Improving the climate resilience of European cities via socially acceptable nature-based solutions

A dynamic and adaptive social acceptance framework that shows how data-driven science can inform the integration of NBS into cities while also ensuring that the public embraces these solutions.
Published in Social Sciences
Improving the climate resilience of European cities via socially acceptable nature-based solutions

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The primary motivation behind this paper is the observed energy and environmental policy failures due to the lack of public support. Once a policy intervention is implemented, we have noticed that the attempted targets may not be achieved smoothly due to social, economic, technical, and environmental barriers. The recent conflicts, particularly those associated with selecting appropriate energy technologies, have underscored the importance of human interactions with environmental systems. Regarding nature-based solutions (NBS) or other sustainability improvements, social acceptance is one of these critical dimensions imperative in planning and implementing policy interventions. However, social acceptance has traditionally been considered solely in the last stage of planning processes, which prevents the incorporation of findings from acceptance studies into policy design and planning procedures. In exploiting social acceptance for a smooth implementation of NBS, developing a generalizable and comparable approach was challenging for several reasons. First, the implementation process of NBS involves interventions embedded in highly complex socio-ecological systems with uncertain responses. Second, the implementation happens over a long time. Third, planning and implementation often involve collaboration among stakeholders with diverse backgrounds and perspectives on solutions. Finally, existing studies on social acceptance are fragmented and cross-disciplinary, making it difficult to compare the acceptance of different cases directly.

The research process

Social acceptance must be quantified like economic, technical, and environmental criteria to be included in multicriteria decision-making processes. However, identifying and quantifying its main determinants is difficult because social acceptance cannot be directly observed. Even though it can be considered a latent factor inferred from measurable or observable items, studies exploring the antecedents of social acceptance employ various methodologies. Comparing or aggregating acceptance data from different methods is not meaningful. We realized that comparable measures of social acceptance require integrating complex, dynamic, adaptive, and multidisciplinary approaches. The approach developed in this study, as a part of the Nature4Cities Horizon 2020 project, provides a common theoretical background that allows for more meaningful comparisons.

Numerous studies in the policy literature have provided useful conceptualizations of social acceptance with a lack of consensus on the definition of the term. We refer to Wüstenhagen et al. to establish the scope of interest. They define three dimensions of social acceptance: socio-political, community, and market acceptance. From a methodological standpoint, each social acceptance dimension determines the population from which a research sample will be drawn. Per the NBS, acceptance can be measured on all three dimensions. Yet, as clarified further in the paper, the four NBS cases under consideration have either been fully implemented or are in the implementation process. Hence, the local and regional planners have already accepted the projects, and that community acceptance is the most relevant dimension in the context of NBS considered in the research. Using these definitions, inspired by Huijts’ works, we based our theoretical framework on three theories of psychology: the theory of planned behavior, theories of affect, and the norm activation theory. Each one of these theories taps into important factors of social acceptance. The suggested factors are combined in Fig.1. This is a modified version of the Huijts et al.  

After the definitions and the theoretical foundation, we needed a framework providing common theoretical and methodological underpinnings to determine antecedent factors driving acceptability and enabling comparability. Increased emphasis on policy-relevant evidence over the recent decades has motivated the need for comparative, replicable, credible, and reliable research to signify policy development with rational decision-making. A framework that enables replication and comparison across NBSs will be valuable for evidence-based decision-making approaches. Comparability must be ensured via process standardization and an accurate snapshot of all the phases involved in the analyses. The standardization is maintained by the framework process and the common questions for any NBS type that rely on the three behavioral theories. Therefore, we created the framework in Fig.2.


Fig. 1: The hypothesized model of the social acceptance of NBS.


Fig. 2: A replicable and comparable decision-making framework for NBS.

The framework development process starts with an extensive review of the social acceptance and NBS literature. Accordingly, NBS typologies are identified. For this study, we refer to Nature4Cities, which identifies 75 NBS types and determines challenges related to each NBS type.

Four NBS Cases

We translate challenges into questions for METU Forest in Ankara, Turkey; Tisza River Bank in Szeged, Hungary; Forest Garden in Alcalá de Henares, Spain; and Quarries in Milan, Italy cases. The questions are then modified for whether the NBS has already been implemented or is planned to be implemented.

Given the complexity of the model and the number of hypotheses considered in this research, we utilize the partial least squares (PLS) method by using SmartPLS 3.0M2 software to determine drivers for each case. PLS results are obtained in two stages: (1) evaluating model fitting, reliability, and validity of the measurement model; and (2) assessing the relationships between constructs in the model

The comparable results

The comparable results are illustrated in Fig. 3-6.


Fig. 3: Structural model results for the social acceptance of Tisza River Bank in Szeged, Hungary.


Fig. 4: Structural model results for the social acceptance of Quarries in Milan, Italy.


Fig. 5: Structural model results for the social acceptance of Forest Garden in Alcalá de Henares, Spain.


Fig. 6: Structural model results for the social acceptance of METU Forest in Ankara, Turkey.


Concluding remarks

We show that social acceptance drivers can vary across NBS and countries. Although there is no one-size-fits-all policy to improve public acceptance of NBS due to differences in types, sizes, locations, and cultural and political landscapes, the determinants of social acceptance and tailored decision-making are vital for the sustainability of NBS. Understanding the risks and benefits of an NBS and developing personal norms related to the environment will affect climate resilience in cities. Overall, the results indicate that procedural and distributive fairness, perceived risks, costs and benefits, knowledge, experience, and personal norms are the critical factors affecting the social acceptance of NBS, either directly or indirectly.

The findings open a venue for formulating powerful and tailored strategies with a destination for the sustainability of NBS for each case independently. For instance, the flow of significant impact goes from experience to knowledge in the METU Forest and Forest Garden. Given that these two cases represent post-implementation NBS examples, experience and knowledge are expected to play a key role in forming attitudes. Including the general public in decision-making has emerged as a strategy applicable to pre-implementation and post-implementation NBS. 

Although this study focuses on the resilience of urban areas to climate change, a similar approach can be used to assess the acceptance of mitigation strategies and low-carbon technologies. 


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Humanities and Social Sciences > Society

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