More than 230 environmental and public-interest groups asked Congress to halt approvals for and construction of new data centers. They want a temporary national moratorium until federal rules address energy use, water needs, local impacts, and emissions. The request came from Food & Water Watch and was signed by national and local groups across the country.
They said that the fast growth of artificial intelligence (AI) and cloud services is putting big new demands on local grids and water systems. They also said current federal rules do not cover the environmental or social impacts linked to data center growth.
Why the Groups Want a Moratorium
Data centers are using more electricity each year. U.S. data centers consumed an estimated 183 terawatt-hours (TWh) of electricity in 2024. That was about 4% of all U.S. power use. Some national studies project that number could rise to 426 TWh by 2030, which would be about 6.7% to 12% of U.S. electricity, depending on growth rates.
Global data centers used around 415 TWh of electricity in 2024. Analysts expect double-digit annual growth as AI loads increase.
AI-ready data center capacity is projected to grow by about 33% per year from 2023 to 2030 in mid-range market scenarios. Industry groups say global data center capacity could reach over 220 gigawatts (GW) by 2030.
Some groups warn that data center CO₂ emissions might hit 1% of global emissions by 2030. That’s about the same as a mid-size industrial country’s yearly emissions. They say the growth rate is rising faster than the reductions in many other sectors.
An excerpt from their letter reads:
“The rapid expansion of data centers across the United States, driven by the generative artificial intelligence (AI) and crypto boom, presents one of the biggest environmental and social threats of our generation. This expansion is rapidly increasing demand for energy, driving more fossil fuel pollution, straining water resources, and raising electricity prices across the country. All this compounds the significant and concerning impacts AI is having on society, including lost jobs, social instability, and economic concentration.”
When AI Growth Collides With the U.S. Power Grid
Several utilities have linked new power plant plans to data center growth. In Virginia, the largest power company and grid planners see data centers as a key reason for new infrastructure.
In Louisiana, Entergy moved forward with a new gas-plant plan expected to support a large hyperscale data center campus. These cases show how utilities now size new plants with AI-related load in mind.
Some utilities believe these expansions might increase local electricity rates by a few percentage points. This depends on how costs are shared. Regulators in various areas say that extra load can increase distribution and transmission costs. This might lead to higher bills for households.
Several grid operators also report congestion or long waiting lines for new power connections. Northern Virginia, Texas, and parts of the Pacific Northwest now have interconnection queues. In these areas, data center projects make up a large part of the pending requests.
Water Use and Siting Concerns
Water demand is another point of conflict. Many large data centers rely on water-cooled systems. A typical water-cooled data center may use around 1.9 liters of water per kWh. More advanced or dry-cooled facilities may use as little as 0.2 liters per kWh, but these designs are not yet common.
One medium-sized data center can use about 110 million gallons of water per year. Large hyperscale sites can use several hundred million gallons annually, and, in some cases, even more. Global estimates suggest data centers could use over 1 trillion liters of water per year by 2030 if growth continues.
These demands have triggered local resistance. In parts of Arizona, California, and Georgia, community groups have raised concerns about water use during drought periods. In some cases, local governments paused or limited data center approvals. A single campus can use more water each year than some small towns.
Trump Plans Executive Order on AI Regulation
While groups push for limits on new data centers, the White House is also preparing an executive order that would reshape AI policy nationwide, as reported by CNN. President Donald Trump has said he plans to issue an order that would block states from creating their own AI rules.
The administration aims to create one national standard for AI. This way, companies won’t have to deal with different state regulations.
Drafts of the plan say the order may tell federal agencies to challenge state AI laws. This could happen through lawsuits or funding limits if the laws clash with federal policy. Supporters say a unified national rule could help U.S. companies compete globally and reduce compliance costs.
State leaders and consumer protection groups argue the opposite. They say states have a legal right to pass their own rules on privacy, safety, and data use. Some governors argue that an executive order cannot override state laws without action by Congress. Minnesota lawmakers, for example, continue to write their own AI bills focused on deepfakes and child-safety concerns.
The debate adds another layer to the data center issue. AI systems require massive computing power. If AI keeps growing quickly, analysts expect even heavier pressure on local grids and water systems. Advocacy groups say that this makes federal regulation more urgent.
