Axie Infinity (AXS) sustainability report

Axie Infinity is present on the following networks: Binance Smart Chain, Ethereum, Harmony One, Ronin.

The Binance Smart Chain (BSC) network utilizes a hybrid consensus mechanism known as Proof of Staked Authority (PoSA). This innovative approach integrates key elements from both Delegated Proof of Stake (DPoS) and Proof of Authority (PoA) to achieve a balance of high transaction speeds, cost-efficiency, and network security, while striving to maintain a reasonable level of decentralization. The core participants in the PoSA mechanism include Validators, referred to as "Cabinet Members," Delegators, and Candidates.

Validators play a critical role, being responsible for creating new blocks, verifying transactions, and upholding the overall security of the network. To qualify as a validator, an entity must stake a substantial quantity of BNB, which serves as collateral to ensure honest conduct. These validators are selected through a dynamic process that considers both the amount of BNB they have staked and the votes they receive from token holders. At any given time, there are 21 active validators, whose rotation aims to enhance decentralization and security. Delegators are token holders who opt not to operate a validator node themselves but can contribute to network security by delegating their BNB tokens to chosen validators. This delegation bolsters a validator's total stake, increasing their likelihood of being selected for block production. In return, delegators receive a share of the rewards earned by their chosen validators, fostering broader participation in network governance and security. Candidates represent potential validators who have met the minimum BNB staking requirements and are awaiting election into the active validator set through community voting. Their presence ensures a continuous pool of ready-to-serve nodes, contributing to the network's resilience and decentralization.

During the consensus process, validators are chosen based on their accumulated BNB stake and delegator votes. The higher these metrics, the greater the chance of selection for validating transactions and producing new blocks. Once selected, these validators take turns in a PoA-like fashion to produce blocks rapidly and efficiently, validating transactions, adding them to blocks, and broadcasting them across the network. BSC boasts fast block times, typically around 3 seconds, leading to quick transaction finality. This rapid finality is a direct benefit of the efficient PoSA mechanism, which allows validators to reach consensus swiftly. To further ensure network integrity, validators face economic incentives such as slashing, where a portion of their staked BNB can be forfeited if they engage in malicious activities. This mechanism aligns validators' interests with the network's well-being, complementing the rewards they receive for their honest participation.

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.

Harmony One's blockchain network employs an innovative consensus mechanism known as Effective Proof of Stake (EPoS), meticulously engineered to achieve a delicate balance between validator influence, network security, and transaction scalability. At its core, EPoS promotes a diverse and decentralized validator set. Unlike systems that might allow large stakeholders to dominate, EPoS actively limits the disproportionate influence of high-stake validators, thereby encouraging broader participation and safeguarding against the centralization of power. This design principle extends to its sharding architecture, where multiple validators engage in competition within each distinct shard, further distributing staking power across the network and significantly bolstering overall security. The network's architectural strength is further amplified by its sharding capabilities, combined with Practical Byzantine Fault Tolerance (PBFT) finality. Harmony One features four independent shards, each capable of processing transactions and executing smart contracts concurrently. This parallel processing capability is crucial for achieving high levels of scalability and throughput, allowing the network to handle a substantial volume of operations simultaneously. Within each of these shards, a modified PBFT model is utilized, which is instrumental in delivering immediate transaction finality. This means that once blocks are validated within a shard, their finality is assured almost instantly, contributing to remarkably high transaction speeds. The integration of EPoS with sharding and PBFT finality ensures that Harmony One can sustain a decentralized, secure, and highly performant environment for its users and applications, making it suitable for high-frequency decentralized applications that require both speed and robust security guarantees.

Ronin operates on a Delegated Proof of Stake (DPoS) consensus mechanism, a system designed to ensure network security and validate transactions through a set of community-elected validators. Unlike traditional Proof of Work (PoW) systems that rely on energy-intensive mining, DPoS leverages the collective participation of token holders to maintain network integrity. The core of Ronin's consensus involves RON token holders delegating their tokens to vote for validators. These validators, chosen based on the amount of delegated stake they receive, are then responsible for key network operations, including producing new blocks, validating transactions, and overall network security. The selection process is dynamic, with validators frequently rotating based on ongoing community votes. This periodic rotation is a critical feature, enhancing decentralization by preventing any single validator group from maintaining long-term, unchallenged control over the network. Such a system promotes fairness and distributes network responsibilities more broadly among participants, thereby strengthening security against potential centralization vectors. An incentive-driven voting system is integral to Ronin’s DPoS model, ensuring that validators consistently act in the best interests of the network and its community. Validators are continuously monitored by the delegating community. If a validator's performance falls short or if they engage in activities that are detrimental to the network's health, they risk losing the votes delegated to them. This mechanism allows for underperforming or malicious validators to be replaced by more trustworthy participants, maintaining a high standard of operational integrity. The ongoing alignment of validator actions with community goals is therefore enforced through direct democratic participation, where token holders directly influence who secures the network. This combination of community-elected validators, periodic rotation, and an incentive-driven voting system underpins Ronin's robust and adaptive consensus, fostering a secure, decentralized, and efficient blockchain environment capable of supporting its diverse ecosystem. The DPoS framework significantly contributes to the network's ability to handle high transaction volumes efficiently while minimizing its environmental footprint compared to PoW alternatives.

