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Climate change vulnerability assessments are an essential instrument to identify regions most vulnerable to adverse impacts of climate change and to determine appropriate adaptation measures. Vulnerability assessments directly support countries in developing adaptation plans and in identifying possible measures to reduce adverse consequences of changing climate conditions. Against this background, this paper describes a vulnerability assessment using an integrated and participatory approach that builds on standardized working steps of previously developed &lsquo, Vulnerability Sourcebook&rsquo, guidelines. The backbone of this approach is impact chains as a conceptual model of cause&ndash, effect relationships as well as a structured selection of indicators according to the three main components of vulnerability, namely exposure, sensitivity and adaptive capacity. We illustrate our approach by reporting the results of a vulnerability assessment conducted in Burundi focusing on climate change impacts on water and soil resources. Our work covers two analysis scales: a national assessment with the aim to identify climate change &lsquo, hotspot regions&rsquo, through vulnerability mapping, and a local assessment aiming at identifying local-specific drivers of vulnerability and appropriate adaptation measures. Referring to this vulnerability assessment in Burundi, we discuss the potentials and constraints of the approach. We stress the need to involve stakeholders in every step of the assessment and to communicate limitations and uncertainties of the applied methods, indicators and maps in order to increase the comprehension of the approach and the acceptance of the results by different stakeholders. The study proved the practical usability of the approach at the national level by the selection of three particularly vulnerable areas. The results at a local scale supported the identification of adaption measures through intensive engagement of local rural populations.

The paper aims to explore the gaps and overlaps between statements of intergovernmental organizations (IGOs) working at the intersection of climate change, sustainable energy, and industrial development regarding the role of Industry 4.0 for climate change mitigation and the scientific literature addressing the energy and resource efficiency of Industry 4.0. To fulfill this objective, we conduct a two-tier review of relevant literature from both IGOs as well as academia. The analysis of documents from IGOs shows that Industry 4.0 is strongly associated with energy efficiency potentials that could contribute to climate change mitigation and more sustainable energy use in the industrial sector. Based on a review of the scientific literature, however, the paper concludes that it is currently not possible to validate this assumption and provide concrete figures since analyses providing a more comprehensive picture of potential energy savings, including possible negative effects and rebounds, are lacking. We suggest that these issues be addressed in further research, e.g., through concrete case studies that go beyond the assessment of single Industry 4.0 technologies. Furthermore, efforts should be strengthened to communicate findings from technology-centered research into political strategy-building and decision-making processes and, at the same time, raise awareness in the technological domain for the information needs of policymakers.

In 1957 , W.M. Hirsch conjectured that every (convex) d -polytope with n facets has edge-diameter at most n−d . Recently, Holt and Klee constructed polytopes which meet this bound for a number of pairs (d,n) with d⩽13 and for all pairs (d,n) with d⩾14 . These constructions involve a judicious use of truncation, wedging, and blending on polytopes which already meet the Hirsch bound. In this paper we extend these techniques to construct polytopes of edge-diameter n−d for all (d,n) with d⩾8 . The improvement from d=14 to d=8 follows from identifying circumstances in which the results for wedging when n>2d can be extended to the cases n⩽2d .