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Knowledge-based and innovative bioeconomy is a cornerstone for achieving the goals of the European Green Deal. Due to its comprehensive coverage, bioeconomy performance is challenging to assess unambiguously. This paper presents the results of a cross-country comparison of 22 EU countries applying the Complex Bioeconomy Sustainability Index for 2012–2018. Results were compared with results of the TOPSIS multi-criteria decision-making method on national bioeconomy strategies in Finland, France, Spain, Italy, Ireland, and Latvia. The research aims to combine a quantitative assessment of bioeconomy output indicators with a qualitative evaluation of bioeconomy strategies of EU Member States. [ABSTRACT FROM AUTHOR]

Coastal environment with high interaction between nature and societies is subject to multi-hazard interaction such as landslides, flood or cliff retreat. These territories are characterized by numerous elements at risk located in valley bottoms, front sea or at the outlets of small dry watershed. The aim is to quantify the potential consequences of EaR by integrating multiple hazards exposure at various scale analyses. To quantify the element at risk, three steps have been required. First, an initial rank has been attributed to each class of element at risk at three different scales analysis. Second, the potential consequences are weighted according to environmental dimension. Third, the consequences are combined with a linear combination of criteria in GIS environment. At medium-scale analysis, element at risk highlighted is built-up areas, national road, railway, lifeline and urban centers. At large-scale analysis, consequences concern any kind of house, apartment and complex located on multiple exposure areas. At local scale, consequences concern buildings located on multiple exposure areas with one floor in mixed materials and built after 1980. Thus, this method proposes an approach with multiple scales analysis and by integrating multiple exposure areas to quantify potential consequences. With the environmental dimension in element at risk analysis, it is an intermediate step to traditional risk analysis and, more specifically multirisk analysis without considering in this case the spatial and temporal dimension of hazards. [ABSTRACT FROM AUTHOR]

The end of iron-mining operations in France''s Lorraine region has raised the problem of post-mining management. Collapses and subsidence have recently occurred in this region, which focused on the necessity to develop a specific methodology for risk zoning. The proposed methodology is based on the multi-criteria decision-aid approach called ‘ELECTRE TRI’, with aim to assign zones at risk into predefined classes. It allows experts opinions, qualitative and quantitative criteria and uncertainties to be taken into account. [Copyright &y& Elsevier]

In risk analyses, two components are taken into account: (1) hazard analysis, including susceptibility and temporal occurrence, and (2) consequence analysis, including characterization of elements at risk (EaRs) and their vulnerability. This study focused on characterization of EaRs, in which items are spatially displayed and impacted by natural events. Several methods can assess these EaRs through expert or engineering approaches. Among the expert approaches, the multicriteria method is more flexible and allows integration of a wide range of information in order to characterize and discretize different EaRs. Traditionally, the mapping and criteria accuracy of EaRs is the same at all spatial analysis scales, while the hazard accuracy changes according to the spatial scales. Therefore, we propose an approach based on the selection of different information/criteria among several private or open access multiple geographical databases to adapt the mapping and criteria accuracy of each EaR according to the hazard analysis spatial scale. After harmonizing the different databases and merging them under GIS, a single database per work scale is created through a specific procedure with interoperability of results between scales. Thus, the number of criteria used to describe these EaRs will depend on the scale of work and the spatial scale of the analysis. To develop and test the transposability of this method, three experimental coastal study sites subject to several hazards (multirisk) have been selected in Normandy (France) with error estimations ranging between 10% and 20%. Subsequently, these data can be integrated into risk and multirisk analyses. • We propose a methodology to characterize the Elements at Risk in multirisk coastal context with multi-criteria approach. • Three spatial scale analyses are used in this method: at medium scale, secondly at large scale and at local scale. • Two integration models are proposed to merge multiple databases in two final data warehouses. • The uncertainties about accuracy of these models are less than 10 % for medium scale and around 15 % at large scale. [ABSTRACT FROM AUTHOR]