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Evaluating Nature-Based Solutions Impacts: A Preliminary Framing of Assessment Methods

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Computational Science and Its Applications – ICCSA 2023 Workshops (ICCSA 2023)

Abstract

Nature-based Solutions (NBS) are increasingly promoted to support resilient urban planning. However, integrating NBS into traditional urban planning requires knowledge about the NBS impacts within the environmental, economic, and social spheres. The objective of this paper is to contribute to this knowledge, by systematically identifying assessment methods ‘both qualitative and quantitative’ for NBS impacts evaluation. This literature review is not fully comprehensive, whereas this study represents a first attempt and aims at guiding future research in this field. The literature review is developed according to a threefold approach that represents the sustainability paradigm, i.e., environmental compatibility, economic development, and social equality. From the literature review imbalances are detected between the environmental, economic, and social spheres.

This contribution is addressed to public and private bodies dealing with NBS, regarding urban practitioners addressing a comprehensive NBS impacts assessment within urban and territorial transformations.

The results of this literature review underline criticalities in dealing with NBS issues comprehensively.

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Acknowledgement

Giulia Datola carried out this research within the Agritech National Research Center and received funding from the European Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR) – MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4 – D.D. 1032 17/06/2022, CN00000022).

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Assumma, V., Datola, G., Quagliolo, C., Oppio, A. (2023). Evaluating Nature-Based Solutions Impacts: A Preliminary Framing of Assessment Methods. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14108. Springer, Cham. https://doi.org/10.1007/978-3-031-37117-2_35

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  • DOI: https://doi.org/10.1007/978-3-031-37117-2_35

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