Through the Deployment Phase of the EGDC project, we are implementing the Net Carbon Methodology (NCM) across diverse sectors, working with companies, technology providers, and smart cities to measure and validate the net carbon impact of ICT solutions. This initiative not only refines our understanding of how digital technologies can reduce emissions but also builds a repository of actionable insights to drive sustainability forward. The Deployment Phase is designed to support organisations in assessing the climate impact of their deployed or planned ICT solutions. Whether you are a technology provider or an end-user, submitting your solution allows you to apply the EGDC Net Carbon Methodology and receive a comprehensive analysis of its net carbon impact in the implementation context which is deployed in. By participating, your organisation gains credible proof of impact, which can be leveraged for marketing, compliance, and stakeholder engagement.
The EGDC Net Carbon Methodology is increasingly recognised as a global standard for quantifying the avoided emissions of digital solutions. Aligned with frameworks such as the WBCSD Guidance on Avoided Emissions and ITU L.1480, our methodology ensures that your case study reflects internationally benchmarked practices.
By participating in the Deployment Phase, your organisation contributes to a collective effort to demonstrate the tangible benefits of digital solutions in reducing emissions. The insights generated from these case studies will be housed in a centralised repository, launching in 2026, and shared with global platforms to amplify their reach.
By participating in the Deployment Phase, your organisation contributes to a collective effort to demonstrate the tangible benefits of digital solutions in reducing emissions. The insights generated from these case studies will be housed in a centralised repository, launching in 2026, and shared with global platforms to amplify their reach.
Whether you are looking to validate your solution’s impact, gain competitive advantage, or align with sustainability goals, the EGDC case studies offer a unique opportunity to showcase your commitment to a greener future. Submitting a case study involves a structured and supported process. After completing a submission form, our team conducts a kick-off call to align on objectives and data requirements. We then handle analysis, and calculation – at no cost to your organisation delivering a custom case calculator, a detailed methodology document, and a one-page summary for easy dissemination. This process not only simplifies the assessment of your solution’s carbon footprint but also positions your organisation as a leader in sustainability, with opportunities for visibility on the EGDC platform, at events, and through international partnerships. Learn more about the process here.
The case studies consist of one Excel calculator and one methodology document providing additional context and transparency around the calculator. Both documents should be consulted to ensure the outcomes are interpreted and used correctly.
As cases are completed in Phase II, they will be uploaded here. As part of Phase II, a new more advanced repository is being built. It is expected to be ready and piloted later in 2026.
Discover the case studies by clicking on the sector icons below.
Opsis Research has developed an application and bike sharing solution to provide safe and accessible bicycles that can be unlocked, used, and relocked at various points around a given city. A pilot study was run in Botosani in Romania and data was collected using the application use as well as a questionnaire to residents. This involved utilising 15 bicycles provided by the municipality and 5 docking stations with Bluetooth locks to lock bikes between uses.
TCS’ Digital Platform for NextGen Agriculture (DNA) supports rice farmers in adopting Carbon-Smart Crop Protocols (CSCP) through a mobile app that records field operations and integrates weather, satellite, and soil data. The platform guides farmers in implementing climate-smart practices such as water-saving irrigation, precision fertiliser use, and organic soil treatments. Data collected and input by the farmers into the app feed into a process-based simulation model to estimate GHG emissions and soil carbon changes, while a machine-learning model analyses crop images to optimise farming practices, such as fertiliser application, reducing N₂O emissions without compromising, and often increasing, yield.
Colt’s Smart Building project, launched in 2023 in partnership with Nuuka, applies Artificial Intelligence and Machine Learning across the building’s HVAC system to optimise performance based on real-world usage. The solution is designed to dynamically adjust heating, cooling, and ventilation settings to minimise energy consumption while maintaining required indoor air quality standards. The initial case study focuses specifically on the ventilation component, as this was the first part of the overall HVAC solution to be implemented. Without such optimisation, HVAC systems are typically configured for maximum occupancy rather than actual demand, leading to unnecessary energy consumption and higher emissions.
Stockholmshem, one of Sweden’s largest municipal housing companies, launched a largescale project to optimise heating in 21,678 of its 29,000 apartments. This involved installing over 21,678 temperature sensors connected to an AI-based control system to reduce energy consumption and improve indoor climate comfort. The solution was implemented gradually between 2021 and 2024.