Vision (VSN) sustainability report

Vision is present on the following networks: Arbitrum, Ethereum.

Arbitrum, an innovative Layer 2 scaling solution built on top of Ethereum, utilizes an Optimistic Rollup consensus mechanism to significantly enhance transaction scalability and reduce operational costs. This optimistic approach operates on the fundamental assumption that all transactions processed off-chain are valid by default. Consequently, transactions only undergo a rigorous verification process if their validity is explicitly challenged during a specific time window.

The core architecture of the Arbitrum network integrates several key components essential for its functionality. The Sequencer plays a pivotal role by efficiently ordering user transactions and aggregating them into batches, which are then processed off-chain. This mechanism is critical for achieving high transaction throughput and maintaining network efficiency. A Bridge facilitates secure and seamless transfers of assets between the Arbitrum Layer 2 environment and the underlying Ethereum Layer 1 mainnet, ensuring interoperability and leveraging Ethereum's robust security. Safeguarding the network from malicious activities are Fraud Proofs, an interactive verification system designed to detect and invalidate fraudulent transactions.

The transaction verification process unfolds as follows: users first submit their transactions to the Arbitrum Sequencer. The Sequencer orders these transactions, bundles them into batches, and subsequently submits these batches along with a cryptographic "state commitment" to the Ethereum mainnet. A crucial "challenge period" then commences, during which any network validator can initiate a fraud proof if they suspect an invalid state transition. Should a challenge be raised, an iterative dispute resolution protocol is activated to pinpoint the exact fraudulent step. If fraud is confirmed, the system rolls back the incorrect state, and the dishonest party is subjected to penalties. The final, validated state is then executed on the Ethereum blockchain, preserving the rollup's integrity. This combination of off-chain computation, batching, and on-chain fraud detection, as seen in networks built on the Arbitrum Nitro stack like Kinto, enables high transaction volumes at considerably lower fees.

The Ethereum blockchain network, following "The Merge" in 2022, operates on a Proof-of-Stake (PoS) consensus mechanism, a significant departure from its previous Proof of Work system. This transition replaced energy-intensive mining with validator staking, aiming to enhance energy efficiency, security, and scalability. In this model, participants willing to secure the network act as validators by staking a minimum of 32 units of the network's native asset (Ether). The network organizes its operations around a precise slot and epoch system. Every 12 seconds, a validator is randomly selected to propose a new block. Following this proposal, other validators on the network verify the integrity and validity of the block. Finalization of transactions, meaning they become irreversible, occurs after approximately two epochs, which translates to about 12.8 minutes, utilizing the Casper-FFG (Friendly Finality Gadget) protocol. The Beacon Chain plays a central role in coordinating the activities of these validators, while the LMD-GHOST (Latest Message Driven-Greedy Heaviest Observed SubTree) fork-choice rule is employed to ensure all network participants agree on the canonical chain, following the branch with the heaviest accumulated validator votes. Validators are economically incentivized for their honest participation in proposing and verifying blocks, but they also face severe penalties, known as slashing, for malicious actions or prolonged inactivity. This PoS framework is designed not only to reduce the network's environmental footprint but also to lay the groundwork for future upgrades, such as Proto-Danksharding, which are intended to further improve transaction efficiency and overall network throughput. The core components like validator selection, block production, and transaction finality are intrinsically tied to the amount of Ether staked, ensuring that participants have a vested interest in the network's security and stability.

Vision is present on the following networks: Arbitrum, Ethereum.

Arbitrum One, serving as a Layer 2 scaling solution for Ethereum, incorporates a sophisticated array of incentive mechanisms to guarantee the ongoing security and integrity of its network. Central to this framework are the Validators and Sequencers. Sequencers are entrusted with the vital task of ordering user transactions and compiling them into batches for efficient off-chain processing, playing a critical role in optimizing network throughput and speed. Validators, conversely, actively monitor the Sequencers' activities, meticulously verifying state transitions and ensuring that only valid transactions are included in the batches. Both Sequencers and Validators are motivated through economic rewards, primarily derived from collected transaction fees and potentially other protocol-specific incentives, contingent on their honest and efficient performance.

