Economic implications of autonomous adaptation of firms and households in a resource-rich coastal city.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
21 Nov 2023
Historique:
received: 08 06 2023
accepted: 30 10 2023
medline: 22 11 2023
pubmed: 22 11 2023
entrez: 22 11 2023
Statut: epublish

Résumé

Climate change intensifies the likelihood of extreme flood events worldwide, amplifying the potential for compound flooding. This evolving scenario represents an escalating risk, emphasizing the urgent need for comprehensive climate change adaptation strategies across society. Vital to effective response are models that evaluate damages, costs, and benefits of adaptation strategies, encompassing non-linearities and feedback between anthropogenic and natural systems. While flood risk modeling has progressed, limitations endure, including inadequate stakeholder representation and indirect risks such as business interruption and diminished tax revenues. To address these gaps, we propose an innovative version of the Climate-economy Regional Agent-Based model that integrates a dynamic, rapidly expanding agglomeration economy populated by interacting households and firms with extreme flood events. Through this approach, feedback loops and cascading effects generated by flood shocks are delineated within a socio-economic system of boundedly-rational agents. By leveraging extensive behavioral data, our model incorporates a risk layering strategy encompassing bottom-up and top-down adaptation, spanning individual risk reduction to insurance. Calibrated to resemble a research-rich coastal megacity in China, our model demonstrates how synergistic adaptation actions at all levels effectively combat the mounting climate threat. Crucially, the integration of localized risk management with top-down approaches offers explicit avenues to address both direct and indirect risks, providing significant insights for constructing climate-resilient societies.

Identifiants

pubmed: 37990111
doi: 10.1038/s41598-023-46318-2
pii: 10.1038/s41598-023-46318-2
pmc: PMC10663627
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

20348

Subventions

Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 758014
Organisme : EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas " Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013))
ID : 758014
Organisme : EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas " Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013))
ID : 758014

Informations de copyright

© 2023. The Author(s).

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Auteurs

Alessandro Taberna (A)

Department of Multi Actor Systems, Delft University of Technology; Faculty of Technology, Policy and Management, Jaffalaan 5, 2628BX, Delft, The Netherlands. a.taberna@tudelft.nl.
International Institute for Applied Systems Analysis, Schlossplatz 1, 2361, Laxenburg, Austria. a.taberna@tudelft.nl.

Tatiana Filatova (T)

Department of Multi Actor Systems, Delft University of Technology; Faculty of Technology, Policy and Management, Jaffalaan 5, 2628BX, Delft, The Netherlands. t.filatova@tudelf.nl.

Stefan Hochrainer-Stigler (S)

International Institute for Applied Systems Analysis, Schlossplatz 1, 2361, Laxenburg, Austria.

Igor Nikolic (I)

Department of Multi Actor Systems, Delft University of Technology; Faculty of Technology, Policy and Management, Jaffalaan 5, 2628BX, Delft, The Netherlands.

Brayton Noll (B)

Department of Multi Actor Systems, Delft University of Technology; Faculty of Technology, Policy and Management, Jaffalaan 5, 2628BX, Delft, The Netherlands.

Classifications MeSH