Shifting Playbook for Corporate Power Procurement

Key Takeaways

• The GHG Protocol Corporate Standard and life cycle assessment (LCA) offer distinct frameworks for measuring electricity-related emissions, one for annual corporate reporting and one for detailed cradle-to-grave analysis, leading to different emissions results.
• Renewable energy certificates (RECs) are accepted under the GHG Protocol's market-based approach to reduce reported scope 2 and scope 3: category 3 emissions, but are not explicitly addressed in ISO LCA standards, where transparent disclosure is essential.
• Using both the GHG Protocol and LCA together, while recognizing their different scopes, boundaries, and purposes, can give organizations a more complete and strategic view of electricity-related emissions and decarbonization opportunities.

Electricity-Related Emissions: Why Measurement Methods Matter

In the era of AI-driven power demand, scrutiny over electricity-related emissions is intensifying. With this increased attention comes growing confusion around how to measure and report these emissions. The GHG Protocol Corporate Standard and life cycle assessment (LCA) are two widely used methods for measuring and reporting electricity-related emissions, but each follows its own complex and often incompatible, set of rules.

This piece will examine the differences between these approaches and answer common questions such as:

• What are the differences between the GHG Protocol Corporate Standard and LCA?
• Why do they result in different emissions for the same type and amount of electricity?
• Can renewable energy contracts reduce electricity-related emissions under both methods?
• When should you use each approach?

Both the GHG Protocol Corporate Standard and LCA are powerful tools that, if used in complementary ways, can help organizations identify emissions hotspots and develop more effective pathways for decarbonization.

What Is the GHG Protocol Corporate Standard?

The GHG Protocol Corporate Standard is a globally recognized framework for corporate entities to publicly report GHG emissions throughout their value chain. It divides emissions into three scopes:

• Scope 1: Direct emissions from owned or controlled sources, such as company-owned vehicles, on-site fuel consumption, or industrial processes.,
• Scope 2: Indirect emissions from the generation of purchased electricity, heat, steam, or cooling. These emissions are generated off-site, but result from an organization's energy consumption.
• Scope 3: Indirect emissions across an organization's value chain. Scope 3 is divided into 15 categories, including a company's supply chain activities, business travel, employee commuting, investments, and product life cycle emissions.

This piece focuses on emissions associated with electricity consumed by a reporting entity. These electricity-related emissions primarily fall under scope 2 and scope 3: category 3 (fuel- and energy-related activities, or FERA).

Scope 2: Electricity Generation Emissions

Scope 2 emissions account for the generation of electricity a company purchases or uses. Hypothetically, if a company were powered by a single solar project, it would report zero scope 2 emissions. In reality, a company is powered by a combination of power generation assets and must report them under scope 2 emissions. These emissions can be reported using two methods:

• Location-based method: Reflects the average emissions intensity of the local electricity grid where the consumption occurs. This approach is mandatory under various reporting frameworks and does not take into account a company's procurement choices.
• Market-based method: Reflects an organization's actual procurement decisions and energy-sourcing strategies. It accounts for specific contracts, such as power purchase agreements (PPAs), renewable energy certificates (RECs), and green tariffs, which allow businesses to claim lower emissions from their purchased electricity.

Scope 3: Category 3 FERA

Scope 3: category 3 FERA reports on non-generation electricity emissions associated with:

• Upstream emissions: Emissions associated with the production and transportation of fuels needed for electricity generation
• Transmission and distribution losses: Emissions associated with the loss of electricity while delivering it from the generator to the consumer.

The GHG Protocol Corporate Standard does not include emissions associated with the manufacturing, construction, and end-of-life phases of electricity generation equipment; however, some datasets used for reporting may include manufacturing emissions. While scope 3: category 3 guidance may not require these emissions to be included, if possible, companies reporting on their electricity-related emissions should include these additional sources of emissions  in order to more completely represent their total emissions impact. The GHG Protocol Scope 2 Guidance allows for the reduction of some of the reported scope 3 FERA emissions by contracting renewable energy (see Appendix B).

What is an LCA?

An LCA is a systematic method used to quantify the environmental impacts of a process, product, or project throughout its full life cycle. A life cycle includes everything from raw material extraction ("cradle") to manufacturing/production ("gate") through disposal ("grave").

LCAs primarily follow a standard published by the ISO organization (ISO 14040/14044). The ISO standards establish industry-wide rules for which processes are included and how to assign environmental burdens to products.

An LCA can be used for any product, process, or project, and can estimate multiple different environmental impacts (i.e., climate change, human health, ecotoxicity, eutrophication, ozone depletion).

Electricity-Related Emissions Can Be Different Using the GHG Protocol and an LCA

The GHG Protocol Corporate Standard and an LCA (as per ISO standards) generally include different life cycle stages of electricity use when estimating GHG emissions. Therefore, the approaches can result in different reported emissions.

Key Differences in Reporting Electricity-Related Emissions

The GHG Protocol Corporate Standard includes emissions in the following phases:

• Generation (scope 2)
• Transmission and distribution losses (scope 3: category 3)
• Fuel, if applicable (scope 3: category 3)

A “cradle-to-grave” LCA considers emissions from all activities associated with power generation, including:

• Manufacturing
• Construction
• Generation
• Fuel, if applicable
• Use-phase, if applicable
• End-of-life

Use-phase electricity-related emissions are emissions generated by electricity-consuming equipment used or sold by the reporting company (representing additional scope 1 or scope 3 emissions, respectively). Examples include sulfur hexafluoride (SF6) emissions from electrical transformers or refrigerant leakage from air conditioners with high global warming potential. Please note that both the ISO and GHG Protocol Corporate Standard provide guidelines for reporting these emissions. However, due to the equipment-specific nature of these emissions, they are excluded from the following table. The table compares electricity-related emissions associated with different electricity sources using the GHG Protocol Corporate Standard approach and the LCA approach.

Reporting Electricity-Related Emissions

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* US average transportation and distribution loss rate (4.2%) times US average grid carbon intensity (410 gCO₂e/kWh). Note: gCO₂e/kWh = grams of carbon dioxide equivalent per kilowatt-hour. Source: GREET 2024 (US grid average. 10% fuel- and energy-related activities; 1% construction, facilities, maintenance, and end-of-life; 89% fuel combustion).

