A groundbreaking report from the United Nations University Institute for Water, Environment and Health (UNU-INWEH) unveils the extensive environmental footprint underpinning artificial intelligence (AI) across carbon emissions, water usage, and land occupation, exposing complexities beyond the often-cited surge in electricity consumption. This comprehensive study paints a sobering picture of the physical infrastructure, resource demands, and environmental justice implications accompanying the explosive growth of AI technologies worldwide.

At the heart of this investigation lies the understanding that AI’s environmental impact extends well beyond energy consumption and carbon footprints. The report emphasizes the intricate supply chains and physical systems supporting AI: sprawling data centers, semiconductor fabrication, cooling mechanisms, and resources extracted for critical minerals. These components introduce significant water withdrawals, land use for energy infrastructure, and the escalating challenge of electronic waste management. In doing so, the report marks a crucial shift from the conventional carbon-centric discussions toward a holistic environmental perspective.

The scale of AI’s operational energy demands is staggering. Projections estimate that data centers, the backbone of AI computing, will consume 448 terawatt-hours of electricity in 2025—an amount equivalent to the national consumption of France, ranking them as the 11th largest global electricity user if considered a country. Notably, AI workloads account for roughly 20% of this power use, a share predicted to rise to 40% by 2030. Should current growth trajectories persist, the energy consumption attributed to AI could nearly triple by 2030, corresponding to around 945 terawatt-hours annually and equating to nearly 3% of worldwide electricity usage. This prodigious demand alone could sustain the energy needs of 1.3 billion people living in Sub-Saharan Africa for over five years—a demographic particularly vulnerable to energy scarcity.

Beyond energy, the water footprint of AI infrastructure poses an underappreciated risk to global freshwater resources. Data centers currently utilize an estimated 9.3 trillion liters of water, sufficing for the drinking requirements of the global population for approximately 1.6 years. The report underscores that water withdrawals, especially in arid or depleted regions, can severely stress aquatic ecosystems and groundwater reserves, even when some of this water is eventually returned. Moreover, land requirements for electricity generation related to AI’s growth are poised to surpass 14,000 square kilometers by 2030, roughly the size of Northern Ireland, presenting additional challenges for land management and biodiversity conservation.

Training state-of-the-art AI models such as ChatGPT-5 demands colossal energy inputs, consuming around 100 gigawatt-hours of electricity—comparable to the annual residential energy consumption of 770,000 individuals in Sub-Saharan Africa. The corresponding water and land footprints—1 billion liters and 1.5 square kilometers respectively—highlight the significant spatial and resource components embedded within AI’s developmental phase. However, the report pivots attention toward the AI’s ubiquitous daily use, which far exceeds the energy footprint of training alone. For instance, ChatGPT processes roughly 2.5 billion prompts daily, translating into annual electricity use of about 383 gigawatt-hours and water consumption sufficient for half a million people’s domestic needs annually, reflecting the enormous cumulative resource drain of AI services.

The environmental cost per AI interaction varies significantly by technology and usage context. For example, Google handles approximately 5 trillion search queries each year, where a traditional search requires around 0.3 watt-hours, but AI-enhanced generative searches inflate this figure to up to 3 watt-hours—a tenfold increase. Additionally, AI-generated video content emerges as a looming environmental crisis. A single high-resolution video clip may demand more than 415 watt-hours of energy, outstripping the energy required for producing hundreds of static AI-generated images. Given that energy requirements rise quadratically with resolution and frame count, the burgeoning prevalence of AI video generation could rapidly escalate infrastructure strain.

Crucially, the report explores the intricate trade-offs between carbon, water, and land footprints in AI energy sourcing. Transitioning from coal to bioenergy production can reduce carbon emissions by an average of 72%, yet simultaneously inflates water consumption more than thirtyfold and enlarges land use by a factor of one hundred. This nuance dismantles simplistic narratives around “green” or “renewable-powered” data centers and compels stakeholders to weigh multifaceted environmental impacts in energy procurement and infrastructure siting. The geographic variance in electricity supply further complicates the notion of universal sustainability metrics.

