Ta-da (TADA) sustainability report

Ta-Da is present on the following networks: Binance Smart Chain, Multiversx, Solana.

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 MultiversX blockchain network operates on a unique consensus model known as Secure Proof of Stake (SPoS), a sophisticated evolution of the traditional Proof of Stake (PoS) mechanism. This design prioritizes high throughput, low latency, and enhanced scalability, crucial for managing a decentralized network efficiently. At its core, SPoS incorporates a rapid, randomized validator selection process, allowing validators to be chosen in under 100 milliseconds based on their staked assets. This quick rotation is fundamental to maintaining network efficiency and preventing any potential centralization, as the validator set is constantly changing.

Key components of the MultiversX consensus include two types of nodes: Validator Nodes and Observer Nodes. Validator Nodes are responsible for the critical tasks of processing transactions and producing new blocks, actively participating in the network's security and data integrity. In contrast, Observer Nodes serve a read-only function, providing essential data access and continuous network monitoring without directly participating in block production. This separation of duties contributes to the network's resilience and efficiency.

Beyond SPoS, MultiversX significantly enhances its scalability through Adaptive State Sharding. This innovative technique segments the network into multiple shards, enabling transactions to be processed in parallel across these distinct partitions. This parallel processing capability is vital for increasing transaction throughput and overall network performance, allowing the blockchain to handle a large volume of operations simultaneously. To ensure coherence and finality across these fragmented processes, the network employs Meta Chain Coordination. The Meta Chain is specifically designed to manage cross-shard transactions, ensuring that blocks are finalized correctly and that data consistency is maintained seamlessly between all shards. This holistic approach to consensus and scaling underscores MultiversX's commitment to building a robust, high-performance blockchain infrastructure.

The Solana blockchain architecture operates through a hybrid consensus model that integrates Proof of History (PoH) with Proof of Stake (PoS). This combination is designed to optimize transaction throughput and reduce network latency while maintaining a high degree of security. Proof of History functions as a decentralized clock, using a Verifiable Delay Function (VDF) to create a permanent, timestamped record of events. This cryptographic sequence allows the network to agree on the chronological order of transactions without requiring nodes to communicate extensively, thereby solving traditional synchronization bottlenecks found in other distributed ledgers. Parallel to PoH, the Proof of Stake component manages the selection of validators and the finalization of the ledger state. Validators are chosen to act as leaders for specific blocks based on the total quantity of the native network assets they have staked. Users who do not run their own hardware can participate in network security by delegating their assets to existing validators, sharing in the rewards generated by successful block production. The consensus process begins when transactions are broadcast and collected for validation. A designated leader then generates a PoH sequence to order these transactions within a block. Subsequently, other validators in the network verify the integrity of the PoH hashes and the validity of the transactions. Once a sufficient number of signatures are collected, the block is finalized and appended to the blockchain. This dual approach ensures that the network remains resilient against attacks; validators must provide collateral through staking, and any malicious activity, such as producing invalid blocks or double-signing, can result in the loss of staked assets through a process known as slashing. This economic deterrent ensures that participants remain aligned with the network's health and operational standards.

Ta-Da is present on the following networks: Binance Smart Chain, Multiversx, Solana.

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 MultiversX blockchain network employs a comprehensive system of incentive mechanisms and applicable fees designed to ensure network security, encourage active participation, and sustain overall performance. At the forefront of these incentives are staking rewards, which are distributed to both validators and delegators. Validators, who are responsible for processing transactions and producing new blocks, earn rewards in the native network token. These rewards are a direct compensation for their crucial role in maintaining the network's integrity and operational continuity. Similarly, network token holders who may not wish to operate a full validator node can still contribute to network security and earn passive income by delegating their tokens to existing validators. Delegators receive a proportional share of the staking rewards, fostering broader participation in the network’s decentralized governance and security model.

In addition to staking rewards, the MultiversX network implements a clear fee structure for various on-chain activities. Transaction fees are a primary component, paid in the network's native token. These fees are dynamically structured, meaning they can vary based on the complexity and size of the transaction, covering a wide range of network interactions such as executing smart contracts, transferring assets, and other data operations. The design ensures that computational resources are appropriately compensated, while maintaining efficiency for users. The fees are distributed among validators as part of their earnings, providing a continuous economic incentive for them to process transactions accurately and efficiently.

Furthermore, the network provides opportunities for passive staking through delegation. This mechanism allows network token holders to support validators by contributing their tokens to a validator's stake. This not only strengthens the network's security posture by increasing the total staked amount but also enables delegators to earn a share of the block rewards and transaction fees, without the technical overhead of running a validator node. This dual system of direct validator rewards and delegator incentives ensures a robust and economically viable ecosystem, encouraging sustained engagement from all participants while guaranteeing the efficient and secure operation of the MultiversX blockchain.