Arbitrum’s security model is heavily reliant on its Fraud Proofs system. Transactions processed off-chain are initially given an "assumption of validity," which enables swift transaction finality and higher throughput. However, a predefined "challenge period" is established, during which any network participant can submit a fraud proof to contest the validity of a transaction. This acts as a powerful deterrent against malicious behavior. If a challenge is successfully brought forward, an interactive verification process is initiated to precisely identify and confirm any fraudulent activity. In instances where fraud is proven, the invalid transaction is reversed, and the dishonest actor faces economic penalties, which may include the slashing of staked tokens or other forms of financial disincentive. This balanced system of rewards for honest participation and strict penalties for malicious actions aligns participants' interests with the overall health and security of the Arbitrum network.

The Applicable Fees on the Arbitrum One blockchain are structured to be cost-effective. Users pay Layer 2 Fees for transactions executed on the Arbitrum network, which are typically significantly lower than those on the Ethereum mainnet due to reduced computational load. A specific "Arbitrum Transaction Fee" is applied to each transaction processed by the sequencer, covering the costs of processing and batch inclusion. Additionally, L1 Data Fees are incurred when batches of Layer 2 state updates are periodically posted as calldata to the Ethereum mainnet. This fee covers the requisite gas costs on Ethereum. A key economic benefit is "cost sharing," where the fixed expenses of submitting these state updates to Ethereum are distributed across multiple transactions within a batch, substantially lowering the per-transaction cost for users. For example, protocols leveraging the Arbitrum stack, such as Kinto, utilize ETH for transaction fee payments.

The Ethereum network's Proof-of-Stake (PoS) system is underpinned by a robust framework of incentive mechanisms and applicable fees, meticulously designed to secure transactions and encourage active, honest participation from validators. Validators, who are essential for the network's operation, commit at least 32 units of the network's native asset (Ether) to secure their role. Their primary incentives include rewards for successfully proposing new blocks, attesting to the validity of other blocks, and participating in sync committees, all of which contribute to the network's integrity and consensus. These rewards are distributed in newly issued Ether, alongside a portion of the transaction fees generated on the network. A key feature of Ethereum's fee structure is the implementation of EIP-1559, which divides transaction fees into two main components. The first is a base fee, which is automatically burned, effectively reducing the overall supply of Ether over time and potentially introducing a deflationary aspect, especially during periods of high network activity. The second is an optional priority fee, also known as a "tip," which users can choose to pay directly to validators to incentivize faster inclusion of their transactions into a block. This dual-fee structure aims to make transaction costs more predictable for users. To enforce honest behavior and prevent malicious activities, the network employs a strict system of economic penalties, including slashing. Validators who engage in dishonest acts or demonstrate extended periods of inactivity risk losing a portion of their staked Ether, providing a powerful deterrent against misconduct and ensuring the long-term security and reliability of the network. This comprehensive system aligns the economic interests of validators with the overall health and security of the Ethereum blockchain.

Vision is present on the following networks: Arbitrum, Ethereum.

The methodology employed for calculating the energy consumption attributed to the Arbitrum network adopts a "bottom-up" approach, systematically assessing individual operational components to arrive at an aggregate consumption figure. Within this framework, network nodes are identified as the central and most significant contributors to the network's overall energy footprint. The foundational assumptions underpinning these calculations are derived from empirical findings, which are compiled through the extensive use of publicly available information sites, proprietary in-house crawlers developed by the assessors, and various open-source data collection tools.

A crucial step in estimating energy consumption involves accurately determining the specific hardware devices utilized within the network. This determination is made by evaluating the technical requirements necessary for operating the client software pertinent to the Arbitrum network. Once these hardware profiles are established, their corresponding energy consumption rates are precisely measured under controlled conditions in certified test laboratories, ensuring a high degree of accuracy and reliability for the baseline data. To ensure a comprehensive and accurate scope, particularly when accounting for diverse implementations of crypto-assets across different networks, the Functionally Fungible Group Digital Token Identifier (FFG DTI) is employed whenever such an identifier is available. This tool assists in clearly delineating all relevant instances of an asset, with these mappings consistently updated based on data provided by the Digital Token Identifier Foundation.