Reducing Electricity Emissions with Renewable Energy

Renewable Energy Mechanisms Under the GHG Protocol

The GHG Protocol Corporate Standard allows companies to contract for renewable electricity as a mechanism to reduce reported emissions. The GHG Protocol Corporate Standard defines allowable energy contracts that can be used to reduce emissions associated with electricity consumption (market-based reporting).

In North America, one of these allowable contracts is RECs, each of which represent one megawatt-hour of renewable generation. Analogous instruments used in other locations, such as Guarantees of Origin in Europe and green electricity certificates in China, are also permissible under the GHG Protocol Corporate Standard.

RECs were developed as a contractual mechanism for renewable electricity in response to the fundamental structure of "a power grid." In a power grid, it is impossible to link a single generator to a single load. Power is injected at a point in the grid and withdrawn at a different point in the grid; there is no traceable pathway.

RECs were created to track the attributes of electricity generation entering into a power grid for the entity that consumes the power at a different point. The GHG Protocol Corporate Standard allows buyers to claim exclusive use of renewable electricity with RECs even if they are actually consuming a mixture of electricity from the grid.

Renewable Energy Mechanisms Under the LCA ISO Standard

The ISO 14040 standard does not address the use of renewable electricity contracts. However, the ISO 14044 standard provides the following guidance:

"When determining the elementary flows associated with production, the actual production mix should be used whenever possible, in order to reflect the various types of resources that are consumed. As an example, for the production and delivery of electricity, account shall be taken of the electricity mix, the efficiencies of fuel combustion, conversion, transmission and distribution losses."

It does not explicitly define whether RECs can or cannot be used in the determination of the "actual production mix." In the event an organization does procure a renewable energy contract to reduce the emissions reported within the LCA, it should disclose that clearly in order to communicate the impact of the contract on the carbon intensity of the LCA with and without the use of RECs.

Powerful Tools for Different Use Cases

The GHG Protocol Corporate Standard and LCAs following the ISO Standard are both powerful tools that can provide insight into emissions associated with electricity use. The GHG Protocol Corporate Standard allows companies to use a standardized framework to report emissions associated with electricity use and interventions on an annual basis. The LCA ISO standard is a detail-driven analysis that allows a deep dive into specific processes, projects, or products. This detailed analysis allows for deeper insights into areas where a company may have more ability to address specific interventions for emission hot spots. Using these tools together, while understanding the boundaries of each, can provide companies with a more effective and impactful approach to decarbonization.

Frequently Asked Questions

What are the differences between the GHG Protocol Corporate Standard and LCA? 

The GHG Protocol is an annual corporate reporting framework covering scope 2 (generation) and scope 3: category 3 (transmission and distribution losses, fuel), while a cradle-to-grave LCA is a detailed analysis governed by ISO 14040/14044 standards that also includes manufacturing, construction, use-phase, and end-of-life emissions. LCA can also be applied to any product or process and multiple environmental impacts, not just greenhouse gas emissions.

Why do they result in different emissions for the same type and amount of electricity? 

They include different life cycle stages. The GHG Protocol excludes manufacturing, construction, and end-of-life emissions of generation equipment, while an LCA includes them.

Can renewable energy contracts reduce reported electricity-related emissions under both methods? 

Under the GHG Protocol, renewable energy contracts (e.g., RECs, PPAs) are explicitly allowed to report zero market-based scope 2 emissions, though scope 3 FERA emissions remain. Under ISO LCA standards, these contracts aren't explicitly addressed. Organizations may choose to apply them, but should transparently disclose LCA results both with and without the contract's impact.

When should you use the GHG Protocol vs an LCA? 

Use the GHG Protocol for standardized, annual corporate-wide emissions reporting and tracking procurement interventions; use an LCA for a detailed, process- or product-specific deep dive to identify specific emissions hotspots. Relae recommends using both together for a more complete, strategic view of electricity-related emissions.

Key Takeaways

• Larger power users are securing behind-the-meter (BTM) power to bypass grid constraints, pairing data centers with third-party-owned generation assets that deliver electricity through a private line rather than the grid.
• BTM power arrangements can create confusion about electricity emissions classification: the power users neither own the generating asset nor purchase electricity from the grid, leading some to misclassify those emissions as scope 3 in their corporate GHG inventories. But the GHG Protocol's Corporate Standard is clear: BTM electricity emissions belong in scope 2.
• Misclassifying BTM emissions can create reputational and regulatory risk. Relae can help organizations get this right before the contract closes.

Why Large Power Users Are Turning to Behind-the-Meter Power

Large power users are consuming more electricity due to data center growth and are looking to add capacity faster than the grid can support, which is having a direct impact on corporate emissions. For example, between 2020 and 2024, Microsoft’s location-based scope 2 emissions rose 130%, and Google’s rose 92%, driven almost entirely by soaring electricity demand from AI infrastructure. 

To bypass grid congestion and long interconnection queues, many are turning to behind-the-meter (BTM) power. It’s a pragmatic solution to a real supply problem, but it’s opening an urgent carbon accounting question: when the BTM asset is owned and operated by a third party, where should we account for those emissions?

There has been some confusion that has resulted in companies pursuing an interpretation that would place those emissions in scope 3. The GHG Protocol’s Corporate Standard says otherwise, and the stakes of getting this wrong are high.

What Is Behind-the-Meter Power Generation?

Behind-the-meter refers to electricity generated on the power consumer’s side of the utility meter, bypassing the grid, and typically located on or near the site where the power is consumed. 

In most BTM arrangements for a data center, a third-party developer builds and operates a generation asset, such as natural gas, geothermal, or renewable energy, and delivers electricity directly to the facility through a private transmission line. There is no utility meter, no grid connection, and no standard energy invoice. 

This structure allows companies to access large, reliable blocks of power without waiting years for grid interconnection approvals. Since the company does not own or operate the generation asset and is not purchasing electricity through a conventional utility relationship, this arrangement has created some uncertainty around how to account for the associated emissions. 

Can BTM Electricity Emissions Be Classified As Scope 3?

In this scenario, no. The GHG Protocol's Corporate Standard is unambiguous: BTM electricity emissions belong in scope 2, not scope 3. Yet, some companies have been confused about this classification.

