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Case study n° 3: Economic effects of adapting critical infrastructure in the Mannheim metropolitan area (D4.2.3, factsheet in German with an English summary)

descriptionPublicationkeyboard_double_arrow_right Article 07 Feb 2023Publisher:ZenodoFunded by:EC | AXIS

Authors: Rome, Erich; Milde, Katharina; Lückerath, Daniel;

doi: 10.5281/zenodo.7635875 , 10.5281/zenodo.7635874

Case study n° 3: Economic effects of adapting critical infrastructure in the Mannheim metropolitan area (D4.2.3, factsheet in German with an English summary)

- Summary
- Subjects
- Metrics

Abstract

The case study focuses on economic effects of adapting critical infrastructure in the Mannheim metropolitan area. The case applied Impact Chain (IC) based Climate Risks and Vulnerability Assessment (CRVA) approach on a regional level. It starts from national Impact Chains and uses the regional results for further climate risk assessment for a single industrial stakeholder. This factsheet presents an evaluation of the outcome for key research innovation areas Impact Chain Modelling and co-production of knowledge.

Related Organizations

Fraunhofer Institute for Intelligent Analysis and Information Systems
Germany
Fraunhofer Society
Germany

Keywords

Critical Infrastructure, Impact Chain based Climate Vulnerability and Risk Analysis, Case study, Climate change adaptation

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average