Cities are responsible for more than 70% of global carbon dioxide emissions. Achieving the European Green Deal’s ambitions of net zero carbon emissions by 2050 requires rapid action to embed sustainability across European cities. However, this transition to climate neutrality will require a transformation in how these complex systems are designed and managed.
This transformation is the focus of the EU’s Cities Innovation Mission, which aims to deliver 100 climate-neutral and smart European cities by 2030, and to leverage these cities as innovation hubs that lead the way for all European cities to become climate neutral by 2050. In support of this ambition, the Mission is working to:
Across these areas for action, the Cities Mission identifies a role for AI in delivering smart city solutions that reduce carbon emissions and increase environmental sustainability across sectors including transport, buildings, water and waste management, and air quality. Examples of potential application areas include:
Inhabitants live in cities for different reasons and have diverse – often competing – requirements, which include employment opportunities, access to transport, energy, and waste services, environmental quality, and social inclusion and community. These requirements shape city planning and development, as decision-makers try to balance the needs of different communities alongside sustainability goals that might include reducing air pollution, reducing traffic, increasing the capacity of energy networks, or other services. Digital twin projects can help explore different scenarios for city planning, by simulating outcomes under different types of policy intervention.
By monitoring activity in buildings – through data generated by smart meters and other sensors – AI-enabled building management systems can predict patterns of demand and optimise energy use in support of sustainability goals. By providing information about the energy intensity of daily activities, AI could play a role in encouraging low-carbon behaviours by building users. By analysing building features and environmental conditions, AI systems also offer an opportunity to target retrofitting interventions to increase the energy efficiency of existing buildings.
Transport and services
City inhabitants rely on various utilities, including waste, water, and energy infrastructures, which are subject to increasing demand as populations increase and the effects of climate change are felt at a local level. AI can optimise the management of these services, increasing their efficiency and resilience. In transport, for example, AI can help develop traffic management systems that adapt to changing traffic flows, reducing emissions by decreasing the number of vehicles in traffic.
In developing digital twins to support urban planning, AI can contribute enhanced weather forecasting tools that support local administrations to adapt to the changing climate.