Incentives within the Solana blockchain network are structured to ensure high performance and decentralized security. The primary participants are validators and delegators, both of whom receive financial compensation for their roles in maintaining the ledger. Validators are rewarded for successfully producing and verifying blocks. These rewards are distributed in the network's native asset and are determined by the validator's overall stake and historical performance. Furthermore, validators receive a portion of the transaction fees associated with the data processed in their blocks, which encourages them to maximize efficiency and maintain uptime. Token holders who prefer not to operate complex infrastructure can delegate their stake to professional validators. This delegation model facilitates a more inclusive security environment, as delegators earn a percentage of the rewards proportional to their contribution, thereby decentralizing the control of the network. Security is further enforced through economic penalties. The network employs a slashing mechanism where a portion of a validator's staked assets is confiscated if they engage in dishonest behavior or fail to meet network requirements, such as remaining offline for extended periods. This introduces an opportunity cost for all participants, ensuring they remain committed to honest operations. Regarding the cost of using the network, the fee structure is designed to be highly competitive and predictable. Users pay transaction fees to compensate for the computational power and bandwidth consumed by nodes. These fees are notably low, facilitating high-volume usage. In addition to transaction costs, the network implements rent fees for data storage. This unique mechanism charges for the persistence of data on the blockchain, discouraging the inefficient use of state storage and prompting developers to prune unnecessary data. Finally, smart contract execution fees are calculated based on the specific resource intensity of the code, ensuring that participants pay a fair rate for the network resources they utilize.

Ta-Da is present on the following networks: Binance Smart Chain, Multiversx, Solana.

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 energy consumption of the MultiversX blockchain network primarily utilizes a 'bottom-up' approach, which considers individual nodes as the fundamental units driving the network's energy footprint. This approach relies heavily on empirical findings derived from a combination of public information sites, sophisticated open-source crawlers, and proprietary in-house developed crawling tools. These resources are employed to gather data about the hardware infrastructure supporting the network.

A critical determinant in estimating the hardware used across the network involves assessing the minimum and recommended requirements for operating the client software. This allows for a reasonable approximation of the types and specifications of computing devices typically employed by network participants. To ensure accuracy in energy consumption figures, the power consumption of these identified hardware devices is meticulously measured in certified test laboratories under controlled conditions. This rigorous testing provides a baseline for attributing energy usage to the operational hardware.

For broader scope and identification of all relevant implementations of the network’s assets, the Functionally Fungible Group Digital Token Identifier (FFG DTI) is utilized whenever available. This identifier helps in systematically mapping and updating all instances of the asset in question, with mappings regularly updated based on data from the Digital Token Identifier Foundation. The information regarding both the hardware in use and the total number of participants in the network is built upon assumptions, which are diligently verified using empirical data to the best possible effort. A core assumption in this model is that network participants generally act in an economically rational manner. Adhering to a precautionary principle, when there is uncertainty or doubt, conservative assumptions are made, typically leading to higher estimates for potential adverse environmental impacts to ensure a robust and comprehensive assessment of energy consumption within the MultiversX ecosystem.

To calculate the energy consumption of the Solana blockchain network, a "bottom-up" methodology is utilized, placing the network nodes at the center of the analysis. This approach relies on identifying the number of active participants and the specific hardware requirements necessary to run the network's client software. Data collection involves a variety of sources, including open-source web crawlers, internal monitoring tools developed by the legal entities, and public information websites. By analyzing these data points, researchers can estimate the hardware profiles of the various nodes operating globally. To ensure accuracy, the energy consumption of typical hardware devices is measured within certified laboratory environments, providing a baseline for the power usage of each node. Furthermore, the methodology incorporates data from the Digital Token Identifier Foundation to map all implementations of the assets within the network's scope. When specific hardware data is not directly observable, assumptions are made based on the principle of economic rationality, assuming participants optimize their setups for cost-efficiency while meeting software specifications. In instances of uncertainty, a precautionary principle is applied, favoring conservative estimates that likely overstate the environmental impact rather than underestimating it. This ensures that the reported energy footprint represents a credible upper bound of actual consumption. The total network consumption is determined by aggregating the energy needs of all identified nodes, accounting for both the computational requirements of processing transactions and the energy consumed by hardware in an idle or supportive state. This rigorous framework allows for a comprehensive assessment of the network’s total power requirements over a defined reporting period, providing a transparent view of the operational costs associated with maintaining the distributed ledger's infrastructure.

Ta-Da is present on the following networks: Binance Smart Chain, Multiversx, Solana.

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 usage within the MultiversX blockchain network is meticulously structured, focusing on geographical data collection and external data integration. The primary step involves accurately identifying the physical locations of the network's nodes. This crucial information is gathered through a combination of diverse data sources, including publicly available information sites, advanced open-source crawlers, and specialized in-house developed crawling tools. These tools systematically scan the network to pinpoint the geographical distribution of its operational infrastructure.

In situations where specific information regarding the geographic distribution of all nodes is not readily available or cannot be precisely determined, a fallback mechanism is employed. Under these circumstances, reference networks are utilized. These reference networks are carefully selected based on their comparability to MultiversX in terms of their incentivization structure and their underlying consensus mechanism. By analyzing networks with similar operational characteristics, a proxy for renewable energy usage can be established.

