Regulated
Austria based and European regulated crypto & securities broker platform
Read more
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 | Bitpanda Asset Management GmbH, Bitpanda GmbH |
Relevant legal entity identifier | 9845005X9B7N610K0093, 5493007WZ7IFULIL8G21 |
Name of the crypto-asset | Ethereum Classic Ether |
Consensus Mechanism | Ethereum Classic operates on a Proof of Work (PoW) consensus mechanism with the Etchash algorithm, which is a modified version of Ethash. This PoW model requires computational work from miners to validate transactions and secure the network. Core Components: Proof of Work with Etchash Mining and Security: Miners use computational resources to perform the work necessary to add blocks to the blockchain, ensuring network security and resistance to tampering. Code is Law Philosophy Immutable Ledger: Following the 2016 DAO hack, Ethereum Classic upheld the “Code is Law” principle by retaining the unaltered blockchain. This commitment to immutability sets Ethereum Classic apart, preserving its original ledger without reverting transactions. |
Incentive Mechanisms and Applicable Fees | Ethereum Classic’s incentive model combines block rewards and transaction fees, encouraging miner participation and network security. Incentive Mechanisms: 1. Block Rewards: o Deflationary Supply Model: Miners receive ETC through block rewards, which decrease over time, similar to Bitcoin’s model. This deflationary design supports ETC’s value retention and incentivizes continued mining efforts. 2. Transaction Fees: o User-Paid Fees: Users pay fees in ETC for sending transactions, interacting with smart contracts, and utilizing dApps. These fees provide miners with additional income and help maintain network security. Applicable Fees: Ethereum Classic’s fee structure involves user-paid transaction fees to support network operations and discourage spam transactions. 1. Transaction Fees: o User-Paid Fees: Every transaction on Ethereum Classic incurs a fee in ETC, based on the computational effort required. These fees ensure that resources are efficiently used and contribute to miner revenue. o Dynamic Demand-Based Fees: Fees vary according to transaction complexity and network demand, helping maintain transaction efficiency and preventing congestion. 2. Mining Rewards: o Block Rewards Reduction: Block rewards, which are scheduled to reduce over time, provide a primary income source for miners. This model aims to balance network security while managing ETC’s supply. |
Beginning of the period | 2024-09-09 |
End of the period | 2025-09-09 |
Energy consumption | 869170232.88162 (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: Etchash. 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. The information regarding the hardware used and the number of participants in the network is based on assumptions that are verified with best effort using empirical data. In general, participants are assumed to be largely economically rational. As a precautionary principle, we make assumptions on the conservative side when in doubt, i.e. making higher estimates for the adverse impacts. |
Renewable energy consumption | 29.306425042 (%) |
Energy intensity | 0.20689 (kWh) |
Scope 1 DLT GHG emissions - Controlled | 0.00000 (tCO2e/a) |
Scope 2 DLT GHG emissions - Purchased | 358094.71257 (tCO2e/a) |
GHG intensity | 0.08524 (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. |