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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 | Stacks |
Consensus Mechanism | The Stacks blockchain, a Layer 2 solution on top of Bitcoin, uses a unique consensus mechanism called Proof of Transfer (PoX). PoX is inspired by Bitcoin’s Proof of Work (PoW) and leverages Bitcoin’s security by anchoring Stacks transactions on the Bitcoin blockchain. Core Concepts of Proof of Transfer (PoX): 1. Recycling Bitcoin’s Security: a. Stacks utilizes Bitcoin’s hash power and PoW energy by requiring Stacks miners to transfer BTC in exchange for the native token STX, essentially “recycling” Bitcoin’s energy without additional mining. b. Transactions on Stacks achieve Bitcoin finality—they are secured by Bitcoin’s immutable blockchain. 2. Two-Layered Peg Mechanism: a. Stacks introduces a decentralized, trust-minimized peg called sBTC, allowing assets to move between Bitcoin and Stacks. b. This peg enables Stacks smart contracts to interact with Bitcoin securely and in a decentralized way, enhancing utility and enabling DeFi on Bitcoin. 3. Smart Contracts with Clarity Language: a. Stacks supports Clarity, a smart contract language designed for predictability and safety. Clarity contracts allow developers to know exactly what a contract will do before execution, ensuring security. 4. Miners and Stakers: a. Miners transfer BTC to earn newly minted STX, securing the network. b. STX Holders (stakers) are incentivized to lock up STX tokens, earning BTC rewards in return. |
Incentive Mechanisms and Applicable Fees | The Stacks network incentivizes secure transactions and network participation through its unique Proof of Transfer (PoX) consensus model, which integrates incentives for both miners and STX holders. Incentive Mechanisms to Secure Transactions: 1. Miners’ Incentives: a. BTC Transfers for Block Rewards: Stacks miners secure the network by transferring Bitcoin (BTC) to compete for the opportunity to mine a new block and earn STX rewards. This transfer of BTC ensures miners are vested in the network's security without directly consuming additional computational power. b. Newly Minted STX Rewards: Miners who successfully mine a block are rewarded with newly minted STX tokens. This reward incentivizes miners to continue participating in securing the Stacks network. c. Bitcoin Finality: Since Stacks blocks are anchored to Bitcoin, the network leverages Bitcoin’s security to ensure finality, meaning that once transactions are confirmed on Bitcoin, they are considered immutable and secure. 2. Incentives for STX Holders (Stacking Rewards): a. Stacking BTC Rewards: STX holders can participate in the consensus process through a mechanism called Stacking. By locking up (temporarily holding) their STX tokens, these participants contribute to network stability and security. In return, they receive BTC rewards paid by the miners. b. Decentralization and Security Contribution: The Stacking process promotes decentralization by encouraging broad participation from STX holders, who help maintain network stability and security. This model reduces reliance on a few large players and provides economic rewards for active participation. 3. Two-Layered Peg and Decentralized Utility: a. sBTC Peg Mechanism: By utilizing a two-way peg mechanism, the Stacks network allows BTC to be moved between Bitcoin and Stacks, enabling secure, decentralized transactions. This enhances the overall utility of the network, encouraging more users and developers to participate in the ecosystem. |
Beginning of the period | 2024-09-14 |
End of the period | 2025-09-14 |
Energy consumption | 9228142.31734 (kWh/a) |
Energy consumption resources and methodologies | 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. |
Renewable energy consumption | 29.306425042 (%) |
Energy intensity | 0.01453 (kWh) |
Scope 1 DLT GHG emissions - Controlled | 0.00000 (tCO2e/a) |
Scope 2 DLT GHG emissions - Purchased | 3801.95829 (tCO2e/a) |
GHG intensity | 0.00599 (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. |