Review article: Insuring the green economy against natural hazards – charting research frontiers in vulnerability assessment

<p>The insurance of green economy assets against natural hazards is a growing market. This study explores whether currently available published knowledge is adequate for the vulnerability assessment of these assets to natural hazards. A matrix is constructed to demonstrate the vulnerability to...

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Bibliographic Details
Main Authors: H. Baskaran, I. Ioannou, T. Rossetto, J. Cels, M. Joffrain, N. Mortegoutte, A. Fallon Saint-Lo, C. Spataru
Format: Article
Language:English
Published: Copernicus Publications 2025-01-01
Series:Natural Hazards and Earth System Sciences
Online Access:https://nhess.copernicus.org/articles/25/49/2025/nhess-25-49-2025.pdf
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Summary:<p>The insurance of green economy assets against natural hazards is a growing market. This study explores whether currently available published knowledge is adequate for the vulnerability assessment of these assets to natural hazards. A matrix is constructed to demonstrate the vulnerability to functional loss of 37 asset classes in the renewable energy, green construction, resource management, carbon capture and storage, energy storage, and sustainable transportation sectors. The 28 hazards adopted range from environmental and geophysical events to oceanic, coastal, and space weather events. A fundamental challenge in constructing the matrix was the lack of an asset–hazard taxonomy for the green economy. Each matrix cell represents the vulnerability of an asset to a specific hazard, based on a comprehensive systematic literature review. A confidence level is assigned to each vulnerability assessment based on a literature density heat map. The latter highlights specific knowledge gaps, in particular a lack of quantitative vulnerability studies that appropriately represent all functional loss mechanisms in green economy assets. Apart from charting research gaps, a main output of this study is the proposal of a representative asset–hazard taxonomy to guide future quantitative research that can be applied by the insurance industry.</p>
ISSN:1561-8633
1684-9981