Problems with the MiCA environmental disclosure regime

The so-called “MiCA 2.0” consultation, in its question 53, inquires how well the crypto environmental disclosure regime is working. The MiCA Crypto Alliance, an organisation specialised in MiCA environmental disclosures, has submitted a response that argues that the regime is not working as intended.

In this article, we argue why this is.

Introduction

Europe has built what is probably the most extensive mandatory sustainability disclosure regime for crypto-assets anywhere in the world.

Under MiCA, issuers and CASPs must disclose the principal adverse impacts on the climate and other environment-related adverse impacts of the consensus mechanisms underlying the crypto-assets they issue or service. The framework asks for energy consumption, renewable and non-renewable energy consumption, greenhouse gas emissions and a series of additional environmental indicators.

There is a legitimate question we should now be asking:

Is the regime actually measuring the environmental impacts that matter?

We argue that it is not. One important reason is that the regime is failing at securing good Bitcoin disclosures. As the largest and most environmentally consequential Proof-of-Work network, Bitcoin provides a critical test of whether the framework can accurately measure the environmental impacts it was designed to capture.

Bitcoin is the real test

MiCA's sustainability framework is not only about Bitcoin. However, it largely is about Bitcoin. The environmental disclosure regime emerged from debate driven largely by concerns over Bitcoin and Proof of Work. The EU finally decided not to ban Bitcoin mining, but rather, to require adverse impact filings for the time being — with a view to potentially still regulating against mining in the future if the filings revealed a high environmental impact.

Therefore, a basic test for whether the system is working is to ask whether the regime results in insightful and accurate Bitcoin metrics. In our experience, it does not.

Instead, we have created a system capable of producing extraordinarily precise-looking figures for hundreds of crypto-assets, including networks whose absolute environmental footprints are negligible, while some of the most widely distributed disclosures for Bitcoin remain based on assumptions that fail to capture important features of how Bitcoin mining actually works.

In other words, the system is prioritising the appearance of microscopic precision over overall macroscopic correctness. 

Where the regime has gone wrong

Not all MiCA environmental data providers disclose their methodologies. Some copy-paste generic narratives in methodology fields without actually going into minimal detail. Some of the ones that do, however, reveal that they calculate their emissions solely using country or state grid emission factors under a location-based approach.

In other words, they assume that miners are grid energy only. 

The problem with this assumption is that it is wrong, significantly biases results, and implies that there is an entire environmental reporting ecosystem that is not actually researching environmental impacts, but merely assuming them. This strongly reduces the value of the system itself, and can inform future policy decisions poorly.

Bitcoin miners are greatly renewable precisely because they frequently deviate from grid patterns. They do not consume the average electricity mix of the grid in the jurisdiction where they operate, but frequently go off-grid and behind-the-meter. As miners are energy hungry and operate in a highly competitive environment, they need low energy prices as a matter of survival in the market. Therefore, they often co-locate with renewable energy sources:

• Wind farms, to mine when there is too much wind and prices are low.
• Solar farms, mining when the “duck curve” shows greatest mismatches.
• Hydroelectric facilities, seasonally mining during the “wet” months of the year.

They also participate in demand-response programmes, turning on when there is too much electricity from excess variable renewables, and turning off when energy prices go up such as winter storms. Miners consume curtailed renewable electricity, or use methane gas that is otherwise flared or even vented (with a much higher radiative forcing than CO2). 

This all means that miners’ energy mix and carbon footprint cannot be simply extrapolated from grid mix numbers. It needs to be studied. Ignoring off-grid mining introduces a methodological flaw introducing very significant biases in practices due to the high renewability of off-grid and behind-the-meter miners. Unfortunately, the current state of compliance under the MiCA environmental regime means formal correctness has been prioritised over substantive correctness.

Cambridge studied it and was ignored

The Cambridge Centre for Alternative Finance's 2025 Digital Mining Industry Report provides an important methodological counterexample.

Instead of relying exclusively on abstractions about where miners are located, Cambridge collected data directly from 49 mining firms operating across 23 countries, representing approximately 48% of global Bitcoin hashrate at the time of the study.

Participating miners reported an electricity mix consisting of 52.4% sustainable energy, including 42.6% renewable energy and 9.8% nuclear energy. Cambridge estimated Bitcoin's annual electricity consumption at approximately 138 TWh and, using the survey-derived electricity mix, annual GHG emissions at approximately 39.8 MtCO₂e.

