Scope 2 Revisions: A Recommended Path Forward

Most of the world shares a common goal: affordable, reliable, clean electricity, everywhere, all the time, for everyone, as fast as possible. The voluntary corporate market has been a powerful catalyst in that effort. By enabling companies to match their annual electricity use with renewable energy through long-term Power Purchase Agreements and Virtual PPAs, the Greenhouse Gas (GHG) Protocol’s 2015 Scope 2 Guidance helped finance massive solar and wind projects. 

Now, as the GHG Protocol revisits those rules, draft proposals are introducing significantly stricter requirements: granular matching. Under these proposals, Renewable Energy Certificates (RECs) would need to be issued and retired for the exact hour and deliverable market boundary of a company’s electricity consumption.

The academic case for this shift is that granular matching would eliminate the market distortions caused by oversupply of annual RECs and broad market boundaries, produce more precise price signals during periods of clean energy scarcity, and direct capital toward newer, less commercially mature clean technologies needed to achieve a 24/7 100% clean grid.

The problem is that the theory and the reality are not yet aligned. The models underpinning these proposals optimize for system-level cost efficiency, but they largely set aside how clean energy projects actually get built: through long-term forward contracts that give developers and lenders the revenue certainty needed to finance construction.

A year ago, Ever.green published a paper[1] recommending a dual-path approach for granular matching and consequential impact for the update of Scope 2 standards by Greenhouse Gas Protocol (GHG Protocol). 

Since then, consequential impact (the placeholder for additionality or at least a test for incrementality) has been removed from the Scope 2 revisions. Requirements for granular matching RECs down to the hour and location of consumption have moved forward without any test for incrementality or additionality (a test assumed by nearly all the research supporting granular-matched RECs). 

We have written extensively about both our hopes and our concerns[2][3][4] with these proposed revisions[5]. Below, we have consolidated and updated the changes we support.

‍

What the GHG Protocol should do

The voluntary market has proven it can finance new clean energy at scale. The goal of updated standards should be to sharpen that impact, not dismantle the mechanisms that made it possible. 

Below are the updates to GHG Protocol guidelines that we support. These recommendations come from a close read of the existing research and our experience in the marketplace.

1. Require incrementality in the Market-Based Method (MBM)

Every major study cited in support of granular matching assumes that, at the very least, procurement goes to newly built projects. The standard should require the same. A qualifying purchase should either come from a project commissioned within the past three years or from a long-term contract signed before the project was built. Incrementality strengthens both annual and granular procurement and focuses voluntary market support on new projects and reinforces the long-term contracts that are essential to project financing. Older projects should remain eligible when they are repowered or when a company's procurement is genuinely material to preventing early closure. 

Incrementality also protects the market from legacy hydroelectric and nuclear generation assets flooding the voluntary market with cheap supply that weakens the investment signals for new builds. Legacy hydro and nuclear should only qualify under the MBM if procurement is genuinely material to expanding, repowering, or preventing the closure of the plant. Without an incrementality requirement, granular matching is unlikely to improve the impact of voluntary action over existing standards.

2. Create guidelines for granular matching in the Market-Based Method (MBM)

The GHG Protocol should establish clear and consistent guidelines for granular matching (both hourly and narrow locational boundaries) for companies and other standards pursuing 24/7 carbon-free electricity targets. These guidelines could also be used for legally required disclosures. 

3. Granular matching, if required, should only be required for very large centralized loads 

The current proposed rules already have a carve-out for smaller buyers allowing continued annual matching. But that carve-out does not cover narrower location matching and is much too low if the intention is to require granular matching only for very large, centralized loads (e.g., data centers, clean hydrogen producers, etc). Carve-outs should be much broader (more MWh/region) and cover both hourly and locational matching. This allows more buyers to continue aggregating demand and using impactful strategies like long-term forward contracts.

