Movement (MOVE) sustainability report

Movement is present on the following networks: Base, Ethereum, Hyperliquid.

Base operates as a Layer-2 (L2) scaling solution built on the Ethereum blockchain, having been developed by Coinbase using Optimism's OP Stack. Critically, Base L2 transactions do not possess an independent consensus mechanism. Instead, their validation is directly linked to and secured by the underlying Ethereum Layer-1 (L1) network. This is achieved through a specialized component known as a sequencer. The sequencer's role is to aggregate multiple L2 transactions into bundles, which are then regularly published to the Ethereum mainnet as a single L1 transaction.

Consequently, all transactions processed on the Base network are indirectly secured by Ethereum's robust Proof-of-Stake (PoS) consensus mechanism once they are recorded on L1. Ethereum's PoS system, established with "The Merge" in 2022, moves away from energy-intensive mining by requiring validators to stake at least 32 ETH. In this system, a validator is randomly selected every 12 seconds to propose a new block, while other validators on the network are responsible for verifying its integrity. The network employs a sophisticated slot and epoch system, with transaction finality typically occurring after two epochs, which translates to approximately 12.8 minutes, utilizing the Casper-FFG protocol. The Beacon Chain is central to coordinating validators, and the LMD-GHOST fork-choice rule ensures the chain adheres to the path with the most accumulated validator votes. Validators are incentivized with rewards for their participation in proposing and verifying blocks, but face stringent penalties, known as slashing, for any malicious actions or prolonged inactivity. This design choice by Ethereum aims to significantly enhance energy efficiency, security, and scalability, with ongoing and future upgrades, such as Proto-Danksharding, further targeting improvements in transaction processing efficiency, thereby benefiting Base as its foundational security layer. Base specifically leverages Optimistic Rollups as part of the OP Stack, meaning transactions are presumed valid unless challenged within a specified period via fault proofs.

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.

The Hyperliquid blockchain network, known as Hyperliquid L1, operates on a proprietary consensus mechanism called HyperBFT. This mechanism is specifically engineered to support the demanding requirements of a decentralized perpetual exchange (DEX), emphasizing high-frequency trading, robust security, and consistent transactional integrity across its ecosystem. HyperBFT draws its inspiration from the HotStuff protocol, a well-regarded Byzantine Fault Tolerant (BFT) consensus algorithm known for its efficiency and resilience in distributed systems. A core characteristic of BFT protocols like HotStuff is their ability to maintain operational integrity and reach agreement even when a certain proportion of network participants (up to one-third) act maliciously or are unresponsive. This fault tolerance is crucial for financial applications where transaction finality and security are paramount.The HotStuff protocol, and by extension HyperBFT, operates on a leader-based model. In this setup, a designated validator node is responsible for proposing new blocks of transactions to the network. Once a block is proposed, other validator nodes, often referred to as replicas, engage in a verification and validation process. This structured approach simplifies the consensus process compared to some more complex models, contributing to high-speed and low-latency transaction processing. To counteract potential centralization risks associated with a leader-based system and to enhance overall fault tolerance, HyperBFT likely incorporates a dynamic leader rotation mechanism. This ensures that the responsibility of proposing blocks is regularly shuffled among eligible validators, preventing any single entity from gaining undue control and maintaining continuous network reliability. The integration of such an efficient BFT consensus mechanism allows Hyperliquid L1 to deliver rapid transaction finality and high throughput, which are essential for a high-performance trading platform, while simultaneously ensuring strong security guarantees against various forms of network attacks or dishonest behavior.

Movement is present on the following networks: Base, Ethereum, Hyperliquid.

The Base blockchain, as an Ethereum Layer-2 solution utilizing Optimistic Rollups from the OP Stack, implements incentive mechanisms primarily focused on optimizing transaction costs and ensuring secure asset transfers, leveraging the economic security of its underlying Ethereum L1. A core incentive to use Base is its efficiency in reducing transaction expenses. This is achieved by a sequencer that bundles numerous L2 transactions together, submitting them as a single, consolidated L1 transaction to Ethereum. This process significantly lowers the average transaction cost for individual L2 operations, as the collective L2 transactions share the cost of the single L1 transaction fee, thereby making Base a more economically attractive option compared to direct L1 usage.

For the secure movement of crypto-assets between Base and Ethereum, a specialized smart contract on the Ethereum network is employed. Since Base, as an L2, does not manage its own consensus for fund withdrawals, an additional mechanism is in place to guarantee that only legitimate funds can be moved off the L2. When a user initiates a withdrawal request on Ethereum's L1, a predetermined challenge period begins. During this window, any other network participant has the opportunity to submit a "fault proof" if they detect a fraudulent withdrawal attempt, triggering a dispute resolution process. This entire system is strategically designed with economic incentives to encourage honest behavior and deter malicious activities, although specific details of these economic incentives for fault proof submission are not explicitly outlined beyond the general principle.