Axie Infinity is present on the following networks: Binance Smart Chain, Ethereum, Harmony One, Ronin.

The Binance Smart Chain (BSC) network employs a robust system of incentive mechanisms and applicable fees, primarily built around its Proof of Staked Authority (PoSA) consensus, designed to secure the network, encourage participation, and maintain operational efficiency. This system ensures that validators, delegators, and other participants are economically motivated to act in the network's best interest.

Validators on BSC, often referred to as "Cabinet Members," are critical to the network's operation. They are incentivized through staking rewards, which include a combination of transaction fees and newly generated block rewards. To become a validator, a significant amount of BNB must be staked. Their selection for block production is determined by the total BNB staked, encompassing both their own stake and delegated tokens, as well as the votes received from delegators. This competitive selection process motivates validators to attract delegators and maintain high performance. Delegators, in turn, are crucial for supporting network decentralization and security. By delegating their BNB to validators, they increase the validators' total stake, enhancing their chances of selection. In exchange, delegators receive a share of the rewards earned by their chosen validators, fostering active community involvement. The system also includes a pool of Candidates, nodes that have staked BNB and are ready to become active validators, ensuring a robust and resilient network of potential participants. Economic security is further reinforced through slashing mechanisms, where validators found engaging in malicious behavior or failing to perform their duties face penalties, including the forfeiture of a portion of their staked BNB. The opportunity cost of locking up BNB also provides a strong economic incentive for all participants to act honestly.

BSC is known for its low transaction fees, which are paid in BNB. These fees are vital for network maintenance and compensate validators for processing transactions. The fee structure is dynamic, adjusting based on network congestion and transaction complexity, though it is designed to remain significantly lower than on some other major blockchain networks, such as the Ethereum mainnet. In addition to transaction fees, validators receive block rewards, further incentivizing their role in maintaining and processing network activity. BSC also supports cross-chain compatibility, enabling asset transfers between Binance Chain and Binance Smart Chain, which incur minimal fees to facilitate a seamless user experience. Furthermore, interacting with and deploying smart contracts on BSC involves fees based on the computational resources required. These smart contract fees are also paid in BNB and are structured to be cost-effective, encouraging developers to build and innovate on the BSC platform.

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 Harmony One blockchain network implements a comprehensive suite of incentive mechanisms and a transparent fee structure designed to foster active participation, maintain network security, and ensure efficient operations. Validators and delegators are primarily incentivized through staking rewards, which are disbursed in ONE tokens. Validators earn these tokens for their critical role in validating transactions and securing the network infrastructure. A significant portion of these earned rewards is then shared with delegators, who contribute to network security by staking their ONE tokens with chosen validators. This tiered reward system encourages a broad base of participation, allowing both active node operators and passive token holders to contribute to the network's robustness. A distinctive feature of Harmony One's incentive model is its decentralization penalty for high-stake validators. This mechanism is specifically designed to adjust and reduce rewards for validators that accumulate an excessive amount of delegated stake. By doing so, the network actively discourages the centralization of staking power, promoting a more equitable distribution among validators and reinforcing the network's decentralized ethos. This helps to prevent a scenario where a few dominant entities could exert undue influence over the network. In terms of applicable fees, Harmony One is structured to provide a cost-effective environment for its users. The network charges minimal transaction fees, which are denominated in ONE tokens. These low fees are particularly advantageous for high-frequency applications, enabling numerous interactions without incurring prohibitive costs. Furthermore, these transaction fees serve a dual purpose: they make the network accessible and efficient for users, while simultaneously providing an additional revenue stream for validators, further aligning their economic interests with the ongoing health and performance of the Harmony One network.