We are sympathetic to proposals that require granular hourly and location matching for very large centralized loads. Large new loads can strain grid reliability and raise rates for other customers. In the U.S., most PPAs are virtual, very large, and hard to break into smaller pieces. Unlike distributed buyers, companies with large centralized loads can still access PPAs, VPPAs, or other long-term forward contracts across multiple technologies even under granular matching requirements.

That said, we remain unsure that the GHG Protocol should require granular matching, even for these very large loads. Unlike permitting reform and local regulation or U.S. 45V tax credits, where granular matching gates a meaningful incentive, the GHG Protocol has no comparable enforcement mechanism. The practical risk is that hyperscalers respond to a requirement they can't meet by exiting voluntary clean energy markets rather than building matching local generation. We’ve also started seeing hyperscalers switch to contracting with existing nuclear and hydro as the path of least resistance, which undermines the impact of the voluntary market.

4. Mandate granular matching for the Location-Based Method (LBM) for accuracy 

The location-based method measures physical electricity consumption. Requiring more granular time and location matching in the LBM strengthens the dual-method framework and improves the accuracy of reported emissions without distorting how companies voluntarily procure clean energy.

5. Give companies credit and incentives for enabling new projects

When corporate procurement demonstrably enables new or repowered clean energy projects, that impact should count toward a company’s net-zero goals. We support a new Consequential Accounting metric to directly measure actual emissions impact under the proposed new Impact Report[6]. But the GHG Protocol should, at the very least, endorse such impact being used to net against a company’s emissions inventory. Staying silent on how an Impact Report is meant to be used creates uncertainty and confusion in the market.

6. Protect existing PPAs with a clear legacy clause 

Ambiguity around whether current long-term contracts like PPAs will count under updated standards is already slowing new deal-making. GHG Protocol should immediately clarify that a legacy clause will protect existing long-term contracts. Companies need to know that a contract signed today will be honored over its full term. 

7. Improve residual mix emissions factors and their use 

Residual mix is an important tool for preventing double counting, and we support efforts to improve both the data quality and consistency of its application. Where residual mix data is unavailable, we support a fossil-based emission factor being applied as a fallback.

8. Reject the Standard Supply Service (SSS) proposal

SSS allows companies to count clean energy received from their utility toward their renewable energy goals. That supply is based on where a company is located, not what it chose to procure or enable. 

The proposed non-allocation pathway compounds issues with SSS. It would allow companies to claim a pro-rata share of regional clean energy from a centralized GHG Protocol database with no requirement that corresponding RECs be retired and no mechanism to prevent double counting.

SSS converts the passive geographic reality already reflected in the location-based method into an active market-based credit. In markets with abundant mandated clean energy, companies could satisfy the majority of their MBM obligation simply by paying their utility bill, dramatically suppressing voluntary EAC demand and hollowing out the mechanism that has financed new clean energy at scale.

Requiring REC retirement for SSS claims would not be enough to resolve these issues: SSS resources are mandatory, not incremental. Companies would be receiving MBM credit for clean energy they did not choose and did not cause.

‍

We’re all on the same team

Everyone working on clean energy and corporate sustainability share the same goal: abundant clean energy for everyone in every hour, as fast as possible. The voluntary corporate market has already shown it can move capital at scale toward that goal. These recommendations are our attempt to raise the bar and help the market do so more effectively.

What that requires is attention to the gaps between the research, the proposed rules, and the realities of the market that determine the impact of new rules. The distance between a well-intentioned standard and its actual impact on project financing, deal-making, and new capacity on the grid can be significant and is worth considering as carefully as the emissions the standard is designed to reduce.

We believe these updates would sharpen the voluntary market's impact without disrupting what has made it work – the fastest path to the grid we all want. We hope GHG Protocol will build it with us.

‍

[1] https://ever.green/papers/scope2 

[2] https://ever.green/papers/hourly-matching 

[3] https://ever.green/insight/hourly-matching-faq 

[4] https://ever.green/insight/prioritizing-capacity-vs-integration 

[5] https://ever.green/ghgp-scope2 

[6] https://ghgprotocol.org/sites/default/files/2026-03/AMI-Phase1-WhitePaper-RFI.pdf