Furthermore, Base inherits and benefits from the robust incentive structure of Ethereum’s Proof-of-Stake (PoS) system, which indirectly secures Base transactions. Ethereum validators, by staking a minimum of 32 ETH, are rewarded for proposing and attesting to valid blocks, as well as for participating in sync committees. These rewards are distributed through newly issued ETH and a portion of transaction fees. Under the EIP-1559 fee model, transaction fees comprise a base fee, which is algorithmically burned to manage supply, and an optional priority fee (or 'tip') paid directly to validators. To maintain network integrity, validators face economic penalties, known as slashing, if they engage in malicious conduct or fail to perform their duties. This comprehensive incentive framework ensures strong security alignment for Base by reinforcing reliable validator behavior on its underlying L1.

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.

The Hyperliquid blockchain network employs a comprehensive system of incentive mechanisms and a dynamic fee structure to ensure network security, encourage participation, and support its ongoing growth and stability. At the core of its incentive model is the native token, HYPE. Validators, who are crucial for the network's operation, earn rewards in HYPE for their diligent efforts in securing the network. This includes their role in validating transactions, participating in the HyperBFT consensus process, and generally maintaining the integrity of the blockchain. By compensating validators, Hyperliquid ensures a robust and reliable network infrastructure.Beyond validators, the network also incentivizes delegators. Token holders who may not have the technical expertise or resources to run a validator node can delegate their HYPE tokens to existing validators. In return for supporting these validators and contributing to the network's pooled security, delegators also earn a share of the HYPE rewards. This mechanism broadens participation in network security and promotes decentralization by allowing a wider range of token holders to have a vested interest in the network's health. Furthermore, Hyperliquid extends incentives to other active users within its ecosystem. Participants can earn HYPE through various activities, such as staking their tokens, providing essential liquidity to the decentralized exchange, and engaging in other contributions that foster the functionality and vibrancy of the platform. This multi-faceted incentive approach, often referred to as a dual-token system (though only HYPE is explicitly mentioned as the native token for rewards in this context), is designed to foster active engagement and align the economic interests of all participants with the long-term success of the network.Regarding applicable fees, Hyperliquid utilizes a dynamic fee model for transactions. These fees are not fixed but rather adjust based on two primary factors: the current level of network activity and the inherent complexity of the transaction being processed. This dynamic adjustment mechanism helps the network manage congestion efficiently and ensures that resource allocation is priced appropriately according to demand. Users conducting transactions on the Hyperliquid L1 blockchain are responsible for paying these fees. The fees serve a dual purpose: they cover the operational costs associated with processing transactions, including the computational resources required, and they act as a crucial component of the incentive structure for validators. By compensating validators through a portion of these transaction fees, Hyperliquid ensures that there is a continuous economic impetus for them to process transactions accurately, maintain high network uptime, and contribute to the overall security of the platform.

Movement is present on the following networks: Base, Ethereum, Hyperliquid.

The energy consumption calculation for the Base blockchain network is meticulously performed using a "bottom-up" approach, where individual nodes are identified as the primary contributors to the network's overall energy footprint. This methodology is based on empirical data collected from a variety of sources, including publicly available information sites, dedicated open-source crawlers, and proprietary in-house crawling tools. The fundamental aspect of estimating hardware usage within the network involves determining the minimum requirements necessary to operate the client software. The energy consumption profiles of the specific hardware devices identified are obtained from measurements conducted in certified test laboratories, ensuring a high degree of accuracy in these foundational figures.

In the process of calculating network energy consumption, the Functionally Fungible Group Digital Token Identifier (FFG DTI) is utilized when available, serving to identify and encompass all relevant implementations of a crypto-asset within the scope of analysis. These mappings are regularly updated, drawing on data provided by the Digital Token Identifier Foundation. However, the source documents do not provide specific URLs for the public information sites, open-source crawlers, or the Digital Token Identifier Foundation, preventing direct external linking within this summary.

The methodology also incorporates assumptions regarding the hardware deployed and the number of participants operating within the network. These assumptions are rigorously verified with "best effort" against empirical data to ensure their realism and accuracy. A key underlying principle is the assumption that network participants generally act in a "largely economically rational" manner. Furthermore, to adhere to a precautionary principle, conservative estimates are applied in situations of uncertainty, leading to higher projected impacts to mitigate underestimation risks. For a specific token on Base, a fraction of the network’s total energy consumption is attributed, based on the token's activity within the network.

