Key messages
- Critical infrastructure is threatened by more frequent and intense climate hazards. Potential cascade effects through interconnected systems are a significant risk.
- Artificial intelligence (AI) has the potential to make infrastructure and nature based solutions more robust, efficient and better adapted to climate impacts.
Critical infrastructure includes assets, networks and systems that are needed for the provision of essential services. When it is damaged, even briefly, the provision of electricity, natural gas, food, drinking water, as well as waste collection and treatment, telecommunication networks and healthcare services, can be disrupted. Escalating challenges posed by climate change – in particular, extreme weather events that are becoming more frequent and severe – are testing the resilience of critical infrastructure. Vital social and economic functions are on the line.
Climate hazards can involve single, compound or coincident extreme weather events, and their impacts can cascade through interconnected systems. Interdependencies between critical systems such as electricity distribution and healthcare, or food supply and transport, can intensify vulnerabilities, causing a domino effect where one failure spreads and disrupts other systems. Assessing vulnerabilities to climate change requires consideration of location-specific conditions, socio-economic trends and legacy factors, as each will affect how systems respond to climate impacts. Tailored strategies are needed for robust resilience and adaptation mechanisms.
There are a range of proposed solutions to the energy sector’s vulnerability to climate-related hazards. Sometimes, highly targeted interventions can substantially increase the resilience of a network. For example, the identification and protection of critical power lines representing just 1% of the network in Texas’s power grid significantly reduced hurricane-induced power outages by a factor of 5 to 20. On the other hand, smart grids powered by artificial intelligence (AI), machine learning (ML) and predictive analysis can raise overall resilience across energy infrastructure. AI/ML tools can assist monitoring grid operations and responding to disruptions in a timely manner. They can also support predictive maintenance and cybersecurity algorithms and forecast the production of renewable energy levels, while also ensuring reliable energy supply in a dynamic environment. Similar tools could enhance resilience in other critical infrastructure systems such as water management, transportation and telecommunications.
Climate adaptation in urban areas is closely linked to enhancing the resilience of critical infrastructure. For example, denser urbanisation can increase the urban heat island effect, leading to greater demands for cooling and higher strain on energy grids, increasing the challenge of energy transition. When populations grow, so does economic activity and resource concentration in urban areas, which require resilient infrastructure. Addressing bottlenecks and threats in supply chains for electricity, food, fresh water and more is essential, as populations in urban areas are expected to double by 2050 compared to 2023, with more than one billion people predicted to live in informal settlements, particularly in the global South, that are especially vulnerable and high risk. Detailed assessments of climate risks and vulnerabilities are thus needed to help prepare for extreme climate events, in particular for underserved and marginalised communities. Nature-based solutions that could potentially mitigate the anticipated climate impacts are also an area of increasing focus, including urban green infrastructure such as vegetation and soil cover for reducing local temperatures and mitigating flood risk, providing social and ecological benefits.
Policy implications
- Initiatives like the Global Methodology for Infrastructure Resilience Reviews launched at COP28 by the United Nations Office for Disaster Risk Reduction (UNDRR) and the Coalition for Disaster Resilient Infrastructure (CDRI) evidence the growing urgency and importance of climate risk assessment for critical infrastructure at the national level. This is the first global methodology providing a holistic approach to infrastructure systems resilience. It supports countries in assessing their current state and identifying areas for improvement.
- Relatedly, this Insight underscores the importance of the Early Warnings for All Initiative, co-led by the UN Office for UNDRR and WMO, aiming for full global coverage by 2027.
- Additional specific considerations for the resilience of critical infrastructure in the energy sector:
- The trend of increasing electrification will create strong interdependencies with other critical infrastructure systems. Hence, investing in the resilience of electricity networks to better withstand climate-related issues will safeguard other interconnected infrastructures.
- Increase dispersed energy networks, such as microgrids, while considering combining with renewables and compatibility with other sectors, to increase equity, resilience, and access to clean energy, support sustainable development and reduce high interconnectedness vulnerabilities.
- Improve guidelines for planning, designing and governance for local sustainable infrastructure construction, including integrated microgrids and linked social/physical infrastructures to enable efficient energy distribution and increased equity, and to manage risks in vulnerable communities during emergencies.
