NEAR Protocol (NEAR) sustainability report

NameBlockNodes SAS
Relevant legal entity identifier969500PZJWT3TD1SUI59
Name of the crypto-assetNear Protocol
Beginning of the period to which the disclosure relates2025-09-27
End of the period to which the disclosure relates2026-09-27
Energy consumption3152031.09127 kWh/a
Renewable energy consumption37.1912070580 %
Energy intensity0.00006 kWh
Scope 1 DLT GHG emission - Controlled0.00000 tCO2e
Scope 2 DLT GHG emission - Purchased1066.67693 tCO2e
GHG intensity0.00002 kgCO2e

Consensus Mechanism

Near Protocol is present on the following networks: Near Protocol.

NEAR Protocol is a sharded proof-of-stake network. Rather than running independent chains alongside one another, it treats the whole system as a single logical chain whose every block is assembled from per-shard pieces called chunks, so one block header commits to the state of every shard at once. An account's address determines which shard holds it. The network launched with a single shard and has since grown to several; a 2026 protocol release made the split automatic, so a shard now divides at an epoch boundary once its state passes a configured size threshold, instead of waiting for a coordinated upgrade.

Participation is decided by a recurring auction over stake. An operator wanting to validate submits a staking proposal; at each epoch boundary the protocol sorts the proposals, derives a seat price from them, and assigns duties to those clearing it, with some accounts producing blocks, others producing the chunks of a particular shard, and the rest acting as chunk validators. Epochs last roughly half a day and assignments are reshuffled each time, so no operator holds a given shard indefinitely. Because the seat price floats with the total stake competing for entry, the threshold rises and falls with demand rather than being fixed in the protocol.

The design that most distinguishes this network is stateless validation, adopted in 2024. A chunk producer publishes, alongside its chunk, a compact witness carrying exactly the state that chunk touched together with proofs against the shard's state root. Chunk validators check the work from that witness alone, so they can verify a shard without storing it, and shards can be added without pushing hardware requirements steadily upward.

Blocks are produced under Doomslug, which allows the next block to be built once more than half of the stake has endorsed its predecessor, giving a fast practical guarantee that the chain will not reorganize. Full finality comes from a separate rule once two-thirds of the stake has endorsed, normally within a small number of blocks. Safety rests on more than two-thirds of staked value behaving honestly, and activity crossing shard boundaries travels as receipts routed asynchronously over subsequent blocks.

Incentive Mechanisms and Applicable Fees

Near Protocol is present on the following networks: Near Protocol.

The network issues a fixed proportion of the supply of its native asset each year, on the order of five percent, and divides it: roughly nine-tenths is paid to the validators of each epoch and the remaining tenth goes to a protocol treasury. Epoch rewards are proportional to the seats an account holds, and they are conditional on work actually performed. A validator that produces fewer than the required proportion of the blocks or chunks it was assigned earns nothing for that epoch and is removed from the set for the following one, with re-entry taking a further two epochs. Holders who do not want to operate infrastructure can delegate to a staking pool contract, which pools their stake behind an operator and passes back rewards net of that operator's commission.

Penalties deserve to be stated precisely. The protocol specifies a design under which stake could be confiscated for provable misbehavior, but that mechanism is not switched on. What actually operates is economic exclusion: forfeited rewards, ejection from the validator set, and the delay before an ejected account can return. Stake itself is not taken.

Execution is paid for in gas. Unlike an auction-priced fee market, the cost of each operation is fixed in protocol configuration, and the gas price moves only gradually in response to how full recent blocks have been, so costs stay predictable and do not spike sharply with congestion. Gas spent is destroyed rather than handed to validators, who are paid from issuance instead. Historically three-tenths of the gas burned by a contract call was credited to the account of the contract being called, a rebate meant to fund contract authors; network governance has voted to set that share to zero so the entire amount is burned.

State is charged for separately through storage staking. An account must keep an amount of the native asset locked in proportion to the bytes it occupies, in the region of one unit per hundred kilobytes, and the lock is released when the data is deleted, so there is no recurring rent. Access keys and meta-transactions additionally let one party cover another's gas.

Energy consumption sources and methodologies

Near Protocol is present on the following networks: Near Protocol.

The figure reported for this network is an estimate assembled from the infrastructure that runs it, not a metered reading. It works upward from the population of machines taking part, and from what each of those machines can be expected to draw.