There is broad agreement that since the power users do not own or operate the generating asset, those emissions do not belong in scope 1. Divergence starts when we consider that the company is purchasing BTM power, i.e., not from the grid. Since no electricity is acquired from the grid, some argue that rather than accounting for these emissions in scope 2, they are better placed in scope 3, category 8: emissions from leased assets. 

The appeal is obvious for BTM power consumers. Scope 3 emissions face less scrutiny from investors, auditors, and regulators who focus most of their attention on scopes 1 and 2. Classifying BTM emissions as scope 3 would reduce near-term pressure to act. However, the GHG Protocol is unambiguous in its stance.

What the GHG Protocol Actually Says

The GHG Protocol’s Scope 2 Guidance states that “organizations must quantify emissions from the generation of acquired and consumed electricity, steam, heat, or cooling (collectively referred to as ‘electricity’).” The method of delivery, whether grid or BTM, does not change the classification. 

If a company consumes electricity from a BTM source, the emissions from generating that electricity belong in scope 2. Section 5.4 of the Scope 2 Guidance addresses BTM power generation directly: “the company with operational or financial control of the energy generation facility reports those emissions in scope 1, following the operational control approach, while the consumer of the energy reports the emissions in scope 2.”

This resolves the question completely. The emissions sit in scope 1 if the company has operational or financial control of the asset, or in scope 2 if a third party controls it.

The GHG Protocol’s Corporate Value Chain (Scope 3) Accounting and Reporting Standard reinforces this conclusion. “Category 8 includes emissions from the operation of assets that are leased by the reporting company in the reporting year and not already included in the reporting company’s scope 1 or scope 2 inventories.”

Because BTM electricity emissions are captured by the Scope 2 Guidance, the scope 3 category 8 does not apply.

Get the Accounting Right Before the Contract Closes

The GHG Protocol is unambiguous: behind-the-meter electricity emissions belong in scope 2 for companies that consume, but do not control the generating asset. This means that BTM contract terms are crucial to determining how the emissions will be classified, since the GHG Protocol assigns scope based on who holds operational or financial control of the generating asset. 

Companies that move fast on BTM capacity without understanding this distinction risk locking in a scope 1 or scope 2 obligation they didn't anticipate or building a reporting strategy around a scope 3 interpretation the GHG Protocol doesn't support. This can become a reputational or even a regulatory liability that is far harder to address after the contract is signed.

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Key Takeaways

• Community opposition has blocked, withdrawn, or stalled more than $170 billion in announced AI data center investment across 20 US states since January 2024. The pace is accelerating: 6 cancellations in 2024, 25 in 2025, and more than 20 additional cancellations by May 15, 2026.
• Data center opposition is bipartisan. It spans red and blue counties, every region, and multiple grid operators, with nearly two-thirds of the blocked investment sitting in counties that voted for Donald Trump in 2024. 
• Process and transparency, more than resource concerns alone, drive the fastest and most durable opposition. How a developer runs the engagement process shapes both community sentiment and the project’s ultimate success.

How Many AI Data Center Projects Have Been Cancelled? 

Between January 1, 2024, and May 15, 2026, community opposition blocked, withdrew, or stalled 46 announced AI data center projects across 20 US states, representing more than $170 billion in announced investment. These values are disclosed or derived for 35 of the 46 projects; the remaining 11 carry no public figure.

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The pace of successful opposition has accelerated sharply. Cancellations rose from 6 in 2024 to 25 in 2025. The first five months of 2026 added more than 20 additional cancellations, the fastest stretch on record. 

Virginia leads the state count with 11 blocked projects, followed by Indiana with 7 and Texas with 5. Together, those three states account for roughly half of all cancellations in the dataset. The PJM grid region carries the largest single share of blocked investment at $70 billion across 13 projects, followed by MISO at $37 billion.

Is Opposition to Data Centers Bipartisan?

Yes. The opposition wave crosses party lines on every measure we examined. Republican-leaning counties hosted 28 of the 46 projects (61%), Democratic-leaning counties hosted 16 (35%), and 2 fell within five points.

Weighted by announced investment, about two-thirds of blocked dollars sat in Republican-voting counties. Strong Republican counties (those Trump won by more than 15 points) account for $99 billion across 23 projects. Strong Democratic counties account for $29 billion across 9 projects. The remaining $44 billion spans Lean Republican, Tossup, and Lean Democratic counties.

Why Are Communities Opposing Data Centers?

Communities raise a consistent set of concerns across the country: water demand, electricity rates, air quality where developers propose gas co-generation, rural character, and a lack of transparency in the development process. 

Across the seven cases that we studied in depth, process, and transparency concerns were the most consistently cited factors associated with opposition. Non-disclosure agreements between developers and local officials, ownership structures in which the ultimate end-user was not publicly identified, and closed-door pre-application negotiations produce opposition faster and more durably than any other concern.

The pattern holds across very different communities: a diffuse civic mobilization in rural Georgia, an NGO water coalition in a Texas college town, a conservation coalition anchored by the Southern Environmental Law Center in Southside, Virginia, and an institutional civic organization with legal-expert and celebrity support in northern Virginia. Each produced the same outcome, and each flagged process and transparency as a dominant or top-three concern in the public record.

By the time a project reaches its first public hearing against organized community opposition, the political path of the project is largely set. Late-stage benefits packages consistently fail to reverse that trajectory. Communities read them as concessions, not commitments.

Assess Community Opposition Risk Before You Site

Community opposition is now a structural feature of the AI data center siting environment. The patterns are clear enough to act on now. Relae's Community Impacts team helps developers and capital partners implement responsible development standards through pre-siting community intelligence, calibration of benefits design to specific community contexts, and building the verification scaffolding that turns commitments into outcomes. 

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Frequently Asked Questions 

Which states are banning data centers in the US?

The first statewide moratoriums on data centers have arrived. In July 2026, Governor Hochul signed the country's first statewide moratorium, an executive order pausing state environmental permits for up to one year for new data centers of 50 MW or more. Texas followed weeks later, halting approvals of new data center grid connections until state regulators audit their power, water, tax, and ownership details. This is a snapshot from August 2026, and we will likely see additional changes in the months ahead.