Once node location data is acquired or estimated, this geo-information is subsequently merged with extensive public data provided by "Our World in Data." This integration allows for the correlation of energy consumption with regional energy mixes, enabling an assessment of the renewable energy penetration. The methodology further defines energy intensity as the marginal energy cost associated with processing one additional transaction on the network. This metric provides insight into the energy efficiency per unit of activity. The comprehensive dataset used for determining the share of electricity generated by renewables is sourced from reputable entities and is accessible via the following link: Share of electricity generated by renewables – Ember and Energy Institute. The data is compiled by Ember and the Energy Institute, with significant processing by Our World in Data, drawing from original data provided by Ember's Yearly Electricity Data and the Energy Institute's Statistical Review of World Energy.

The determination of energy sources for the Solana blockchain network involves a sophisticated geolocation mapping of the global node infrastructure. By utilizing internal and open-source crawlers, the physical locations of validator nodes are identified. Once the geographic distribution is established, this information is cross-referenced with regional energy data to calculate the percentage of renewable energy utilized by the network. For regions where specific node data is unavailable, researchers utilize reference networks that share similar consensus mechanisms and incentive structures as proxies to estimate the geographic spread of the infrastructure. The primary data source for these regional energy profiles is the Share of electricity generated by renewables dataset provided by Our World in Data, which incorporates research from Ember and the Energy Institute. This dataset provides yearly electricity data that allows for a granular assessment of how much of the network's power is derived from wind, solar, hydro, and other renewable sources. In addition to the total percentage of green energy, the methodology focuses on energy intensity, which is defined as the marginal energy cost required to process a single additional transaction on the network. This figure helps quantify the efficiency of the blockchain's resource usage relative to its utility. By integrating global energy statistics with real-time node distribution data, the network can report a more accurate picture of its sustainability, currently indicating that a significant portion of its operational energy comes from renewable sources, reflecting the broader global transition toward cleaner power grids.

Ta-Da is present on the following networks: Binance Smart Chain, Multiversx, Solana.

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 Greenhouse Gas (GHG) emissions within the MultiversX blockchain network closely mirrors the process for assessing energy sources, emphasizing a rigorous approach to geographical data and external data integration. The initial and paramount step involves precisely ascertaining the geographical locations of all operating nodes within the network. This critical locational data is compiled through a multi-faceted approach, leveraging public information sites, sophisticated open-source crawlers, and internally developed crawling software to systematically map the distribution of the network’s infrastructure.

Should there be instances where comprehensive geographic distribution data for all nodes is unavailable or cannot be definitively established, a robust contingency plan is put into action. In such cases, the assessment references other blockchain networks that exhibit similar characteristics, particularly concerning their incentivization frameworks and consensus mechanisms. By analyzing these comparable networks, an informed estimation of GHG emissions can be derived, providing a reliable proxy where direct data is limited.

Upon collecting or estimating the geographical information of the nodes, this data is then seamlessly integrated with extensive public datasets from "Our World in Data." This merging allows for the precise correlation of energy consumption patterns with the carbon intensity of electricity generation in those specific regions, thereby enabling the calculation of associated GHG emissions. The methodology quantifies GHG intensity as the marginal emission generated per additional transaction processed on the network, offering a detailed perspective on the environmental impact of network activity. The authoritative dataset for the carbon intensity of electricity generation is provided by Ember and the Energy Institute, with significant processing by Our World in Data, and is made available under a CC BY 4.0 license. This dataset can be accessed at: Carbon intensity of electricity generation – Ember and Energy Institute.

Quantifying the greenhouse gas (GHG) emissions of the Solana blockchain network requires a methodology focused on carbon intensity and the geographic footprint of its decentralized nodes. Similar to the energy source analysis, the process begins by locating active nodes using a combination of public data and specialized web crawling technology. This geographic information is critical because the carbon footprint of electricity varies significantly between different jurisdictions depending on their local power generation mix. For nodes that cannot be precisely located, the analysis uses data from comparable blockchain networks to ensure the estimation remains as complete as possible. The carbon intensity of the electricity used by these nodes is derived from the Carbon intensity of electricity generation dataset, accessible via Our World in Data. This dataset, which is licensed under CC BY 4.0, provides essential metrics on the amount of CO2 equivalent emitted per kilowatt-hour of electricity produced in various countries. By merging node locations with these carbon intensity values, the network can calculate its Scope 2 emissions, which represent the indirect emissions from the generation of purchased electricity. The methodology also focuses on GHG intensity, measuring the marginal emissions generated by one additional transaction on the blockchain. This allows for a performance-based assessment of the network's environmental impact. The results are typically reported in tonnes of CO2 equivalent (tCO2e), providing a standardized metric that allows for comparison with other industries and financial systems. This data-driven approach ensures that the network’s environmental disclosures are rooted in empirical global energy statistics and verifiable infrastructure data.