The first input is the size and composition of that population. It is estimated from publicly observable network data, including peer discovery, the published validator set and its per-epoch duty assignments, and open directories of operators, gathered by automated collection of the same information. For a sharded network this matters more than a headline count, because duties are divided between block producers, the producers of each shard's chunks, and the chunk validators that verify them; the estimate has to cover all of those roles rather than only the accounts holding seats. Machines that take no part in consensus but that the network needs in order to be usable, such as archival nodes and query-serving infrastructure, are included as well.

The second input is consumption per machine. A representative hardware profile is inferred from the resources the client software states it requires, covering processor cores, memory, disk and bandwidth, and power draw is attributed from laboratory measurement of devices matching that profile. Draw is counted continuously, including the large idle component, since a validator has to stay online whether or not it currently holds an assignment. Multiplying the per-device figure across the estimated population produces the network total.

The limits should be read plainly. Both the population and the hardware mix are inferences drawn from public observation and from stated software requirements; operators are not surveyed and meters are not read. Where the evidence runs out, the assumption chosen is the one that makes the impact look larger rather than smaller, so the resulting figure is more likely to overstate than understate. Stateless validation also changes the profile over time, since verifying a shard no longer requires storing it, and the estimate is revised as observation of the network improves and as the shard count changes.

Key energy sources and methodologies

Near Protocol is present on the following networks: Near Protocol.

The renewable share attributed to this network is derived from where its machines sit, not from any claim about the electricity the network chooses to buy. The first step is to place the node population geographically. Locations are inferred from publicly observable network data, including the addresses peers announce to one another, information operators publish about themselves, and the hosting providers and data-center ranges those addresses resolve to, all gathered by automated crawling of the peer network. Sharded duty assignment does not complicate this step, since what matters is where a machine physically sits rather than which shard it happens to serve in a given epoch.

Coverage is never complete. Some operators sit behind relays or cloud infrastructure that hides the physical site, and others publish nothing at all. Where a network's own geographic spread cannot be observed in sufficient detail, the distribution observed for a structurally similar network is used in its place, chosen because its participants face comparable incentives and carry comparable consensus duties, and can therefore be expected to cluster in broadly the same regions.

Those locations are then matched to regional electricity statistics. Each machine is associated with the grid serving its location, and the renewable proportion of that grid's generation is applied, weighted by the share of estimated consumption sitting in each region. The result is a consumption-weighted renewable share for the network as a whole, which moves both when operators relocate and when the underlying grids change from year to year.

Energy intensity is reported alongside it and means something narrow: the marginal energy associated with processing one further transaction. Because most of this network's consumption is the fixed cost of keeping validators online rather than anything proportional to throughput, that marginal figure falls as activity rises, and it should not be read as an average cost per transaction. Grid statistics come from Share of electricity generated by renewables, compiled by Our World in Data with major processing from Ember and from the Energy Institute's Statistical Review of World Energy.

Key GHG sources and methodologies

Near Protocol is present on the following networks: Near Protocol.

Emissions for this network are derived from its electricity use and from the carbon content of the grids supplying it. The estimated energy total is first broken down by location, using the same geographic picture built for the energy analysis: node addresses observed on the peer network, operator information published openly, and the hosting ranges those addresses belong to. Where the observed spread is too sparse to rely on, the distribution of a structurally comparable network is substituted, selected for similar incentives and similar validation duties rather than similar size.

Each block of consumption is then multiplied by the carbon intensity of the grid serving it, expressed as emissions per unit of electricity generated in that region, and the results are summed. This means the outcome is driven as much by where operators choose to host as by how much electricity the network draws, and it changes year to year as national generation mixes shift.

The reported figures separate two scopes. Scope 1 covers emissions from sources the network's operators control directly, such as on-site fuel combustion; for a network of this kind that is effectively nil, since the infrastructure is commodity servers drawing grid power in third-party facilities. Scope 2 covers the indirect emissions embodied in the electricity purchased to run that infrastructure, and it accounts for essentially the whole footprint. Emissions embodied in manufacturing the hardware, and in building and cooling the facilities that house it, fall outside both and are not included.

GHG intensity is the marginal figure, the emissions attributable to one additional transaction. As with energy, the bulk of the total is a fixed cost that continues regardless of throughput, so intensity falls as usage grows and is not an average. Carbon intensity values come from Carbon intensity of electricity generation, compiled by Our World in Data with major processing from Ember and from the Energy Institute's Statistical Review of World Energy, and made available under the CC BY 4.0 license.