The environmental and social implications extend deeply into the realm of mineral extraction and electronic waste. AI infrastructure relies on minerals often mined under conditions that disproportionately harm communities in the Global South, exacerbating environmental degradation and social injustices. By 2030, AI-related hardware waste could reach 2.5 million metric tons annually—equivalent to discarding a quarter of a million Eiffel Towers—posing severe challenges for hazardous material management and pollution control. The report calls for robust lifecycle governance spanning from resource acquisition through responsible disposal to mitigate these burdens on vulnerable populations.

Disparities in AI infrastructure distribution exacerbate global inequalities. Currently, 90% of specialized AI cloud infrastructure capacity is concentrated in just two countries—the United States and China—with only 32 nations worldwide hosting such facilities at all. The vast majority of over 150 countries remain dependent consumers of AI services, bearing metal extraction and e-waste costs disproportionately while reaping scant strategic benefits. This digital divide manifests not only as an economic disparity but as an environmental justice concern demanding urgent attention and coordinated global action.

Ireland stands as a cautionary exemplar of the perils of unregulated AI infrastructure growth. Data centers now consume 21% of the country’s total metered electricity—a sharp rise from 5% in 2015—exceeding the energy used by all urban households combined. The national grid operator’s decision to pause new data center approvals until 2028 encapsulates the critical need for integrative energy planning and sustainable infrastructure development, highlighting the risks that other nations might encounter without proactive governance.

The report presents a compelling call to action and a roadmap for responsible AI governance framed around six foundational principles: transparency in environmental impact reporting; efficiency engineered at the design phase; equity and environmental justice considerations; lifecycle accountability; international collaboration; and sustainable use practices. It addresses varied stakeholders—from governments integrating AI into energy and land-use policy, to industry prioritizing footprint-aware model development, to users selecting appropriate computational scales—emphasizing governance as a collective, multilevel imperative.

Finally, the report recognizes user interface design and behavioral choices as potent instruments for environmental stewardship. For instance, adopting a “concise mode” in AI interactions, which avoids unnecessary politeness or verbosity, can reduce token output by 30%, saving significant electricity—estimated at 87 to 98 gigawatt-hours annually. This reduction parallels the residential energy usage of 760,000 individuals in Sub-Saharan Africa, illustrating how seemingly small efficiency gains in user interactions and product defaults can cascade into substantial sustainability dividends.

In its starkest summary, UNU-INWEH’s report declares that AI’s environmental footprint is neither fixed nor inevitable; it is the product of cumulative engineering, usage, and policy decisions rooted in physical realities. Confronting AI’s rapid expansion with holistic, transparent, and just frameworks offers the only viable path to ensuring that technological progress advances human well-being within planetary boundaries. Without systemic and cooperative stewardship, the opportunity for AI to be a force for sustainable innovation risks being eclipsed by escalating environmental costs and intensifying inequalities.

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Subject of Research: Environmental impacts of AI infrastructure and usage, including energy, carbon, water, land footprints, and associated social justice concerns.

Article Title: Environmental Cost of AI’s Energy Use: Carbon, Water and Land Footprints

News Publication Date: 2026

Web References:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints

References:
Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026). Environmental Cost of AI’s Energy Use: Carbon, Water and Land Footprints. United Nations University Institute for Water, Environment and Health (UNU-INWEH), Richmond Hill, Ontario, Canada. doi: 10.53328/INR26RMA002

Image Credits: United Nations University Institute for Water, Environment and Health (UNU-INWEH)

Keywords

Artificial intelligence, AI energy consumption, carbon emissions, water footprint, land footprint, environmental justice, data centers, AI infrastructure, e-waste, sustainable AI, mineral extraction, global digital divide

Satellites are creating a massive pollution problem, according to University College London researchers, who say the growing atmospheric carbon source has a 500 times greater climate impact than ground-based emissions, potentially blocking the Sun.

