Artificial intelligence opens new horizons in reducing carbon emissions from cities to energy systems

Reducing carbon emissions requires a wide range of innovative solutions, from city-wide planning to the digital transformation of energy systems. A new tool developed by researchers at the University of Notre Dame in the US and the European Commission's AI-driven energy systems report reveal concrete and promising steps being taken in this area.

Researchers at the University of Notre Dame have developed a digital platform called "EcoSphere" that helps reduce urban carbon emissions by analyzing them on a building-by-building basis. This AI-powered tool allows city managers, architects, and policymakers to comprehensively assess the emissions generated by buildings throughout their lifecycle. EcoSphere combines satellite imagery, Google Street View data, and machine learning models to present each building's current condition, potential energy efficiency improvements, and the environmental impact of renovation scenarios in a user-friendly interface.

Researchers tested the tool in major cities like Chicago and Indianapolis. The results are striking: Renovating existing structures instead of building new reduces carbon emissions by thousands of times. This approach also stands out as a more cost-effective solution, allowing cities to make strategic decisions that can achieve greater carbon reductions with limited resources.

Meanwhile, a new report published by the European Commission in July 2025 focuses on the role of AI in the digital transformation of Europe's energy systems. The report emphasizes that AI can make significant contributions in areas such as the integration of renewable energy sources, energy consumption forecasting, grid stability, and balancing supply and demand.

"Digital twin" technology, in particular, holds great potential for real-time modeling of energy infrastructures and predicting maintenance needs. The report also notes that AI solutions developed for local energy communities align with the goal of creating a more participatory and resilient energy system by transforming energy consumers into producers.

It is emphasized that for this transformation to occur, the data infrastructure that will enable the development and dissemination of artificial intelligence models must be strengthened. Common data standards, secure sharing protocols, and high-performance computing infrastructures are among the fundamental building blocks of this process. Furthermore, transparency and accessibility principles that will facilitate active consumer participation in the system are also highlighted.

The EcoSphere tool developed by the University of Notre Dame and the European Commission's vision report stand out as two important, complementary initiatives. The first aims to reduce building-based emissions at the urban level, while the other addresses the holistic transformation of energy systems at a larger scale. The common denominator is the potential of AI technology to provide decision-makers with scientific, data-based, and human-based solutions.