The local picture is more developed. Individual municipalities and counties have adopted moratoria and zoning ordinance amendments that block or restrict data centers within their jurisdictions. The City of Peculiar, Missouri, removed data centers from its light-industrial zoning entirely. Monroe County, Georgia, and Jones County, Georgia, both adopted moratoria after project denials in 2025. Cassville Township, Wisconsin, and San Marcos, Texas adopted zoning and code amendments in 2026. State legislatures in Virginia, Indiana, Texas, and Missouri have taken up data center siting, ratepayer, and permitting legislation, though most bills remain in progress rather than enacted.

How much data center investment has been blocked in the US?

More than $170 billion in announced AI data center investment has been blocked, withdrawn, or stalled by community opposition across 46 projects and 20 US states between January 1, 2024 and May 15, 2026. 

Relae arrived at this figure from data on 35 of the 46 projects; 11 have no publicly disclosed investment value. The pace has accelerated sharply: 6 cancellations in 2024, 25 in 2025, and more than 20 additional cancellations in the first five months of 2026 alone. Virginia leads the state count with 11 projects. The PJM grid region carries the largest single share of blocked capacity at $70 billion across 13 projects.

What causes a data center project to be cancelled by community opposition?

As of August 2026, communities cite a consistent set of concerns across cancelled projects: water demand, grid strain and residential rate impacts, air quality where developers propose gas-fired co-generation, rural character and farmland conversion, and lack of transparency in the development process. 

In the seven cases we studied in depth, process and transparency were together the most consistent driver of opposition. Non-disclosure agreements between developers and local officials, shell LLC ownership structures that conceal the end-user, and closed-door pre-application negotiations produce faster and more durable opposition than any single resource concern. Late-stage benefits packages consistently fail once that transparency-driven frame has formed.

Key Takeaways

• Trust in carbon credits remains low. In part, this is because many mistakenly treat every credit type as interchangeable.
• Reduction, removal, and avoidance credits are verified against fundamentally different baselines, so credit quality must be judged based on type and project specifics, never with one blanket standard.
• The Integrity Council for the Voluntary Carbon Market's Core Carbon Principles now give buyers an independent bar to check against, including 44 methodologies approved across 13 eligible crediting programs, as of August 2026.
• Removal credits still make up only 5–6% of the market, even as compliance-driven demand accelerates, per our 2026 State of the Voluntary Carbon Market report.

Three Types of Carbon Credits: Reduction, Removal, and Avoidance

A carbon credit is a mechanism that allows one party to compensate another for their carbon mitigation activities. Based on their net emissions impact, there are three types of carbon credits: reduction, removal, and avoidance. 

1. Reduction credits reflect activities that decrease greenhouse gas emissions, compared to prior practices. 
2. Removal credits reflect activities that remove carbon dioxide already present in the atmosphere and oceans and lock it away for decades, centuries, or millennia.
3. Avoidance credits reflect activities that prevent greenhouse gases from being emitted in the first place. For all three types, credits are assessed and issued by measuring or estimating how much carbon is reduced, removed, or avoided as a result of a credit purchase and its associated activities.

While credits are assessed in different ways depending on the type, one of the most important indicators of quality is a project's baseline - the emissions that would be present in a business-as-usual scenario, without action being taken to reduce, remove, or avoid them. Project developers use baselines as a means of comparison to assess the net emissions impact of a project. 

• Baselines must be accurately set and data-driven. 
• Emissions impacts of a project must be correctly calculated against its baseline. 

Reduction, removal, and avoidance projects involve very different activities and, for some types of projects, it may be more challenging to establish an accurate baseline. However, without accurate baselines, climate impacts cannot be reliably determined.

Across the voluntary carbon market, Reduction credits represent roughly 20% of the purchases. Removal credits represent roughly 5% of the purchases. The remainder, roughly 75%, are avoidance credits.

Carbon Reduction Credits

Carbon reduction must drive the majority of our push to net zero, but translating carbon reduction activities into carbon credits that can be purchased is challenging. Examples of activities represented by carbon reduction credits include reducing fossil fuel use by improving fuel efficiency, or programs that reduce the methane that is generated from farms or municipal waste processing. 

Reduction credits are measured and quantified against the baseline emissions of an existing technology or process. Some reduction credits are easy to track and measure, such as efficiency investments or destruction of fugitive methane. Other projects are more complex. For example, low-emission cookstove projects in developing regions rely on tracking patterns of cookstove use and quantifying emission factors for various fuel and stove combinations, both of which are hard to do. The result, as studies have shown, sometimes leads to overcrediting in reduction projects. 

Superpollutant Credits

One class of reduction credit, superpollutant credits, has garnered recent attention. These credits involve the reduction of non-CO2 greenhouse gases with very strong radiative forcing, such as methane, nitrous oxides, or fluorinated gases like chlorofluorocarbons. These are not a substitute for CO2 removal, but can provide rapid and profound reductions at modest cost. Many different kinds of superpollutants exist in today’s market, worth roughly $60M today. Recent purchases by tech companies and others have highlighted the potential of these reduction credits.

Another class of reduction credit, transition credits, involves the deliberate early closure of emitting assets like coal-fired power plants or heavy manufacturing facilities. Early efforts by governments, banks, and companies around the world under the Just Energy Transition Partnership agreement jump-started transition credits as a concept at COP26. The Kinetic Coalition, in partnership with many groups including Relae, has launched work to bring transition credits to market with several pilot efforts, including closing a coal plant in the Philippines 10 years early. 

Carbon Removal Credits

Projects that remove carbon come from a diverse set of solutions, from nature-based solutions like reforestation, to hybrid solutions like biochar, to engineered solutions such as direct air capture and storage. Roughly 5–6% of credits on the voluntary carbon market today are classified as removals, up from roughly 3% a few years ago.

Carbon removal baselines are determined differently depending on whether a project uses an engineered, hybrid, or nature-based solution. For engineered removals, the baseline is zero, because no carbon removal was occurring in the absence of the project. The credited removal will be the difference between the quantity of carbon removed and any emissions that occur to facilitate the removal (determined through a carbon credit life cycle assessment). Baselines for hybrid and nature-based removals can be more challenging. In natural systems, changes in carbon stocks created by removals must be measured and approximated over time, and creditable removals represent the additional carbon removed by the intervention relative to the baseline (e.g., fallow land versus a reforestation project).

