Solana (SOL)

N

Field

Content

General information

S.1

CASP Name

BB TRADE ESTONIA OÜ

S.2

Relevant legal entity identifier

984500L05A5D0E66Q610

S.3

Blockchain network name

Solana

S.4

Name of the crypto-asset

SOL

S.5

Consensus Mechanism

Proof of History (PoH) + Proof of Stake (PoS)

S.6

Incentive Mechanisms and Applicable Fees

Solana's mechanism relies on a hybrid consensus model to achieve high throughput and low fees. Validators stake SOL tokens to participate in block creation and validation. The Proof of History (PoH) component is a cryptographic clock that orders transactions before they are added to a block, significantly improving efficiency.

Incentives: Validators earn rewards for successfully proposing and validating blocks, based on their staked amount. These rewards typically come from transaction fees and inflation (newly minted SOL). <br><br> Fees: Solana has a predictable and low-cost fee structure.

Base Fees: A fixed fee per transaction (e.g., 0.000005 SOL or 5,000 lamports), which is split: 50% is burned to reduce supply, and 50% is rewarded to the validator.

Priority Fees: Users can optionally add a priority fee to encourage faster inclusion of their transactions in a block during periods of high network congestion. These fees are paid per Compute Unit (CU) requested by the transaction.

Vote Transactions: Validators also pay a fixed daily fee (e.g., 0.9 SOL/day) for vote transactions to secure the network.

The system is designed to incentivize honest behavior and efficient processing, while discouraging malicious activities through slashing mechanisms for validators.

S.7

Beginning of the period to which the disclosure relates

2024-01-01

S.8

End of the period to which the disclosure relates

2024-12-31

Mandatory key indicator on energy consumption

S.9

Energy consumption

~8,755,000 kWh (8,755 MWh) per calendar year

S.10

Energy consumption sources and methodologies

The energy consumption is primarily attributed to the electricity used by validator nodes and RPC (Remote Procedure Call) nodes supporting the network. Methodologies typically involve a "bottom-up" approach, estimating the power consumption of representative hardware (e.g., Dell PowerEdge servers) used by validators and RPC nodes, then scaling by the number of active nodes. Geographic distribution of nodes is considered to account for varying energy grid mixes. Data is often collected from on-chain sources, direct validator sampling, and publicly available information.

Supplementary key indicators on energy and GHG emissions

S.11

Renewable energy consumption

~40%

S.12

Energy intensity 

~0.00001 kWh per transaction

S.13

Scope 1 DLT GHG emissions – Controlled

0 t CO2eq per calendar year

S.14

Scope 2 DLT GHG emissions – Purchased

~5,047.90t CO2eq per calendar year

S.15

GHG intensity 

~0.00000 kg CO2eq per transaction

S.16

Key energy sources and methodologies

Energy sources reflect the electricity grid mix where validator nodes are geographically located (e.g., coal, natural gas, hydro, solar, wind, nuclear). Methodologies involve tracking the locations of validators and RPC nodes through public information and crawlers, then integrating this geo-information with datasets on national/regional electricity generation mixes and their associated carbon intensities (e.g., from Our World in Data, Ember, Energy Institute).

S.17

Key GHG sources and methodologies

GHG emissions are predominantly Scope 2 (indirect emissions from purchased electricity). Methodologies involve multiplying the estimated electricity consumption by the carbon intensity (g CO2eq/kWh) of the electricity grid in the regions where nodes operate. This is based on publicly available data on carbon intensity of electricity generation. Data providers like CCRI (Crypto Carbon Ratings Institute) often contribute to these methodologies, which also consider marginal emissions from increasing network demand.