Artificial intelligence is transforming industries at an unusual pace, but the rapid expansion of AI infrastructure is also creating a significant environmental challenge. A new study suggests that carbon capture could cut over 90% of AI data center emissions, offering a practical pathway to reduce the growing carbon footprint of the digital economy. Published in the journal Energy & Fuels, the research estimates that U.S. data center power capacity will increase from 40 gigawatts (GW) in 2025 to 169 GW by 2030, a more than fourfold jump in just five years. If powered largely by fossil fuel-based electricity, annual carbon dioxide (CO₂) emissions from these facilities could surge from 90 million metric tons in 2025 to more than 404 million metric tons by 2030.

Researchers argue that integrating carbon capture and storage (CCS) with natural gas power plants could dramatically reduce these emissions while ensuring the reliable electricity supply required to power AI technologies.

<img class="aligncenter wp-image-87157 size-full" src="https://sigmaearth.com/wp-content/uploads/2026/07/ChatGPT-Image-Jul-14-2026-01_32_29-PM.png" alt="Carbon Capture Could Cut Over 90% Of AI Data Center Emissions” width=”1536″ height=”1024″ />

AI Data Centers Are Fueling Unusual Energy Demand

Artificial intelligence applications such as large language models, cloud computing, machine learning, and real-time analytics require enormous computational resources. These workloads are processed in hyperscale data centers that operate around the clock, consuming vast amounts of electricity.

The study, co-authored by Hon Chung Lau, adjunct professor at Rice University and founder of Low Carbon Energies LLC, along with energy consultant Steve C. Tsai, highlights that AI data centers are becoming one of the fastest-growing sources of electricity demand in the United States.

According to the International Energy Agency (IEA), global data centers already account for approximately 1-1.5% of worldwide electricity consumption, and that share is expected to grow rapidly as AI adoption accelerates.

Also Read: India’s Artificial Intelligence Data Centre Faces Climate Threats As Temperatures Climb

Projected Growth in U.S. AI Data Centers

The researchers analyzed publicly available information on announced U.S. data center projects, evaluating projected power requirements, state electricity mixes, and nearby carbon storage opportunities.

These estimates are considered conservative because the analysis only included data centers with publicly announced power requirements.

Also Read: AI Data Centers Drive 25% Jump In Microsoft’s Carbon Emissions, Report Shows

Why Carbon Capture Matters

• The study concludes that carbon capture could cut over 90% of AI data center emissions when underground storage capacity across multiple states is utilized.
• Carbon Capture and Storage (CCS) involves capturing carbon dioxide produced during electricity generation before it reaches the atmosphere.
• The CO₂ is then compressed and transported to deep underground geological formations, typically saline aquifers, where it can be stored safely for decades or even centuries.
• Unlike intermittent renewable energy sources, natural gas combined-cycle power plants equipped with CCS can provide reliable, 24-hour electricity that AI infrastructure demands while significantly reducing greenhouse gas emissions.

Also Read: Residents File Lawsuit Against Microsoft’s US AI Data Centre Over Noise Concerns

Saline Aquifers Offer Massive Storage Potential

One of the study’s most significant findings is the availability of geological storage across the United States.

• Researchers found that 34 U.S. states possess enough underground saline aquifer capacity to store more than 100 years of projected data center-related carbon dioxide emissions beyond 2030.
• By 2025, these formations could store approximately 59 million metric tons of CO₂, representing 66% of emissions from AI-related data centers.
• By 2030, storage capacity could accommodate 299 million metric tons, or roughly 74% of projected emissions.

When interstate carbon transport and storage networks are considered, researchers estimate that carbon capture could cut over 90% of AI data center emissions, making CCS one of the most promising solutions for balancing AI growth with climate goals.