Scale of AI and Hyperscale Build-out
The U.S. is in the middle of a major build-out of hyperscale and AI-optimized data centers. Industry trackers report that hundreds of new hyperscale facilities are planned or already under construction through 2030. Many of these campuses are designed specifically for AI training and inference workloads.
Major cloud and social media companies have sharply increased capital spending to support this build-out. Amazon, Google, Microsoft, Meta, and other major platforms, combined spending on AI chips, data centers, and network upgrades reached hundreds of billions of dollars per year in the mid-2020s. These spending levels signal how fast demand is growing.
Some experts track how major technology firms have changed over time. For example, one big cloud provider said its data center electricity use has more than doubled in the last ten years. This increase happened as its global reach grew. This gives a sense of how long-term trends feed current infrastructure pressures.
AI also adds new layers of demand. Training one large AI model can use millions of kilowatt-hours of electricity. Operating a popular chatbot can require many megawatt-hours per day, especially at peak traffic.
Research shows that processing one billion AI queries uses as much electricity as powering tens of thousands of U.S. homes for a day. This varies with the model’s size and efficiency.
Cities and States Move Faster Than Washington
Local governments have acted faster than federal agencies to respond to public concerns. More than 100 counties and cities have passed temporary moratoria, zoning limits, or new environmental rules since 2023. Examples include parts of Georgia, Oregon, Arizona, and Virginia, where communities plan to evaluate energy and water impacts before approving new projects.
Advocacy groups also argue that federal standards have not kept up. The U.S. does not have national energy-efficiency rules for private data centers. It also does not require detailed, mandatory reporting on energy, water, or emissions for the sector. The groups pushing for a moratorium say Congress must update these policies before more sites break ground.
What the Debate Means for 2026 and Beyond
Congress will review the environmental groups’ request in the coming months. Lawmakers are expected to weigh economic benefits against rising tensions around energy, water, and local resources. At the same time, the White House may release its AI executive order, which could shape how states and companies set their own rules.
With rapid AI growth, rising electricity use, and expanding data center construction, both debates are likely to continue through 2026. Many experts say long-term solutions will require national standards, better reporting, and closer coordination between states, utilities, and federal agencies.
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Insetting program design starts with your supplier map. The carbon claim comes much later.
Consider a coffee procurement team that funds a farm intervention before checking its sourcing data. The supplier aggregates coffee lots from several regions. The buyer lacks farm-level traceability. Another purchaser expects to report the same outcome. A more attractive project brochure solves none of these problems.
If the distinction between a value-chain intervention and a purchased credit is still open, read CCC’s Insetting vs Offsetting guide before you set the brief.
Insetting program design begins with the purchasing relationship and works outward. You need to decide 1) where an intervention belongs, 2) what business problem it addresses, 3) who pays for it, 4) how results will be measured, and 5) what the evidence will let you say about them. This five-step playbook turns that sequence into a procurement plan.
Step 1: Insetting program design starts with supplier mapping
Start with the commodities that matter most to your Scope 3 inventory and sourcing continuity. Ask finance for spend by supplier, sustainability for the emissions baseline, and category managers for origin and volume records. Then identify which suppliers can trace material to a jurisdiction, sourcing region, producer group, or individual land-management unit.
The level of traceability affects what you can account for. Under the GHG Protocol Land Sector and Removals Standard, the spatial boundary for purchased land-based products depends on the traceability associated with each volume. Farm-specific factors or removals require physical traceability through an acceptable chain-of-custody model. A contract with a tier-one trader, by itself, does not establish a link to the farms behind its deliveries.[1]
Build a first-pass table with five columns: commodity and annual volume; supplier and origin; current traceability level; land-use and production risks; and the business owner who can change the purchasing terms. Mark missing data plainly. A blank cell is cheaper to fix before a program starts than after a claim is drafted.
If your company sets an SBTi Forest, Land and Agriculture target (FLAG), keep its land-related target boundary separate from energy and industry emissions. The current FLAG guidance also requires relevant companies to assess primary deforestation-linked commodities in their value chains.[2]
Step 2: Choose a commodity and jurisdiction for a pilot
Select one supply corridor where the sourcing connection can be established and procurement has a reason to stay. A useful pilot has repeat purchases, suppliers willing to share records, an intervention matched to a diagnosed problem, and a defined plan to measure the result. Carbon potential alone is a poor selection rule if the supplier cannot deliver the crop your business needs.
