Zyfai (ZFI) sustainability report

Zyfai is present on the following networks: Base, Zksync.

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.

Zksync utilizes a sophisticated Layer 2 scaling architecture built on zero-knowledge rollup (ZK-Rollup) technology. Unlike traditional Layer 1 networks that require every node to execute every transaction, this network aggregates numerous transactions into discrete batches off-chain. The core of its consensus and security mechanism lies in the generation of validity proofs, specifically employing zk-SNARKs (Succinct Non-Interactive Arguments of Knowledge). These cryptographic proofs provide a mathematical guarantee that all transactions within a batch are legitimate and adhere to the protocol's rules. Once a validity proof is generated, it is submitted to the Ethereum mainnet. This approach allows the network to inherit the robust security of Ethereum's base layer while significantly increasing throughput. A critical component in this process is the sequencer, which is responsible for the ordering and bundling of user transactions. Unlike optimistic rollups that rely on a challenge period and fraud proofs, Zksync provides immediate finality once the validity proof is verified on the Layer 1 chain. This architectural choice eliminates the withdrawal delays often associated with other scaling solutions. Furthermore, the network ensures data availability by publishing transaction data on-chain, which allows any participant to reconstruct the state of the network independently. This transparency maintains the decentralized nature of the system while offloading the heavy computational burden from the primary blockchain, resulting in a highly efficient and secure environment for decentralized applications.

Zyfai is present on the following networks: Base, Zksync.

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 Zksync network employs a multifaceted incentive and fee structure designed to balance operational efficiency with network security. The primary participants, including validators and sequencers, are compensated through transaction fees paid by users. Sequencers play a vital role in the ecosystem by ordering and bundling transactions into batches; they receive a portion of the transaction fees to cover the costs of maintaining high-performance processing and fast confirmation times. Validators, who are responsible for the computationally intensive task of generating validity proofs, are likewise rewarded for ensuring that these batches are processed accurately and efficiently. Unlike some Layer 2 solutions that might use a native utility token for all operations, Zksync utilizes Ether (ETH) as the primary currency for paying transaction fees. This integrates the network more closely with the Ethereum ecosystem and simplifies the user experience. The fee model itself is dynamic, calculating costs based on the complexity of the specific transaction—such as smart contract interactions versus simple transfers—as well as the current gas prices on the Ethereum mainnet for submitting the aggregated proofs. By batching transactions, the network significantly reduces the individual gas burden on users, making it far more cost-effective than direct Layer 1 interactions. Additionally, the protocol includes provisions for ecosystem growth rewards, allocating resources to incentivize developers and projects that contribute to the proliferation of decentralized finance (DeFi) and non-fungible token (NFT) marketplaces. This holistic approach ensures that all roles, from infrastructure providers to end-users and developers, have clear economic reasons to participate in and support the network's long-term sustainability.

Zyfai is present on the following networks: Base, Zksync.

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.

To determine the energy consumption of the Zksync network, a comprehensive methodology is applied that aggregates data from various infrastructure components. The process begins by assessing the total energy requirements of the blockchain environment, considering all participants involved in transaction processing and proof generation. A key element of this calculation involves the use of the Functionally Fungible Group Digital Token Identifier (FFG DTI) system. This identifier allows for the precise mapping of all implementations and activities associated with the network, ensuring that energy data is tracked accurately across different protocols and platforms. The data used for these assessments is frequently updated based on records from the Digital Token Identifier Foundation. In instances where direct measurements are unavailable, the methodology relies on a set of standardized assumptions regarding hardware efficiency and the number of active participants. These assumptions are grounded in the principle of economic rationality, positing that participants will optimize their operations for cost-effectiveness. However, to ensure environmental integrity, a "precautionary principle" is adopted. This means that when there is uncertainty in the data or the empirical evidence, the model leans toward more conservative estimates, which generally result in higher projected figures for energy consumption. This rigorous approach aims to capture the full scope of the network's ecological footprint, from the off-chain computation performed by sequencers and provers to the finality achieved through the Ethereum mainnet. By verifying these assumptions with the best available empirical data, the methodology provides a robust framework for understanding how Layer 2 scaling solutions interact with global energy resources.

Zyfai is present on the following networks: Zksync.

The identification of key energy sources for the Zksync network relies on determining the geographic distribution of its infrastructure. This is achieved through a combination of public information portals, open-source web crawlers, and proprietary software designed to locate the nodes and servers supporting the network. When precise geographic data for specific nodes is missing, the methodology utilizes reference networks that share similar consensus mechanisms and incentive structures to estimate location patterns. This geographical data is then integrated with statistical information from Share of electricity generated by renewables - Ember and Energy Institute to calculate the proportion of renewable energy being utilized by the network's participants. This dataset provides a global view of electricity generation trends, allowing for a more accurate assessment of whether the power consumed comes from sustainable or traditional sources. The energy intensity of the network is further refined by calculating the marginal energy cost associated with each additional transaction. This approach moves beyond simple averages, providing insight into the incremental environmental impact of network activity. By merging internal node telemetry with external datasets like those from the Energy Institute, the analysis can distinguish between regions with high renewable penetration and those still reliant on fossil fuels. This level of detail is essential for a transparent view of the network's sustainability profile, ensuring that the environmental benefits of Layer 2 scaling are documented alongside the specific energy mix of the underlying infrastructure.

Zyfai is present on the following networks: Zksync.

The methodology for evaluating Greenhouse Gas (GHG) emissions for Zksync mirrors the geographic assessment used for energy sources, focusing on the carbon intensity of the power grids where the network's nodes are situated. By identifying the locations of validators and sequencers through specialized crawlers and public data, the analysis assigns specific emission factors based on regional electricity profiles. These profiles are derived from the Carbon intensity of electricity generation - Ember and Energy Institute dataset, which offers comprehensive information on the grams of CO2 equivalent produced per kilowatt-hour across different nations. The methodology categorizes emissions into different scopes, typically focusing on Scope 2 emissions related to purchased electricity for running the hardware. To provide a granular view of the network's impact, the GHG intensity is expressed as the marginal emission generated by a single additional transaction on the blockchain. This allows users and developers to understand the carbon footprint of their specific interactions with the protocol. In cases where node data is sparse, the model employs reference network comparisons to ensure that the global footprint is not underestimated. The integration of this geo-information with the data provided by Ember and the Energy Institute ensures that the final figures reflect the most current and peer-reviewed information available in the field of energy statistics. This evidence-based approach to carbon accounting allows the network to maintain a high standard of transparency and align with international sustainability reporting standards.