These findings were in line with MiCA Crypto Alliance data. However, the rest of the industry did not follow the best available research. In our opinion, they should have. The difference between Cambridge/MiCA Crypto Alliance data and other methodologies in the market amounts to almost forty megatons of CO₂ per year, which is roughly equivalent to Denmark’s entire annual greenhouse gas emissions.

In science, all methodologies have limitations and there are always trade-offs to any research approach. Therefore, it is “technically valid” to employ a methodology with flaws, as long as one discloses it. In practice, however, reasonable limits to this have to exist — especially in compliance settings where disclosures can inform retail investor behaviour or public policy. Unfortunately, some even published disclosures arguing that 15% of Bitcoin’s energy was renewable — less than half the world on-grid average, without a methodological justification.

Bad estimates become infrastructure

Ultimately, the reason for these discrepancies is that a large fraction of MiCA environmental disclosures are not actually engaging in “best efforts” attempts to study crypto carbon footprints, but rather they assume the data that they seek to disclose.  That the assumptions are decorated in a slightly obscure model does not take away the fact that the industry is assuming the data that it is supposed to be studying.

These disclosures are meant to produce accurate measurements. If Bitcoin mining becomes more carbon-intensive, disclosures should show that. If Bitcoin mining becomes less carbon-intensive, disclosure should also reveal it. The current state of affairs, unfortunately, is that neither will be achieved because the most crucial data points are being assumed.

If the object of study is not being studied, but merely assumed, there will never be any findings around it. All that Bitcoin environmental disclosures under MiCA are going to disclose is how the global energy mix is moving, no more. The result is an environmental disclosure ecosystem that appears to be complex and populated by highly technical parties selling their services, but does little more than reproduce IEA grid mix estimates that one could find anyway by consulting “Our World in Data”. This is not worth the time and monetary expenses the system creates.

The problem with inaccurate sustainability estimates is that they do not remain an isolated research error. They propagate. 

A sustainability data provider produces a dataset. That dataset enters a MiCA white paper or Article 66 disclosure. Exchanges and other CASPs rely on those disclosures. The same numbers are reproduced across websites, regulatory documents and databases.

A methodological weakness becomes regulatory infrastructure, and informs future policy decisions.

Ten decimal places are not precision

This gets to a broader problem with the sustainability regime. Current disclosure templates create the appearance of scientific rigour by introducing numerous digits after the decimal point. However, this precision is an artifact of modelling only. A model produces an output, the output can be published with many decimals if desired. However, the additional decimal places do not represent enhanced accuracy in reality.

Decimal places are not wrong in themselves, but if the same system materially mischaracterises crypto electricity mixes,  they are of little regulatory value, and in fact obfuscate the lack of accuracy of numerous disclosures plaguing the system.

In other words, the completion of templates is becoming an objective in itself. As formulated in Goodhart’s Law, “when a measure becomes a target, it ceases to be a good measure.”

Our recommendations to the European Commission

The MiCA Crypto Alliance remains committed to the scientific endeavour, and to accurately studying the important variables such as Bitcoin’s energy mix. Our environmental disclosures are based on a best-efforts approach to studying the energy sources actually used by the validators of the ledgers under study. Furthermore, we have submitted a formal response to the European Commission Targeted Consultation on the Review Of Regulation on the Markets in Crypto-Assets (MICA) Regulation, arguing these points further. 

We have recommended that, for networks with material energy-intensive validation, the assessment of off-grid and behind-the-meter activity is either explicitly required, or that it at least becomes necessary to explicitly disclose the absence of off-grid data in the estimates. Furthermore, as our response states, “the framework should permit contextual indicators for renewable energy, nuclear and other low-carbon energy, curtailed or stranded energy, flared or vented gas and, where supportable, grid-balancing benefits. Offsetting and mitigation should have dedicated optional indicators and not be netted against gross impacts.” This will allow the construction of adequate, comparable time series that can inform public policy, and better educate retail investors. 

Ultimately, we encourage policymakers and regulators to keep in mind that the goal of this regime was not to create the illusion that it is possible to study the energy use of a small token’s transaction in a minor forty-node blockchain with microscopic precision, but to adequately gauge the impacts of crypto as a whole. The system should be optimised for the latter rather than the first.