Ronin's economic model is built upon a comprehensive suite of incentive mechanisms, slashing protocols, and governance features, all designed to foster network security, stability, and active community engagement. At its foundation, the network rewards both validators and delegators for their participation. Validators, who are responsible for the critical tasks of producing blocks and validating transactions, earn RON tokens as staking rewards. These rewards serve as a direct financial incentive, encouraging validators to perform their duties diligently and maintain the operational integrity of the network. Complementing this, delegators, who are RON token holders that stake their tokens with chosen validators, also receive a proportional share of these staking rewards. This shared reward system is crucial for promoting widespread participation from the broader token-holding community, thereby enhancing the network's overall security and decentralization by distributing economic benefits more broadly. To ensure accountability and deter malicious behavior, Ronin incorporates a stringent slashing mechanism. Validators found to be acting dishonestly or failing to meet the network's performance standards face penalties, which involve the forfeiture of a portion of their staked RON tokens. This economic disincentive is a powerful tool against misconduct and ensures that validators remain committed to responsible network participation. Furthermore, delegators are also subject to risk; if they stake their tokens with a misbehaving validator, they too may experience slashing. This inherent risk encourages delegators to carefully research and select trustworthy validators and to actively monitor their performance, strengthening the network's security posture by promoting informed decision-making among participants. Beyond staking and transaction processing, the RON token also serves as a critical governance instrument, empowering token holders to actively participate in the network's strategic direction. This includes the ability to vote on crucial network upgrades, the selection of new validators, and other significant protocol-level decisions. This governance role provides token holders with a direct voice in shaping the future and policies of the Ronin network, fostering a truly community-driven ecosystem. In terms of operational costs, transaction fees on the Ronin network are paid in RON tokens. These fees contribute directly to the rewards earned by validators, essential for sustaining network operations. Designed to be affordable, these transaction fees ensure accessibility for a wide range of users, thereby supporting both user engagement and the continuous, efficient functioning of the validator ecosystem.

Axie Infinity is present on the following networks: Binance Smart Chain, Ethereum, Ronin.

The methodology for calculating the energy consumption of the Binance Smart Chain (BSC) network, which then serves as a basis for attributing a fraction of energy to tokens operating on it, primarily utilizes a "bottom-up" approach. This method focuses on the individual components of the network to aggregate a comprehensive energy profile. The central factor in this calculation is identified as the network nodes themselves.

Assumptions regarding the hardware used within the BSC network are derived from extensive empirical findings. These findings are gathered through a combination of public information sites, sophisticated open-source crawlers, and proprietary in-house developed crawlers. The primary determinants for estimating the specific hardware deployed are the technical requirements necessary to operate the client software of the network. To ensure accuracy, the energy consumption of these identified hardware devices is rigorously measured in certified test laboratories. This precise measurement allows for a detailed understanding of the power demands of the operational infrastructure.

For the comprehensive identification of all implementations of an asset within scope, the Functionally Fungible Group Digital Token Identifier (FFG DTI) is employed, where available. The mappings associated with the FFG DTI are regularly updated based on data provided by the Digital Token Identifier Foundation. The information regarding both the hardware in use and the total number of participants active within the network is based on assumptions that undergo best-effort verification using empirical data. Generally, participants are presumed to be largely economically rational in their decision-making. As a precautionary principle, in situations of uncertainty, assumptions tend to err on the conservative side, meaning higher estimates are made for potential adverse impacts. When determining the energy consumption for a specific token that operates on BSC, the initial step involves calculating the energy consumption of the entire Binance Smart Chain network. Following this, a fraction of the total network energy consumption is attributed to the particular crypto-asset, a fraction determined by the asset's specific 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 energy consumption within the Ronin blockchain network, as described in the provided documents, primarily focuses on attributing a fraction of the network's overall energy use to individual crypto-assets operating on it, rather than detailing the specific energy sources or calculation methods for the Ronin network itself. According to this approach, the first step involves calculating the total energy consumption of the underlying network, in this case, Ronin. However, the documents do not explicitly outline the detailed methodologies or the specific data points utilized to determine this foundational "network energy consumption." Instead, they state that the information regarding the hardware deployed and the number of participants supporting the network is based on assumptions. These assumptions are purportedly verified with a "best effort" using empirical data, and a precautionary principle is applied, often leading to higher estimates for potential adverse impacts when there is uncertainty. For instance, while the process indicates that the network's energy consumption is "calculated first," there is an absence of specific information regarding the types of hardware (e.g., servers, data centers, networking equipment) employed by Ronin validators, their operational characteristics, or the specific energy intensity metrics used for these components. Similarly, the exact methodologies for measuring or estimating electricity usage, such as direct metering, power usage effectiveness (PUE) factors, or regional electricity grid mix data, are not detailed for the Ronin network's foundational operations. The documents also mention the use of the Functionally Fungible Group Digital Token Identifier (FFG DTI), where available, to identify all implementations of an asset, with mappings updated regularly by the Digital Token Identifier Foundation. This identifier helps in accurately scoping which assets are considered when attributing energy consumption. In essence, the disclosed methodology serves as a framework for the attribution of energy consumption from the Ronin network to specific tokens. It specifies that once the network's total energy consumption is theoretically established, a fraction of this total is assigned to a token based on its activity within the network. This highlights a gap in the publicly available information regarding the precise energy sources that power the Ronin infrastructure and the transparent, granular methodologies for calculating the network's base energy footprint. Without these specific details, a comprehensive understanding of Ronin's direct energy consumption profile remains partially unaddressed in the provided texts, as the focus is on a top-down attribution model for assets rather than a bottom-up calculation of network infrastructure energy use.