In a recent paper published in the journal Earth’s Future, researchers demonstrate that satellites are driving a significant rise in upper-atmosphere pollution, raising concerns related to the ongoing climate crisis. By the end of this decade, almost half of this pollution will come from satellite megaconstellations launched since 2019, the researchers claim.

Satellite Pollution

While satellites do emit some exhaust when they engage their thrusters, this is not the primary source of pollution they produce, according to the University College London researchers.

Instead, they point to rocket launches, as they generate a massive amount of carbon soot when discarded rocket bodies and dead satellites burn up on reentry into the Earth’s atmosphere. This carbon is particularly problematic, remaining in the upper atmosphere for an extended period and generating a 500-fold climate impact compared to ground emissions.

The team also investigated other forms of launch-related pollution, noting that chlorine released into the atmosphere by these launches harms the ozone layer, which blocks harmful UV rays; however, this impact is far less severe than the carbon soot. Even projecting out to 2029, the team seems confident that rocket launches, accounting for under a tenth of ozone depletion, and some organizations, such as Blue Origin, will be conducting launches that release no chlorine at all.

This is nonetheless important to monitor, they argue, as China’s space launches typically do release chlorine and are expected to grow in the coming years.

Satellite Reentry Carbon

Data for the research were sourced from satellite deployments and rock launches conducted between 2020 and 2022, which found that circulation patterns in the upper atmosphere move very slowly, allowing soot particles to linger for extended periods. In the lower atmosphere, rain and other weather systems remove such particles from car and factory exhaust much more rapidly. With this longer atmospheric life span, each particle in the upper atmosphere has a much greater impact on the environment.

Air pollution from launches and reentry is accumulating in the atmosphere at such a rate that by the end of the decade, it could block as much sunlight as artificial geoengineering projects aimed at reducing global warming. However, the actual cooling effect produced would likely be far below the expected temperature rise due to global warming over the same period, the study authors say.

“The space industry pollution is like a small-scale, unregulated geoengineering experiment that could have many unintended and serious environmental consequences,” said Professor Eloise Marais, the project’s leader and a researcher at UCL Geography. “Currently, the impact on the atmosphere is small, so we still have the chance to act early before it becomes a more serious issue that is harder to reverse or repair. So far, there has been limited effort to effectively regulate this type of pollution.”

The Pace Quickens

Their data indicates that megaconstellations, which the team sees as a significant concern, accounted for 35% of the climate impact of these events, and they expect this to grow to 42% by the end of the decade.

Recent years have seen exponential growth in satellites in near-Earth orbit, primarily driven by the rise of megaconstellations composed of hundreds of thousands of objects. The most well-known of these, SpaceX’s Starlink, accounts for 12,000 individual satellites. Megaconstellations are now consuming over half of the rocket fuel expended, as launches rose from just 114 a year in 2020 to 329 in 2025.

The researchers note that real-world megaconstellation launches between 2023 and 2025 have outpaced their projections based on 2020 to 2022 data, suggesting their predictions may actually underestimate the scale of the problem.

“The cooling effect from the reduction in sunlight that we calculate with our models may sound like a welcome change against the backdrop of global warming, but we need to be extremely cautious,” Professor Marais warned.

“Rocket launches are a unique source of pollution, injecting harmful chemicals directly into the upper layers of the atmosphere and contaminating Earth’s last remaining relatively pristine environment,” lead author Dr. Connor Barker, also with UCL Geography, noted.

“Though this soot’s impact on climate is currently much smaller than other industrial sources, its potency means we need to act before it causes irreparable harm,” Barker says.

The paper, “Radiative Forcing and Ozone Depletion of a Decade of Satellite Megaconstellation Missions,” appeared in Earth’s Future on May 14, 2026.

Ryan Whalen covers science and technology for The Debrief. He holds an MA in History and a Master of Library and Information Science with a certificate in Data Science. He can be contacted at ryan@thedebrief.org, and follow him on Twitter @mdntwvlf.

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