Compare candidate regions on land-use risk, supplier concentration, local rights and tenure, the availability of baseline data, and exposure to drought, erosion, or forest conversion. Check the relevant legal requirements separately. A nature project does not satisfy a due-diligence obligation merely because it has a carbon method attached.
Consider a coffee buyer sourcing from two districts. In the first, producer-group records identify the farms, while recent dry seasons have increased rejected green coffee lots. In the second, deliveries pass through several intermediaries and farm origins are unknown. Pilot shade management in the first district, with local agronomic advice and quality checks built into the plan. The buyer can trace purchases there and test the intervention against a defined sourcing problem.
Use a short decision memo to record why the selected corridor beats the alternatives, what remains uncertain, and what would stop the pilot. That memo is the first control against a project drifting toward whatever happens to photograph well.
Step 3: Design the supplier engagement and commercial model
The intervention needs an owner on each side of the contract. Decide who supplies planting material or training, who maintains the practice, who bears the cost if a harvest disappoints, and how long the buyer expects to purchase from participating suppliers. Where smallholders participate, budget cash flow and technical support for practices that offer a later return.
Put these terms in a supplier agreement or pilot addendum. It should cover eligible farms and volumes, consent to data collection, access for monitoring, any land or carbon rights that matter, benefit sharing, and what happens if the purchasing relationship ends. Ask local counsel and producer representatives to review the arrangement. The Accountability Framework is a useful reference for supply-chain work involving forests, ecosystems, and human rights.[3]
Avoid assigning an automatic carbon benefit to the buyer. The contract should say which party has the right to report each outcome, how overlapping claims will be checked, and how any issued credits will be handled. A reduction reported in a buyer’s inventory cannot simply be sold for someone else’s offset claim without an accounting review. SBTi FLAG guidance excludes purchased credits used as offsets from near-term FLAG target achievement.[2]
Set commercial measures beside environmental ones: delivered volume, rejection rate, supplier retention, and procurement cost. They tell you whether the program works as a supply-chain investment, even if carbon accounting takes longer to resolve.
Step 4: Build monitoring, reporting, and verification before rollout
Agree on the baseline and data flow before paying for a full rollout. Identify the land units or sourcing regions in scope, the practices that change, the records suppliers already keep, and the additional measurements the program requires. Decide which data can come from field visits, transaction records, or remote sensing, and who checks each source.
For carbon, separate three questions. Did the practice happen? Did emissions or removals change under an applicable method? Can the buyer attribute a defensible share to its purchased goods without double counting? The GHG Protocol’s 2026 guidance includes dedicated chapters on spatial boundaries, data and methods, evaluating actions, credited outcomes, and assurance.[1] These are distinct jobs. A photograph of a planted tree answers only part of the first.
CCC’s MRV and Additionality article explains the separate evidence questions a project reviewer will ask.
Create an evidence file for every reporting period: dated supplier and farm records, purchase volumes, methods and emission factors, uncertainty, quality checks, and changes from the baseline. Specify who can challenge the data and how corrections are recorded. If a project also seeks credit certification, keep project accounting and corporate inventory accounting separate. The GHG Protocol says its land standard focuses on entity-level inventories and does not set the rules for credit certification.[4]
Start with the minimum viable measurement design that can survive review. Add complexity when the pilot tells you which data actually changes a decision.
Step 5: Decide what can be reported and claimed
Insetting program design needs reporting rules before the marketing copy. Procurement, sustainability, finance, and legal should agree on four distinct outputs: operational performance; observed land or nature outcomes; inventory effects, if the accounting criteria are met; and any separately issued credits. One dashboard can display them, but they should not share a single unqualified headline.
SBTi FLAG guidance allows certain land-based removals within a company’s operations or supply chain to contribute to FLAG pathways, subject to criteria including permanence, traceability, data quality, and allocation. It does not allow purchased offsets to meet near-term FLAG targets.[2] Eligibility therefore depends on evidence and the applicable target rules, not on calling an activity “insetting.”
Draft a claims register. For each proposed sentence, record the period, boundary, data owner, calculation method, reviewer, and whether the result is measured, estimated, or still a goal. If the evidence supports only “we funded a pilot with 200 farms,” say that. Do not turn a funding fact into a verified emissions reduction.