Also Read: Australia Faces Climate Costs from Rapid Data Centre Expansion

States Leading the AI Infrastructure Boom

The study identifies several states expected to experience substantial AI-driven data center expansion:

• Texas
• Virginia
• Pennsylvania
• Ohio
• Arizona
• Colorado
• Utah
• Illinois

Texas alone may require approximately 25 GW of additional electricity generation by 2030 to support projected data center demand.

Many of these regions are also located near suitable underground saline aquifers, making them ideal candidates for integrated carbon capture and storage projects.

Also Read: Artificial Intelligence’s Environmental Footprint: Balancing Innovation With Sustainability

Why Natural Gas Still Plays a Role

Although renewable energy continues to expand, AI data centers require uninterrupted electricity every hour of every day.

Solar and wind power depend on weather conditions and require large-scale battery storage to provide a continuous supply. Until energy storage technologies mature further, researchers believe that natural gas combined-cycle plants equipped with CCS represent one of the most practical near-term options for delivering dependable low-carbon electricity.

Natural gas also emits significantly less carbon dioxide than coal-fired power plants, further reducing emissions before carbon capture is even applied.

Also Read: Comparison of Carbon Capture Technologies: Effectiveness and Costs

Challenges That Still Need to Be Addressed

Despite its promise, CCS is not a complete solution.

Several barriers remain:

• Building carbon capture systems requires substantial upfront investment.
• New CO₂ transportation pipelines will be needed to connect power plants with storage sites.
• Regulatory approvals and long-term monitoring frameworks must continue to evolve.
• Renewable energy, nuclear power, and battery storage will remain essential components of a diversified clean energy system.

The researchers emphasize that carbon capture should complement, not replace, other decarbonization strategies.

Also Read: CCS In Heavy Industry: Decarbonizing Cement, Steel, And Chemical Production

Supporting Climate Goals in the AI Era

As governments and technology companies invest billions of dollars in AI infrastructure, ensuring sustainable electricity generation has become increasingly important.

Microsoft, Google, Amazon, and Meta have all reported rising emissions associated with expanding AI data centers, highlighting the growing tension between digital innovation and climate commitments.

The findings provide policymakers and energy planners with a state-by-state framework for identifying where electricity demand will grow, where emissions are likely to increase, and where underground carbon storage can play the greatest role.

Also Read: Economic Viability Of Carbon Capture And Storage (CCS): Balancing Costs And Climate Benefits

The Road Ahead

Artificial intelligence will remain one of the world’s fastest-growing technologies, driving innovation across healthcare, manufacturing, finance, education, and scientific research. However, that progress must be matched with equally ambitious strategies to reduce environmental impacts. The latest research demonstrates that carbon capture could cut over 90% of AI data center emissions, particularly in regions with abundant geological storage and reliable natural gas infrastructure.

While CCS alone will not solve climate change, it offers a scalable and practical solution that could help power the AI revolution while supporting global decarbonization goals.

Also Read: The Role Of CCS In A Sustainable Energy Future

Frequently Asked Questions

1. What does the study say about AI data center emissions?

The study concludes that carbon capture could cut over 90% of AI data center emissions by capturing carbon dioxide from power plants and storing it underground in geological formations.

2. Why are AI data centers consuming so much electricity?

AI models require massive computing power to process large datasets, train machine learning systems, and support cloud-based applications. This increases electricity demand significantly.

3. What is Carbon Capture and Storage (CCS)?

Carbon Capture and Storage is a technology that captures CO₂ emissions from industrial facilities or power plants and permanently stores them underground in geological formations such as saline aquifers.

4. Which U.S. states are expected to see the largest AI data center growth?

The study highlights Texas, Virginia, Pennsylvania, Ohio, Arizona, Colorado, Utah, and Illinois as major growth regions for AI infrastructure.

5. Why is natural gas considered alongside carbon capture?

Natural gas combined-cycle plants provide reliable, continuous electricity needed by AI data centers. When equipped with CCS technology, they can deliver lower-carbon power while maintaining grid stability.

Also Read: Policy Frameworks For CCS: Incentives And Regulations Driving Adoption