Carbon 2.0: How dMRV Is Turning Carbon Credits Into Data-Driven Assets

Web3 has spent years promising to bring real-world assets on-chain. In carbon markets, that promise is starting to materialize—but not for the reasons most people expected.

The early narrative was simple: blockchain would make carbon credits transparent, tradable, and trustworthy. Tokenise the credit, put it on a ledger, and the problem is solved.

That story has been tested repeatedly since 2020. It didn’t hold up.

What’s now changing carbon markets isn’t tokenisation alone. It’s improvements in Monitoring, Reporting, and Verification (MRV)—specifically digital MRV (dMRV)—which aim to make carbon outcomes more observable, more frequent, and more auditable. Distributed ledgers may still play a role, but increasingly as infrastructure layered on top of better data, not a substitute for it.

Carbon 1.0: Why the First Wave Struggled

Between 2020 and 2024, the voluntary carbon market faced a credibility crisis. Investigations and academic studies raised concerns about over-crediting, weak baselines, non-additionality, and permanence risks in parts of the market. These issues didn’t apply uniformly, but they were widespread enough to affect buyer confidence.

A key limitation sat upstream: how carbon outcomes were measured and verified.

Traditional MRV processes often relied on:

• periodic field audits,

• project self-reporting,

• and verification cycles that could lag real-world activity by 12–24 months.

As a result, many credits represented retrospective estimates rather than near-real-time measurements.

Tokenisation did not address this. Recording a credit on a blockchain can improve traceability and auditability, but it does not improve the underlying data. If the inputs are uncertain, the output remains uncertain—just more visible.

Pricing Signals Are Beginning to Differentiate Quality

By 2025–2026, markets have begun to differentiate more clearly between credit types, particularly between avoidance-based credits and carbon dioxide removal (CDR).

• Engineered and high-durability CDR credits (e.g. DAC, mineralisation) have been reported in the $170–$500+ per tonne range, depending on method and contract structure.

• Biochar credits have been reported around the mid-$100s per tonne in some datasets, though pricing varies widely across suppliers and deal structures.

• Higher-rated credits (e.g. those scoring well under independent rating frameworks) account for a growing share of total retirement value, though lower-quality supply remains a significant portion of overall market volume.

These are still thin and fragmented markets, but the direction is clear: data quality and durability are increasingly reflected in price.

What dMRV Actually Changes

Digital MRV refers to the use of remote sensing, automation, and digital data pipelines to improve how carbon outcomes are measured and verified.

Instead of relying solely on periodic audits, dMRV systems can incorporate:

• satellite imagery,

• LiDAR and geospatial analysis,

• IoT sensors,

• and automated data ingestion into verification systems.

This does not always mean continuous real-time measurement, but it can significantly increase data frequency, reduce reporting lag, and improve auditability.

Conceptually, this shifts carbon credits from static certificates toward data-backed, periodically updated records.

The architecture typically breaks into three layers:

1. Measurement layer
   Remote sensing providers, sensors, and project-level instrumentation generate observational data.

2. Verification layer
   Statistical models, machine learning, and rule-based systems are used to detect changes (e.g. deforestation, biomass shifts) and flag anomalies. These systems still require validation and are not error-free.

3. Registry / infrastructure layer
   Registries and, in some cases, distributed ledgers record issuance, transfers, and retirements. At this stage, infrastructure becomes more useful because it is anchored to higher-quality inputs.

A Real Milestone: Verra’s dMRV Pilot

In February 2026, Verra approved the first credits under a dMRV pilot.

The initial project:

• is a solar installation in Comoros,

• uses fully digital data submission and verification,

• enables monthly or bi-monthly issuance instead of annual cycles,

• and includes a safeguard structure where 80% of credits are issued initially and 20% are withheld pending further validation.

This is a meaningful milestone, but it is explicitly a pilot, not a market-wide shift.

More complex project types—such as large-scale forestry or some forms of DAC—still face challenges including:

• cost of instrumentation,

• uneven data availability across regions,

• and the difficulty of validating models across ecosystems.

The implication is not that MRV has been “solved,” but that a new direction is being tested in production environments.

Toward More Programmable Carbon Workflows

One area where improved data could have downstream impact is in how carbon credits are used operationally.

Today, most offsetting still happens on an annual accounting cycle. Emissions are calculated after the fact, and credits are purchased and retired accordingly.

At the same time, some large buyers are experimenting with higher-resolution energy matching:

• Google has a stated goal of operating on 24/7 carbon-free energy by 2030.

• Microsoft has piloted hourly matching approaches in specific contexts and continues to expand carbon removal procurement.

Separately, companies including Microsoft have signed long-term offtake agreements for engineered removals, including projects like STRATOS direct air capture plant, which has targeted initial operations around 2026.

These developments suggest a possible future where:

• emissions data is generated more frequently,

• carbon supply is contracted in advance,

• and parts of the procurement and retirement process could be automated.

Technologies such as smart contracts could support this kind of automation. However, fully automated, real-time carbon matching systems are still in development and not yet widely deployed at scale.

Carbon as an Emerging Financial Asset

Carbon credits are increasingly being evaluated with tools familiar from financial markets:

• Independent firms such as Sylvera provide quality ratings (AAA to D scale) assessing integrity and delivery risk.

• Higher-rated credits are often associated with price premiums and stronger buyer demand.

• Standardisation efforts, including the Integrity Council for the Voluntary Carbon Market Core Carbon Principles (CCPs), aim to define minimum quality thresholds for the market.

That said, carbon is not yet a fully mature asset class:

• liquidity is uneven,

• pricing is fragmented,

• and the use of credits as collateral or in structured finance remains limited and case-specific rather than standardised.

Tokenisation and digital settlement infrastructure are being explored by both startups and incumbents, including pilots involving large financial institutions. These efforts may improve settlement speed, transparency, and interoperability, but they are still evolving.

Regulation and the “Integrity Premium”

Policy is also reinforcing the importance of reliable carbon data.

The European Union’s Carbon Border Adjustment Mechanism (CBAM) enters its definitive phase in 2026. Importers of certain goods must account for embedded emissions and purchase corresponding certificates, making carbon accounting a matter of trade compliance rather than voluntary disclosure.

At the same time, voluntary market initiatives like CCP labels are beginning to influence procurement decisions by large buyers.

Across both compliance and voluntary systems, a consistent pattern is emerging:
higher-confidence data → stronger demand → higher pricing

But this “integrity premium” is still forming and varies significantly across markets and methodologies.

Risks That Don’t Go Away

Improved infrastructure changes where risk sits—it does not eliminate it.

Key risks include:

• legacy supply: large volumes of older credits with weaker methodologies still circulate

• measurement risk: sensors can fail or be manipulated; remote sensing has limits

• model risk: AI and statistical models may not generalise well across geographies or ecosystems

• standard fragmentation: multiple registries and methodologies remain in use

• financialisation risk: as markets mature, there is a risk of optimising for price or liquidity rather than climate impact

These constraints are central to how the market evolves over the next decade.

Conclusion

Tokenisation alone did not fix carbon markets. Improvements in measurement and verification are beginning to address some of the underlying challenges.

dMRV does not make carbon perfectly measurable, but it can make it more observable, more timely, and more auditable. That, in turn, makes downstream infrastructure—whether registries, marketplaces, or programmable settlement—more meaningful.

Carbon markets are not yet fully transformed. But they are starting to shift:

from static claims → toward data-backed environmental assets

Whether that shift holds at scale will depend less on infrastructure narratives—and more on whether the underlying data continues to improve.