Ren (REN) sustainability report

Ren is present on the following networks: Ethereum, Harmony One, Near Protocol.

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.

The NEAR Protocol blockchain network operates on a distinctive consensus mechanism that synergistically combines the principles of Proof of Stake (PoS) with a proprietary innovation known as Doomslug, further enhanced by dynamic sharding through Nightshade. This multi-faceted approach is engineered to deliver high efficiency, rapid transaction finality, and robust security across the network. At its foundation, the system relies on Proof of Stake, where participants, termed validators, secure the network by staking their native NEAR tokens. The greater the stake, coupled with community trust, the higher their probability of being chosen to propose and validate blocks.Doomslug significantly accelerates transaction finality. Unlike single-stage block confirmations, Doomslug introduces a two-stage process. Initially, validators propose new blocks. Finality is achieved swiftly when two-thirds of the participating validators formally approve the proposed block, making confirmed transactions irreversible and preventing potential forks. This rapid finality is crucial for applications demanding near-instant confirmations. Complementing this, NEAR integrates Nightshade, a dynamic sharding technique. Nightshade segments the network into multiple shards, allowing for the parallel processing of transactions. Each shard handles a distinct subset of transactions concurrently, and their respective processing outcomes are then consolidated into a single "snapshot" block. This dynamic sharding is vital for scalability, enabling the network to efficiently manage increasing transaction volumes and user demand without compromising performance.The consensus process also emphasizes decentralization and fairness through epoch rotation. Validators are regularly reshuffled across distinct intervals called epochs. This rotation mechanism ensures a balanced distribution of block proposal opportunities and validation responsibilities among eligible validators, mitigating centralization risks and promoting sustained network resilience. By integrating PoS for economic security, Doomslug for fast finality, and Nightshade for scalable throughput, the NEAR Protocol establishes a high-performance and secure blockchain environment.

Ren is present on the following networks: Ethereum, Harmony One, Near Protocol.

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.

The NEAR Protocol blockchain network employs a comprehensive suite of economic mechanisms designed to ensure network security, incentivize active participation from its community, and manage resource allocation efficiently. A core incentive is the staking reward system, where validators and delegators are compensated for their role in securing transactions. Validators, selected based on their staked NEAR tokens and community trust, receive a share of newly minted tokens, constituting about 90% of the approximate 5% annual inflation. They earn these rewards for proposing and validating blocks. Similarly, token holders who choose not to operate a full validator node can delegate their NEAR tokens to active validators, thereby contributing to network security and earning rewards proportional to their delegated stake. This delegation model fosters broader participation and strengthens the network's overall decentralization.To uphold network integrity, NEAR Protocol implements a robust slashing mechanism. Validators engaging in malicious activities, such as incorrect validation or dishonest behavior, face economic penalties, including the deduction of a portion of their staked tokens. This serves as a powerful deterrent against harmful actions, ensuring validators operate in the network's best interest. Additionally, the network promotes fairness and prevents undue concentration of power through regular epoch rotations. During these predefined intervals, validators are periodically reshuffled, and new block proposers are selected, maintaining a healthy balance between network performance and decentralization.Regarding applicable fees, the NEAR blockchain charges users for transaction processing and data storage, paid in NEAR tokens. A unique aspect of its fee structure is the burning mechanism for transaction fees, which reduces the total circulating supply of NEAR tokens over time, potentially introducing a deflationary effect. While a portion of these fees is burned, the remaining part is distributed to validators as additional compensation, providing a continuous incentive for network maintenance. Furthermore, the protocol imposes storage fees based on the amount of blockchain space consumed by user accounts, smart contracts, and associated data. Users are required to hold NEAR tokens as a deposit commensurate with their storage usage, which encourages efficient resource management and helps prevent network spam. This dual system of incentives and fees creates a self-sustaining economic model for the NEAR Protocol.

Ren is present on the following networks: Ethereum, Near Protocol.