Furthermore, the methodology relies on specific assumptions regarding the type of hardware deployed and the estimated number of active participants within the network. These assumptions are subjected to continuous validation using best-effort empirical data. A general guiding principle in these estimations is the presumption that network participants act in a largely economically rational manner. In accordance with a precautionary principle, conservative estimates are applied whenever there is uncertainty, typically resulting in higher assessments of potential adverse environmental impacts. When quantifying the energy consumption for a particular crypto-asset operating on Arbitrum, a proportionate fraction of the overall network's energy consumption is allocated to that asset, based on its observed activity within the Arbitrum ecosystem. The source documents do not provide any direct external links related to this methodology.

The methodology for calculating the Ethereum network's energy consumption primarily employs a "bottom-up" approach, which focuses on the energy demands of individual nodes that are central to the network's operation. These nodes are considered the fundamental factor driving the network's overall energy use. The assumptions underpinning these calculations are derived from empirical data gathered through a variety of sources, including public information sites, open-source crawlers, and proprietary in-house crawlers developed for this purpose. A critical step in this methodology involves determining the hardware used within the network, primarily by assessing the computational and other requirements necessary to run the client software. The energy consumption characteristics of these identified hardware devices are then rigorously measured in certified test laboratories to ensure accuracy. When quantifying the energy consumption for the network, the Functionally Fungible Group Digital Token Identifier (FFG DTI) is utilized, when available, to identify all implementations of the asset in scope, with mappings regularly updated based on data from the Digital Token Identifier Foundation. The information regarding the specific hardware deployed and the total number of participants in the network relies on assumptions that are diligently verified using empirical data whenever possible. Generally, participants are presumed to act in an economically rational manner. Furthermore, adhering to a precautionary principle, if there is any doubt in estimations, conservative assumptions are made, meaning higher estimates are used for potential adverse impacts to ensure a comprehensive and cautious assessment of energy consumption.

Vision is present on the following networks: Ethereum.

To ascertain the proportion of renewable energy utilized by the Ethereum network, a specific set of methodologies is applied. The initial step involves pinpointing the geographical locations of the network's nodes. This crucial geo-information is gathered through various means, including publicly available information sites, as well as both open-source and internally developed crawlers designed to scan the network. In instances where comprehensive geographical data for nodes is not directly accessible, the analysis resorts to leveraging "reference networks." These are comparable networks chosen for their similar incentivization structures and consensus mechanisms, providing a proxy for node distribution. Once the geo-information is established, it is then integrated and cross-referenced with public data obtained from "Our World in Data." This comprehensive dataset offers insights into the energy mixes and renewable energy penetration across different regions globally. The final calculation of energy intensity is defined as the marginal energy cost incurred for processing one additional transaction on the network. This approach allows for an estimation of the energy footprint associated with scaling the network's transactional volume. For detailed information and the underlying data sources on the share of electricity generated by renewables, relevant information can be found through sources such as Ember (2025) and the Energy Institute - Statistical Review of World Energy (2024), with further processing by Our World in Data, accessible via Share of electricity generated by renewables – Ember and Energy Institute.

Vision is present on the following networks: Ethereum.

The methodology for determining the Greenhouse Gas (GHG) emissions of the Ethereum network closely mirrors the approach used for energy consumption, focusing on identifying emission sources and their quantification. The initial and fundamental step involves precisely identifying the geographical locations of the network's operational nodes. This data collection is facilitated through a combination of publicly available information, as well as specialized open-source and proprietary crawlers designed to actively discover and map node distributions across the globe. Should there be an absence of specific geographic information for the nodes, the analysis intelligently defaults to utilizing "reference networks." These are carefully selected networks that exhibit comparable characteristics in terms of their incentivization structures and consensus mechanisms, providing a basis for estimating the geographic spread when direct data is unavailable. This collected geo-information is then meticulously integrated with publicly accessible data from "Our World in Data." This integration allows for the application of regional carbon intensity factors to the estimated energy consumption, thereby enabling the calculation of associated GHG emissions. The overall GHG intensity is quantified as the marginal emission generated per additional transaction processed on the network, offering a metric for the environmental impact of increased network activity. For detailed information and original data regarding the carbon intensity of electricity generation, sources include Ember (2025) and the Energy Institute - Statistical Review of World Energy (2024), processed by Our World in Data, available at Carbon intensity of electricity generation – Ember and Energy Institute. This resource is licensed under CC BY 4.0.