What good looks like by year three
Treat year three as a review point, not a promised payback date. A mature pilot should have mapped participating supply volumes, a stable supplier agreement, a repeatable data collection process, and a comparison of commercial and environmental results against the baseline. It should also have a documented answer for outcomes that cannot be included in the buyer’s inventory.
Scale only where the pilot improves a sourcing decision and the evidence can follow the product. If neither condition holds, redesign the intervention or change the corridor. A disciplined program can conclude that a site is unsuitable. That is useful procurement intelligence.
Discuss your insetting program with CCC
Carbon Credit Capital designs nature-based supply chain investments around sourcing needs and measurable sustainability outcomes. Schedule a consultation with our carbon and sustainability experts to map your tier-one supplier network, FLAG exposure, and first pilot decision.
Sources
[1] GHG Protocol, Land Sector and Removals Standard, version 1.1, and companion Guidance, June 2026: https://ghgprotocol.org/land-sector-and-removals-standard ; https://ghgprotocol.org/land-sector-and-removals-guidance
[2] Science Based Targets initiative, Forest, Land and Agriculture Science-Based Target-Setting Guidance, version 1.2, March 2026, especially pp. 16–17, 37, and 41: https://sciencebasedtargets.org/resources/files/SBTiFLAGGuidance.pdf
[3] Accountability Framework initiative, Accountability Framework and guidance for companies: https://accountability-framework.org/
[4] GHG Protocol, Frequently Asked Questions: Land Sector and Removals Standard, questions 10 and 18: https://ghgprotocol.org/blog/frequently-asked-questions-land-sector-and-removals-lsr-standard
Nature-based carbon investments deserve consideration when they address a specific business dependency and produce outcomes you can measure. Imagine Moonbucks, a global coffee roaster planning next season’s espresso blend. It is considering natural Grade 4 coffee from Jimma, in southwestern Oromia, Ethiopia. Its sourcing decisions affect the roasting schedule and the cash tied up in coffee purchases. Moonbucks needs to understand which measures could protect that supply, what they would cost and how it would judge the results.
1. Define the sourcing problem before choosing a project
Moonbucks needs a dependable component for its espresso blend. Its procurement team wants continuity of volume and an agreed cup profile. Replacing a shipment at short notice could require new sample approval and changes to the blend, and given the schedules for cultivation, processing, and freight delivery, is practically impossible. Moonbucks needs to get this right, and its initial concern is inconsistent deliveries. It commissions an assessment of the supplying farms and post-harvest chain. The questions cover land condition, harvest availability and whether drying or storage problems are affecting saleable lots.
This distinction changes the investment brief. A tree-planting proposal cannot be assumed to fix drying problems. Better storage cannot restore eroded land. The team must establish which problem exists before selecting the response.
CCC’s guide to finding nature-based solutions in your supply chain explains where to look. Here, the next task is to turn a broad concern into a testable proposal.
2. Develop nature-based carbon investments around the actual supply chain
The assessment would trace Moonbucks’ purchases back through the exporter and supplying producer groups. Which farms supply the contracted lots? Who controls land-management decisions? How long does the buyer expect to maintain the purchasing relationship?
Furthermore, Jimma natural Grade 4 cannot be treated as interchangeable with every Ethiopian coffee. Moonbucks would need to test any substitute against its own blend and quality requirements.
Suppose Moonbucks’ assessment identifies an opportunity to maintain shade trees and restore vegetation along exposed streambanks. The IPCC describes agroforestry as a way to store carbon in vegetation and soil, with potential benefits for erosion control and water quality.1 Moonbucks would need local advice on species, growing conditions and maintenance before deciding how these measures fit its sourcing plan.
The proposal now has a defined sourcing connection and a candidate intervention. The next steps are to test its effect on production, assess carbon eligibility and build the financial case.
3. Compare the proposal with other ways to protect supply
WBCSD’s Nature-based Solutions Blueprint recommends comparing nature-based options with other responses across their benefits and costs.2 For Moonbucks, that means evaluating the landscape proposal alongside drying improvements, storage controls and alternative sourcing arrangements.
The product’s natural-process designation matters. Moonbucks should examine the drying and dry-milling chain alongside land conditions. Its team would check storage practices, contamination risks and incoming-lot quality to see whether problems arise before or after the coffee leaves the farms.
