* Ej realtidsdata.
* Denna beskrivning av kryptotillgången har inte godkänts av någon behörig myndighet inom EU. Utgivaren av kryptotillgången är ensam ansvarig för innehållet i denna beskrivning av kryptotillgången.
Energiförbrukning: 265057277.93436 kWh/a | Förnybar energi: 24.134702976
ESG (Environmental, Social, and Governance) regulations for crypto assets aim to address their environmental impact (e.g., energy-intensive mining), promote transparency, and ensure ethical governance practices to align the crypto industry with broader sustainability and societal goals. These regulations encourage compliance with standards that mitigate risks and foster trust in digital assets.
| Name | Coinmotion Oy |
| Relevant legal entity identifier | 743700PZG5RRF7SA4Q58 |
| Name of the crypto-asset | Nervos Network |
| Consensus Mechanism | The Nervos Network utilizes the Proof-of-Work (PoW) mechanism combined with the NC-MAX consensus algorithm to achieve consensus across the decentralized network. This ensures a secure, decentralized, and efficient blockchain, while addressing issues inherent in traditional consensus protocols. Key Features of Nervos' Consensus Mechanism: 1. Proof-of-Work (PoW): Decentralization: PoW is chosen for its adaptability to external factors like mining equipment, energy consumption, and regulation, ensuring that no single participant can dominate the network over time. The continuous reinvestment needed to stay competitive discourages monopolization. Security: PoW is simpler and more robust than other consensus mechanisms, with fewer assumptions required, making it less prone to vulnerabilities. Fairness: PoW ensures an equitable distribution of rewards over time, unlike Proof of Stake (PoS), which may favor early participants. 2. NC-MAX Consensus Algorithm: Built on Nakamoto Consensus: NC-MAX is based on Bitcoin’s Nakamoto Consensus (NC), which has proven to be secure and resilient over time. Resistance to Transaction Withholding Attacks: NC-MAX addresses vulnerabilities in traditional PoW systems, such as transaction withholding, by splitting the block confirmation process into two steps: propose and commit, allowing transactions to propagate fully before commitment. Enhanced Block Propagation: This approach eliminates bottlenecks and delays in block propagation, improving network efficiency and reducing the risk of network congestion. Improved Block Throughput: NC-MAX dynamically adjusts block intervals based on network performance to maximize throughput while maintaining security, ensuring that shorter block times don’t come at the cost of network stability. Robust Resistance to Selfish Mining: NC-MAX makes selfish mining strategies unprofitable by accurately measuring the network’s computing power and preventing miners from gaining unfair rewards, enhancing network security. |
| Incentive Mechanisms and Applicable Fees | The Nervos Network employs a unique incentive mechanism and fee structure to ensure security, scalability, and sustainability. Incentive Mechanism: 1. Proof-of-Work (PoW) Consensus: Nervos utilizes a PoW consensus mechanism to secure its Layer 1 blockchain, the Common Knowledge Base (CKB). Miners validate transactions and add them to the blockchain, ensuring network integrity. 2. CKByte (CKB) Token: CKByte is the native token of the Nervos Network. It serves multiple purposes: Data Storage: Holders can store data on the blockchain, with one CKByte granting the right to store one byte of data. Transaction Fees: CKBytes are used to pay for transaction fees, compensating miners for their work. State Rent: CKBytes are required to store data on the blockchain, with fees paid to miners for providing storage space. 3. Nervos DAO (Decentralized Autonomous Organization): The Nervos DAO allows CKByte holders to lock their tokens in return for "CKB cells" that yield rewards over time, promoting long-term network growth and resource management. Applicable Fees: 1. Transaction Fees: Users pay CKBytes to miners for processing transactions. The fee amount depends on the transaction size and complexity. 2. State Rent: To store data on the blockchain, users must lock CKBytes equivalent to the data's size. These CKBytes remain locked for the data's duration. 3. Cycles (Computation Fees): For smart contract execution, users pay for computational resources consumed. These fees are also paid in CKBytes and compensate miners for their computational work. |
| Beginning of the period | 2024-06-09 |
| End of the period | 2025-06-09 |
| Energy consumption | 265057277.93436 (kWh/a) |
| Energy consumption resources and methodologies | For the calculation of energy consumptions, the so called “top-down” approach is being used, within which an economic calculation of the miners is assumed. Miners are persons or devices that actively participate in the proof-of-work consensus mechanism. The miners are considered to be the central factor for the energy consumption of the network. Hardware is pre-selected based on the consensus mechanism's hash algorithm: NC-Max. A current profitability threshold is determined on the basis of the revenue and cost structure for mining operations. Only Hardware above the profitability threshold is considered for the network. The energy consumption of the network can be determined by taking into account the distribution for the hardware, the efficiency levels for operating the hardware and on-chain information regarding the miners' revenue opportunities. If significant use of merge mining is known, this is taken into account. When calculating the energy consumption, we used - if available - the Functionally Fungible Group Digital Token Identifier (FFG DTI) to determine all implementations of the asset of question in scope and we update the mappings regulary, based on data of the Digital Token Identifier Foundation. |
| Renewable energy consumption | 24.134702976 |
| Energy intensity | 1.51288 (kWh) |
| Scope 1 DLT GHG emissions - Controlled | 0.00000 (tCO2e/a) |
| Scope 2 DLT GHG emissions - Purchased | 109202.55454 (tCO2e/a) |
| GHG intensity | 0.62330 (kgCO2e) |
| Key energy sources and methodologies | To determine the proportion of renewable energy usage, the locations of the nodes are to be determined using public information sites, open-source crawlers and crawlers developed in-house. If no information is available on the geographic distribution of the nodes, reference networks are used which are comparable in terms of their incentivization structure and consensus mechanism. This geo-information is merged with public information from Our World in Data, see citation. The intensity is calculated as the marginal energy cost wrt. one more transaction. Ember (2025); Energy Institute - Statistical Review of World Energy (2024) – with major processing by Our World in Data. “Share of electricity generated by renewables – Ember and Energy Institute” [dataset]. Ember, “Yearly Electricity Data Europe”; Ember, “Yearly Electricity Data”; Energy Institute, “Statistical Review of World Energy” [original data]. Retrieved from https://ourworldindata.org/grapher/share-electricity-renewables |
| Key GHG sources and methodologies | To determine the GHG Emissions, the locations of the nodes are to be determined using public information sites, open-source crawlers and crawlers developed in-house. If no information is available on the geographic distribution of the nodes, reference networks are used which are comparable in terms of their incentivization structure and consensus mechanism. This geo-information is merged with public information from Our World in Data, see citation. The intensity is calculated as the marginal emission wrt. one more transaction. Ember (2025); Energy Institute - Statistical Review of World Energy (2024) – with major processing by Our World in Data. “Carbon intensity of electricity generation – Ember and Energy Institute” [dataset]. Ember, “Yearly Electricity Data Europe”; Ember, “Yearly Electricity Data”; Energy Institute, “Statistical Review of World Energy” [original data]. Retrieved from https://ourworldindata.org/grapher/carbon-intensity-electricity Licenced under CC BY 4.0 |
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