📋 Tender Overview
Cross-Sectoral Framework For Socio-Economic Resilience To Climate Change And Extreme Events In Europe
Funded Under
Climate, Energy And Mobility
Total Cost
€ 3 444 625,00
Eu Contribution
€ 3 444 624,00
Coordinated By
Administratia Nationala De Meteorologie R.A.
Romania
Objective
The project CROSSEU aims to respond to the increasing societal needs to reduce climate-damaging actions, adapt to the expected consequences and increase socio-economic resilience. The project aims is to deliver a climate-sensitive framework, including a ready-to-use decision support system platform and technical recommendations, to inform investment decisions, cost-effective adaptation and mitigation options and policy response to climate change. The project will contribute to advancing the understanding of the socio-economic risks and response options associated with climate change impact in Europe in different timeframes, including the post-COVID19 societal-environmental transformation, and derive practical recommendations for political and societal action. The solutions proposed are based on an extensive assessment of the socio-economic risks of climate change in a cross-sectoral hierarchical approach, based on storylines addressing key categories of climate hazards in different socio-economic sectors and climate change-sensitive areas across countries and European regions. The project will offer a ready-to-use solution that integrates complex information from available climate risk data sets and non-climatic sectoral data collected during the project implementation and derived through modelling based on demand-driven climate-socio-economic pathways. CROSSEU is designed to bridge the science-based information about the economic impacts of climate change and the unique contributions of the project will be (i) the quantification of costs of existent and emergent socio-economic risks and opportunities at NUTS3 level, (ii) an improved representation of adaptation within biogeophysical climate change risk and (iii) a better consideration of modelling uncertainties by identifying their nature, assessing their characteristics in a systematic way to determine a better informed and robust decision-making.