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.

The methodology for assessing the energy consumption of the Hyperliquid blockchain network, and by extension, any crypto-asset operating on it, follows a standardized approach that aggregates data across various components. The initial step involves calculating the total energy consumption of the underlying network itself. For networks such as Hyperliquid, which host multiple crypto-assets, this overarching network consumption is determined first. Subsequently, to ascertain the energy footprint specifically attributable to a particular crypto-asset on the Hyperliquid network, a proportional fraction of the network's total energy consumption is allocated. This attribution is meticulously determined based on the observed activity levels of that specific crypto-asset within the Hyperliquid ecosystem.To ensure accuracy and comprehensive coverage, if available, the Functionally Fungible Group Digital Token Identifier (FFG DTI) is utilized to identify and scope all implementations of the crypto-asset in question. The mappings for these identifiers are regularly updated, drawing on data provided by the Digital Token Identifier Foundation, ensuring that the assessment remains current and reflects any changes in asset deployment.The underlying assumptions regarding the hardware utilized by network participants and the overall number of active participants are critical to these calculations. These assumptions are not arbitrary but are rigorously verified using empirical data and a 'best effort' approach. A general guiding principle is that participants within the network are presumed to behave largely as economically rational actors. Furthermore, in adherence to a precautionary principle, conservative assumptions are applied when there is any uncertainty, meaning that estimates for potential adverse impacts, such as energy consumption, are biased towards higher figures to ensure a robust and cautious assessment.

Movement is present on the following networks: Ethereum, Hyperliquid.

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.

The methodology for determining the key energy sources and the proportion of renewable energy utilized by the Hyperliquid blockchain network involves a multi-pronged approach focused on identifying the geographical distribution of its operational nodes. The primary method for establishing node locations leverages a combination of publicly available information sites, advanced open-source crawlers, and specialized in-house developed crawling technologies. These tools collectively work to pinpoint where Hyperliquid's validator and other network nodes are physically situated.In instances where precise geographic distribution data for the nodes is insufficient or unavailable, a pragmatic approach is adopted: reference networks are employed. These reference networks are carefully selected based on their demonstrable comparability to Hyperliquid in terms of both their incentivization structures and their underlying consensus mechanisms. By analyzing comparable networks, an informed estimation of the geographical energy mix can still be made.Once the geographical information pertaining to the nodes is gathered, it is systematically integrated with comprehensive public data sets sourced from Our World in Data. Specifically, this involves utilizing datasets like the "Share of electricity generated by renewables - Ember and Energy Institute" to understand the renewable energy penetration in those regions. This merger allows for a detailed assessment of the renewable energy proportion in Hyperliquid's operational energy consumption. The energy intensity of the network is then quantified as the marginal energy cost associated with the execution of one additional transaction.This rigorous methodology provides a robust framework for evaluating the network's renewable energy profile and its overall energy efficiency. Further details on the data sources can be found at Our World in Data.

Movement is present on the following networks: Ethereum, Hyperliquid.

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.

The methodologies employed to ascertain the key Greenhouse Gas (GHG) sources and their associated emissions for the Hyperliquid blockchain network are directly linked to its operational infrastructure. The initial and critical step involves precisely determining the geographical locations of the network's nodes. This process relies on a combination of publicly accessible information sites, sophisticated open-source crawlers, and proprietary crawling systems developed specifically for this purpose. These tools are instrumental in identifying the physical whereabouts of Hyperliquid's various network participants, including validator nodes, which are central to its operation.Should there be a lack of concrete data concerning the geographic distribution of Hyperliquid's nodes, the methodology provides for the use of reference networks. These are carefully chosen based on their structural similarities to Hyperliquid, specifically in terms of their incentive frameworks and consensus mechanisms. This comparative analysis allows for an informed estimation of the GHG impact even when direct geographical data is sparse.Once the geographical data for the nodes is successfully compiled, it is then meticulously combined with public information obtained from Our World in Data. This integration specifically utilizes datasets such as the "Carbon intensity of electricity generation - Ember and Energy Institute." By merging the location data with region-specific carbon intensity figures, a comprehensive picture of the GHG emissions attributed to the electricity consumption of the Hyperliquid network can be constructed.The overall GHG intensity of the network is subsequently calculated as the marginal emission associated with the processing of one additional transaction. This metric offers insight into the incremental environmental impact of network activity. For more detailed information on the data sources and their licensing, please refer to Our World in Data. This resource is licensed under CC BY 4.0, ensuring transparency and accessibility of the underlying environmental data.