Another important consideration for carbon removal credits is project durability, a measure of the likely duration of carbon storage. Stored carbon can re-enter the atmosphere either through deliberate actions (e.g., deforestation) or accidental ones (e.g., wildfires). Nature-based removals are especially vulnerable to being re-released and are usually considered less durable (i.e., stored for less than 50 years). In contrast, engineered solutions offer high durability (i.e., stored for hundreds to thousands of years), and hybrid removals also offer durability periods that are typically longer than those of nature-based removals.

While less durable, nature-based solutions are effective, cost-effective, and widely available today. They made up over 95% of all carbon removal credits issued in 2025. Engineered and hybrid solutions are more expensive and scarce but offer longer durability. Prices of engineered carbon removal are likely to fall with innovation and increased market participation, but are currently much higher than most nature-based credits. With SBTi's finalized Corporate Net-Zero Standard V2.0, this balance is likely to shift. Large companies must now purchase removal credits covering 1–100% of scope 1, scope 2, and scope 3 emissions between 2035 and their net-zero year, with an explicit focus on more durable CO2 removal credits.

Carbon Avoidance Credits

Examples of carbon avoidance include avoiding deforestation that would result in the release of carbon dioxide into the atmosphere or clean energy projects that avoid the release of emissions from burning fossil fuels in possible facilities. This can be confusing, since many avoided credits are called reduction credits, as is the case with projects under the Reducing Emissions from Deforestation and Forest Degradation (REDD+) framework. Avoidance credits make up roughly 75% of certified credits on the voluntary carbon market today - an overwhelming majority - in part due to high availability and low price. 

Avoiding emissions is an important goal with numerous environmental, climate, community, and other benefits. Relae works with clients and customers across industries on developing and implementing strategies to avoid emissions within their value chain. However, there are significant challenges with the way that many carbon avoidance credits are created.

• Carbon avoidance credits are based on an estimate of the emissions that might have existed had a project not been funded. Because it is impossible to observe what might have happened in the absence of a project, carbon avoidance estimates are determined by considering historic data and contextual information. Statistical models can be used to create a presumed baseline that represents what would have happened in the absence of the project.

• Because the baseline is not observed in an avoided emissions project, there is uncertainty in calculating the number of carbon credits it produces. If the baseline is not set accurately, a project can overcredit. While the lack of a directly observed and measured baseline means avoidance credits will always have some degree of uncertainty, high-quality avoidance projects present compelling evidence to support their baselines, greatly reducing uncertainty. 

New datasets, statistical techniques, and methodologies are providing opportunities for developing avoidance credits with more certainty. Three REDD+ methodologies have now cleared the Integrity Council for the Voluntary Carbon Market (ICVCM) assessment for its Core Carbon Principles (CCPs), a concrete sign that credit quality standards for avoidance projects are maturing.

Defining and Standardizing Quality in the Voluntary Carbon Market

Carbon credits are intended to reduce, remove, or avoid emissions. They pay for an environmental service that must be delivered. Companies working to generate climate benefits through credit purchases must grapple with the differences and uncertainties of credit quality to ensure that the intended benefits are realized. 

While high-quality credits exist for all types of projects, a rich understanding of the differences in methodologies, geographies, physics, and ecology is required to identify high-quality projects and understand varied certainty, durability, and risk terms. Identifying high-quality carbon projects demands extensive and project-specific diligence beyond carbon market certification.

Our own diligence work reveals that high-quality projects can be hard to find. Fewer than 10% of the carbon removal projects we assessed for our 2026 State of the Voluntary Carbon Market report met our quality criteria. This diligence work now has an additional, independent backstop. As of August 2026, the ICVCM has approved 44 methodologies across 13 programs, as eligible for its CCP label, including ACR, Gold Standard, and VCS. For buyers, considering projects that are CCP-eligible should be used as a first filter—not a substitute for project-level diligence, but representing a legitimate floor.

While realized emissions impacts may be difficult to prove in some cases, it is important to remember that some projects provide additional co-benefits. REDD+ projects, for example, may have a positive impact on conservation and biodiversity, and cookstove projects may offer clear human health and social welfare benefits. However, these benefits should be assessed separately from carbon reduction, removal, or avoidance benefits.

Frequently Asked Questions

What's the difference between a carbon credit and a carbon offset? 

A carbon credit represents one verified tonne of emissions reduced, removed, or avoided. A  carbon offset describes how a buyer uses that credit, typically to counterbalance emissions it has not yet accounted for. The credit itself does not change type based on how it's claimed.

Which type of carbon credit—reduction, removal, or avoidance—is highest quality? 

No single type is inherently highest quality. Each project, regardless of type, is verified against a defined baseline. Quality depends on how rigorously that specific baseline was set and how well the project meets other quality criteria. Removal credits from engineered sources have the most straightforward baseline (zero), and avoidance credits carry the most baseline uncertainty by design, but these are only one determinant of credit quality.

Do carbon removal credits automatically meet the ICVCM’s Core Carbon Principles? 

No. The ICVCM assesses methodologies and programs, not individual projects. If a project uses a methodology that is eligible for the CCP label, this can be a useful floor but is not a guarantee of high quality.

How does SBTi's near-term removal mandate change which credits I should buy now?

SBTi's finalized Corporate Net-Zero Standard V2.0 doesn't require removal purchases until 2035, but it sets the ramp now (i.e., 1% of scope 1, scope 2, and scope 3 emissions in 2035, scaling to 100% by the net-zero year). This means the highest-durability removal supply that is scarcest and most in demand today is the same supply that many companies will need later. The SBTi guidelines are still changing, so buyers and project developers must track them closely.

Key Takeaways

• Buyers have been navigating the low-carbon fuels (LCF) market without a map.  The LCF market is expanding rapidly, but standards, definitions, and quality claims vary widely across regions, certification schemes, and regulatory systems, leaving voluntary buyers without a holistic framework for evaluating what they procure.
• Certifications cover some of the picture, not all of it. Existing certification schemes provide valuable assurance but vary in scope and rigor, and few, if any, were designed specifically with voluntary market buyers in mind. 
• The 2026 criteria give buyers a legible quality framework. The 2026 Criteria for High-Quality Low Carbon Fuels bring together key sustainability considerations across six principles, including social and environmental integrity, carbon accounting, additionality, feedstock sourcing, and leakage, giving buyers and producers a legible, living framework to navigate procurement decisions with confidence.