The revised proposal might combine land stewardship with separate post-harvest controls. Each component needs its own purpose and budget. A sustainability label should not obscure which activity is expected to solve which problem.
The project develops as the evidence improves. Its scope should follow the diagnosis rather than preserve the first idea unchanged.
4. Establish what the carbon outcome could count toward
Moonbucks’ sustainability team now tests the proposed carbon case separately from the sourcing case. Is the objective a measurable change in Moonbucks’ value-chain emissions, verified credits for separate voluntary use, or distinct outcomes under carefully defined arrangements?
Scope 3 covers value-chain emissions. A purchasing relationship alone does not prove that a farm intervention can be included in Moonbucks’ inventory. The team needs an applicable accounting method, defensible boundaries and evidence supporting attribution.
SBTi’s FLAG Guidance (forest, land and agriculture), version 1.2, says purchased credits used as offsets cannot meet near-term FLAG or energy and industry targets. Eligible land-based removals are subject to accounting requirements.3 Moonbucks needs to test its proposal against those rules before including an outcome in its targets.
For Moonbucks’ Jimma proposal, maintaining existing trees and establishing new vegetation could involve different carbon questions. Specialists must examine the baseline and additionality, meaning what changes because the project proceeds. They must also assess measurement and the risk that stored carbon is lost. CCC’s MRV and additionality article introduces those tests.
Until that work is complete, Moonbucks should not budget an assumed Scope 3 reduction or credit-sale receipt. Direct emissions reductions remain the priority.
5. Build a financial case that survives weaker assumptions
Moonbucks’ finance team would now build a multi-year budget. UNEP’s State of Finance for Nature 2023 compares current finance with the investment needed to meet climate, biodiversity and land-restoration goals.4 The company would cost its proposed activities, farmer participation and ongoing monitoring. Verification, where required, is a separate expense. Maintenance and responsibility for replacing failed plantings must remain visible after the initial establishment budget ends.
Operational benefits need equally careful treatment. If fewer rejected lots reduce emergency purchasing, count that saving once. Do not add “supply resilience” as another financial benefit when it represents the same avoided cost.
Moonbucks should compare a base case with slower benefits, higher implementation costs and no carbon revenue. It should also distinguish production outcomes from quality and shipment outcomes. A single good harvest would not prove that the landscape intervention caused better delivery performance.
A project can remain worth funding even when its carbon case needs more work. That decision must rest on the operational evidence and the company’s objectives, without unsupported environmental claims.
6. Fund a pilot with a clear expansion decision
Moonbucks’ first approval would fund a bounded pilot, rather than commit the entire sourcing program. Before spending, Moonbucks would agree on participating farms, responsibilities and the evidence needed at review.
Its scorecard could track farmer participation, implementation costs and plant survival, alongside accepted coffee volumes and lot-quality results. Carbon measurements would follow the selected method. Farm-level traceability must connect the intervention to the actual sourcing relationship.
Suppose Moonbucks’ review later finds that storage changes explain most quality improvements, while the land measures need longer observation. Those findings would shape the next decision: expand the proven component, adjust the landscape work or pause further spending. They would not justify crediting all improvements to tree planting.
This gives nature-based carbon investments a practical place in a multi-year strategy. Funding increases as the evidence supports it, and the project can change direction before a larger commitment.
Discuss a sourcing opportunity with CCC
Carbon Credit Capital’s nature-based supply-chain investment service uses its Dual-Value Model to examine supply-chain economics alongside potential sustainability outcomes.
Schedule a consultation to discuss your sourcing exposure and the questions to resolve before allocating capital.
Sources
- Intergovernmental Panel on Climate Change (IPCC), Climate Change 2022: Mitigation of Climate Change, Chapter 7, Agriculture, Forestry and Other Land Uses, section 7.4.3.3 (Agroforestry).
- World Business Council for Sustainable Development (WBCSD), Nature-based Solutions Blueprint, 5 June 2024.
- Science Based Targets initiative (SBTi), Forest, Land and Agriculture Science-Based Target-Setting Guidance, version 1.2, March 2026, section 3.1.4, pp. 37–38.
- United Nations Environment Programme (UNEP), State of Finance for Nature 2023, 2023.
A plastic credit funds the collection of plastic waste in places where no formal system exists to collect it. Each credit represents a measured, independently audited quantity of plastic taken out of the environment or returned to use, tracked on a public registry.
