Quantifying co-benefits and disbenefits of Nature-based Solutions targeting Disaster Risk Reduction

Ommer, J., Bucchignani, E., Leo, L. S., Kalas, M., Vranić, S., Debele, S., Kumar, P., Cloke, H. L. ORCID: https://orcid.org/0000-0002-1472-868X and Di Sabatino, S. (2022) Quantifying co-benefits and disbenefits of Nature-based Solutions targeting Disaster Risk Reduction. International Journal of Disaster Risk Reduction, 75. 102966. ISSN 2212-4209 doi: 10.1016/j.ijdrr.2022.102966

Abstract/Summary

Nature-based Solutions function as an umbrella concept for ecosystem-based approaches that are an alternative to traditional engineering solutions for Disaster Risk Reduction. Their rising popularity is explained partly by their entailing additional benefits (so called co-benefits) for the environment, society, and economy. The few existing frameworks for assessing co-benefits are lacking guidance on co-benefit pre-assessment that is required for the NBS selection and permission process. Going beyond these, this paper develops a comprehensive guidance on quantitative pre-assessment of potential co-benefits and disbenefits of NBS tackling Disaster Risk Reduction. It is based on methods and frameworks from existing literature around NBS and related disciplines. Furthermore, this paper discusses the evaluation of the quantified results of the pre-assessment. In particular, the evaluation focuses on the significance of change of the estimated co-benefits and disbenefits as well as the sustainability of the NBS. This paper will support decision-making in planning processes on suitability and sustainability of Nature-based Solutions and assist in the preparation of Environmental Impact Assessments of projects.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/104747
Identification Number/DOI	10.1016/j.ijdrr.2022.102966
Refereed	Yes
Divisions	Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Elsevier
Download/View statistics	View download statistics for this item