Verifying Quality Is Challenging in the Current Low-Carbon Fuels Market

For airlines, logistics companies, and large corporations with hard-to-abate transportation emissions, low-carbon fuels (LCFs) have become an important part of the decarbonization toolkit. Yet it remains difficult for procurement teams to answer a fundamental question: what does high-quality procurement actually look like? 

Standards, definitions, and sustainability claims vary widely across regions, certification bodies, and regulatory programs. The result is a market where quality is difficult to verify, certifications are difficult to compare, and the gap between a fuel's claims and its actual sustainability profile can be hard to close. Sustainable production will be especially critical as the market scales, because low-carbon fuel systems are deeply embedded in land, agriculture, forestry, and communities. 

The 2026 Criteria for High-Quality Low Carbon Fuels are designed to close this gap, giving voluntary buyers a consistent framework to evaluate the quality of what they procure and identify where additional diligence is still needed.

What Is a Low-Carbon Fuel?

For the purposes of the criteria, a low-carbon fuel, or LCF, is defined as a fuel or energy source whose lifecycle greenhouse gas (GHG) emissions are lower than those of a relevant, use-case-specific fossil fuel alternative. In this case, we are referring to the physical biofuel and its associated environmental attributes. 

While LCFs may be produced through biological, synthetic, or other non-fossil pathways, the 2026 edition focuses on biofuels for transportation, which currently represent the majority of LCF production and use. 

Understanding the Complex LCF Regulatory and Certification Landscape

The LCF market sits at the intersection of multiple regulatory and voluntary markets. In the US, this includes compliance programs such as the Renewable Fuel Standard (RFS) and state-level Low Carbon Fuel Standards (LCFS). Europe, the United Kingdom, Canada, and many other nations host comparable programs, often with specialized regulatory regimes for various transport sectors, e.g., aviation or maritime. 

These regulatory markets coincide with and often intersect voluntary markets, which contain a multitude of standards and certifications. For producers, this creates a complex landscape of market options. For buyers, it creates a signal problem: a fuel may carry one or more certifications, comply with one or more regulatory programs, and still leave meaningful sustainability questions unaddressed.

Several organizations, including the Roundtable on Sustainable Biomaterials (RSB) and the International Sustainability and Carbon Certification (ISCC), have developed widely used standards for LCFs. These certifications assess supply chains from feedstock to end use and provide important baseline assurance. 

However, they were developed with different primary audiences in mind and can vary in scope and rigor. Few existing schemes were designed to serve as a comprehensive sustainability reference for voluntary market buyers evaluating what a given fuel's certification covers and where gaps may still exist.

Simplifying High-Quality Procurement for Voluntary Buyers 

The 2026 Criteria for High-Quality Low Carbon Fuels are not designed to replace or compete with existing certification schemes. Rather, they consolidate key sustainability considerations from across the landscape of existing frameworks into a single, legible reference built specifically for voluntary market decision-makers.

The criteria apply across the full LCF supply chain, covering not only fuel producers but also fuel blenders, aggregators, and certificate traders. This LCF systems view encompasses the full set of production, certification, and procurement arrangements through which LCFs are generated and claimed. This reflects the reality that sustainability outcomes in this market are shaped by many actors, not just at the point of production.

The criteria distinguish between requirements that must be met (minimum thresholds for quality and integrity) and considerations that should be addressed, reflecting best practices and aspirational standards. This distinction is intentional: the criteria set a floor while leaving room for market participants to demonstrate quality in ways appropriate to their specific context. 

The criteria are organized around six core principles that together define what high-quality LCF production and procurement looks like. 

Six Principles for Procuring High-Quality Low-Carbon Fuels

1. Social harms, benefits, and environmental justice: preventing new harms to communities, reducing existing ones, and ensuring equitable distribution of benefits
2. Environmental harms and benefits: minimizing impacts on air, soil, water, and biodiversity
3. Carbon accounting: accurately quantifying lifecycle GHG emissions using credible methodologies and tracking environmental attributes to prevent double-counting
4. Additionality: demonstrating that voluntary market support enables outcomes that would not otherwise occur
5. Feedstock sourcing: ensuring responsible and equitable sourcing practices and requiring end-to-end chain-of-custody documentation traceable to the point of generation
6. Leakage: assessing and mitigating activity-shifting and market leakage associated with the LCF system

Where a fuel's existing certification or regulatory program adherence already addresses one or more of these core principles, that coverage should be disclosed to the buyer by the producer. Buyers can then use the criteria to identify where certification coverage aligns with quality expectations, and where supplemental diligence is needed.

A Living Framework for a Market in Motion  

The LCF market will continue to evolve as policy frameworks are shifting, certification systems are maturing, and new production pathways are emerging. The 2026 edition reflects the current state of the LCF market and is intended as a living resource, with future updates possible as the market develops and new science emerges. Future editions may expand to cover synthetic LCF pathways, renewable natural gas, and sector-specific considerations such as maritime fuels.

For buyers navigating voluntary LCF procurement, the criteria offer a practical starting point: a framework to evaluate what existing certifications cover, identify where additional diligence is needed, and build procurement decisions on a consistent quality foundation. For producers, they provide clear guidance on what a sustainability demonstration looks like for voluntary market buyers.

Read the 2026 Criteria for High-Quality Low Carbon Fuels to learn more about how the criteria apply to your procurement strategy or production system.

Frequently Asked Questions

What is a low-carbon fuel?
A low-carbon fuel is a fuel whose lifecycle greenhouse gas emissions are lower than a comparable fossil fuel alternative for the same use case. The 2026 LCF Criteria focus specifically on biofuels for transportation, which currently make up most LCF production and use.

What do the 2026 Criteria for High-Quality Low Carbon Fuels cover?
The criteria are organized around six principles: social harms, benefits, and environmental justice; environmental harms and benefits; carbon accounting; additionality; feedstock sourcing; and leakage. Together they give buyers and producers a consistent way to evaluate what high-quality LCF production and procurement looks like.

Do the LCF criteria replace existing certifications like RSB or ISCC?
No. The criteria aren't designed to replace or compete with existing certification schemes such as the Roundtable on Sustainable Biomaterials (RSB) or the International Sustainability and Carbon Certification (ISCC). Instead, they consolidate key sustainability considerations from across those frameworks into a single reference so buyers can see what their certification already covers and where supplemental diligence may be needed.

