OVERTAKE (TAKE) sustainability report

OVERTAKE is present on the following networks: Binance Smart Chain, Sui.

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 Sui blockchain network employs a sophisticated Byzantine Fault Tolerant (BFT) consensus mechanism, specifically optimized for achieving high transaction throughput and minimal latency. At its core is the Mysten Consensus Protocol, an advanced evolution of Practical Byzantine Fault Tolerance (pBFT). A distinguishing feature of Sui’s design is its leaderless architecture, which deviates from traditional BFT models that often rely on a single leader to propose blocks. Instead, multiple validators can simultaneously propose blocks, thereby significantly enhancing network efficiency and mitigating risks associated with potential leader failures or targeted attacks. This parallel processing capability is crucial, allowing transactions to be executed concurrently across various cores and threads. This design choice maximizes the network's processing capacity, leading to faster transaction confirmations and superior scalability compared to systems with sequential processing.

Transaction validation on Sui is handled by validators who receive requests directly from clients. Each transaction undergoes rigorous checks, including digital signature verification and adherence to network rules. Crucially, validators can process these transactions in parallel, a contrast to many other blockchain networks that enforce a strict, leader-driven sequence. The network further benefits from an optimistic execution approach, where non-contentious and independent transactions can be processed without requiring full consensus upfront. This "optimistic consensus" significantly reduces transaction latency for many common use cases, enabling near-instant finality in most scenarios. For a transaction to achieve finality, the Sui system mandates only three rounds of communication among validators. This streamlined communication protocol contributes directly to the network's low-latency consensus and rapid transaction confirmation times, ensuring both scalability and robust security. The system is also designed with strong fault tolerance, capable of maintaining the integrity of its consensus process even if up to one-third of its validators are faulty or behave maliciously. This robust BFT implementation underpins Sui’s capacity for efficient and secure operations.

OVERTAKE is present on the following networks: Binance Smart Chain, Sui.

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 Sui blockchain network employs a comprehensive set of security and economic incentive mechanisms designed to ensure robust participation and network integrity. Central to these incentives are the validators, who play a critical role in the consensus process. Validators are required to stake SUI tokens as collateral to participate in transaction validation and network security. In return for their honest efforts, they are compensated with rewards. To uphold network security and promote honest behavior, Sui incorporates a "slashing" mechanism. This means validators can face penalties, including the forfeiture or "slashing" of a portion of their staked SUI tokens, if they engage in malicious activities such as double-signing transactions or failing to perform their validation duties correctly. This economic disincentive acts as a powerful deterrent against misconduct.

Beyond active validators, the Sui network encourages broader community participation through a delegation system. SUI token holders who may not have the technical capacity or desire to run a validator node themselves can delegate their tokens to trusted validators. In exchange for their delegated stake, these token holders receive a share of the rewards earned by the validators, fostering widespread involvement in securing the network.

Regarding the financial aspects of network operation, users on the Sui blockchain incur transaction fees for the processing and confirmation of their activities. These fees are paid to the validators, compensating them for the computational resources expended. All transaction fees are denominated in SUI tokens, which serves as the native cryptocurrency for the Sui blockchain. The network also implements a dynamic fee model, meaning that transaction costs are not fixed but adjust according to prevailing network demand and the intrinsic complexity of the transaction being processed. This adaptive fee structure aims to efficiently manage network congestion and resource allocation, ensuring that costs remain responsive to actual usage and demand.

OVERTAKE is present on the following networks: Binance Smart Chain, Sui.

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 energy consumption of the Sui blockchain network is determined through a meticulous "bottom-up" methodological approach, which aggregates data across various operational components. This method considers the nodes as the primary contributors to the network's overall energy footprint. The underlying assumptions for these calculations are derived from empirical findings, gathered through the utilization of public information sites, proprietary in-house crawlers, and open-source crawlers. These tools collectively aid in collecting comprehensive data on the network's infrastructure and activity.

