Sustainability

Explore the environmental footprint of the IOTA network

Driving sustainability forward by creating a greener, more energy-efficient decentralized blockchain infrastructure to build and secure our digital world

Energy efficiency by design

IOTA’s lightweight protocol architecture consumes significantly less energy than traditional blockchains – enabling more responsible digital infrastructure at scale.
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Comparison of Electricity Consumption

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Sustainability Indicators

ESMA's Final RTS provides a set of required and voluntary sustainability indicators.¹

MiCA (Markets in Crypto-Asset) Regulation defines roles and responsibilities for entities in the crypto ecosystem. Among other requirements, CASPs (Crypto-Asset Service Providers) and Crypto-Asset Issuers are required to disclose the sustainability metrics of the currencies they offer. If you are a CASP, CCRI may help you by providing respective data for your website or in your application.

Glossary

Disclaimer

² We derive the values of the electricity sources of relevant countries and calculate a renewable energy share. Considering node locations and node counts, we are able to derive the total renewable energy consumption of the network. (Comparison: US, 20.7 %. Germany, 41.2 %.)

CCRI is a leading data provider for cryptocurrency sustainability metrics. CCRI evaluates the sustainability metrics of the IOTA Ecosystem since 2024 and deploys industry-leading measurement methodologies for its metrics generation. In the context of the Markets in Crypto-Asset (MiCA) Regulation, sustainability data gain increasingly importance.
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Collected Data Points

Hardware Assessment

CCRI gathers data on the hardware requirements for the IOTA Ecosystem

Hardware Measurement

CCRI maintains a state-of-the-art, temperature-controlled lab in Munich that houses a variety of hardware configurations. Depending on the hardware needs, node software is set up on the devices and monitored for their electricity usage over a full day.

Transaction Impact Analysis

CCRI monitors, alongside the power demand of an individual node, the transaction throughput of the node, building a model that allows to account for the increased electricity consumption due to larger transaction throughputs.

Network Energy Analysis

CCRI then uses an average best-guess electricity consumption and transaction throughput to calculate the total network electricity consumption by multiplying with the number of validators in the network.

Carbon Impact Estimation

By pinpointing node locations, CCRI generates a network-specific carbon intensity profile. The carbon intensity is then used to calculate the total carbon footprint of the network

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