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Infrastructure is crucial to the functioning of society and the economy. Yet, to avoid precipitating environmental breakdown, it must undergo transformation. We argue that citizens who rely on infrastructure's services should have a say in how transformation is managed. However, the complex nature of infrastructure means that public dialogue is difficult and rarely done well. Infrastructure has several characteristics, which make elicitation of perceptions challenging: it is connective, relational, obdurate, collective and subject to fragmented governance. We held a series of deliberative workshops in a city in the UK, to examine how public perceptions of infrastructure are shaped by these characteristics. We found that using infrastructure's characteristics as a framework for deliberation built participants' capabilities to articulate perceptions of infrastructure. We argue that using these characteristics also placed more emphasis on the socio-materiality of infrastructure and can address the disconnect between scales of participation and scales of decision making. This offers an alternative way to debate the desirable attributes of infrastructure, which we argue is more productive and inclusive. [ABSTRACT FROM AUTHOR]

• Empirical studies of community acceptance of large-scale solar farms are lacking. • We present a case study of the UK's first 'nationally significant' solar farm. • We identify 28 determinants shaping community acceptance of large-scale solar farms. • Key issues are 'green-on-green'; scale; place attachment; policy; process; justice. • We also propose a novel 'relational' understanding of community acceptance. New renewable energy infrastructure is essential to deliver net zero policies in response to climate change, but a lack of community acceptance is a potential barrier. It is therefore important to understand what shapes community acceptance and identify policy responses. This paper presents a case study of community acceptance of a large-scale solar farm in the UK, the first to be classified as 'nationally significant' infrastructure. In doing so, it provides the first empirical study of community acceptance of a large-scale solar farm in a developed country context, building on existing studies which use hypothetical approaches such as choice experiments, or surveys which measure general attitudes rather than responses to specific developments. The paper uses mixed methods (quantitative content analysis of online comments on the planning proposal; qualitative semi-structured interviews with local residents and key stakeholders; and participant observation) to identify determinants shaping community acceptance of large-scale solar farms. We discover 28 determinants which we group into eight categories: aesthetic, environmental, economic, project details, temporal, social, construction and process. We argue that these findings help to reveal broader issues underlying community acceptance of solar farms and other renewable energy infrastructure: 'green-on-green' tensions; issues of scale and place attachment; policy, process and justice. We also contribute a novel understanding of community acceptance as 'relational', by which we mean it is informed by the deployment of other energy technologies and the wider energy policy landscape, not just the specific project. We conclude with recommendations for how policymakers can respond to the issues identified by this article. [ABSTRACT FROM AUTHOR]

• "Predict and act" decision making is ineffective in the face of deep uncertainty. • Decision making under deep uncertainty (DMDU) methods support robust and adaptable decisions. • However, DMDU methods do not fully reflect the context in which decisions are made. • This influences the availability of feasible options and limits capacity for change. • Decision contexts signpost the selection of full or "hybrid" DMDU approaches. Deep uncertainties like environmental and socio-economic changes create challenges to decision making. Decision Making under Deep Uncertainty (DMDU) methods are recognised approaches to navigate deep uncertainties and support robust and adaptable decisions. However, their ability to fully reflect the context in which these decisions are made has been criticised. This paper presents a synthesis across cases and methods to provide a holistic understanding of the application of DMDU methods to support long-term decision making. We carried out a structured literature review and analysed 37 infrastructure DMDU case studies. The analysis shows that DMDU methods are effective at developing plans to address a range of deep uncertainties and in some cases, reflecting the institutional context of the decision. However, they largely overlook the organisational and individual contexts in which decision making happens. We argue that the use of existing DMDU methods in practice should start with a better understanding of the institutional, organisational and individual contexts. We then suggest modifications to the applications of DMDU methods, i.e. internalising the context at different stages of the decision-making process and developing a decision typology to signpost decision makers to the best approach for a specific context. [ABSTRACT FROM AUTHOR]