Who do the LCF criteria apply to across the supply chain?
The criteria apply across the full LCF supply chain, not just producers, but also feedstock suppliers, fuel blenders, aggregators, and certificate traders, reflecting that sustainability outcomes are shaped by many actors, not only the producer.

What's the difference between the "must" and "should" requirements in the LCF criteria?
"Must" requirements set minimum thresholds for quality and integrity that need to be met, while "should" considerations reflect best practices and aspirational standards market participants can work toward. This sets a floor while leaving room for participants to demonstrate quality in ways suited to their specific context.

Key Takeaways

• Power demand is outrunning buildout. Meeting large load growth requires more than new generation; it requires faster interconnection and congestion relief on existing transmission lines. 
• Dynamic line rating (DLR) is available today, deploys in months, and enables faster speed-to-power. On the right thermally congested lines, DLR can unlock more capacity at a fraction of new infrastructure cost. In one utility demonstration, 5% to 10% of additional capacity was enough to clear most of the congestion on the lines studied.
• DLR has been held back by weak incentives, but that is changing. Utilities earn a regulated return on capital they invest in new assets, which favors building new infrastructure over lower-cost solutions like DLR. Load growth and new Federal Energy Regulatory Commission (FERC) mandates are starting to shift the calculus.

The Grid Cannot Expand Fast Enough for AI Demand, But It Can Carry More

Power demand is booming as data centers scale across the US grid, and current grid infrastructure cannot supply it. This constraint is physical, not financial. Meeting this demand requires a significant amount of power generation and infrastructure upgrades. More than 2 terawatts of generation and storage sit in interconnection queues, roughly 1.5x the total installed generation capacity in the US. 

Regional markets are working to accelerate generation buildouts, but connecting that generation to the transmission network remains expensive and slow to match speed-to-power needs. New high-voltage lines take years to permit, cost between $2 million and $6 million per mile to build, and major projects routinely take five to ten years from identification to energization. For example, PJM Interconnection LLC (PJM) identified the Doubs–Goose Creek 500 kilovolt (kV) corridor as a bottleneck feeding Data Center Alley in 2023 and set June 2027 as the date a fix was needed. Dominion Energy's published schedule for its portion of that rebuild anticipates a completion date of 2031.

A number of studies^1,2 show there is headroom in the bulk transmission system. Grid-enhancing technologies, such as dynamic line rating (DLR), can convert part of that headroom into capacity today while new generation and transmission are being built. DLR lets suitable transmission lines increase their carrying capacity in real time, unlocking that headroom at a fraction of the cost of a buildout. Realizing that value is a targeting exercise with a key question: On which thermally limited lines can DLR actually relieve congestion? 

What Is Dynamic Line Rating?

Dynamic line rating is a method for calculating a transmission line's real-time carrying capacity using live weather and conductor-temperature data. It lets grid operators safely carry more power whenever weather conditions allow.

Most transmission lines operate under a static rating: a fixed, conservative limit on current, set for worst-case weather and held all year. The limit is based on temperature, because pushing too much current can overheat the conductor wire. Metal conductors expand as they heat, which can make them sag and touch trees or other obstacles, causing short circuits or fires. Real conditions almost always cool a conductor better than the worst-case assumption a static rating is built on. That means the line can carry more current while staying at the same maximum conductor temperature, and therefore within the same sag and clearance envelope. That headroom is exactly what DLR captures: instead of leaving it on the table, DLR recalculates the line's rating in real time so operators can use the extra capacity safely.

Beyond a static rating is the ambient-adjusted rating (AAR), which many utilities have begun adopting. An AAR recalculates the rating from forecast ambient air temperature, typically hourly and out to several days. DLR goes further, adding wind speed and direction, solar heating, and in some deployments the conductor's measured temperature.

DLR technologies rest on a heat-balance algorithm: how fast a line heats up (from electric current and sunshine) versus how fast it cools off (from wind and cold air). The calculations are standardized in IEEE 738 in North America and CIGRE 601 internationally. The data feeding those calculations can come from line-mounted sensors, weather models, or both, depending on a tradeoff between per-span accuracy and the cost of installing sensors along every span.

Even so, DLR remains limited in the US, and AAR has been slow to arrive. FERC's Order 881 required the transmission providers it regulates to adopt AAR by July 2025, but FERC has granted numerous extensions. PJM became the first to fully implement AAR in March 2026, while Midcontinent Independent System Operator (MISO) and New York Independent System Operator (NYISO) are not expected until 2028.

The Near-Term Value of DLR: Reducing Grid Congestion

DLR's value is immediate. It can be installed in months, not years, so a currently congested line can start carrying more power the moment conditions allow, reducing congestion right away. When cheaper generation is available upstream of that line, DLR cuts costs directly, because grid operators no longer need to dispatch pricier generation downstream of the congestion to supply load. That means DLR can reduce congestion costs in the current delivery year, compared to a transmission line rebuild that sits in a decade-long queue. 

Over a longer horizon, utility planners can build that headroom into long-term capacity models. This is important, because current capacity-expansion and integrated resource plan (IRP) models still run on static or seasonal ratings, and typically leave out the potential gains from grid-enhancing technologies like DLR. 

NERC's large loads white paper and FERC's RM26-4 rulemaking both raise the issue of how utilities can absorb multi-hundred-megawatt data center requests without a decade-long transmission build. Solutions like DLR are one of the few tools that can compress that timeline. 

The hardware itself is cheap: sensors and data management cost a small fraction of any physical upgrade. That means the economics comes down to identifying the lines that benefit most from DLR. This is particularly important because on most US grids, congestion concentrates on a small number of lines that repeatedly reach their limits. On those lines, DLR can cut congestion costs directly and defer costlier upgrades, while its potential on other lines may be far lower. As a result, identifying those high-potential, thermally congested lines is essential.

Proven DLR Examples in the Industry 

Real deployments show DLR can reduce a meaningful share of transmission congestion costs, with extra carrying capacity above the static rating running roughly 5% to 30%, depending on how often that capacity is available. In Oncor's ERCOT demonstration, 5% of additional capacity would have relieved up to 60% of congestion on the target lines, and 10% would have practically eliminated it. PPL Electric in Pennsylvania/PJM reports annual customer savings of $23 million after deploying DLR across its initial three lines. The DLR installation cost about $250,000, against a rebuild alternative that would have cost about $50 million and taken far longer. 