Axie Infinity is present on the following networks: Binance Smart Chain, Ethereum.

To ascertain the proportion of renewable energy utilized by the Binance Smart Chain (BSC) network, a detailed methodology focuses on identifying the geographical distribution of its operational nodes. This process begins with leveraging a variety of data sources, including public information websites, general open-source crawlers, and specialized in-house developed crawlers. These tools collectively help pinpoint the physical locations where the network's nodes are hosted. The precise geographic distribution of these nodes is a crucial piece of information for accurately assessing renewable energy integration.

In instances where comprehensive information regarding the geographic distribution of nodes is unavailable or insufficient, the methodology incorporates a fallback mechanism. This involves using reference networks that exhibit comparable characteristics in terms of their incentivization structures and underlying consensus mechanisms. By analyzing the renewable energy usage patterns of these similar networks, an informed estimate can be made for BSC. Once geographical data for the nodes (either direct or inferred from reference networks) is established, this geo-information is meticulously merged with publicly accessible data from Our World in Data. This external dataset provides crucial insights into the share of electricity generated by renewables globally, drawing from sources like Ember (2025) and the Energy Institute’s Statistical Review of World Energy (2024). The integration of this data allows for a granular understanding of the renewable energy mix at the node locations.

Furthermore, the energy intensity of the network is calculated as the marginal energy cost with respect to one additional transaction. This metric quantifies the energy expenditure incurred for each incremental transaction processed on the network, providing a measure of its operational efficiency from an energy perspective. The consistent use of reputable public data sources and a robust methodology ensures transparency and accuracy in reporting the renewable energy profile of the Binance Smart Chain network.

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.

Axie Infinity is present on the following networks: Binance Smart Chain, Ethereum.

The methodology for determining the Greenhouse Gas (GHG) Emissions associated with the Binance Smart Chain (BSC) network, much like the energy consumption assessment, places a strong emphasis on geographically situating its operational nodes. The initial step involves identifying the physical locations of these nodes, which is achieved through a combination of public information sites, open-source crawlers, and specialized in-house developed crawlers. Accurately mapping these locations is fundamental, as regional electricity mixes and their associated carbon footprints vary significantly.

In situations where detailed geographical information for all nodes is not readily available, the methodology incorporates a pragmatic approach. This involves utilizing reference networks that share similar characteristics, specifically in their incentivization structures and consensus mechanisms. By studying these comparable networks, reasonable inferences can be made about the likely geographic distribution and, consequently, the emissions profile of BSC's nodes. Once the geographic data is gathered or estimated, it is then meticulously integrated with publicly available information from Our World in Data. This authoritative dataset provides critical data on the carbon intensity of electricity generation across various regions, compiling information from sources such as Ember (2025) and the Energy Institute’s Statistical Review of World Energy (2024).

This integration allows for the calculation of GHG emissions based on the electricity consumption at specific node locations and the carbon intensity of those regional grids. The intensity of GHG emissions for the network is specifically calculated as the marginal emission with respect to one additional transaction. This metric quantifies the increase in GHG emissions for each incremental transaction processed on the network, offering a direct measure of its environmental impact per unit of activity. The entire process adheres to a principle of transparency, utilizing established external data sources and a consistent approach to ensure the reported GHG emissions are as accurate and comprehensive as possible, always acknowledging that the data from Our World in Data is licensed under CC BY 4.0.

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.