The industry has moved beyond the old abstractions

One of the most encouraging developments is that Bitcoin mining itself is becoming easier to study empirically.

Researchers can increasingly engage directly with miners. Public mining companies disclose operational information. Mining conferences bring together operators, energy companies, grid specialists and researchers. Cambridge has demonstrated that large-scale primary-data collection is possible.

Our own work at MiCA Crypto Alliance increasingly involves precisely these conversations. We are engaging directly with the mining industry, participating in specialist mining events such as the European Mining Summit and contributing research to the academic discussion with multiple published academic papers subjected to peer-review. We need to demand better from our compliance industry so that we get our money’s worth.

Disclosure itself is not the objective, and we now have better empirical evidence about Bitcoin mining. We know that electricity sourcing is more complicated than applying an average grid mix to an estimated geographical distribution. And we know that different methodologies can produce dramatically different carbon estimates. Europe's sustainability disclosure framework should evolve accordingly.

If we can produce thousands of compliant sustainability indicators but still cannot get Bitcoin approximately right, we have complied with the template and missed the point.

Additional recommendations

We have also submitted additional recommendations on how to improve the environmental adverse impact regime.

Notably, there is an enforcement problem. Professional ESG providers have shown what genuine best efforts look like. Yet parts of the market still publish back-of-the-envelope estimates, or even verbal, narrative descriptions where the regulation explicitly requires actual numbers. It is not uncommon to see the statement “less than 500,000 kWh per year” in the energy consumption field of a white paper, or disclosures without prescribed XBRL tagging. Accepting this makes best efforts largely meaningless and penalises providers investing in better data.

Once the main recommendations are addressed, much of the remaining architecture is workable. We still have recommendations, but they are more minor in nature. These include:

Transparency of third-party data providers

A further concern is the emergence of sustainability data providers that sell their data for use in MiCA disclosures without being identified in the resulting disclosure. This makes it difficult for investors, regulators and other market participants to determine who produced the underlying estimates, scrutinise the methodology used, compare disclosures produced from the same dataset, or identify systematic methodological weaknesses.

This practice also appears difficult to reconcile with CDR 2025/422. Where information is sourced from a third-party data provider, Article 6(8) requires disclosure of the provider's name, a description of the information provided and, where available, a link to its website. Article 6(4) separately requires identification of third parties used to verify the information disclosed.

These requirements serve an important purpose. Sustainability estimates can propagate from a single provider into white papers, CASP disclosures, websites and databases, turning one methodology into regulatory infrastructure. The identity of the party producing the underlying data should therefore not disappear along that chain. Commercial arrangements should not result in effectively anonymous sustainability data used for regulatory disclosures.

Technological neutrality

A core principle for environmental disclosures should be technology neutrality. If the objective of the framework is to understand the environmental impact of a crypto-asset, the relevant question should be the impact of the particular network in practice, rather than assumptions derived primarily from the consensus mechanism it uses.

In current templates and European Commission materials, Proof of Work is itself sometimes treated as a proxy for environmental impact. While MiCA does not expressly do so, its implementation can create that effect. For instance, disclosure templates refer to impacts “of the consensus mechanism” in a way that can suggest that the choice of consensus mechanism is the principal variable determining environmental impact. In reality, both PoW and non-PoW systems can have high or low footprints depending on their particular characteristics, including other architectural choices (such as block time, block size and block subsidy), prices, market adoption and, critically, the sources of energy consumed.

The framework should therefore avoid starting from the assumption that PoW is environmentally favourable or unfavourable simply because it is PoW. Instead, disclosures should measure what a particular network actually consumes, how it operates and the environmental impacts that result. This would make the framework both more technology-neutral and more useful: materially different networks would be distinguished by evidence of their actual impacts rather than by broad technological categories.

This principle is particularly important because a negative presumption towards PoW can be perceived in a number of public documents, as well as third-party work relied upon by public authorities. One example is the “MESMERICE” study, funded by the European Commission but conducted by third parties. We identified several methodological issues in that study which, in our view, illustrate the risks of approaching environmental assessment through assumptions associated with particular technologies rather than through technology-neutral measurement of actual impacts. We raised these concerns both in a public hearing-style webinar and in writing in a formal submission, although they were largely not addressed by the lead researchers.

