From hazard and exposure through to impacts, adaptation responses and their evaluation, with extreme heat and cities as the main empirical domain.
This theme follows the full gradient from climate hazard to adaptation outcome. It quantifies exposure to hazards at high spatial and temporal resolution (with a focus on heat and humid heat), estimates their consequences for health, mortality, labour productivity, economic activity and public budgets using quasi-experimental and machine learning methods coupled with downscaled climate ensembles, and then evaluates the responses available to households, cities and governments: cooling access, urban greening and shading, building interventions, early warning systems, cooling shelters and behavioural adjustment. Recurring questions concern how adaptation options interact (their synergies, trade-offs and limits), how effectiveness is unevenly distributed across social groups, and how uncertainty should be propagated and communicated in risk assessments intended for policy. Systemic cooling poverty sits within this theme. Work is carried out through the development of URBADAPT-HEAT, an open framework for city-scale assessment of heat adaptation pathways, the URGED project (IIASA Innovative and Bridging Grant, 2024), the Interreg Euro-MED project HEATSAFE, the participation in the Horizon Europe projects ACCREU, ADELE, CASCADEX and Adapt4EU on European climate risk assessment.
Access to infrastructure and public services as a determinant of who is able to adapt, and what that implies for planning, spending and equity.
Adaptive capacity is mediated by physical and social infrastructure: electricity supply and its reliability, water services, transport, health facilities, housing, and green and blue space. This theme measures the coverage, quality and reliability of these systems, including through satellite-based detection of electricity service interruptions and geospatial mapping of access to critical facilities and to urban green space. It then asks how public provision substitutes for or complements private adaptation, examining how public budgets are actually allocated to climate-relevant spending (with ongoing work on the climate expenditure of Italian and European municipalities) and how the resulting distribution of protection compares with the distribution of need. A third component develops planning and prioritisation approaches that make distributional consequences explicit rather than incidental, so that justice considerations enter the assessment rather than the discussion. An emerging line of work examines the interface between public infrastructure provision and individual climate adaptation decisions.
Interactions across energy, water and food systems, and how climate change reshapes demand, access, security and transition pathways.
Where the previous theme looks at infrastructure provision and its distribution, this one takes a systems perspective on the resources that flow through it. It covers climate-driven changes in energy demand (notably space cooling), the water-energy-food interactions that shape agricultural and irrigation outcomes, energy access and its productive uses in low-income settings, and the implications of all of these for energy system security, planning and decarbonisation pathways. Methods span techno-economic and integrated assessment modelling, geospatial electrification and irrigation planning, applied econometrics and scenario analysis, with applications in Europe, the Mediterranean, Central Asia and sub-Saharan Africa. Recent work includes the coordination of modelling activities in RE4AFAGRI, part of the EU-African Union LEAP-RE partnership on renewables for African agriculture, research on groundwater irrigation and energy access in sub-Saharan Africa.
Spatially granular data, Earth observation and reproducible tooling underpinning all three themes.
Across these areas I work with gridded climate and urban climate model output, satellite and remote sensing products (nighttime lights, vegetation indices, thermal indices), household surveys and administrative microdata, combined through spatial statistics, causal inference and machine learning.