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 NEAR Protocol network relies on a "bottom-up" approach, meticulously aggregating data across its various operational components. This method primarily considers the network's nodes as the central contributors to overall energy usage. The fundamental assumptions underpinning these calculations are derived from empirical findings obtained through a combination of public information sources, proprietary in-house crawlers, and publicly available open-source crawlers. These tools are instrumental in gathering essential data about the network's operational footprint.A critical determinant in estimating the hardware deployed within the network is the specific computational requirements necessary to run the client software. Based on these identified requirements, the energy consumption of the corresponding hardware devices is rigorously measured in certified test laboratories. This ensures accuracy and consistency in energy attribution. Furthermore, when calculating energy consumption, the Functionally Fungible Group Digital Token Identifier (FFG DTI) is utilized, where available, to precisely identify and encompass all relevant implementations of any crypto-asset within the network's scope. These mappings are regularly updated, leveraging data from the Digital Token Identifier Foundation, to maintain current and accurate representations.The information pertaining to the hardware used and the total number of participants in the network is built upon assumptions, which are diligently verified using the best available empirical data. A general underlying premise is that network participants are largely economically rational actors. In adherence to a precautionary principle, conservative estimations are favored when uncertainties arise, leading to higher projected adverse impacts to ensure a robust and responsible assessment of energy consumption. This comprehensive methodology allows for a detailed and conservative estimation of the NEAR Protocol network's energy footprint.

Ren is present on the following networks: Ethereum, Near Protocol.

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.

To accurately determine the proportion of renewable energy utilized by the NEAR Protocol network, a systematic methodology is employed focusing on the geographic distribution of its operational nodes. The initial step involves identifying the precise locations of these nodes using a combination of public information sites, advanced open-source crawlers, and internally developed specialized crawlers. This comprehensive data collection ensures a broad and accurate understanding of the physical presence of the network's infrastructure.In instances where precise geographic information for certain nodes might be unavailable, the methodology incorporates a fallback mechanism. It leverages data from reference networks that are deemed comparable to NEAR Protocol in terms of their incentivization structures and underlying consensus mechanisms. This comparative analysis helps to fill data gaps and provide a reasonable proxy for renewable energy usage in such cases.Once the geographical data for the nodes is established, this geo-information is meticulously integrated with publicly available datasets from reputable sources, notably "Our World in Data." This integration allows for the correlation of node locations with regional energy grid compositions and the prevalence of renewable energy sources in those areas. The final aspect of this methodology involves calculating the energy intensity of the network. This is defined as the marginal energy cost incurred with respect to processing one additional transaction on the NEAR Protocol blockchain. This metric provides a granular view of the energy efficiency per unit of network activity. For detailed information regarding the underlying energy data, the following sources are utilized: Share of electricity generated by renewables – Ember and Energy Institute. This rigorous approach ensures a transparent and verifiable assessment of renewable energy integration within the network's operations.

Ren is present on the following networks: Ethereum, Near Protocol.

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 assessment of Greenhouse Gas (GHG) Emissions for the NEAR Protocol network follows a structured methodology that prioritizes the precise geographical identification of its operational nodes. This process begins by actively determining the locations of all network nodes, utilizing a combination of publicly accessible information sites, sophisticated open-source crawling tools, and specialized crawlers developed in-house. This multi-pronged data acquisition strategy aims to gather comprehensive location data for the network's infrastructure.Should specific geographic distribution data for certain nodes prove unobtainable, the methodology incorporates the use of reference networks. These are carefully selected based on their similarity to the NEAR Protocol in terms of their incentive structures and consensus mechanisms, allowing for an informed estimation of GHG emissions in the absence of direct data. This comparative approach ensures that even with limited direct information, a credible assessment can still be made.The collected geo-information is subsequently integrated with extensive public datasets, prominently featuring data from "Our World in Data." This integration enables the cross-referencing of node locations with regional carbon intensity data of electricity generation, providing a basis for calculating the associated GHG emissions. A crucial metric derived from this methodology is the GHG intensity, which quantifies the marginal emission attributable to processing one additional transaction on the NEAR Protocol network. This metric offers insights into the environmental footprint per unit of network activity. For detailed data on carbon intensity, the following resource is referenced: Carbon intensity of electricity generation – Ember and Energy Institute. This rigorous and transparent methodology underpins the network's efforts to measure and report its environmental impact.