The contrast abroad is instructive. Austria's grid operator, APG, recorded about $13 million a year in congestion savings across roughly 15% of its network. While these savings are real, it's important to recognize that these results come from single, well-chosen, badly congested lines. 

The UK's National Grid began with a two-year DLR trial on a single 275 kV circuit in 2022, expanded to more than 275 kilometers of its network by 2025, with estimated consumer savings of about $26 million a year. In April 2026, National Grid signed a five-year contract covering 585 kilometers more, with most installations due by 2028 and potential savings of up to $66 million. Each expansion followed measured results from the stage before it.

Where the Headroom Is: Screening PJM's Data Center Alley

To illustrate the congestion savings from DLR, Relae screened PJM's five-minute real-time market record for every binding transmission constraint in 2025. For each one, we captured the shadow price, the marginal value of relaxing that constraint.³

Our analysis focused on thermal constraints, and then identified lines that bind frequently, in conditions milder than the worst case their static rating was set for, which is when a conductor's true rating sits above its static assumption. For the lines that we identified, congestion costs were added over the binding hours to set a bound on the savings that could result from DLR. That full amount would not necessarily be realized in practice, because the shadow price values only the next megawatt freed, and relieving one line can shift the constraint to the next. However, it serves as a useful estimate for the scale of savings that could be achieved.

We ran the analysis on the Dominion (DOM) zone in PJM, home to Data Center Alley in Loudoun County, Virginia. Figure 2 shows a high-level section of the grid. The 500 kV bulk grid steps down through transformers to the 230 kV substations feeding the data centers, with the lines that experience recurring congestion highlighted. A handful of those 230 kV lines showed up as binding thermal constraints again and again. 

The congestion in DOM isn't constant, and it concentrates in particular months and within the day in particular hours. Figure 3 shows three transmission lines within the DOM zone and the number of hours each was thermally congested in each hour-of-day slot over 2025. Binding concentrates in the warm months and, within the day, from late morning through early evening. 

At first glance, this period looks like the wrong window for DLR. The local weather record says otherwise. These periods turn out to be some of the windiest hours of the day, not the stillest. Median wind speed at Dulles ran about 3.5 m/s, above the 0.6 m/s crossflow a static rating conventionally assumes, with fewer than 5% of observations falling below that threshold. Median ambient temperature in those hours was about 26°C, against the 35–40°C a static summer rating is typically built for. Across all three lines, the large majority of congested hours coincided with weather that would have supported a materially higher rating. 

Valuing just one megawatt of DLR relief at each five-minute shadow price, the estimated savings are worth roughly $300,000 in this three-line example across about 263 line-hours.⁴

Because the value concentrates on a handful of thermally limited, heavily congested lines, and because the operational case has to be made line by line, capturing the opportunity is fundamentally an analytics problem: find the right lines, and prove the savings.

What Does It Take to Scale DLR?

DLR is cheap and effective, but two things stand between it and broader adoption: incentives and advanced grid analytics.

The utility cost-of-service model recovers investment in generation and transmission assets and earns its profit as a regulated return on the capital deployed. Because rates recover capital rather than power delivered, utilities have a stronger incentive to build or upgrade lines than to move more power across the ones they already own. That bias toward capital investment over optimization is why a mature technology has stayed niche in the US for years. Regulators have started to look more closely at this, but the main federal rule still mandates the milder AAR, not DLR, and leaves the return model untouched.

Contingency analysis compounds the problem. Current models are built around fixed line limits. A rating that changes hour to hour adds real modeling work, and more importantly, the system still has to hold under worst-case contingencies. So while operators already forecast weather daily for wind and solar, the harder step is trusting a forecast enough to commit a transmission limit against it. That takes significant predictive analytics built into system planning, not bolted on after.⁵

How Policy Is Starting to Shift the Calculus

Policy is starting to move the incentive problem. FERC's Order 881 made AAR the minimum for the transmission providers it regulates (effective July 2025, with several operators on extended timelines) and required markets to be capable of accepting dynamic ratings. PJM has started to implement this: PPL Electric has run sensor-based DLR on nine congested lines since 2022, feeding PJM's day-ahead markets. 

Order 1920, FERC's first long-term transmission-planning overhaul in more than a decade, now requires planners to formally evaluate grid-enhancing technologies like DLR against conventional builds. It stops short of mandating deployment, but it forces a comparison utilities used to skip. That comparison is now written into filed tariff processes (PJM filed its plan in December 2025). Those first cycles only began in 2026, and the order allows up to three years to reach a selection, so the results are still pending. 

A shared-savings incentive, letting a utility keep a slice of the congestion savings it creates, has been proposed to FERC and championed in the Advancing GETs Act, but it isn't yet a rule, so the core misalignment stands. DOE's GRIP program has funded grid-enhancing deployments, and by early 2026, 16 states had some form of advanced transmission technology requirement, with Colorado adding its Grid Optimization Act in April 2026.

The newest pressure is coming from the demand side. Through 2025–26, FERC began overhauling how large loads connect to the grid, and while none of it touches the utility's return on capital, it changes who sees the costs. FERC issued show-cause orders directing all six grid operators to justify or reform their large-load rules. This tees up consideration of alternative transmission technologies in study processes and greater transparency into costs. 

And the rules are moving toward making the large load pay for the upgrades its connection requires. Pennsylvania's model large-load tariff, for example, recommends utilities charge data centers for the upgrades their interconnection makes necessary. It also instructs utilities to let those customers self-construct certain upgrades, including some affecting the wider grid. That combination is what matters. The party paying the bill now has a reason to ask whether a cheaper fix exists and, in at least one state, a route to build it. We have not yet seen a DLR deployment selected this way, because these frameworks are only months old, but the cost gap between a DLR fix and a rebuild is becoming visible to the party who pays the difference.

How Relae Helps Find the Value of DLR  

Through our Power, Data, and Innovation practice, Relae combines transmission congestion data, line-level thermal constraints, and short-term weather forecasts into a single view of where dynamic ratings would actually pay. The output is a short list of candidate lines, each with a modeled capacity uplift and an estimated dollar value, turning a vague “DLR is promising” into a priced, line-by-line decision. It is the transmission-side complement to our work on the interconnection queue and demand-side flexibility. All three are ways of closing the gap between demand and delivered capacity faster than new construction allows.