Marginal energy factors

“Energy per transaction” can easily be misunderstood as the amount of additional energy required to process an individual transaction. For networks such as Bitcoin, this is not necessarily what the figure represents. Bitcoin miners consume energy to produce blocks regardless of how many transactions those blocks contain. If the network processed twice as many transactions while consuming the same amount of energy, a simple “energy per transaction” figure would fall by half, even though the network’s total energy consumption had not changed.

However, Commission Delegated Regulation 2025/422 clearly requires the energy intensity and GHG intensity fields to report “average” energy used per transaction and “average” GHG emissions per validated transaction. This suggests a straightforward calculation: dividing the network’s total energy use and GHG emissions by its total number of transactions. The resulting figures allocate a share of the network’s overall impact to each transaction, rather than measuring the additional energy or emissions caused by that transaction.

However, current best practices have moved away from this. At present, researchers often use “marginal” approaches rather than average approaches.

A “marginal” approach consists of studying the “additional” energy and carbon footprints from transaction processing. This is not “marginal carbon accounting”, which examines which electricity source responds to an additional unit of electricity demand (e.g. when a gas peaker plant is turned on to service the marginal consumer). The idea is simpler: much of a crypto-asset network’s energy consumption does not vary directly with the number of transactions being processed. For example, if Bitcoin processed no transactions for a full day and miners produced only empty blocks, the network could still consume roughly the same amount of electricity. Therefore, under a marginal approach, only the additional electricity consumed by Bitcoin when transactions are processed would be attributed to the transactions.

There are good reasons for retaining the average approach. Ultimately, Bitcoin’s ability to process transactions is fundamental to the network, and allocating its total energy consumption across the transactions it processes is therefore not inherently incorrect. We have outlined additional reasons supporting this approach in the MiCA Crypto Alliance’s “Methodologies to Calculate Sustainability Indicators under MiCA”. Nonetheless, both retail and institutional investors are interested in understanding if their usage of the Bitcoin network will have a marginal effect.

Some sustainability providers are already attempting to answer this second question through marginal factors, for example by multiplying Bitcoin’s total energy use by the share of transaction fees in the total block reward and treating only the resulting amount as transaction-related energy use. This can produce materially different figures from the simple average approach and therefore undermine comparability between environmental disclosures.

The problem is that different data providers are using different approaches.  Ultimately, the regulation does say “average”, not “marginal”.  Therefore, we recommend that the European Commission explicitly address the distinction between average and marginal approaches and issue guidance or enhanced technical standards clarifying which methodology should be used.

Optional indicator recommendations

Optional indicators are rarely used. MiCA Crypto Alliance has shown broader reporting is feasible, but few players beyond the Alliance itself engage in reporting usage of natural resources, water usage, or electronic waste, as  minimum-cost compliance gives little incentive for this. Where material and reasonably measurable, certain optional indicators should be expected or their omission explained. Furthermore, optional intensity measures could include energy use or emissions per value settled, transaction volume, data processed or another suitable denominator.

In this vein, we also believe that land use should be a standardised quantitative indicator in square metres. The existing system offers the option to write a free-text description of usage of natural resources, which results in incomparable narrations that cannot be collated.

Energy mix shortcomings

There are fields in the technical standards and MiCA XBRL taxonomy that concern the energy mix. However, these fields only allow one value to be reported. By definition, energy mix reporting requires disclosing each energy source separately. Therefore, we recommend that the MiCA XBRL taxonomy pairs each energy source with its share, including decimals and multiple sources. We also recommend that the taxonomy validates the 500,000 kWh annual threshold, so that applicable supplementary requirements are automatically triggered and machine-checkable. 

Unit requirements

Technical amendments should improve readability, comparability and machine-readability. We recommend exploiting the metric system better, relying on Wh/transaction rather than kWh/transaction for energy intensity disclosures, for instance, and g CO₂e/transaction rather than kg CO₂e/transaction for GHG intensity. Current units create unnecessarily small values otherwise.

Update requirements

Finally, update requirements should be harmonised. CASPs currently update on material changes or annually, while white papers should be updated where underlying information changes “materially” — with materiality being undefined. We favour a symmetrical quarterly cycle for both, removing this asymmetry and uncertainty around the meaning of materiality. We believe that a quarterly — or alternatively, annual — harmonised cycle should apply.

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