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Climate change will impact many economic sectors and aspects of natural and human wellbeing. Quantifying these impacts as they vary across regions, sectors, time, and social and climatological scenarios supports detailed planning, policy, and risk management. This article summarises and compares recent climate impact assessments in Europe (the JRC PESETA III project) and the USA (the American Climate Prospectus project). Both implement a multi-sector perspective combining high resolution climate data with sectoral impact and economic models. The assessments differ in their coverage of sectors and scenarios, mix of empirical and process-based methods, handling of uncertainty, and representation of damages. Despite the dissimilarities, projected relative economic impacts are comparable, with human mortality as the dominant impact category. Both studies further show a large spatial heterogeneity of impacts that may amplify pre-existing economic inequality in the EU and US, and that mitigation can considerably reduce economic impacts. The comparison highlights the various decision-points involved in interdisciplinary climate impact modelling and lessons learnt in both projects, on the basis of which we provide recommendations for further research.

Quantitative estimates of the economic damages of climate change usually are based on aggregate relationships linking average temperature change to loss in gross domestic product (GDP). However, there is a clear need for further detail in the regional and sectoral dimensions of impact assessments to design and prioritize adaptation strategies. New developments in regional climate modeling and physical-impact modeling in Europe allow a better exploration of those dimensions. This article quantifies the potential consequences of climate change in Europe in four market impact categories (agriculture, river floods, coastal areas, and tourism) and one nonmarket impact (human health). The methodology integrates a set of coherent, high-resolution climate change projections and physical models into an economic modeling framework. We find that if the climate of the 2080s were to occur today, the annual loss in household welfare in the European Union (EU) resulting from the four market impacts would range between 0.2–1%. If the welfare loss is assumed to be constant over time, climate change may halve the EU's annual welfare growth. Scenarios with warmer temperatures and a higher rise in sea level result in more severe economic damage. However, the results show that there are large variations across European regions. Southern Europe, the British Isles, and Central Europe North appear most sensitive to climate change. Northern Europe, on the other hand, is the only region with net economic benefits, driven mainly by the positive effects on agriculture. Coastal systems, agriculture, and river flooding are the most important of the four market impacts assessed.

Quantitative estimates of the economic damages of climate change usually are based on aggregate relationships linking average temperature change to loss in gross domestic product (GDP). However, there is a clear need for further detail in the regional and sectoral dimensions of impact assessments to design and prioritize adaptation strategies. New developments in regional climate modeling and physical-impact modeling in Europe allow a better exploration of those dimensions. This article quantifies the potential consequences of climate change in Europe in four market impact categories (agriculture, river floods, coastal areas, and tourism) and one nonmarket impact (human health). The methodology integrates a set of coherent, high-resolution climate change projections and physical models into an economic modeling framework. We find that if the climate of the 2080s were to occur today, the annual loss in household welfare in the European Union (EU) resulting from the four market impacts would range between 0.2–1%. If the welfare loss is assumed to be constant over time, climate change may halve the EU's annual welfare growth. Scenarios with warmer temperatures and a higher rise in sea level result in more severe economic damage. However, the results show that there are large variations across European regions. Southern Europe, the British Isles, and Central Europe North appear most sensitive to climate change. Northern Europe, on the other hand, is the only region with net economic benefits, driven mainly by the positive effects on agriculture. Coastal systems, agriculture, and river flooding are the most important of the four market impacts assessed.

In its third edition, the EU Blue Economy Report continues to analyse the scope and size of the Blue Economy in the European Union. It aims at providing support to policymakers and stakeholders in the quest for a sustainable development of oceans, coastal resources and, most notably, to the development and implemen-tation of polices and initiatives under the European Green Deal in line with the new approach for a sustainable Blue Economy. For the purposes of the Report, the Blue Economy includes all those activities that are marine-based or marine-related. Therefore, the Report examines not only established sectors (i.e. those that traditionally contribute to the Blue Economy) but also emerging (those for which reliable data are still developing) and innovative sectors, which bring new opportunities for investment and hold huge potential for the future development of coastal communities. Analyses are provided for the EU as a whole and by sector and industry for each Member State. The European Green Deal and the European Strategy for data will necessitate reliable, accurate and centralised data for its initiatives. This Report intends to serve as a useful input to assessing the potential of oceans and coasts for shifting to more sustainable economy and to supporting the development of policies in line with the strategic approach for a sustainable blue economy at all levels of governance. The third edition of the Report seeks to include new elements, which have an impact on the Blue Economy, including challenges like climate change, new sectors such as Submarine cables), enablers such as Maritime Spatial Planning, new areas of analysis such as Ecosystem Services or potential solutions like Multi-purpose platforms. The Blue Economy established sectors include the follow-ing seven sectors: Marine living resources, Marine non-living resources, Marine Renewable energy, Port activities, Shipbuilding and repair, Maritime transport and Coastal tourism. The analysis of these sectors is based on the data collected by the European Commission through Member States and the European Statistical System. Fisheries and aquaculture data were collected under the EU Data Collection Framework (DCF). Analyses for all other established sectors are based on Eurostat data from Structural Business Statistics (SBS), PRODCOM, National Accounts and tour-ism statistics.

Epidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations that offer limited spatial and temporal coverage. Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, and yet are to be systematically explored for their suitability in assessing temperature-related health risks at a global scale. Here we provide the first comprehensive analysis over multiple regions to assess the suitability of the most recent generation of reanalysis datasets for health impact assessments and evaluate their comparative performance against traditional station-based data. Our findings show that reanalysis temperature from the last ERA5 products generally compare well to station observations, with similar non-optimal temperature-related risk estimates. However, the analysis offers some indication of lower performance in tropical regions, with a likely underestimation of heat-related excess mortality. Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk. ; The study was primarily supported by Grants from the European Commission's Joint Research Centre Seville (Research Contract ID: JRC/SVQ/2020/MVP/1654), Medical Research Council-UK (Grant ID: MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), European Union's Horizon 2020 Project Exhaustion (Grant ID: 820655). The following individual Grants also supported this work: J.K and A.U were supported by the Czech Science Foundation, project 20-28560S. A.T was supported by MCIN/AEI/10.13039/501100011033, Grant CEX2018-000794-S. V.H was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant agreement No 101032087. This work was generated using Copernicus Climate Change Service (C3S) information [1985–2019]. ; Peer reviewed