Bitpanda Asset Management GmbH, Bitpanda GmbH

9845005X9B7N610K0093, 5493007WZ7IFULIL8G21

Core

Core employs the Satoshi Plus consensus mechanism, which combines Delegated Proof of Work (DPoW), Delegated Proof of Stake (DPoS), and Non-Custodial Bitcoin Staking to provide robust security and scalability. Core Components: Delegated Proof of Work (DPoW): Integrates Bitcoin miners into the network by allowing them to contribute hash power to secure Core, without interfering with Bitcoin's primary operations. Delegated Proof of Stake (DPoS): CORE token holders delegate their tokens to validators who handle block production and transaction validation, ensuring efficiency and decentralization. Non-Custodial Bitcoin Staking: Bitcoin holders can stake their BTC to participate in the network consensus, adding an extra layer of security while preserving ownership of their assets.

Core incentivizes network participation through staking rewards, transaction fees, and governance opportunities. Incentive Mechanisms: Validator Rewards: Validators earn rewards from transaction fees and newly minted CORE tokens distributed through the blockchain's inflation policy, with payouts proportional to their delegated hash power and CORE stake. Staking Incentives: Both CORE and Bitcoin stakers receive rewards for contributing to network security and stability, encouraging broader participation across asset classes. Governance Participation: CORE token holders have voting rights, allowing them to influence protocol upgrades and network parameters, supporting decentralized decision-making. Applicable Fees: Transaction Fees: Users pay transaction fees in CORE tokens for executing transactions and smart contracts. These fees are distributed to validators as compensation for securing the network. Inflation Policy: A portion of validator rewards comes from newly minted CORE tokens, providing an additional incentive while maintaining a controlled inflation model.

2024-11-27

2025-11-27

155236384.27702 (kWh/a)

For the calculation of energy consumptions, the so called 'bottom-up' approach is being used. The nodes are considered to be the central factor for the energy consumption of the network. These assumptions are made on the basis of empirical findings through the use of public information sites, open-source crawlers and crawlers developed in-house. The main determinants for estimating the hardware used within the network are the requirements for operating the client software. The energy consumption of the hardware devices was measured in certified test laboratories. 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.

34.478147108 (%)

0.05586 (kWh)

0.00000 (tCO2e/a)

63956.77890 (tCO2e/a)

0.02301 (kgCO2e)

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.

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.