Climate mitigation and adaptation strategies tailored for different types of European cities: a typology and associated systematic review

This study provides a more systematic comparative analysis of urban climate change mitigation and adaptation by establishing city types using available big data and machine learning. The current review points to the need for a shift from the narrow focus on constrained simulation-based modelling of technological options towards more systematic collection and disclosure of real-world data and rigorous implementation designs of climate interventions that allow for the evaluation of uptake and impact in an experimental or quasi-experimental design.

Based on harmonised data for all 1263 cities in Europe, the authors identify sectoral and climate impact hotspots requiring concerted climate action across the four city types. These include reducing building- and transport-related greenhouse gas emissions in Metropolises and Established cities, heat and drought risk in Growing cities, and flood risk in Shrinking cities. Drawing on the existing case study literature comprising 1613 climate action assessments, the authors provide context-specific recommendations for addressing these climate hotspots and unlocking co-benefits by overcoming reported implementation challenges such as limited finance, local governance capacity, behavioural inertia and distributional conflicts. In this regard, longitudinal geospatial data and deeper municipality-university collaborations are still underexplored sources to assess environmental impacts of realised adaptation and mitigation projects, pointing towards the need to move from hypothetical case scenarios to actual implementation. Cities that engage in structured co-learning and advanced science-policy-practice partnerships may be better positioned to intensify their ambition in climate action. The proposed approach could inspire city networks into creating task forces and systematic, evidence-based ecosystems for deep learning, going beyond knowledge sharing and one-way mentoring.