A critical aspect of estimating hardware usage within the network involves analyzing the specific requirements for running the client software. This forms the basis for inferring the types and quantities of hardware devices deployed across the network. The energy consumption of these identified hardware devices is then accurately measured in certified test laboratories, ensuring precision in the energy assessments. For a holistic calculation of energy consumption, the Functionally Fungible Group Digital Token Identifier (FFG DTI) is employed, where available, to identify all relevant implementations of the crypto-asset within scope. These mappings are regularly updated, leveraging data provided by the Digital Token Identifier Foundation, to maintain accuracy and completeness.

Furthermore, the information regarding the specific hardware utilized and the total number of participants in the network relies on assumptions. These assumptions are meticulously verified with best effort, drawing upon empirical data to ensure their robustness. Participants within the ecosystem are generally presumed to act with economic rationality. In adherence to a precautionary principle, whenever there is uncertainty, estimates for potential adverse impacts, such as higher energy consumption figures, are made conservatively. This approach ensures that the reported energy consumption reflects a cautious and robust assessment of the network's environmental impact. To attribute energy consumption to a specific token on the network, the overall energy consumption of the entire Sui network is first calculated, and then a fraction of this total is assigned to the token based on its activity within that network.

OVERTAKE is present on the following networks: Binance Smart Chain, Sui.

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.

The methodology for determining the proportion of renewable energy utilized by the Sui blockchain network involves a detailed process focused on identifying the geographical distribution of its operational nodes. This identification is achieved through a combination of public information sources, custom-developed in-house crawlers, and various open-source data collection tools. In instances where specific geographic information about the nodes is not readily available, the methodology pivots to referencing comparable blockchain networks. These reference networks are carefully selected based on similarities in their incentivization structures and consensus mechanisms, providing a proxy for estimating the node locations when direct data is absent.

Once the geo-information regarding node locations is established, it is then meticulously integrated with publicly available data sourced from "Our World in Data". This integration allows for a comprehensive assessment of the energy mix supporting the network's operations. The energy intensity, which measures the environmental impact per unit of activity, is computed as the marginal energy cost associated with processing one additional transaction on the network. This metric provides insight into the incremental energy footprint of network operations. The data utilized for these calculations is derived from authoritative sources, including Ember (2025) and the Energy Institute – Statistical Review of World Energy (2024), with further processing by Our World in Data. Specifically, the dataset titled "Share of electricity generated by renewables - Ember and Energy Institute" is retrieved from [Our World in Data](https://ourworldindata.org/grapher/share-electricity-ren ewables). This systematic approach ensures that the renewable energy assessment is grounded in verifiable data and rigorous analytical methods, reflecting a commitment to transparent reporting of the network's energy profile.

OVERTAKE is present on the following networks: Binance Smart Chain, Sui.

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 quantifying Greenhouse Gas (GHG) Emissions attributable to the Sui blockchain network is systematically designed, beginning with the precise determination of the physical locations of the network's operational nodes. This critical geographic data is gathered through a combination of publicly accessible information sites, internally developed crawlers, and various open-source data collection mechanisms. Should direct information on the geographical distribution of these nodes prove unavailable, the assessment relies on data from reference networks. These alternative networks are chosen for their structural similarities, particularly concerning their incentivization mechanisms and consensus protocols, allowing for a reasonable estimation of node locations.

Following the acquisition of node location data, this geo-information is subsequently integrated with relevant public data from "Our World in Data". This merging of datasets facilitates a robust calculation of the network's GHG emissions. A key metric in this assessment is the GHG intensity, which is defined as the marginal emission produced per additional transaction processed on the network. This provides a granular understanding of the environmental impact of each unit of network activity. The foundational data for these emissions calculations is sourced from reputable entities such as Ember (2025) and the Energy Institute - Statistical Review of World Energy (2024), with further analytical processing undertaken by Our World in Data. Specifically, the dataset employed for this purpose is "Carbon intensity of electricity generation - Ember and Energy Institute", which can be accessed via Our World in Data. This dataset is made available under a CC BY 4.0 license. This comprehensive methodology ensures a transparent and empirically-backed evaluation of the Sui network’s carbon footprint.