] and thus slowing or shutting down other important functions, resulting in a decline in health and shorter lifespans”, says Young. It also explains why previous studies sometimes found the trade-off only in lower socioeconomic groups, which were effectively always living in relatively resource-scarce environments, he says. According to Bolund, the fact that this trade-off seems to occur in particularly tough circumstances, and when women typically had many children, may partly explain why women generally live longer than men today, with girls born between 2021 and 2023 in the UK expected to live four years longer than their male counterparts. The costs of reproduction are now fairly low in Western societies, where the average number of children women give birth to has reduced considerably over the centuries, says Bolund. As a result, few women today will probably reach the threshold where the cost to their lifetime becomes obvious. Bolund and her colleagues’ research on a historical population in Utah, for instance, found this only appeared when women had more than five children – well below the 1.6 births that the average woman in the US is expected to have in her lifetime. Other environmental factors may therefore become more significant in explaining the lifespan gap between men and women. Men tend to be more likely to smoke than women and also drink more alcohol, which affect lifespan, says Bolund. The current longevity gap between men and women is probably a combination of the latter’s reduced reproductive costs compared with other times in history and lifestyle differences between the sexes. Research also suggests that sex chromosomal differences are involved. “Sexes differ in a multitude of ways, beyond reproductive costs, so we need to conduct more research into how different factors contribute to sex-specific ageing,” says Young.

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