Climate risk and adaptation assessments generally estimate aggregate damages, avoided impacts, or cost-effectiveness. Yet aggregate metrics mask who is exposed, who can adapt, who benefits from adaptation investments, and who bears residual, transferred, or cascading risk. This session asks how conclusions about climate risk and adaptation change when distributional outcomes, adaptive capacity and adaptation limits become explicit components of assessment and decision-making.

We invite quantitative, data-driven and mixed-method contributions representing inequality throughout the assessment chain, from hazard, exposure and vulnerability to impacts, adaptation appraisal and decision-making. Of particular interest are studies moving beyond generic exposure and vulnerability to capture differentiated and dynamic adaptive capacity linked to income, wealth, access to services and infrastructure, housing tenure, mobility, informality and demography.

A central focus is the operationalisation of equity and justice as measurable outcomes. This includes inequality in baseline climate risk (e.g. via revised exposure and vulnerability functions), the distribution of adaptation costs and benefits, inequalities created or exacerbated by adaptation itself, and limits to adaptation. We welcome work that stratifies impacts and avoided losses across population groups, embeds equity metrics in cost-benefit and multi-criteria assessment, examines non-monetised losses, or tests whether conventional welfare and efficiency metrics underrepresent particular populations. Contributions on adaptation-induced inequalities, including displacement, green gentrification, unequal infrastructure protection, and the exclusion of underreported populations, are especially welcome.

The session spans hazards, sectors and scales, including urban systems, critical infrastructure, health, accessibility, macroeconomic impacts, and loss and damage. We particularly encourage assessments of direct, indirect and cascading risks, asking who inherits risk when adaptation protects particular places, infrastructures or groups while shifting impacts elsewhere. We also welcome methodological work on data challenges in distributional risk assessment, including high-resolution socioeconomic data, Earth observation, mobility and geospatial data, citizen science, and alternative sources complementing conventional statistics.